management engineering - ingegneria gestionale

The course ‘Accounting Finance & Control’ (AFC) aims at providing students with the state-of-art, theoretical frameworks and instruments to measure and manage the overall performance of a (for profit) enterprise
The course fits into the overall program curriculum pursuing some of the expected learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

At the end of the course, students will know and understand:
The main methods for assessing and reporting the financial and non-financial (e.g. ESG / sustainability) performance of an enterprise
The different drivers of value creation and the linkages among them
The goals, the structure and the processes of the Planning & Control (P&C) Cycle
The organisational role of the “Accounting, Finance and Control” Units in an enterprise and its evolution over time
Students will be able to:
Apply the methods and models discussed during the course to real cases (e.g., to enterprises that belong to different sectors or have different organizational structures)
Design tailored performance measurement systems (e.g., systems that match the goals and the peculiarities of real enterprises)
Prepare performance reports tailored to the information needs of different stakeholders
Read and interpret the financial and non-financial performance of an enterprise (and of its constituencies)

The context:
The “Accounting, Finance and Control” (AFC) domain: the role of financial accountants and controllers and its evolution over time
The “AFC” organizational unit within the enterprise
Financial Accounting:
The multidimensional nature of financial accounting and its role and evolution over time
The concept of group of companies and consolidated financial statements
Corporate Performance Measurement:
Accounting-based Performance Measures. The analysis of consolidated financial statements of a business group
Value Based indicators: Discounted Cash Flow techniques; Enterprise Value vs. Equity Value; the calculation of Free Cash Flows; the Cost of Capital; Relative Valuation
Value Drivers (non-financial performance measures and risk indicators)
The integrated Planning & Control Cycle:
The “Planning” phase: the elaboration of operating; capital and cash flow budgets; and financial planning
The “Control” phase: periodic management reporting; the structure and content of management reports; corporate dashboards and balanced scorecards
Measuring and reporting performance of internal responsibility centers (business units, divisions, functions); corporate costs allocation and transfer pricing

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Altro
For attending students, the assessment is based on a combination of in-class applied activities and final individual assessment. This format allows students to progressively build part of their final grade during the semester and to apply the methods discussed in class to real-world cases.
Two hackathons (40%), held during the semester, aimed at assessing students’ ability to apply the methods presented in the course to real-world cases. The participation to both hackathons is mandatory and the mark of the hackathons cannot be refused and it remains valid for one year.
Written test (60%), which aims at assessing students' knowledge and full comprehension of key concepts, methods and tools illustrated during the course (with particular focus on pre-requirements for their application, pros and cons of alternative solutions, etc.)
Conditioned Oral test (+/- 2 points/ fail), which aims at assessing students’ capability to choose the most appropriate solution among the different alternatives according to the peculiarities of the application context.
For non-attending students and for students who receive an insufficient grade (<18) in the hackathons, the assessment consists of two parts:
Written test (50%), which aims at assessing students' knowledge and full comprehension of key concepts, methods and tools illustrated during the course (with particular focus on pre-requirements for their application, pros and cons of alternative solutions, etc.)
Oral test (50%), the oral examination is mandatory for non-attending students and has a substantial impact on the final grade. It is a comprehensive individual assessment aimed at evaluating students’ full comprehension of all the course concepts, and their ability to select, apply and justify the most appropriate methods and solution among different alternatives, considering the specific features of the application context.

Arnaboldi, A. Azzone, G. and Giorgino, M., Performance Measurement and Management for Engineers, Editore: Elsevier, Anno edizione: 2014, ISBN: 9780128019023
Anthony R. and Govindarajan V., Management Control Systems, Editore: McGraw-Hill Higher Education, Anno edizione: 2006, ISBN: 9780072819311

The goal of the course is to enable students understanding innovation and leadership dynamics in order to act as innovative leaders within and across organizations.
The course offers the opportunity to learn frameworks and tools do understand and guide innovative solution and its implementation in real contexts, while experiencing team dynamics and interpersonal relationships.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:

• Understand context, functions, processes and performance
• Develop new ideas and solutions in business and industrial scenarios evolving over time
• Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members
  The course adopts the following innovative teaching methods:
• development of soft skills
• Team projects
• Case study analysis

Lectures, activities and team-based projects will allow students:
-To know and understand the different strategies to foster the innovation process and their applications (lectures)
-To know and understand the different leadership theories and models to comprehend inter-personal processes (lectures)
-To know how to gather and structure relevant information to deepen the knowledge about the context in which an innovation is taking place (project)
-To develop an innovative vision and propose a solution under different constraints (project)
-To improve collaborative attitudes and know relevant drivers to foster team effectiveness (project)
-To communicate effectively an innovative idea (project)

The key topics that will be covered in the course are the following, divided in the two main areas:
Innovation
In this module you will learn how to promote and mange innovation with a strategic perspective, as well a show to manage and lead an innovation process. The module focuses especially on the capabilities of leaders to create innovative visions and to catalyze the resources that are needed to make that vision come through and all the phases, activities and methodologies needed to transform and idea into a product-service solution to be launched in the market. The topics characterizing the module are the following:
o What is innovation, what is its value and its challenges
o The drivers and the timing of innovation
o The innovation strategies and the creation of vision: innovation of meaning and design-driven innovation
o Technology strategy: key technologies, dynamic capabilities, complementary assets, profiting from innovation
o Collaborative and Open Innovation
o Guiding principles and models for managing innovation processes
o Users analysis and users integration in innovation processes
Leadership
In this module you will learn how to develop the capabilities to engage yourself and others in becoming innovative leaders and effectively managing change and innovation in organizational settings. The topics characterizing the module are the following ones:
o What is leadership, what is the difference between leaders and managers
o How to assess people and effectively communicate with collaborators
o The motivational theories that help leaders to trigger others’ commitment
o How to design and lead effective teams; teams roles and dynamics in innovation processes
o Team dynamics: group behaviours, group decision making, conflicts and negotiation, psychological safety
o How to effectively face change and lead innovation in complex organisational settings
The course adopts the following innovative teaching methods:

• development of soft skills
• Team projects
• Case study analysis

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
Evaluation will be based on the two different options in which the course can be followed:
Team-based option:
o Individual written exam
o Individual oral exam
o Team project: Leadership & Innovation Story. Leadership & Innovation Story is a project-based assignment in which students investigate a real organizational innovation through primary (interviews) and secondary data, critically analyzing the case using leadership and innovation theories covered in the course. The project culminates in a written report presenting the case and its analysis
Participation in the activities of the course during class and in terms of contribution to the work of teams will be also evaluated through a bonus/malus mechanism.
Individual-based option:
o Individual written exam
o Individual oral exam
o Individual assignment: Leadership & Innovation Story. Leadership & Innovation Story is a project-based assignment in which students investigate a real organizational innovation through primary (interviews) and secondary data, critically analyzing the case using leadership and innovation theories covered in the course. The project culminates in a written report presenting the case and its analysis

Roberto Verganti, Owercrowded: Designing meaningful products in a word awash with ideas, Editore: MIT Press, Anno edizione: 2017, ISBN: 9780262035361
Melissa Schilling, Strategic Management of Technological Innovation, Editore: McGraw-Hill, Anno edizione: 2010, ISBN: 978-0078029233
Kreiter R., and Kinicki, A., Organizational behaviour (11th Edition), Editore: McGraw-Hill/Irwin, Anno edizione: 2013

GOALS
The goals of this course are to enable students to understand and interpret the current competitive and marketing environment and their evolution; and to evaluate their impact on business performance. This course will allow students to understand a Company’s value generation mechanisms and its strategic and marketing processes in the light of the ongoing digital transformation, and how to translate these processes into managerial activities.
The course will present the major concepts, theories, methodologies and tools to support the strategic and marketing decision making process. It will also introduce the strategic methodologies and tools to launch a new business, either within an existing company or through a startup company. The discussion of business cases and real-world examples, will encourage students to examine and get familiar with the abovementioned theories and models as well as their practitional implications.
The course focuses on strategic and marketing concepts and models that can be applied to both for-profit and non-for-profit organizations, as well as for initiatives with a positive impact on several dimensions and domains (e.g. social, environmental), starting from a holistic perspective that assesses the ability of companies to generate both tangible and intangible value to guarantee sustainable growth.

EXPECTED LEARNING OUTCOMES
Dublin Descriptors
MsC Learning goals – Management Engineering
Expected learning outcomes
DdD 1: Knowledge and understanding
Understand context, functions, p rocesses and performance
Students will:
Understand and interpret the current competitive environment and its evolution
Understand a Company’s strategic and marketing processes and the related operational activities
Know the main steps and processes employed when launching a new business
DdD 2: Applying knowledge and understanding
Identify trends, technologies and key methodologies in a specific domain
Students will:
Identify and apply the appropriate tools to analyze the competitive environment (including the impacts of political, economical, social, technological, environmental and legal trends) and the Company strategy
Discern and select the appropriate strategic approaches and marketing practices for different company typologies
Identify the appropriate strategic methodologies and tools to launch a new business

TOPICS
Strategy
Concepts, theories and models supporting the strategic decision making process. The main topics are: strategy, strategic decision and strategic analysis; business unit strategy, value chain, competitive advantage, competitive forces, SWOT analysis; corporate portfolio strategy, portfolio matrices; strategic innovation and creativity (e.g. resource-based view and blue ocean strategy), business model (design, innovation and validation through Lean Startup Approaches), digital disruption, strategic entrepreneurship and entrepreneurial strategy (introduction to business planning).
Marketing
Concepts, theories and models supporting the marketing decision making process. The main topics are: customer behaviour, segmentation and targeting, value proposition and positioning, branding, marketing mix & customer experience.
The lectures will be supplemented by the active class discussion of business cases and by real-world examples.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
ASSESSMENT
The assessment will be based on the weighted average of a mandatory written exam (50% of final grade) and a mandatory oral exam (50% of final grade) at the end of the course.
Students will also have the possibility to carry out an optional, non-mandatory project work, which will be graded as a -2/+2 decrement/increment to the final grade (calculated, as described above, as the weighted average of the written exam and oral exam).
Written exam
The written exam will introduce a case-based approach. Students will be given a short case relevant to the course at the beginning of the exam session.
Questions: Following the case analysis, students will be required to answer open-ended questions related with:
Assess: Develop an external and/or internal analysis of the competitive scenario
Apply: Demonstrate the ability to use appropriate strategy and marketing tools to address a complex challenge
Envision: Show your skills at developing original and rigorous solutions to the given strategic problem.
Assessment: Written exam grades range from 0 to 30 points and the written exam accounts for 50% of the final grade. It aims to evaluate the individual analytical and theoretical knowledge of each student, as well as the ability to apply theory to practice.
Oral exam
The oral exam will cover all course content and will explore the ability of students to apply Strategy & Marketing concepts in different case-based contexts. Oral exam grades range from 0 to 30 points and accounts for 50% of the final grade. In order to be admitted to the oral exam, the written exam grade should be at least equal to 18.
Optional, non-mandatory project work
Students in groups up to 3 people (from the same Course Section) will be given the possibility to perform an optional, non-mandatory project work requiring an original and real-world implementation of Strategy & Marketing tools and concepts.
The project work will be submitted to the instructor at the end of the course. Project work grades range from -2 to +2 points as decrement or increment to the final grade (calculated, as described above, as the weighted average of the written exam and oral exam).
Please consider that a project work can be evaluated either positively (up to +2 points) or negatively (up to -2 points).
Overall Final Grade
The overall final grade presented to the students will result from sum of the weighted average of the Written Exam grade (50%), the Oral Exam grade (50%) and the -2/+2 decrement/increment from the optional, non-mandatory project work.
[(Written Exam Grade*0.5+Oral Exam Grade*0.5) + (Project Work grade, ranging between -2 and +2)]= Overall Final Grade
The grade “30 cum laude” can be assigned to outstanding performance at the oral exam, and/or thanks to the positive contribution of the optional, non-mandatory project work.
Type of assessment
Descriptor
Written test
· O pen-ended questions with answers on a short case relevant to the course assigned during the written test
Oral test
· Theoretical questions on course content
· Questions to investigate the student ability to make connections among the different topics discussed along the course
· Questions to investigate the student ability to apply the concepts discusses to real business cases and contexts
Optional, non-mandatory project
· Application of the course content to a real business case

R.Grant, Contemporary Strategy, Editore: John Wiley & Sons
P. Kotler,K. Keller, Marketing Management, Editore: Prentice Hall

The course “Advanced Performance Measurement” contributes to the following objectives of the programme:
understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment
Specifically, the course contributes to the development of the following capabilities:
understand how organizations are changing the way of running performance management systems and how this change entangles with business context, decision makers and data analytics;
understand how different data types, such as geo-located and textual data, contribute to performance management of organizations and to the development of useful business insights;
define appropriate performance indicators according to the available data and combine these indicators to monitor processes and organizational goals;
understand how data analytics models can be integrated within a performance management system, to support, plan, lead and control activities and processes of organizations considering the different decision makers and challenges within an organization;
understand the importance of using dashboards and visualization techniques to report information relevant to specific decision makers;
adopt a critical and rigorous reasoning to design effective reporting solutions to face performance management issues and opportunities connected to the existence of different sources and typologies of data.

At the end of the course, students will be able to:
understand the different approaches and challenges within an organization when it comes to monitoring performances and defining goals;
rigorously design, define and monitor different KPIs, based on various types of advanced data, analytics, and models, and to critically evaluate the feasibility and implications of the adoption of specific KPIs to support organizational decision-making;
develop well-organized and functional managerial reports and dashboards for different decision makers within an organization, to support the delivery and interpretation of data insights.

The course is organized in the following units:
Introduction to the course. Definition of Advanced Performance Measurement.
Advance Performance Measurement and Decision Making: how performance measurement changes and how it relates with the business context and the different internal users of information.
Advanced Performance Measurement and reporting: how reporting is changing thanks to Business Intelligence tools and how this change is grasped to improve performance management through data visualization and profiled reporting.
Advanced Performance Measurement and Data as Assets: how performance measurement within an organization relate with data sources of various types, including text and geo-localized data
Data cleaning and preparation;
Assessment of data analytics;
Data translation.

Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam consists of a project work to be developed in teams of students during the first semester. The details of the assignment will be explained during the course and will require:
the development of a dashboard on PowerBI;
the development of a written report;
an oral presentation of the project work.
At the end of the project work, students will be asked to evaluate in an anonymous form their group companions on a scale from 1 to 5. The goal of this peer-to-peer (P2P) review is to make sure that everyone actively participates to the activities of the project work. Based on the P2P review, one or more members of the group may be given a penalty of “-3” (minus three) points to be applied to the final grade of the course.
An optional oral exam assessing the individual comprehension of course topics by the student will be illustrated during the course. The oral exam evaluation is added to the project work grade and can either increase or decrease the project work grade: the oral exam grade ranges between a minimum of “-3” (minus three) points and a maximum of “+3” (plus three) points. Notice that the oral exam is mandatory for students receiving the P2P penalty in the project work.

The global business environment and the increased complexity in supply chain planning require an extended set of competences, ranging from collaborative planning methods to advanced IT tools.
In this scenario, the Lab objective is to provide state-of-the-art knowledge on management practices, techniques and tools for advanced Supply Chain planning tasks, including also some topics about Supply Chain Execution. By mixing traditional theoretical lessons, business games and application cases, guest lecturers, Python lab sessions and a company-based project work, a wide set of thorough yet practical skills will be transferred to the students.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Identify trends, technologies and key methodologies in a specific domain
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating other group members

Given the above mentioned learning goals, the following learning outcomes are expected:
Knowledge of the state-of-the-art challenges, practices and tools related to the task of planning complex supply chains. E.g.: the relevance of financials performances in planning, the most used practices to enhance collaboration, data exchange and risks sharing in supply chains, the available technologies in the IoT arena, the adoption of cloud platforms and application to collect data and to enable business integration, and eventually the use of AI agents to automate/augment planners in their activities. These elements will be have to be known both in general terms, as well as contextualized (knowing relevance / priority) in specific industries;
Capability to use basic (MS Excel) and advanced (Python) tools to analyse data so as to support plannign related-decision, e.g. data preparation, integration and cleaning, basic clustering, time series analysis, etc.
Capability to analyse, redesign and improve a real SC planning process, starting from the detailed map of the current process of a company (activities, tools, responsibilities) and the quantititive assessment of the current performances, then moving to the identification of criticalities (process, organization, technology), then re-designing all of the above mentioned process elements, including the assessment of cost/benefits and the definition of a roadmap to implement the new process (considering organizational, technological, financial, regulation etc. constraints).
Capability to accomplish several (i.e. parallel) demanding tasks during the semester, managing stress, working in multi-language & multi-cultural team, interacting with external company stakeholders and respecting deadlines in internal (for the teacher) and external (for the company) deliverables.

The Lab program will encompass the following contents:
Introduction / reprise about supply chain planning tasks, examples from different industries; the relevance of information and data processing in nowadays planning.
Models and techniques for advanced planning, deep dive on Andvanced MRP and DD-MRP tools, deep dive on state-of-the-art Inventory Planning and Forecasting approaches.
Technologies for Advanced Planning: APS systems, Internet of Things, Industrial Analytics and Artificial Intelligence, Cloud IoT platforms, Cloud SaaS and related ecosystem, Classical AI, Generative AI and Agentic AI;
Tools: data analytics for planning, python (AI augmented) coding and its application to planning problems
Methodologies for Value Assessment: a framework for tangible and intangible benefits, approaches and models for a quantitative assessment, and for business case constructing
Industries and vertical markets: depending on the availability of guest speakers, focus on Advanced planning in the following industries: Automotive, Retailing, Food and Fashion Luxury
Outlook on the job market: the role of human planner in the future technology playground.
Each topic will be first introduced through a practical case, then deepened through traditional therethical lessons, and then followed by extensive applicative contents. Overall, the Lab will resort to the following teaching methodologies:
Traditional lessons, providing theoretical background, scenario analysis, outlook on market needs and technology solutions;
Traditional computer hand-on lectures, dedicated to AI enhanced use of Python analytics specifically for planning problems;
Business cases, so as to practice with specific planning problems, techniques and tools in limited-size problems. Students' presentations will enhance presentation skills and will be used to assess the degree of involvement with the proposed contents
Computer aided learning (e.g. business games)
Visit to the Internet of Things Lab of Politecnico di Milano (if allowed by logistic constraints)
Company guest lecturers
Autonomous work on Thematic assignment, 2-week elapsed project on SC Data Analytics using Python
Autonomous work on Company Project Work assignment, 2-month elapsed project on a real SC problem, provided by a top company operating in Italy

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Altro
The evaluation will be based on:
Assignment(s): The assignment(s) evaluation will allow to achieve a maximum mark of 29/30 (including peers' review), and will be valid for one academic year (till next next years' February sessions). See next for more details
Oral examination: The oral examination will evaluate individual contribution to the teamwork, and will focus on the course’s topics, including those presented by guest speakers, so as to assess the understanding of the theoretical elements provided. The oral examination could give an extra 2/30 point, so allowing to reach the top mark.
Two assignments are arranged, a thematic one (focused on data analysis for planning) and a company Project Work.
The thematic assignment will rely on real-company data, disguised for the sake of confidentiality, will involce students for about 2 weeks, and will assess the second learning outcome.
T he company Project Work, which will involve the students for about 2 months with a real company, under the guidance of a company tutor and of an academic tutor, in order to solve a real planning problem, will assess the third and the fourth learning outcomes.
For both assignments, students will be divided in groups (4/5 people, arranged by the teachers so as to mix and balance people’s experience and background). The assignments will be given during the semester (1 st after 30% of the course, 2 nd after 60% of the course) and will require autonomous work of the team, with in-class assistance by Lab teachers. The student participation will also be assessed by his/her team members.
Class attendance, especially when Company Guest Lecturers are invited, will be incentivated.

Varie
Note: Several recommended readings, mostly academic papers and business research reports will be uploaded / recommended during the course, also depending on current business trends and on the selected guest speakers

Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment:
Master and understand design practices and making capabilities in accelerating innovation projects [Individual Written Exam].
Develop new ideas and solutions in business and industrial scenarios evolving over time:
Early prototype innovative concepts [Team Design Sprint Project].
Manage uncertainty of innovation projects adopting agile approaches [Team Design Sprint Project].

Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment:
Manage design practices and making capabilities in accelerating innovation projects [Individual Written Exam];
Develop new ideas and solutions in business and industrial scenarios evolving over time;
Early prototype innovative concepts [Team Design Sprint Project];
Manage uncertainty of innovation projects adopting agile approaches [Team Design Sprint Project];
Develop solutions that transform the current ecosystem by leveraging the collaboration and cooperation of stakeholders [Team Design Sprint Project].
Through these activities, students will learn:
Knowledge and understanding: By the end of the course, students will be able to demonstrate a clear understanding of the key concepts and methods related to agile innovation;
Applying knowledge and understanding: Students will apply their acquired knowledge and comprehension to analyse real-world cases and propose innovative agile solutions;
Communication skills: Students will effectively communicate their ideas, solutions and analyses both verbally and in writing, tailoring their message to different stakeholders.

Today’s world, where speed is gaining increasing relevance to make innovation happen, has called for the emergence of approaches that leverage continuous testing and iteration. After the introduction of the Agile Manifesto in 2001, a wide range of industries has experienced the massive diffusion of Agile approaches. These approaches leverage agility, flexibility, and the rapid development of new solutions. On the one hand, Agile emerges as a tool to change the development process; on the other, it emerges as a culture to embrace flexibility. Especially this cultural aspect is crucial in agile innovation approaches, to face emerging issues and have an impact on companies solutions. Design is recognized as a powerful approach to reduce uncertainty; more specifically several studies show that adopting a design mindset can help embracing ambiguity and foster innovation even when the problems are wicked and ill-defined. In discovering new technologies, knowledge and uncertainty are always high, and the search for the right application might require different and complex iteration and experimentation processes. Design Sprint represents a new approach deeply rooted on agile culture, design attitude and experimentation mindset. It aims at accelerating innovation by the adoption of sketching, testing and prototyping tools.
The course has been designed around the following main topics:
Agile Culture: Making innovation happen in a continuously changing environment where ambiguity, variability and complexity is raising requires new mindset and approaches. Thus, agile innovation is gaining traction as a culture to cope with these shortcomings, in promoting both a agile culture and tools to make innovation happen. Furthermore, lean development and lean startup are approaches that are getting more and more relevance in today’s panorama not only in hi-tech industries. Agile methodologies and specific approaches such as SCRUM are fundamental to properly manage innovation projects in turbulent environments;
Design Attitude: The emergence of new paradigms such as human-centered design, participatory design and design thinking, have marked the transforming role of design in the field of innovation management. Design is not only an aesthetic driver of innovation but represents a new set of innovation management practices. It is something practiced not only by designers but by everyone in organizations who seeks to innovate;
Experimentation Mindset: Innovation approaches, such as agile development, and lean startup, may differ on some principles and practices, but they have one key ingredient in common: experimentation. Recent approaches leverage experiments for exploratory learning. In particular, “quick & dirty” prototypes are used to search the most valuable innovation opportunities. The changing nature of experimentation in innovation is supported by the digitalization trend. The increasingly digital nature of products and services facilitates early, less expensive, higher-fidelity prototypes and the subsequent tests.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation modality is divided into two main activities: an individual written exam and a team project called Team Design Sprint Projects that students conduct in the semester with factories (activities led by external companies) and team-based reviews with the faculty. More details will follow below.
The final evaluation of the course is different for attending and not-attending students.
Attending Students
The evaluation is based on the following elements:
The evaluation is based on the following elements:
Individual Written Exam: open questions about case studies and theoretical contents; the written exam is based on the content included in the course slides, case studies, and class discussion.
Team Design Sprint Projects: teams are engaged in designing new solution for a specific brief presented in the first day of lecture. Presentations and video are due one day before the final presentation day, happaning on the last day of lecture.
Design Connoisseurship: each team presents in 10 minutes a case of a company or a product that leveraged a design mindset to evolve over time. It is a way to nurture team critical reflection.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Individual
Written Exam
Team
Design Sprint Project
Design Connoisseurship
Attending Students
9
18
5
In order to pass the exam:
Sum must be >= 18;
Individual Written Exam >= 5;
Team Design Sprint Project >=10
Design Connoisseurship 0-5
The Team Design Sprint Project is valid for the entire academic year, so for all the calls the students that attend the course will keep that mark for all the five exam calls.
Not-Attending Students
The evaluation is based on the following elements:
Individual Oral exam: open questions about case studies and theoretical contents; the individual oral exam is based on the content included in the course slides, case studies, textbooks, guest speakers’ presentations;
Individual Design Sprint Project: same brief as the attending studnets. Presentation are to be sent on the day of the exam and presented during the oral exam.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Individual
Oral Exam
Individual
Design Sprint Project
Not Attending Students
18
14
In order to pass the exam:
Sum must be >= 18;
Individual Oral Exam >= 11;
Individual Design Sprint Project >= 7.

Magistretti, S., Sanasi, S., Dell'Era, C., & Ghezzi, A., Entrepreneurship as design: A design process for the emergence and development of entrepreneurial opportunities, Anno edizione: 2023
Knapp J, Zeratsky J, and Kowitz B, Sprint: How to solve big problems and test new ideas in just five days, Editore: Simon and Schuster, Anno edizione: 2016
Thomke SH, Experimentation Works: The Surprising Power of Business Experiments, Editore: Harvard Business Press: Boston, Anno edizione: 2020
Cooper RG and Sommer AF, The Agile-StageGate Hybrid Model: A Promising New Approach and a New Research Opportunity, Editore: Journal of Product Innovation Management, Anno edizione: 2016
Magistretti S, Dell'Era C, and Verganti R, Look for New Opportunities in Existing Technologies: Leveraging Temporal and Spatial Dimensions to Power Discovery, Editore: Research-Technology Management, Anno edizione: 2020
Magistretti S, Dell'Era C and Doppio N, Design sprint for SMEs: an organizational taxonomy based on configuration theory, Editore: Management Decisions, Anno edizione: 2020
Magistretti S, Allo L, Verganti R, Dell'Era C, and Reutter F, The microfoundations of design sprint: how Johnson & Johnson cultivates innovation in a highly regulated market, Editore: Journal of Knowledge Management, Anno edizione: 2021
Magistretti S, Pham C, and Dell'Era C, Enlightening the dynamic capabilities of design thinking in fostering digital transformation, Editore: Industrial Marketing Management, Anno edizione: 2021
Pham C, Magistretti S, and Dell'Era C, The Role Of Design Thinking In Big Data Innovations, Editore: Innovation: Organization & Management, Anno edizione: 2021

The course intends to allow students to work hands-on on top-notch, concrete issues in analytics for business. Through a strong collaboration with companies and the possibility to work on real cases, the intended objectives of the lab are to:

• Introduce advanced methods for managing analytics for marketing and performance management;
• Allow students to apply these methods, and others studied in the stream and the study course, in real contexts in order to identify effective, viable and reliable solutions to actual problems
• Favor an understanding of the actual needs and problems of companies when approaching issues related to data-powered decision making in different aspects of their business
  By doing this, the course targets the following learning objectives:
  Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
  Identify trends, technologies, key methodologies and stakeholder needs in the specific domain of business analytics
  Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment

Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society: the course introduces topics that lie at the forefront of analytics for business in such industries as retail, media planning and marketing agencies
Identify trends,technologies, key methodologies and stakeholder needs in analytics for business: through its strong tie with companies all along the program, participants will meet the challenges and the everyday approaches to data analytics by companies
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment: the laboratorial activity will focus on advanced topics, requiring students to develop innovative and complex solutions, as well as drawing actionable insights from the results.

The course will consist of three main parts:
Advanced analytical methods: seminars to introduce top-notch methods and advanced tools to address marketing and performance management real problems, combining a technical introduction and a discussion of their applications, complementarily to what has already been analyzed in the other stream courses. A particular emphasis shall be put on the investigation of the causal nature of the relationship between variables, boing beyond mere correlation
Seminars with practitioners: testimonials from the business community will take part in the classes to show their experiences and discuss with participants the real issues they deal with in their day-to-day job
Lab: students will form groups and be provided with a detailed outline of a business scenario, a dataset to ground their analysis and will be required to develop, in team, a concrete, viable and effective solution applying analytical methods encountered in the stream. During the lab, tutors will deepen the tools and methods required for the solution, also by running ad hoc deep dives and exercises. In the final part of the lab, groups will present their result to the representatives of the companies that will provide the cases and the datasets in order to get also their feedbacks
With respect to the advanced analytical methods, the topics addressed will be:
Professional data processing:
Effective and ethical data representation
Possible biases in data representation and analysis
The relationship between creativity and analytical skills
Principles of causal inference
Anomaly Detection Methods (methods for identifying outliers, frauds or other non-standard situations)
Traditional statistical approaches: z-scores, IQR, IQR-alpha, …
Advanced statistical methods: Gaussian Mixture Models, Independent Component Analysis (ICA), Regression-model based
Ensemble Methods: Isolation Forests
Reconstruction and subspace-based Methods: AE, PCA
Classification Methods: One-class SVM
Advanced Market basket analysis (beyond support, confidence and lift, to dig into the underlying association rules)
Frequent Itemset Mining
Association Rule mining
Statistical evaluation of Association Rules, other measures of "interestingness" for AR
Contrast set learning
Sequence Analysis
Marketing Mix modelling and marketing spending optimization
Linear models
Bayesian models
The problems of Ad-Stock and latency/lag
Applications to attribution modelling
Design of experiments and its application to causal marketing modelling

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
100%: evaluation of the project work (group-based)

The course covers advanced approaches in the areas of statistical modeling and data analysis, using ideas that bridge the gap between statistics and computer science and developing tools for the statistical mining of data. The focus is on predictive learning, with particular emphasis on recent advances in regression.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members

• At the end of the course students are expected to be able to design and run with R a data driven analysis, aimed at interpretation or prediction, by fitting a regression model when heteroscedasticity or dependence among the observation is a relevant issue. Special focus will be deserved to linear models with heterogenous variance, to fixed effects linear models for correlated data, to mixed-effects linear models, to nonparametric regression models, and to kriging, when dependence is spatial. Overtures to dynamic linear models and Markov models will complement their tools for statistical data exploration and prediction. Leveraging on their engineering forma mentis and on the skills in data analysis acquired in the course, students are expected to be able to evaluate the practical and statistical significance of the final result of their data analysis, to quantify its uncertainty and to diagnose its potential shortcomings, either when used to provide an empirical explanation of the industrial or scientific problem under study or when its main goal is to formulate predictions.
• To prepare for responsible and efficient interactions in a working environment, every student is required to take part in a real data analysis project developed by an independently formed team of 2-4 members. The work in progress of the projects will be collectively discussed during general meetings scheduled along the course; final analyses and results will be presented in a workshop which will take place at the end of the course.

Program:
Introduction: a short recap on linear models for independent data
The case of heterogeneous variance
Linear fixed-effects models for correlated data
Linear mixed-effects models
Nonparametric regression models
Spatial statistics: kriging
A brief introduction to Dynamic Linear Models and Kalman filtering
A brief introduction to Markov Models and Hidden Markov Models
All methods will be illustrated using applications from marketing, finance, biology and other areas; the R free software environment for statistical computing and graphics (downloadable at www.r-project.org ) will be used throughout the course and its lab sessions.
Through the course, students are required to work in team on a real data analysis project whose progress will be shown periodically to the class.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Altro
The exam consists of two parts:
(a) A written exam. The written exam consists of a few (usually three or four) data analysis problems to be solved with R. The exam is open book: the use of a personal computer is allowed as well as that of books, personal notes etc.
(b) Team Project evaluation. Projects will be collectively evaluated by the teachers of the course and by the students participating to a final workshop at the end of the course.
To pass the exam the student must pass each part of the exam with a score greater than or equal to 18/30; the final score is then obtained as the weighted average of the two scores, with weights respectively equal to 0.6 for the written exam and 0.4 for the project evaluation.

Galecki A. e Burzykowski T, Linear Mixed-Effects Models using R, Editore: Springer, Anno edizione: 2013
Cressie N., Statistics for Spatial Data (Revised Edition), Editore: Wiley, Anno edizione: 1993

Artificial intelligence (AI) is a combination of methods, techniques, and tools, that are revolutionizing today's life. At the core of AI is machine learning, i.e. the elaboration of data that allows systems to learn, recognize properties in data, improve performance, without being explicitly programmed. On the other hand, robotics is a well-established technology that is making a significant shift towards broader application thanks to the use of AI.
The purpose of this course is to familiarize the students with the most common tools of machine learning and expose them to both basic elements of robotics and new trends (like collaborative and humanoid robotics), with special emphasis on the application of AI to robotics.

The expected learning outcomes of the course can be classified according to the Dublin descriptors.
Dd1 (Knowledge and understanding)
Students will understand
-the whole machine learning workflow, including data visualization techniques, features engineering, model training and validation, and interpretability assessment;
-the main machine learning paradigms and their role and applicability in engineering use cases;
-the role of industrial robots in the factory, why and where they should be used in the production systems;
-the new trends in industrial robotics, like collaborative robotics.
Dd2 (Applying knowledge and understanding)
Students will learn how to:
-design and implement a machine learning pipeline tailored to the structure of the available data;
-train and compare different models based on their predictive and interpretability performance;
-use mathematics to describe the motion of a robot, in terms of its kinematics;
-plan a suitable motion for the robot both in the joint and in the operational space.
Dd3 (Making judgement)
Students will be able to decide which machine learning technique to adopt in selected problems (within or outside the robotics domain) and how to apply them.

1. Introduction to Artificial Intelligence and Machine Learning
Learning from data.
AI and Machine Learning applications in engineering
2. Machine learning for atomic data
Data quality and quantity.
Univariate and multivariate visualization techniques.
Data normalization and pre-processing.
Features extraction and selection, learning paradigms, performance assessment, interpretability for atomic data.
3. Machine learning for time series
Time series: filtering, detrend, feature extraction and selection.
Learning paradigms, performance assessment, interpretability for time series data.
4. Introduction to robotics
Industrial robots: basic concepts and examples.
Market and trends of industrial robotics.
5. Robot kinematics
Position and orientation of a rigid body.
Direct and inverse kinematics.
Differential kinematics: Jacobian and singularities.
6. Robot planning and control
Robot programming.
Trajectory generation in joint space and in operational space.
Closed loop control (elements).
7. Collaborative and humanoid robotics
Collaborative robotics: motivation and use cases.
Safety standards.
Humanoid robots: a general introduction.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Students will be evaluated through a written exam with open-ended questions and an optional project work that will be assigned during the semester.
In the written exam the student should be able to:
-describe a complete machine learning workflow and, for each estate, commenting upon strengths and limitations of different techniques (Dd1, Dd2);
-select appropriate machine learning techniques for a given problem, justify methodological choices, interpret model outputs, and critically discuss the presented results (Dd1, Dd2);
-discuss the kinematic model of a robot, including detection of singularities (Dd1, Dd2);
-discuss and evaluate trajectories in joint space or in the operational space (Dd1, Dd2).
In the project work, students will address a simple problem of learning from data, within or outside the robotics domain (Dd1, Dd2, Dd3).

Slides available in the WeBeep channel
Bruno Siciliano, Luigi Villani, Giuseppe Oriolo, Alessandro De Luca, Foundations of Robotics, Editore: Springer, Anno edizione: 2025, ISBN: 978-3-031-85522-1 https://doi.org/10.1007/978-3-031-85523-8

The goals of this LAB can be summarized as follows:
Understand context, actors, functions, and processes in a business and industrial environment, and the impact of those factors on business performance
Design business solutions for real challenges in a business and industrial environment, building on all the methods and learning accumulated in previous courses and on the Analysis, Learning, Reasoning, and Modeling capabilities deriving from a solid and rigorous multidisciplinary background
Transform the organizational setting to accommodate the innovation proposed in the design phase
Interact in a professional, responsible, effective, and constructive way in a working environment, also motivating group members

Understand context, actors, functions, and processes in a business and industrial environment, and the impact of those factors on business performance
Extrapolate the business needs from a specific situation/context and summarize a list of requirements to be matched in order to fulfill those needs
Design business solutions for real challenges in a business and industrial environment, building on all the methods and learning accumulated in previous courses and on the Analysis, Learning, Reasoning, and Modeling capabilities deriving from a solid and rigorous multidisciplinary background
Generate and develop an innovation proposal impacting the business and, at the same time, identify the related business and organizational transformations needed to implement the innovation. Finally integrate both plans to achieve both business innovation and transformation
Transform the organizational setting to accommodate the innovation proposed in the design phase
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members
Drive the team work in a professional environment interacting both with team mates and professors, and with professionals in the companies providing the brief

What does it mean to re-design and transform a business ? How can we move from a vision to an actioned new purposeful organization ?
Introducing an innovation (like a new product or service) is difficult but still more straightforward than transforming a business.
Changing the very nature of a company goes beyond designing and manufacturing new products and/or developing and delivering new services.
An automotive company wanting to enter in the mobility arena with the car sharing;
a postal company introducing financial branch;
or a software company wanting to develop strategic consultancy skills to help its customers to correctly assess the business value of the technological solutions they provide,
are possible examples of what we mean by Business Transformations.
These transformations are difficult to be conceived. They require to have a vision, to scout the human and social mega-trends, to interpret the changes in users’ behaviors, and to create new solutions.
Besides that, though, they will also challenge the way people work inside the company. If you want to do radically different things, you must be different yourself. People in the organization must change their skills but also their mindsets. This human transformation is hard-wired into the business re-design and transformation, and no business transformation can survive without helping people in the company to transform themselves.
The Lab leverages the rules of project-based learning. It will provide a business (re)design and transformation experience, proposing a business transformation live experience. It will be developed either with the innovation and transformation department of corporations or with consulting companies helping corporations to achieve a major business transformation and to make it really happen.
The knowledge acquired in previous courses regarding strategy, design thinking, vision and change, leadership, etc. will be seamlessly integrated into a single effective and agile process.
Students will work in teams to design the answers to the brief proposed by companies. The project development will require to interact with the managers in the real field through interviews and project review meetings. Each team will design and develop a workshop with external stakeholders to either investigate the customers’ needs, validate the proposed solution, or trigger the transformation, helping people move towards the new direction.
Finally, teams will also co-operate to design the overall experience collaborating with the professors to share methodologies and tools already used in previous courses but possibly not known by part of the team members.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The course final evaluation is made up of three mandatory components:
Group Project evaluation
Company evaluation
Individual evaluation (based on the contribution to the course community beyond the project team: peer review)

The course aims at guiding the learner on the theme of Circular Economy through a deliberate alternation of practical cases and application examples to a more theoretical view of the phenomenon. The core of the course is the design and evaluation of business models, either of established companies willing to embrace the new paradigm or of start-ups and new ventures born on a Circular Economy idea.
Particular attention will be paid to the pervasiveness of the paradigm, with examples and good practices relating to several business sectors.

Students will learn: (i) the core meaning of Circular Economy in business environment, being able to properly recognize and distinguishing circular business models from "green", "esg" or "sustainable" business models; (ii) the tools and frameworks to design and evaluate a circular business model, in different industries; (iii) the tools and frameworks to analyse the context and the ecosystem around a circular business model, with particular reference to the role of regulations and of digital technologies in enabling circularity.
Morevoer, students will be engaged in lively debates with entrepreneurs and managers in the field of Circular Economy, thus allowing also a deeper understanding of the enablers and barriers to the diffusion of the new paradigm.

The top 12 core topics of the course can be summarized as follows:
1. The Genesis of the Circular Economy concept, the main differences between Circular Economy and Linear Economy. Circular Economy and Sustainability
2. The basic frameworks for understanding Circular Economy: the butterfly model and the RESOLVE model
3. The CE Matrix (Upstream-Downstream-Full Circular) and the classification of Circular Economy business models.
4. Cases of adoption of Circular Economy in established companies and in start-ups
5. The “Circular” Business Model Canvas: designing a successful transition towards Circular Economy
6. Circular Business Models and Circular Supply Chain: Connecting Eco-Systems for Circular Economy
7. Measuring Circular Economy: methods and tools for assessing circularity
8. The enabling role of IT & IoT in the transition towards Circular Economy
9. The "platform" business models in the Circular Economy
10. Financing Circular Economy
11. The role of Policies in Circular Economy
12. Circular Cities: adopting a broader perspective for the diffusion of the Circular Economy paradigm
The course is intented to be based on lively discussions and participated classes. In-course team works will be required.
Teaching material consists in slides (ppt format) and case studies. Further references to complementary material (books, articles extracted from scientific journals, reports by research centers, other readings) will be provided during the classes.
Additional materials can be found at the Ellen Macarthur Foundation Learning Hub ( https://www.ellenmacarthurfoundation.org/explore )

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The course will be assessed with: (i) a written exam with open-ended questions and case-based questions, covering all the topics of the course; (ii) an oral exam, evaluating the understanding of the concepts and the ability to sustain a business discussion on Circular Economy.
The written exam will count for 50% of the total grade. It will be assessed on a scale up to 30/30. In order to be ammitted to the oral exam, students will have to pass the written exam with a minimum grade of 18/30.
The oral exam will count for 50% of the total grade. It will be assessed on a scale up to 30/30. It has to be sustained in the same call of the written exam. Students who fail the oral exam (grade below 18/30) or refuse the grade will have to retake the entire exam.
Cum Laude grade is assigned to those students who show a brilliant and well above average ability to sustain a discussion on the core topics of Circular Economy.

Davide Chiaroni, L'Impresa Circolare, Editore: EGEA, Anno edizione: 2022, ISBN: 978-88-238-3763-8

Understand complex projects, their dimensions of complexity, implication for stakeholders and sustainability implications.
Identify the methods and approaches to deal with the planning and delivery of complex projects. Identify different options in terms of planning and delivery and their implications.
Design different approaches for planning and delivery complex projects, including different options of project governances, strategies to engage with stakeholders and plan to deal with risks and opportunities.
Develop rigours and professional reports and presentations that are scientifically sound, rigorous and suitable to be used in a professional environment.
Interact in a professional, responsible, inclusive, effective and constructive way with team members, industrial and academic tutors and professional managers which will present the case studies and develop the coursework.

After successful completion of this module, students:
Will demonstrate the ability to identify and analyse the key elements of complex projects and project-based companies, eventually discussing planning and delivery strategies (Knowledge and understanding);
Will be able to select and apply proper qualitative and quantitative tools and techniques at different project life cycle stages (Applying Knowledge and understanding);
Will be able to critically evaluate real projects, identify key elements, such as stakeholders, risks, costs and benefits (Making Judgements and Learning skills), and prepare a technical report describing the best course of action for decision-makers (Communication).

Managing complex projects is about transforming “a vision” into a “reality”. It is about designing and building a new transportation or energy infrastructure, a bridge or a house, or even find and deliver a cure for Covid. Project Management is a topic incredibly interdisciplinary. Cost estimation of new engineering systems, communication management in temporary organisations, financing infrastructure invetments, social and environmental sustainability are all common topics in project studies that are widely applicable across stakeholders, such as companies and government.
This course aims at transferring to students the key empirical elements to work in the Project Business. The key goals are enabling students to:
Bring together and apply the concepts learned in other courses of this major to deal with large engineering projects and project business challenges.
Apply tools and techniques learned in other more theoretical courses to real and pseudo-real scenarios in project ecology
Gain the soft and hard skills to evaluate, plan and manage complex projects
he course enables students to apply the state-of-the-art approaches, methods and models for deciding, planning, and delivery complex projects. There are four key elements in this course:
Interaction with industry and practitioners: A number of industrial guests will be invited in the module to expose students to real-life experiences. Each guest will introduce him/herself explaining his/her experience with project business. He/She will present his/her company, its role in the project ecology. One or more real projects will be presented and discussed with specific questions/challenges proposed to the students and debriefed with the expert.
Guest lectures: Academics or Experts will be invited to lecture on relevant topics related to complex projects which are not covered in other modules. Examples of these topics might include: governance of Special Purpose Entities (SPE), Future-proofing infrastructure, Mental Health in Projects. Each lecture will include both theory and activities for students
Case studies: A series of case studies of the duration of a lecture will be proposed to the student. Each case study will require students to develop a critical analysis applying tools and techniques learned across the major and present an ideal solution/strategy to deal with this case
Development of a major coursework. Students will be required to develop a major coursework concerning a real complex project planned or delivered in Italy or abroad. The students will critically evaluate this project, present their findings to hypothetical decision-makers, and will prepare a report. This will be group work, and a certain number of lectures will be devoted to introducing the coursework, provide feedback during the development and present the final results. Compny managers will be involved as tutors.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Written Coursework: This will be a report, prepared as a group, where the instructor will be able to assess the achievement of the learning outcomes.
Coursework discussion: discussion on the coursework produced

Jeffery Pinto, Project Management: Achieving Competitive Advantage, Anno edizione: 2019

The course objectives are as follows:
Analyzing the financial structure and governance decisions of a company
Learning how the company may raise money to finance growth, projects and investments, and which instruments can be used
Analyzing the characteristics of financial securities, and their valuation methodologies
Analyzing derivatives contracts, their valuation methodologies and how they can be used to hedge company liabilities
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes and instruments in firm and investment financing
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in corporate finance
Develop new ideas and solutions in financial modelling

Comprehension of the logics of the firm financial structure, selecting between equity and debt
Demonstrate the knowledge of the characteritics and pricing models of debt and equity securities
Capability to evaluate the effects of financing decisions on firm and investment appraisal, designing solutions and models
Demonstrate the knowledge of the characteritics and pricing models of derivatives (forward contracts and options) and their use in hedging strategies

The course of Corporate Finance (5 credits) analyzes the process of corporate investments’ financing through the selection of security typology, capital issuance, corporate governance and hedging.
Topics:
Financial structure: Modigliani & Miller propositions, debt vs. equity, agency costs
Debt raising: bonds (valuation, duration, term structure of interest rates, volatility)
Equity raising: shares (valuation) and risk-return equilibrium
Interactions between value and financing (adjusted present value, wacc)
Derivatives (forward contracts, options)
The course may be taken as optional by students enrolled in any concentration of the M.Sc. of Management Engineering.

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
Written text (compulsory) and oral text (optional).
The written text will consist of 3 numerical exercises, in order to test the capability of the students to reach the expected learning objectives.

Brealey Myers, Principles of Corporate Finance

Identify future trends, technologies and key methodologies in a specific domain;
Frame and reframe problems by combining empathy with the ability to challenge existing interpretations;
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment.

Identify future trends, technologies and key methodologies in a specific domain;
Understand and exploit technological and socio-cultural trends, explicit and latent user needs, together with a capability to interpret competitive dynamics in industries [Individual Written Exam].
Frame and reframe problems by combining empathy with the ability to challenge existing interpretations;
Apply human-centered, abductive and iterative reasoning to connect technology, people and business.
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment;
Generate and develop new meaningful directions based on a deep understanding of the future dynamics of competition, society and technology [Team Design Thinking Project].

Practitioners and scholars acknowledge the central role of design as a driver of innovation and change. What has driven the steep growth of attention to design in the latest years in the business community is a change of perspective: design is not only an aesthetic driver of innovation but as a whole innovation management practice, a new set of processes, mindsets, capabilities, and organizational settings. It is something practiced not only by designers but by everyone in organizations who seeks to innovate. Design Thinking, in particular, is making the headlines, with an extremely rapid diffusion in the interest and practice of organizations. The increasing attention of practitioners to Design Thinking is evident by looking at the recent moves of large consulting organizations and tech corporations. Design Thinking is booming in those industries where the digital transformation requires new competences and capabilities for developing effective customer experiences. Also, software developers and integrators have extensively adopted Design Thinking practices.
We live in a world where technological opportunities are cascading on society at an unprecedented speed, a world awash with technologies and information. But humans do not use technologies or data; they need products and services, and design can allow people to navigate an overcrowded world. Far from being connected with the “form” of products, Design Thinking is accepted as a formal approach to foster innovation. It looks at value and change from the perspective of people; or, even better, from the perspective of what is meaningful to people. In other words it aims at shaping meaningful futures (i.e. desirable, sustainable, inclusive). Similarly to many other approaches, also Design Thinking combines three factors: (i) technologies, how things are made and their performance improved; (ii) people, how these things are valuable for customers; (iii) business, how organizations can profit from offering them. The perspective embedded in Design Thinking makes it unique: Design Thinking starts from people. Design Thinking for Business course aims at enriching the capabilities to envision innovative scenarios and to lead transformations. The approach embedded in Design Thinking is human-centered, abductive, iterative and intrinsically oriented to change and to envision new possibilities. An increasing number of firms in fact have recognized the importance of Design Thinking as a mean to achieve sustainable competitive advantage.

Prova scritta condizionata (a scelta del docente), senza prove in itinere
Progetto/i - Elaborato/i condizionato (a scelta del docente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The final evaluation of the course is different for attending and not-attending students.
Attending Students
The evaluation is based on the following elements:
Individual Written Exam: open questions about case studies and theoretical contents; the written exam is based on the content included in the course slides, case studies, guest speakers’ presentations and class discussions;
Team Design Thinking Project: teams are engaged in designing a new meaningful direction for the Partner Company(ies). Teams will be supported by the Faculty along the entire course during the Factories and Teamworking sessions even if Team Design Thinking Projects will be assessed during the final presentations that will take place during the last sessions of the course.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Individual
Written Exam
Team
Design Thinking Project
Attending Students
12
20
In order to pass the exam:
Sum must be >= 18;
Individual Written Exam >= 7;
Team Design Thinking Project >=11.
Peer evaluations among team members will be performed to guarantee a balanced commitment. The Team Design Thinking Project is valid for the entire academic year, so for all the calls the students that attend the course will keep that mark. The participation to the exams during the off-lectures period implies the cancellation of the associated marks obtained during the course.
Not-Attending Students
The evaluation is based on the following elements:
Individual Oral Exam: open questions about case studies and theoretical contents; the individual oral exam is based on the content included in the course slides, case studies, textbooks, guest speakers’ presentations;
Individual Design Thinking Project: individuals are engaged in designing a new meaningful direction for the Partner Company(ies). Presentation sent one week before the oral exam ([email protected]) and delivered during the oral exam.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Individual
Oral Exam
Individual
Design Thinking Project
Not-Attending Students
20
12
In order to pass the exam:
Sum must be >= 18;
Individual Oral Exam >= 11;
Individual Design Thinking Project >= 7.

Brown T, Change By Design: How Design Thinking Transforms Organizations and Inspires Innovation, Editore: Harper Collins Publishers, Anno edizione: 2009
Kelley T, and Kelley D, Creative Confidence. Unleashing the creative potential within us all, Editore: New York: Crown Business, Anno edizione: 2013
Knapp J, Zeratsky J, and Kowitz B, Sprint: How to solve big problems and test new ideas in just five days, Editore: Simon and Schuster, Anno edizione: 2016
Martin RL, The design of business: Why design thinking is the next competitive advantage, Editore: Boston: Harvard Business Press, Anno edizione: 2009
Verganti R, Design Driven Innovation: Changing the Rules of Competition by Radically Innovating What Things Mean, Editore: Harvard Business Press, Anno edizione: 2009
Verganti R, Overcrowded - Designing Meaningful Products in a World Awash with Ideas, Editore: MIT Press, Anno edizione: 2017
Beckman SL, and Barry M, Innovation as a learning process: Embedding design thinking, Editore: California Management Review, Anno edizione: 2007
Beckman SL, To Frame or Reframe: Where Might Design Thinking Research go Next?, Editore: California Management Review, Anno edizione: 2020
Brown T, Design thinking, Editore: Harvard Business Review, Anno edizione: 2008
Buchanan R, Wicked problems in design thinking, Editore: Design Issues, Anno edizione: 1992
Carlgren L, Rauth I, and Elmquist M, Framing design thinking: The concept in idea and enactment, Editore: Creativity and Innovation Management, Anno edizione: 2016
Dell'Era C, Cautela C, Magistretti S, Verganti R, and Zurlo F, Four Kinds of Design Thinking: From Ideating to Making, Engaging, and Criticizing, Editore: Creativity and Innovation Management, Anno edizione: 2020
Dorst K, The core of 'design thinking' and its application, Editore: Design Studies, Anno edizione: 2011
Dorst K, and Cross N, Creativity in the design process: Co-evolution of problem-solution, Editore: Design Studies, Anno edizione: 2001
Elsbach KD and Stigliani I, Design thinking and organizational culture: A review and framework for future research, Editore: Journal of Management, Anno edizione: 2018
Kolko J, Abductive thinking and sensemaking: The drivers of design synthesis, Editore: Design Issues, Anno edizione: 2010
Kolko J, Design thinking comes of age, Editore: Harvard Business Review, Anno edizione: 2015
Liedtka J, Perspective: Linking design thinking with innovation outcomes through cognitive bias reduction, Editore: Journal of Product Innovation Management, Anno edizione: 2015
Liedtka J, Why Design Thinking Works, Editore: Harvard Business Review, Anno edizione: 2018
Liedtka J, Putting technology in its place: Design thinking's social technology at work, Editore: California Management Review, Anno edizione: 2020
Magistretti S, Ardito L, and Messeni Petruzzelli A, Framing the Microfoundations of Design Thinking as a Dynamic Capability for Innovation: Reconciling Theory and Practice, Editore: Journal of Product Innovation Management, Anno edizione: 2021
Magistretti, S., Bianchi, M., Calabretta, G., Candi, M., Dell'Era, C., Stigliani, I., and Verganti, R, Framing the Multifaceted Nature of Design Thinking in Addressing different Innovation Purposes, Editore: Long Range Planning, Anno edizione: 2022
Magistretti S, Dell'Era C, Verganti R, and Bianchi M, The contribution of Design Thinking to the R of R&D in technological innovation, Editore: R&D Management, Anno edizione: 2022
Micheli P, Perks H, and Beverland MB, Elevating Design in the Organization, Editore: Journal of Product Innovation Management, Anno edizione: 2018
Micheli P, Wilner SJ, Bhatti SH, Mura M, and Beverland MB, Doing design thinking: Conceptual review, synthesis, and research agenda, Editore: Journal of Product Innovation Management, Anno edizione: 2019
Seidel V, and Fixson S, Adopting design thinking in novice multidisciplinary teams: The application and limits of design methods and reflexive practices, Editore: Journal of Product Innovation Management, Anno edizione: 2013
Verganti R, The Power of Criticism, Editore: Harvard Business Review, Anno edizione: 2015
Verganti R, and Dell'Era C, Design-Driven Innovation: meaning as a source of innovation, Editore: in Dodgson M, Gann D, and Philips N (eds.), The Oxford Handbook of Innovation Management, Oxford University Press, Anno edizione: 2014
Verganti R, and Norman D, Why Criticism Is Good for Creativity, Editore: Harvard Business Review, Anno edizione: 2019
Zurlo F, and Cautela C, Design Strategies in Different Narrative Frames, Editore: Design Issues, Anno edizione: 2014

Digital Business is the transformation of a company business generated by the Information and Communication Technology (ICT) and, more in general, by Digital Innovation. It can involve the internal processes, (e.g. the supply chain management, market relationship management, etc.), people and organization (e.g. digital capabilities, digital and agile organization, HR transformation), but also the entire business model. Digital Business means also the transformation of entire industries and supply chains, the creation of new sectors (e.g. those of Apps, eCommerce, etc.) and of completely new companies (i.e. Startups).
The objective of this course is twofold.
a) Understand context, functions, p rocesses and performance with refernce to the application digital innovation projects/solutions
b) Identify trends, technologies and key methodologies in the domain of digital innovation

a) With reference to objective a), in particular, s tudents will: 1) Understand and interpret the strategic role of digital innovation, the current competitive digital business environment and its evolution; 2) Learn and critically understand – form a strategic point of view - the most important “digital trends” affecting the business, the competitive environment and the industries, such as cloud, big data, Internet of Things, Artificial Intelligence, blockchain, digital marketing etc; 3) Know the main steps and methodologies to be exploited when launching a digital business (start up) or renewing a traditional business. In this light, a specific emphiasis will be given on the following methodologies: lean start up approach, business planning, business process reengineering, investment evaluation etc; 4) Know the main steps and methodologies to be exploited when supporting and innovating an existing business leveraging on digital innovation.
b) with reference to objective b), in particular, students will: 1) Identify and apply the appropriate tools and methodologies for digital business innovation; 2) Discern and select the appropriate strategic approaches and technology trends related to a digital business; 3) Identify the appropriate strategic methodologies and tools to launch a new digital business or renew an existing traditional business.

Strategic analysis applied to digital business. SWOT analysis, Value Chain, competitive advantage and competitive forces, strategic innovation and creativity (e.g. resource-based view and blue ocean strategy), business model design, digital disruption
Models, methodologies and tools enabling the launch of a new business and to compete in high tech contexts. Business model design through the business model canvas, the lean start-up approach, the start-up financing, resource gathering and allocation.
Digital-Driven analysis and Business Process reengineering. Methodologies, techniques, and tools to analyse and re-design processes, when launching digital projects in existing companies
Value Assessment models. How to develop a model to assess the value and impacts generated by Digital Innovation projects. Application of the methodology to real examples and case studies.
Digital Markets & New Business Models. A deep dive into the most important digital trends enabling the development of new markets. Digital Commerce, Mobile Content & Apps, Digital Payments, Mobile Enterprise, Social Networks, Cloud and ICT-as-a-service, Big Data, Internet of Things, Artificial Intelligence, etc.
Digital marketing. Advanced market research (how to use big data and data tracking to better understand the customer behaviour), Customer experience design (methodologies and tools to design multichannel customer experiences), Tool supporting marketing planning (methodologies and techniques to target customers and to develop customized marketing plans), KPI of a multichannel marketing plan (tools and techniques supporting customer accountability, development of scorecards to measure a multichannel marketing plan).
Digital Operations. eSupply Chain (automation and integration of the supply chain operative processes, e.g. logistics, sales, administration, etc.), Supply Chain Collaborative Planning (integrated and collaborative supply chain management, e.g. co-design, collaborative planning, etc.), Supply Chain Visibility (Internet of Things, tracing and visibility along the supply chain, anti-counterfeiting).
People and Organization. Digital capabilities assessment and strategy, digital and agile organization, smart working and new ways of working, employer branding, HR process transformation

Prova scritta obbligatoria, senza prove in itinere
ASSESSMENT (5 CFU)
The assessment will be based on a written exam at the end of the course.
Specifically, t he written exam will consist of questions covering all course content. Questions could refer to both theoretical concepts and short business cases (other than those discussed in class). Written exam grades range from 0 to 30 points. 18 is considered as the minimum threshold to pass the written exam. Students with a grade lower than 18 shall retake the written exam in any future call.

Ries, E. (2011). The lean startup: How today's entrepreneurs use continuous innovation to create radically successful businesses. Crown Books.
Downes, L., & Nunes, P. (2013). Big bang disruption.

Digital Business is the transformation of a company business generated by the Information and Communication Technology (ICT) and, more in particular, by new Digital Technologies based on Artificial Intelligence. It can involve the internal processes, (e.g. the supply chain management, market relationship management, etc.), people and organization (e.g. digital capabilities, digital and agile organization, HR transformation) but also the entire business model. Digital Business means also the transformation of entire industries and supply chains, the creation of new sectors (e.g. those of Apps, eCommerce, etc.) and of completely new companies (i.e. Startups). The objective of this course is twofold. First, it aims to provide the methodologies and tools to develop and assess Digital Innovation projects (in both existing and new companies/market). Second, it aims to create an arena in which students can apply the methodologies to real cases in different digital areas.
Objectives:
a. Understand context, functions,processes and performance (DdD1)
b. Identify trends, technologies and key methodologies in a specific domain (DdD2)
c. Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment (DdD3)

a) With reference to objective a, in particulars, students will:1) Understand and interpret the strategic role of digital innovation, the current competitive digital business environment and its evolution; 2) Learn and critically understand – form a strategic point of view - the most important “digital trends” affecting the business, the competitive environment and the industries, such as cloud, big data, Internet of Things, Artificial Intelligence, eSupply Chain, eProcurement, digital marketing etc. 3) Know the main steps and metholdologies to be exploited when launching a digital business (start up). In this light, a specific emphiasis will be given on the following methodologies: lean start up approach, business planning, etc. 4) Know the main steps and metholdologies to be exploited when supporting and innovating an existing business leveraging on digital innovation.
b) With reference to objective b): in particular, students will 1) Identify and apply the appropriate tools and methodologies for digital business innovation; 2) Discern and select the appropriate strategic approaches and technology trends related to a digital business; 3) Identify the appropriate strategic methodologies and tools to launch a new digital business or renew an existing traditional business.
c) With reference to objective c): in particular, students will 1) Integrate knowledge on digital innovation and technologies with business strategy and processes; 2) Manage the complexity of making judgements on digital business innovation and related social impact with limited information available. 3) Designsolutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment; 4) Develop new ideas and solutions in business and industrial scenarios evolving over time.

Change Management. Tool and techniques to design and lead change in the context of Digital Transformation
Business Process reengineering. Methodologies, techniques, and tools to analyse and re-design organisations processes, when launching digital projects in existing companies
People Strategies and Future of Work. Designing and implementing and effective strategy to align competences and organisations to the new challenges of digital Transformation
Digital and Agile Organisations. New Organisational Models for effective Digital Innovation, Agile Organisations
New ways of working. Designing and managing new ways of working enabled by Digital Technologies. Smart Working models. Effective use of collaboration tchnologies
People Engagement and motivation. How to understand, measure and improve People Engagement for effective digital Transformation.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
ASSESSMENT
The evaluation of the digital business innovation LAB is based on the evaluation of the project. The project will be carried out in groups of 3-6 students. Students work on some real projects proposed by existing companies.
Project evaluation
The evaluation will be based on three criteria: 1) Correctness in applying tools and methodologies; 2) Empirical Effort; 3) Usefulness for the company proposing the project or innovativeness of the new business idea proposed by students.

Ries E., The lean startup: How today's entrepreneurs use continuous innovation to create radically successful businesses, Editore: Crown Books, Anno edizione: 2011
Downes, L & Nunes, P., Big bang disruption, Anno edizione: 2013

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

The main expected learning outcomes for each of the following capabilities are:
1. Understand: the students will learn how the automation and digital technolgoies (i.e. Industry 4.0) are effecting the future manufacturing systems, both in the process industry as well as in the discrete manufacturing systems;
2. Identify: the students will learn how to select (i.e. identify) the best technology and the best application scenario;
3. Design: designing a manufacturing systems is a complex process which requires to deal with the hard, soft and organisational dimensions of the design of the system. Quantitative and qualitative techniques will be explained. The impact evaluation will also be assessed in order to give students the know-how on how to understand the impact of their decisions.

Part I – Advanced and Sustainable Manufacturing Strategies (9 hours)
1.1. Sustainable development: social, environmental, and economic megatrends — 3 hours
Examines the global trends reshaping industry and society, and how sustainability considerations are embedded into manufacturing strategy.
1.2. The role of manufacturing in the regional, national, and global economy — 3 hours
Analyzes how manufacturing drives economic growth, employment, and competitiveness across different geographic scales.
1.3. Manufacturing as a key enabler of Europe's societal challenges — 3 hours
Explores how manufacturing contributes to addressing major European priorities such as climate action, resource efficiency, and industrial resilience.
Part II – Digital Manufacturing in the Process Industry (9 hours)
2.1. Process control — 4 hours
Introduces the principles and tools used to monitor and regulate continuous production processes.
2.2. Control architecture typologies: monitoring, direct digital control, and supervisory control — 5 hours
Compares different levels of automation and control system architecture used in process industries.
Part III – Digital Manufacturing in the Discrete Manufacturing Industry (32 hours)
3.1. Design and management of Advanced Manufacturing Systems (AMS) — 6 hours
Covers the design principles and operational management of flexible, technology-driven production systems.
3.2. Real-time control systems: loading and dispatching approaches — 5 hours
Examines methods for scheduling and coordinating production activities in real time on the shop floor.
3.3. Introduction to industrial robots and humanoid applications in manufacturing — 5 hours
Provides an overview of robotic technologies, including humanoid robots, and their growing role in production environments.
3.4. Artificial Intelligence (AI) in manufacturing — 6 hours
Explores how AI techniques are applied to optimize processes, predict outcomes, and support decision-making in manufacturing.
3.5. Human-machine interaction — 4 hours
Studies how humans and machines collaborate effectively and safely within modern manufacturing systems.
3.6. Business case analysis (class work, seminars, etc.) — 6 hours
Applies course concepts to real-world industry cases through hands-on classroom activities and seminar discussions.

Prova orale obbligatoria
The final exam will be conducted orally. Each student will be asked a series of questions covering the topics addressed throughout the course, and will be expected to answer clearly and demonstrate a solid understanding of the material, including the ability to connect concepts across different parts of the syllabus. The exam typically lasts between 30 and 45 minutes per student, depending on the depth of the answers given. Students should be prepared to discuss theoretical concepts, provide examples, and, where relevant, work through problems or reasoning aloud. The final grade will reflect not only the accuracy of the answers but also the clarity of exposition and the ability to reason critically about the subject matter.

Il corso Diritto dell'energia è diretto a fornire agli studenti gli strumenti di base necessari per comprendere il quadro giuridico e i principi che governano la regolamentazione del mercato dell'energia. La norma giuridica è punto di partenza e di arrivo di un percorso interpretativo particolarmente complesso. Attraverso la lettura approfondita di alcune norme, gli studenti potranno comprendere le caratteristiche principali del ragionamento giuridico ed interpretare il funzionamento di un mercato in continua evoluzione. Ad una prima parte di carattere introduttivo generale, seguirà lo studio più specifico della regolazione giuridica con particolare riferimento al settore energetico, cui seguirà l'approfondimento dell'intreccio tra energia e ambiente, l'analisi di alcuni segmenti della filiera elettrica, il ruolo e i problemi delle FER, lo studio di casi giurisprudenziali e di atti adottati dall'Autorità di regolazione del settore.

Globalization has created new growth opportunities for companies by accessing resources and serving markets worldwide. This course focuses on the strategic and organizational challenges involved in managing activities across borders (e.g. different cultures, administrative systems, geographic distances) in an increasingly interconnected world. Students will be provided with analytical frameworks that help them to understand: Why firms do (or don’t do) international business? How do they do it? What are the international strategies firms use as they go overseas? How firms build a global presence by choosing countries, products and modes of entry? How firms organize for international business?
The course will combine the development of conceptual frameworks primarily through the lectures with the analysis and discussion of key cases in the classes. Guest speakers from industry will provide students with a strong overview of teh business reality.

The course fits into the overall program curriculum pursuing some of the defined general learning goals. Lectures and exercise sessions will allow students to:
Justifying the internationalization pattern of MNEs by implementing theories on the management of activities across borders through case studies;
Demonstrating how multiple global dynamics (i.e sustainability, digitalization, geopolitical shifts) have shaped the internationalization choices of MNEs in the last decade;
Identifying how International Business theories have impacted on MNEs development;
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members.

Economics and Management of Multinational Enterprises ( 5 CFU)
Prof. Marianna Marra
The players:
Firms: Multinationals
Countries: Global cities, geographical clusters
Individuals: Invenstors, scientistis, engineers. International migration and knowledge spillovers.
Theories of International Business.
Complexity and MNEs in the global economy.
MNEs and Innovation:
Introductory issues and data/indicators of Innovation.
R&D data and indicators.
Patent data and indicators.
Entry modes in the global economy
Location choices.
Host Countries' Knowledge Networks and Embeddedness.
Industrial policies and foreign direct investments.
Additionally, guest speakers from different indutries will help students in getting a better understanding of mutinationals operations.
Contacts
For further information, please send an email to: [email protected]

Prova scritta obbligatoria, senza prove in itinere
The course will include traditional lectures and discussions of real-world cases, as well as student group projects presented in class. The final grade will be based on (1) group presentations in class and (2) a written exam on the material presented in the lectures.
Students who do not take part in the group projects will have to take a more comprehensive final written exam.
For students who attend lectures during the first term
Student evaluation will be based on two items:
1) A group presentation in person (50%) during the course [group composition to be communicated by week 3 - Details on how this is evaluated will be available to students on WeBeep].
2) Written exam (50%), multiple-choice questions at the end of the course on selected material communicated during lectures.
For students who do not attend lectures:
Student evaluation will be based on one written exam (100%) during the formal exam session covering the entire program (compulsory and optional reading material).

Jonas Puck and Thomas Lindner, International Business: Mastering Strategic Challenges in the 21st Century, Editore: Sage Publishing, Anno edizione: 2025
Hall, B.H. and Rosenberg, N., Handbook of the Economics of Innovation, Editore: Elsevier, Anno edizione: 2010
Moretti, Enrico, The new geography of jobs, Anno edizione: 2012 https://sbi.sydney.edu.au/wp-content/uploads/2017/03/JIBS2013.pdf
Brass, Daniel, New Developments in Social Network Analysis/ Annual Review of Organizational Psychology and Organizational Behavior, Anno edizione: 2022, Fascicolo: 9: 225–46
Exequiel Hernandez, Jason K. Lee, J. Myles Shaver, Toward an improved causal test of network effects: Does alliance network position enhance firm innovation? Strategic Management Journal, Anno edizione: 2022 https://sms.onlinelibrary.wiley.com/doi/full/10.1002/smj.3679
Freeman, C., The National System of Innovation in historical perspective/Cambridge Journal of Economics, Special Issue on Technology and Innovation (February 1995), pp. 5-24, Anno edizione: 199, Fascicolo: 19(2) https://sbi.sydney.edu.au/wp-content/uploads/2017/03/JIBS2013.pdf
Barabasi, L., Emergence of Scaling in Random Networks/ Science, Anno edizione: 1999 https://networksciencebook.com/chapter/5#barabasi-model
Arpit Raswant, Bo Bernhard Nielsen, Peter J Buckley, Space: a new frontier for international business/Journal of International Business Studies, Anno edizione: 2025 https://sbi.sydney.edu.au/wp-content/uploads/2017/03/JIBS2013.pdf
Fagerberg, Jan, Mowery, David C. and Nelson, Richard R. (, Innovation Handbook. Chapter 22. Pages 599-631, Editore: (Oxford: Oxford University Press, Anno edizione: 2005
Maryann P. Feldman, Dieter Franz Kogler, Handbook of the Economics of Innovation (pp.381-410) Chapter: Stylized Facts in the Geography of Innovation Hall B. and Rosenberg N., Editore: ElsevierEditors
Dany Bahar Prithwiraj Choudhury Sara Signorelli James M. Sappenfield, Talent Flows and the Geography of Knowledge Production: Causal Evidence from Multinational Firms, Anno edizione: 2022
Heather Berry, The Influence of Multiple Knowledge Networks on Innovation in Foreign Operations, Organization Science, Anno edizione: 2018
Anthony Goerzen, Christian Geisler Asmussen, Bo Bernhard Nielsen, Global cities and multinational enterprise location strategy, Journal of International Business Studies, Anno edizione: 2013 https://sbi.sydney.edu.au/wp-content/uploads/2017/03/JIBS2013.pdf

This course is designed to provide students with the concepts and instruments necessary for a) assessing from an economic perspective the adoption of technologies in the renewable energy, energy efficiency and digital domains; b) understanding the impact of emerging societal, technological, economical and regulatory-political trends on the business models of companies in the energy value chain; c) understanding and analysing industrial practices in terms of their energy performance and identifying the potential of energy-efficient technologies and services within the energy value chain.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance.
Identify trends, technologies and key methodologies in the energy sector.
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

A student that has successfully attended the course is expected to:
Know the fundamental principles of energy use and efficiency.
Understand and interpret the impact of energy efficient technologies and services on economic and environmental performance of companies.
Be able to identify and apply appropriate instruments for economic evaluation of investments in the energy transition domain
Be able to identify emerging trends in the energy sector and their implications in terms of managerial and organizational issues.
Be able to understand the impact of emerging societal, technological, economical and regulatory-political trends on the investments evaluation in the energy transition domain

Economic assessment of investments in Renewable Energy Sources: Advanced tools and methodologies of economic assessment of investments in renewable energy domain (solar, wind).
Economic assessment of investments in Energy Storage Systems and other enabling technologies: Advanced tools and methodologies of economic assessment of investments in energy related industries.
Energy Scenarios and emerging business models: societal, technological, economical and regulatory-political trends affecting the investment evaluation in the energy domain: the case of energy communities.
The course leverages the following teaching methodologies:

• lectures,
• in-class exercises
• project work on a company problem
• regular project progress reviews and discussions.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The final course evaluation is based on the development of a Project work. The project should take the form of a systematic analysis of industrial practices by making use of the concepts and instruments discussed in class.; it is to be implemented in a group of 4-5 students. The project is intended to evaluate a student’s ability to critically analyse a novel problem and discuss possible alternative solutions, by integrating different perspectives and contributions emerging in the team. students will need to submit the final report for evaluation at the end of the semester.
Composition of the final grade: Project work (the report and the presentation) = 100%.

The course is meant to provide frameworks, models and tools to understand the early-stage financing of (innovative) privately-held entrepreneurial firms. The course will actively engage students in an experiential learning process. The instructors will provide theory and empirical evidence on entrepreneurial finance as well as the methodology commonly applied in this context. Guest speakers, such as venture capitals, business angels, crowdfunding platform mangers and entrepreneurs will share their practical experience with the class. Teamwork activities are designed to involve students actively.
The course contributes to the development of the following general learning goals:
Describe the context and the actors involved in the entrepreneurial finance ecosystem;
Understand the functions and the decisions of entrepreneurs and managers of financial intermediaries as regards early-stage financing of (innovative) privately-held entrepreneurial firms;
Identify and apply the key methodologies to assess the valuation of (innovative) privately-held entrepreneurial firms;
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to overcome the specific challenges of (innovative) privately-held entrepreneurial firms in accessing entrepreneurial finance, in a context of case study discussion;
Interact in a professional, responsible, effective and constructive way in a team-based working environment, also motivating group members.

At the end of the course, after passing the exam, the students will be able to:
Describe the key players and compare their roles within the entrepreneurial finance ecosystem;
Identify the challenges that (innovative) privately-held entrepreneurial firms face in accessing early-stage financing;
Apply theory and empirical evidence on entrepreneurial finance to identify the best financial decision among several options, in the context of multiple-choice tests based on case studies;
Explain and discuss the decisions of (innovative) privately-held entrepreneurial firms as regards access to early stage finance, in the context of (team-based) in-class case study discussions (case study assignment);
Design and propose appropriate strategies to alleviate the challenges for (innovative) privately-held entrepreneurial firms in accessing early-stage financing, in the context of (team-based) in-class case study discussions (case study assignment);
Estimate the valuation of (innovative) privately-held entrepreneurial firms by identifying and applying the proper key valuation methodologies, in the context of a (team-based) valuation assignment (valuation assignment);
Interpret team working dynamics and develop leadership, negotiation skills, and conflict management ability, in the context of team-based valuation assignment and case study discussions;
Develop communication skills to communicate the key concepts of their assignments in a public context, i.e. in front of the class, as well as in a written document (valuation assignment / case study assignment).

The course includes:
Lecture sessions: they aim at illustrating, sharing and discussing models, conceptual frameworks, tools and empirical evidence;
In-class case study discussions: they aim at making students apply the insights from theory and empirics to make financing decisions in real world-like situations. Students have to read case study materials in advance and have to prepare presentations and discuss a case in team.
Teamwork valuation assignment: it aims at making students learn how to estimate the valuation of (innovative) privately-held entrepreneurial firms by identifying and applying the proper key valuation methodologies
Testimonials: guest speakers (entrepreneurs, venture capitalists, business angels) are invited to share their practical experience with the class.
Course Detailed Program:
Introduction to entrepreneurial finance
Bootstrapping and debt financing
Independent VC finance
Valuation of entrepreneurial firms
Exit strategies
Corporate VC finance
Governmental VC finance
Crowdfunding, ICOs & Business Angels
Incubators and Accelerators

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The final evaluation depends on the students’ status (attending, non-attending).
Attending students (i.e., students that come regularly to class for at least 70% of the lectures and actively participate in the in-class activities described below) will be tested through:
Final exam (50%): The final exam consists in written-based closed questions to mini case studies in multiple choice format. After the first call, the final exam will be oral. The final exam aims at testing students’ ability to:
apply the theory and empirics discussed in class to identify the best financial decision among several options, as regards early-stage financing of (innovative) privately-held entrepreneurial firms;
interpret and understand the reasons behind the decisions of entrepreneurs and managers of financial intermediaries as regards early-stage financing of (innovative) privately-held entrepreneurial firms, in light of the theory and empirics discussed in class;
Case study teamwork assignment and presentation (25%): The case study teamwork assignment is mandatory and consists of the analysis of a business case study provided by the instructor. The team will present the case study analysis in class, followed by questions and discussion. Each team will present only one case study, but everyone is required to read all case studies in advance and actively participate in each discussion. With the case study group assignment, students must show that:
they can apply theory and empirics presented in class to interpret the decisions of entrepreneurs and managers of financial intermediaries as regards early-stage financing of (innovative) privately-held entrepreneurial firms;
they can summarize and communicate the key concepts of their analysis in a public context (i.e., presentation in front of the class) as well as in a written document;
they can work effectively in teams.
Valuation teamwork assignment (25%): For the valuation teamwork assignment, students will select an entrepreneurial venture following the guidelines of the instructor and will prepare a mandatory team-based 2-pages report assessing the valuation of that entrepreneurial ventures by applying the key methodologies presented during the course. With the valuation teamwork assignment, students must show that:
they can estimate the valuation of (innovative) privately-held entrepreneurial firms using key methodologies;
they can summarize and communicate the key concepts of their valuation exercise in a written document;
they can work effectively in teams.
Non-attending students (i.e., the students that do not classify as attending due to their impossibility to regularly attend lectures, e.g. working students) will be tested through:
Final exam (50%): The final exam consists in an oral discussion of case studies presented at the beginning of the exam by the instructor. The final exam aims at testing students’ ability to:
apply the theory and empirics discussed in class to identify the best financial decision among several options, as regards early-stage financing of (innovative) privately-held entrepreneurial firms;
interpret and understand the reasons behind the decisions of entrepreneurs and managers of financial intermediaries as regards early-stage financing of (innovative) privately-held entrepreneurial firms, in light of the theory and empirics discussed in class;
Case study individual assignment (25%): The case study individual assignment is mandatory consists in the analysis of a business case study provided by the instructor. Students are asked to prepare an individual 2-pages document to synthesize the most important aspects of the analysis of their own case. With the case study individual assignment, students must show that:
they can apply theory and empirics presented in class to interpret the decisions of entrepreneurs and managers of financial intermediaries as regards early-stage financing of (innovative) privately-held entrepreneurial firms;
they can summarize and communicate the key concepts of their analysis in a written document;
Valuation individual assignment (25%): For the valuation individual assignment, students will choose an entrepreneurial venture with the guidance of the instructor and will prepare a mandatory 2-pages report assessing the valuation of that entrepreneurial ventures by applying the key methodologies presented during the course. With the valuation individual assignment, students must show that:
they can estimate the valuation of (innovative) privately-held entrepreneurial firms using key methodologies;
they can summarize and communicate the key concepts of their valuation exercise in a written document;

The course is conceived as an experiential based learning process, where students acquire frameworks, models and tools to develop their business mainly from the experience and advising of practitioners, i.e. entrepreneurs, venture capitalists, business angels, incubator/accelerator’s managers, with whom the course is designed. The faculty will provide a core of preliminary concepts through frontal lectures on high-tech start-ups’ creation and funding, after that the students will start to work in teams on their own business models, receiving inputs and feedbacks from practitioners, who participate as guest speakers, and throughout tutoring sessions.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand and design solutions, applying a scientific and engineering approach, in relation to the setting up of a new business, the design of its business model, and the identification of the proper funding channels
Interact in a professional, effective and constructive way in teams and with external practitioners

At the end of the course, the students will be able to:
Comprehend the functioning of the entrepreneurial ecosystem
Understand what is a business model and its building blocks
Identify the key challenges for the creation of high-tech start-ups and the funding mechanisms available, and understand when it is appropriate to use each of them, according to the specific start-up’s industry, funding requirements and stage of the life cycle.
Through the project work, the students will also be able to:
Test and validate the business model in the real world with potential customers
Write an effective business proposal to ask for funding (i.e., to business angels, venture capitalist, incubator programs..)
Effectively work in teams
Interact with practitioners of the entrepreneurial ecosystem
Summarize and present the results achieved in the business proposal in front of potential investors clearly and convincingly.

The course program includes the following topics:
The creation of high-tech start-ups. Entrepreneurship in high-tech industries and high-tech start-ups in Italy and in the world
The development of of high-tech start-ups, and their performances, including the success factors
The Business Model: what is a business model and how to fund it through equity capital, debt capital and public subsidies
How to design the Business Model: the value proposition and business model testing; the use of the Business Model Canvas framework; organizational structure and management; market strategy and market positioning; competitors’ analysis; how to protect competitive advantages; business model risk assessment
The financing of high-tech start-ups: a series of guest speakers, including entrepreneurs, venture capitalists, business angels, incubator/accelerator’s managers, will bring their direct experience through success stories regarding the funding (and creation) of high tech start-ups (entrepreneurs) and explaining their decision-making and investment process (investors)
How to design and perform an effective elevator pitch.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Students must identify a new business idea based on an innovative technology (e.g., the result of current scientific research) or an innovative way of doing business in an incumbent business (e.g., innovative business model), form an entrepreneurial team, create a document describing the business model and prepare an "elevator pitch".
The exam consists in the evaluation by the faculty and by a commission of practitioners (including guest speakers of the course) of the document describing the business model and the presentation of the document in front of the same commission of practitioners ("elevator pitch").
In the exam the students must show that:
They have a good comprehension of the challenges in creating and funding a new start-up and how financial intermediaries and other actors of the financial ecosystem may support the start-up’s development
They understand how the business model is articulated, and are able to properly build one, tailored to their business idea
They have effectively validated the business model developed, in the real world, and they are able to select the appropriate funding channels
They are able to summarize and communicate the key concepts of their business model in a public context.
During the tutoring sessions, as well as in the exam, the students must also show that:
They are able to effectively work in teams
They are able to take advantage of the advise provided by practitioners and guest speakers.
Participation in the final presentation is mandatory, while participation in the tutoring sessions is optional but highly recommended.

1. Understand the distinctive strategic and managerial factors distinguishing the family business form of orgnization, and the impact of those factors on business performance
2. Design solutions to strategic problems in family firms, applying a scientific and engineering approach based on rigorous models and frameworks
3. Present strategic solutions in a family business organization in a professional, responsible, effective and constructive way, also working effectively within a group

At the successful completion of the course, students will:
DdD 1: Knowledge and Understanding
Know the fundamental principles, generalizations, theories, and concepts related to family influence on business
Understands the functioning and characteristics of family enterprises and their strategic and managerial implications
DdD 2: Applying Knowledge and Understanding
Be able to apply rigorous methods to assess the role of families in creating and sustaining competitive advantages and disadvantages
Be able to articulate a family firm's vision, mission, values, and goals
Be able to predict and explain how family enterprises change and evolve over generations and how they may succeed in disruptive environments
Be able to systematically evaluate and choose between different strategies and courses of action in the family enterprise
Be able of developing critical evaluations of the strengths and weaknesses of family enterprises in context
DdD 3: Making Judgements
Be able to handle problems not strictly related to the issues addressed in the degree program by making well-founded decisions and understanding the specific dynamics of family enterprises
DdD 4: Communication Skills
Be able to communicate the results of their analysis and evaluation of family enterprises clearly and convincingly, articulating vision, mission, and strategies
DdD 5: Learning Skills
Be able to make strategic and project choices for family enterprises based on a deep and critical understanding of their dynamics
Be able to make and communicate project choices in the field of family enterprises, demonstrating continuous learning and adaptation to new contexts and challenges

Family-owned companies are highly prevalent across countries and industries, ranging from small to large, from local to multinational, from privately-held to publicly-traded family business groups.
For long time, family companies have been the engine of the world’s economic growth and development. Today, however, their traditional strengths are put into question by fast-changing global competition and technology disruptions. Moreover, recent research suggests that about 30% of family companies in Europe will undergo generational succession within the next 10 years.
This new course will help you understand and implement the driving factors that help family companies succeed and thrive in the digital age.
Whether you are part of a business family, or whether you intend to work with a family company as a non-family manager, consultant, investment banker, private banker or in other roles, you will gain important insights about how to leverage the strengths of family companies, address their inherent vulnerabilities, and sustain their competitive advantage over time
Course contents include:
The future of family firms in the 21st century: Definitions of family business; Types of family firms; Impact of demographic and societal changes on family firms.
Designing effective governance for the family enterprise: Definition of corporate governance; Differences in corporate governance between family and non-family firms; The relationship between corporate governance and firm performance; Key constitutes of family and business governance.
Succession planning and generational change: Internal and external succession options in family firms; Assessing the successor’s fit and readiness; Planning and executing a succession plan.
Professionalization: Professionalization defined; Internal and external dimensions of professionalization in family firms; The impact of professionalization on firm growth and performance.
Managing resources, capabilities, and competitive (dis)advantages in family firms: The effect of family ownership and management on firm performance; Resources and liabilities of family firms; The success paradox; Assessing competitive advantage in family firms; Building sustainable competitive advantage in family firms.
Strategy formulation and execution in family business: Family business strategy defined; Drivers of strategic decision making in family firms; The role of financial wealth and socio-emotional wealth considerations in family business strategy.
Financing issues in family firms: Advantages and disadvantages of family business finance; Financing options in family firms; Financing growth in family firms; venture capital, private equity and public stock markets (IPO).
Managing innovation in the family enterprise: Opportunities and challenges for family firm innovation; Innovation Through Tradition (ITT); Innovation and generational change in family firms.
Family Offices: The evolution from family business to business family; Types of single and multi family offices; Strategizing on family wealth.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Altro
Project work (15 points)

• Each group of 4–5 students will analyse an assigned family business, using only verifiable public sources
• Students will conduct an initial assessment of the company across the six main dimensions covered in the course and identify two priority challenges
• The project must include:
  1. A concise overview of the company, the family, the ownership structure, the governance system and the business model
  2. An assessment of the company across the six dimensions covered in the course
  3. The selection and in-depth analysis of two priority challenges, supported by relevant evidence
  4. The evaluation of alternative strategic options
  5. An integrated and actionable recommendation addressing both challenges, including an implementation roadmap, key risks and conditions for success
• The final deliverable is a self-standing presentation deck of no more than 20 slides, to be submitted and presented at the end of the course
• All sources must be clearly cited
  Optional mid-term case studies
• Two optional case studies will be presented and discussed in class during the course
• For each case, students will apply the same analytical approach used for the project work and submit a concise presentation deck of 5–6 slides, including the company and challenge framing, analysis and proposed solution
• Each case study may award up to 1 additional point on the final project work grade, for a maximum of 2 additional points
• Non-participation does not result in any penalty
  Written exam (15 points)
• Aimed at assessing overall understanding of the main course contents and the achievement of the course's learning objectives
• Multiple choice questions & open questions

Thomas Zellweger, Managing the Family Business: Theory and Practice, Editore: Edward Elgar, ISBN: 9781783470709 https://www.e-elgar.com/shop/family-business-in-theory-and-practice

The course aims to provide students with an integrated understanding of technological innovation and corporate finance transactions in the financial services industry. It combines conceptual frameworks with practical applications in M&A, Private Equity and LBO, and Fintech. Particular emphasis is placed on the ability to interpret market and regulatory developments, assess companies and transactions, and make financial decisions under incomplete information and potentially conflicting stakeholder interests.
The course also aims to develop students’ analytical, modelling, communication and negotiation skills through case discussions, spreadsheet-based exercises and business simulations

At the end of the course, students will be able to:
analyse the strategic rationale, structure and main stages of an M&A transaction;
apply basic company valuation methodologies and estimate reservation prices in an acquisition context;
explain the structure and economics of PE and LBO;
assess the financial sustainability of an LBO, considering valuation, debt financing, value creation and exit assumptions;
develop and interpret spreadsheet-based financial models;
communicate financial analyses through concise reports, presentations and investment memorandum;
work effectively in teams and negotiate with stakeholders having different objectives and information;
define and classify Fintech innovations and identify their main technological, business and regulatory drivers;
explain the evolution from Open Banking to Open Finance and assess the role of APIs, data sharing and digital platforms in financial services.

The Finance Lab provides a unique opportunity to go in depth into the financial matters illustrated over the track, with an experimental approach and an integrated logic. The theoretical contents are complemented by case studies, exercises and simulations.
The topics introduced in this part of the Finance Lab are:
M&A
Strategic rationale, main transaction structures and key stages of buy-side and sell-side M&A processes.
Company valuation, due diligence, synergies, transaction documentation and negotiation.
PE and LBO
Private Equity funds, investment processes, portfolio management, value creation and exit strategies.
LBO structuring, company valuation, debt financing, financial sustainability and investors’ returns.
Fintech and digital finance
FinFintech business models, enabling technologies and applications in banking, payments, investment services and insurance.
Open Banking and Open Finance, digital finance regulation, data sharing and innovation ecosystems
Students will have also the opportunity to develop a project work (mandatory), in cooperation with banks, financial and industrial companies, where students could experience the real life of a career in finance.
Students are expected to attend classes regularly, prepare the assigned materials and participate actively in exercises, discussions and simulations. Detailed instructions and deadlines will be communicated through WeBeep.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua facoltativa (a scelta dello studente)
For all students, it is mandatory to successfully pass the assignments of FINANCE LAB [MOD. 1], the three assignments of this part, and the project work.
Detailed assessment criteria and role-specific rubrics will be communicated before each assignment.
The final grade of the Finance Lab is composed as follows:
25% of the grade based on FINANCE LAB [MOD. 1] assignments
25% of the grade based on 3 class assignments on this part (equally weighted) [details below]
50% PW, to be developed in group of 5-6 students, jointly with a company (selected by Professors); the project work will deal with the contents of the course, applied in a real-world context, and the students are expected to deliver a final report; each group will be assigned a Tutor. IMPORTANT: Grading is based on the work that the students accomplish from April to June in a project provided by one company that participates in the lab. It is consequently not possible for students to take the project work or be graded at another time of the year, or to propose a company or project selected by them.
The grade of this part assignments will be as follows:
ALTERNATIVE 1 - Students attending the course on a regular basis
Assignment 1 – group based, individually graded
Assignment 2 – group based, group graded
Assignment 3 - indivually based, individually graded
ALTERNATIVE 2 - Students missing one or more lectures
These students have to retake each of the three assignments during regular calls. While assignment 3 will remain the same, Assignment 1 and 2 will be based on a case to be solved individually (written exam).

Scaling up the FinTech business: Competition, regulation & data management https://doi.org/10.1016/j.jeconbus.2022.106085
Do we still need financial intermediation? The case of decentralized finance - DeFi https://doi.org/10.1108/QRAM-03-2021-0051
How does a data strategy enable customer value? The case of FinTechs and traditional banks under the open finance framework https://doi.org/10.1186/s40854-022-00378-x
Examining insurance companies' use of technology for innovation. https://doi.org/10.1057/s41288-021-00258-y
Translating technological innovation into efficiency: the case of US public P&C insurance companies https://doi.org/10.1007/s40821-021-00189-7
A strong year for banking-as-a-service in Europe https://www.thebanker.com/World/Western-Europe/A-strong-year-for-banking-as-a-service-in-Europe

The course aims to let Students to:
Understand roles and functions of financial markets and how they support the real economy;
Know what are the major activities of banks and other financial institutions;
Share the impact coming from digital innovation and sustainability on financial markets and institutions.

At the end of the course, Students will be able to indicate and understand:
how financial systems and financial intermediaries operate;
what are the main figures of banks and financial institutions and how they are related to the businesses;
main trends related to the financial and digital innovation and sustainability.

OVERVIEW
The course focuses on financial markets and institutions. In particular, it concentrates on the features, the objectives, the role and the typologies of financial markets and of the different categories of financial intermediaries and institutions. A major attention will be dedicated on banks. Moreover, some lectures will provide insights about the banks P&L, their supervision and regulation and the Banking Union. The course will also focus on the asset management industry and on corporate governance and sustainable value creation. All the items will include a description about how the digital transformation and the fintech as well as sustainability are playing a major role on financial markets.
CONTENTS DESCRIPTION
Fundamentals of the financial system
Financial and economic systems
Financial markets and institutions
The theory of financial intermediation
Fintech and digital transformation
Financial markets and instruments
Securities: bonds, equity, derivatives, forex
Banks: structure, supervision and management
Banks
Bank supervision, prudential regulation and the Banking Union
Banks P&L, economic and financial equilibrium, asset liability management
Banks risk management: RAF and IXAAP
Asset management
Industry value chain (players, products, relationship with other intermediaries…)
ESG investing
Corporate governance and sustainability
Internal and external governance
Governance and sustainable value creation
ORGANIZATIONAL ISSUES
The contents are provided through class lectures, which consist in both theoretical lessons and exercises. Lectures have a strong correspondence with the suggested textbook. Students should attend class regularly and actively participate, contributing to class learning and discussion. Some sessions will be given through practitioners coming from the most important and highly-reputed financial risk management departments.

Prova scritta obbligatoria, senza prove in itinere
Individual written test at regular calls.
Students may re-take the exam in any regular exam session, as many times as they wish; doing so requires formally rejecting the previous grade.

A. Saunders, Financial Markets and Institutions., Editore: McGraw Hill, Anno edizione: 2021

The aim of the course is the analysis of the instruments to finance complex projects in the infrastructure sector (i.e. energy, transport, real estate, healthcare). The course will introduce the role of infrastructure investments as driver of growth and will cover the structure and the characteristics of the structured finance transactions, in terms of financial structure, technical characteristics, players involved, risk analysis, capital budgeting and valuation. In the course, students will analyze the specific characteristics of instruments to finance infrastructure and to cover risks during the construction and operating phases. During to the course guest speakers will share their practical experience on infrastructure and project finance projects.

At the end of the course, students will be able to analyze financial characteristics of complex projects, to identify key elements of the deal and identify proper solutions for deal structuring with financial prospective.

Introduction: the role of complex projects as alternative investment asset. Taxonomy of project and infrastructure finance. Key features of infrastructure assets
Structure and characteristics of project finance deals
The role of the parties involved in complex project financing: banks, sponsors, syndication
The risk profile of complex projects: identification and mapping and instruments to manage risks
Capital budgeting of infrastructure
Financial valuation for project finance

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Valutazione continua facoltativa (a scelta dello studente)
Students will be graded based on:
a Final Written Exam
a Business Case;
Case Studies.
The Final Written Exam
The Final Written Exam will be composed by:
open-ended essay questions;
short exercises;
multiple choice questions (MCQ). No penalties will be deducted for a wrong pick.
The Business Case
The Business Case will be executed by groups of students and it will be presented after the mid-semester break. Its reports will be delivered and presented orally to the class by the last sessions of the course.
Case Studies
Throughout the semester, a few Case Studies will be presented to support class discussion. Short written reports will be prepared by the students, prepared in-class or as a quick take-home homework, as individuals or in groups, on a case-by-case basis. Details on each Case Study that contributed to this portion of the examination will be announced in class and on WeBeep. The Case Studies’ overall score will be based both on the quality of the deliverables and on the student’s in-class participation.
The mimimum pass grade is 18, with no separate minimum threshold for the three components of the final score. Please consider that students that do not participate in the group Business Case or in the Case Studies, and who do not meet the requirements to sit the test as an eligible student (more detail in the Syllabus) will be awarded 0 points in the Business Case and 0 in the Case Studies, but they will still be allowed to sit the Final Written Exam.

Slides and case studies available on Beep
S. GATTI, Project Finance in Theory and Practice, Editore: Academic Press, Anno edizione: 2018
Note: III Edition

This laboratory is designed as a training arena based on learning by doing.
The laboratory aims to provide students with concepts and instruments for new sustainability and global social challenges. Students will explore and become familiar with business models and corporate strategies through new managerial approaches, new forms of collaboration, innovative technology, and product and process innovation.
In particular, the students will study and apply tools to analyse and manage corporate sustainability strategies, social innovation processes, sustainability and impact integration in new hybrid organizations, new social business models, innovative scaling strategies, as well as partnerships among different actors of the purpose-driven economy.
Students will work hands-on dealing with profit companies, hybrid companies, social enterprises, and non-profit organizations as a core and innovative part of the Lab, with the goal of mastering the evolution of sustainability and impact integration.
Finally, classroom-based, collaborative (small-group) sessions will provide students with an opportunity to apply concepts, methods, and tools acquired throughout the course
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
Develop new ideas and transformative solutions to deliver a positive impact on business, industrial and societal scenarios evolving over time
Interact in a professional, responsible, inclusive, effective and constructive way in a working environment, also motivating group members

At the end of the course, the student will gain the following skills:
Ability to understand sustainable and social challenges and identify appropriate and innovative solutions, through an impact assessment of the options and a critical review of the results.
Ability to analyze the role of technological innovations in meeting the emerging societal needs.
Ability to understand a business scenario and develop solutions to improve social and sustainability impact by applying new impact strategies and assessing the implications in the short and long term.
Ability to re-interpret the traditional managerial tools to manage the impact integration process
Ability to apply different impact management models for different organization forms, to improve the scalability and non-financial performance.
Ability to present solutions and ideas professionally and constructively, fostering the value of teamwork, and using a language adequate to both managers and fellow students

I – GLOBAL SUSTAINABILITY AND IMPACT INNOVATION
Introduction to sustainability, impact and purpose-driven innovation
Global sustainability challenges and their social, environmental and economic interconnections
Sustainability transitions across advanced and emerging economies
The role of social innovation and the social economy in addressing societal challenges
II –SUSTAINABILITY AND IMPACT MANAGEMENT
Hybrid organizations and purpose-driven enterprises
Innovation-driven business models capable of managing environmental, social and economic trade-offs
Circular economy principles and their application to sustainable business model innovation
Managing social, environmental and technology-enabled innovation
Strategies and tools for scaling impact through multi-stakeholder collaboration across different geographical, institutional and organizational contexts
The Social and Sustainable Business Model Canvas
III – SUSTAINABILITY AND IMPACT MEASUREMENT
Sustainability and impact measurement approaches, standards and tools
Processes for managing and measuring social, environmental and economic impact
Multi-stakeholder perspectives on impact measurement, involving businesses, financial actors, public institutions, hybrid organizations and non-profit organizations
The use of impact evidence to support accountability, organizational learning and decision-making
IV – TRAINING ARENA
Group Project work: participation in real-world projects developed in collaboration with companies, hybrid and purpose-driven organizations, social enterprises, non-profit organizations, public administrations and financial institutions

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The final exam will be composed of four different parts:
Project work evaluation
Peer evaluation of the group activities
Presentation of the project work
Short final exam on the content of the class lectures
The final project is to be submitted at the end of the semester
Bibliography
A Primer will be provided as well as additional readings and case studies during the course.

"Obiettivo del corso è di introdurre alla gestione degli asset industriali come una metodologia integrata per ottimizzare la gestione degli asset fisici lungo il ciclo di vita. Definita oggi come "le attività coordinate di un'organizzazione per generare valore dagli asset" (ISO 55000), l'Asset Management offre un focus primario su una prospettiva strategica di lungo termine, orchestrando decisioni e attività nei vari stadi del ciclo di vita degli asset industriali. Il corso indirizza l'evoluzione della disciplina nella gestione attraverso diversi settori, includendo gli impianti manifatturieri, le flotte di asset, le infrastrutture come casi di applicazione.
Una particolare attenzione sarà data alle capacità per una pratica sistematica e coordinata al fine di una gestione sostenibile degli asset fisici di una organizzazione, e di prestazioni, rischi e costi associati lungo il loro ciclo di vita, con l'obiettivo di contribuire al raggiungimento del piano strategico organizzativo. Questo è possibile grazie alla co-evoluzione dei bisogni e requisiti, nuove pratiche nelle operations, e l'uso di tecnologie abilitanti specialmente dovute alla digitalizzazione. Il corso combina pratiche tecnologiche, organizzative, manageriali per un approccio ingegnerizzato alla gestione del ciclo di vita, focalizzandosi sulla valutazione di prestazioni e costi in scenari incerti, e considerando requisiti di affidabilità, disponibilità, qualità, sicurezza, e produttività di sistema."

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members

The student successfully taking this course is expected to be able to:
Understand the context, and the problem to solve / opportunity to improve
Carry on first hand a consulting project in a real company
Apply scientific methods and tools to collect data, analyse them in a structured way so to find the root causes of the problem, design countermeasures through creative thinking, implement them, check the results and take consequent actions
Interact with other members of the team that is working on the problem, and with the other people involved, in a constructive way

LAB IMPROVEMENT PROJECT
Students work in groups, and to each group will be assigned a consulting project in a Company, a Company tutor and a Methodological tutor. The content of the project will be to solve a problem/make improvements in the area of Industrial Management of manufacturing, service, or consultancy companies. The methodological tutor will coach her team meeting them once a week to help them learn and get the most out of the extraordinary experience
Each group is responsible to set the targets, together with the company, and to carry out the project at the best of its capabilities, following the A3 metodology.
The project is also designed to dramatically increase self confidence and leadership skills of the participants.
The overall effort required is about 250 hours per person

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua obbligatoria
Group project work in managing improvement and innovation (groups of 2 members)
The students address a practical problem in a company, and the evaluation is based on two aspects: one is related to the output, though the evaluation of a final report and the feedback from the company (understanding of the project, correctness of tools applied, and effectiveness and efficiency of the solution implemented). The other aspect is related to the process, i.e. how the project has been carried out, how problems and perturbation have been handled, and how relationships with the teammates and the other people involved have been managed. This evaluation is performed considering the feedback by the Methodological tutor that supervises the group work, meeting with the team once a week, and the feedback of the company tutor, who also meets the team frequently during the project. This allows a continuous evaluation together with the final evaluation.

The lab challenges the students to move from learning to action and accomplish a real-life innovation project in a company. Particularly, the learning goals are as follows:

• Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment.
• Develop new ideas and transformative solutions to deliver positive impact on business, industrial, and societal scenarios evolving over time.
• Interact in a professional, responsible, inclusive, effective, and constructive way in a working environment, also motivating group members.
  At the beginning of the spring term, the students are assigned to teams of 2 members.
  Each team is assigned to a partner company and to a competent academic tutor. The company provides a project with a set of deliverables or KPIs that the students are expected to accomplish.
  The students work at the company’s premises approximately once/twice a week for 15 weeks from March to June. During this period, they report on a weekly basis to the company tutor and the academic tutor. They attend two meetings in classroom, which provide them with methodological tools to address their project and to communicate effectively. In late April, the students discuss their progress towards the goals in a midterm presentation to the professors, and gain feedback useful to complete the work.

Applied knowledge and understanding (DdD 2):

• Understand the "double-diamond" and its application to a real-life company project.
• Understand a real company organization structure, and its decision-making processes.
• Interact in a professional, responsible, effective, and constructive way in a working environment, practising self-discipline, teamwork and professional attitude.
• Identify the needs of real company projects, by applying the most appropriate concepts, tools and practices with rigorous analytical skills.
  Authonomy of judgement (DdD 3) and learning (DdD 5):
• Identify the spectrum and pros/ cons of alternative solutions.
• Develop and deliver a creative practical solution that fits the company's needs and meets its goals within the project timeline.
  Communication skills (DdD 4):
• Identify the sub-audiences of communication and its different sets of goals.
• Design and deliver effective communication - in written and oral form - that fits the needs of the different sub-audiences identified.

IN-CLASSROOM ACTIVITY: Students meet in class only 4 times.
1- Kickoff meeting. During the kickoff meeting, the students receive instructions concerning the organization of the activities and form the teams
2- Methodological meeting. During the second meeting, the tutors explain the "double diamond" method to be used to tackle the company project
3- Communication seminar. During the third meeting, organized before the midterm presentation, the professors explain how to communicate effectively in professional meetings.
4- Q&A session. It is organized before the midterm presentation to allow discussing and solving any potential issue encountered by the students when applying the double diamond
approach to their project.
IN-COMPANY ACTIVITY: Each company project is different and projects vary every year based also on the latest market and industry trends. Companies provide a description of the project they assign about 2-4 weeks prior to the start of the course.
The professor and tutor assign the projects taking into account the teams' preferences.
Examples of projects that were assigned in the last years include:

• identify an area of improvement in the company process and propose a suitable process innovation
• outline the strategy and/or implementation plan of a new company service
• scout external sources to identify new technologies or providers to address a company problem
• support the R&D function in designing a new product and/or in its launch into the market
• outline the patent and IP strategy of a new product

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
IMPORTANT: This is a lab (not a classical academic course) and grading is based on the work that the students accomplish from February to July in a project provided by one company that participates in the lab.
It is consequently not possible for students to take the lab or be graded at another time of the year, or to propose a company or project selected by them.
Please visit the FAQ on the WeBeeP platform for additional information.
Upon completion of the project, each team prepares a short written report and presents the outcomes live to the company and the professors.
The evaluation of the lab is the weighted average of 4 items, each graded separately at the team level, as follows (evaluator in brackets):

• 10%: Adequate application of the double diamond and presentation skills (professors)*
• 30%: Professionalism in organizing and conducting meetings. Proactiveness and problem-solving attitude. Ability to work in a team (academic tutor)**
• 30%: Professionalism in organizing and conducting meetings. Proactiveness and problem-solving attitude. Ability to work in a team and to integrate in company organization and processes (company tutor)**
• 30%: Achievement of goals and quality of the solutions proposed. Communication skills in the presentation and in the final report (professors).**
• Evaluated after the midterm presentation
  ** Evaluated at the end of the project

The course introduces students to the functioning of the global economy, with the goal of equipping them with both theoretical frameworks and empirical tools to analyze the key features of economic interdependence among countries. Central questions addressed include: Why do countries engage in trade? What are the gains from trade? How does trade affect inequality? What are the implications of trade policies? Particular emphasis is placed on understanding the channels through which individual agents’ decisions interact with aggregate economic outcomes. On one hand, the course examines how the cross-border movement of production factors—such as firms, labor, and capital—shapes macroeconomic variables like employment, income, and productivity. On the other hand, it explores how real and financial shocks, as well as macroeconomic and industrial policies, influence the behavior and outcomes of firms, workers and investors in an interdependent world.
Throughout the course, contemporary issues such as protectionism, trade wars, digital trade, and the restructuring of global supply chains are critically analyzed. By the end of the course, students will be able to assess trade policies and strategies with a critical and informed perspective, understand the economic and political dimensions of international trade, and apply theoretical insights to real-world business and policy contexts.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment
Develop new ideas and transformative solutions to deliver positive impact on business, industrial and societal scenarios evolving over time

Lectures and exercise sessions will enable students to:
Understand the main determinants of international trade and factor movements and their effects on the aggregate economy, as well as the effects of crises and macro-policies on firms, workers and capitals flows in a global economy.
Have the ability to select data, identify and apply the suitable theoretical and empirical tools to analyse determinants and effects of producing, working and investing in a global economy.
Develop a critical view on central themes and issues related to international trade and factor movements and the working of the global economy as well as have the ability to communicate it.

The course is divided into three modules:
The first module offers a comprehensive overview of the fundamental principles and core theories of international trade, alongside an empirical assessment of their real-world implications. It begins with an introduction to the historical evolution and economic significance of global trade, and proceeds with an in-depth analysis of classical trade theories, including Comparative Advantage (Ricardian model), Factor Endowment models (such as Heckscher-Ohlin), and the Specific Factors model. The module also covers key trade policy instruments—such as tariffs, quotas, and subsidies—highlighting their effects on domestic and international markets.
The second module focuses on firms’ international activities and the mobility of production factors across borders, drawing on the insights of the modern trade theories. Particular attention is given to the internationalization of production through the rise of multinational firms and foreign direct investment (FDI), as well as the cross-border flows of knowledge and capital. The module also explores migration decisions, considering different types of workers and skill levels. The macroeconomic implications of international factor mobility are analyzed in terms of employment levels and composition, income distribution, and overall economic performance.
The third module examines the impact of real and financial crises, as well as the role of macroeconomic policies in shaping firms’, workers’, and investors’ responses to economic shocks. The analysis focuses on how both crises and the policy measures adopted to address them—such as fiscal stimulus, monetary interventions, or trade restrictions—can influence business decisions, labor market outcomes, and investment patterns across different countries.

Prova scritta obbligatoria, senza prove in itinere
Valutazione continua facoltativa (a scelta dello studente)
The exam could be undertaken with two different modalities.
Type 1:
The final evaluation will be in two parts:
a) there will be a final written test on all the topics covered in class, which will count 60% of the final grade, aiming to verify the acquired knowledge on modules 1, 2 and 3.
b) the remaining 40% of the grade will be given on a group assignment and presentation to be done in class, agreed with the instructor.
Alternatively
Type 2:
(Written) Exam in the regular sessions (June, July, September) on all the topics covered in class.

Lecture notes as well as selected chapters of the textbook and academic papers represent the teaching materials of the course. The textbook selected chapters and a full reading list of journal articles will be announced at the beginning of the course.
P. Krugman, M. Obstefeld, M. Melitz, International Economics. Theory and Policy. 12th Edition., Editore: Pearson

SELECT UP TO MAXIMUM 3 GOALS AMONG THE FOLLOWING 5, DELETING THOSE NOT PRIOR FOR THIS SPECIFIC COURSE
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members

The course will allow students to:
1) understand the functioning of some of the main European institutions;
2) know how European decision making and policy is formed;
3) develop policy proposals impacting European firms and citizens;
4) discuss issues and solutions in international teams.

The course will introduce students to the European economic integration, the European instititutions, and various economic policies at the European level. In particular, it will cover a basic framework for the economics of European integration, discussing scale effects, market size, preferential liberalization, growth effects, while providing examples of specific related EU policies.

Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Valutazione continua facoltativa (a scelta dello studente)
The final evaluation will be in two parts:
a) Maximum 22 points out of 30: Final written team project which will be a mock European Commission proposal. These proposals will be discussed during some of the practice sessions, allowing students to receive feedback before submitting the final version. This will be graded on a 0-24 scale. There is no possibility to resubmit this project (unless the mark is a fail).
b) Maximum 8 points out of 30: After lectures students will have to undertake an online test on WeBeep (five tests will have to be done). The tests are taken during the beginning of the following lecture, and cannot be taken at a different time. The aim of this is to ensure continous learning during the course. The online test will be open book (without use of internet or AI). All tests will be marked, contributing with 8 marks to the final grade (the average mark of the five tests will be used). You can pass the course without taking these tests.

R. Baldwin and C. Wyplosz, The economics of European integration, Editore: McGraw-Hill, Anno edizione: 2022
Addition readings from the EU website and from websites of other international institutions https://europa.eu/european-union/about-eu_en

The INVEST IN FOREIGN MARKETS LAB aims to provide students with the theoretical knowledge and practical skills needed to establish, manage, and expand international business ventures.
To achieve this objective, students will engage in lectures, exercises, case studies, business talks, role-playing activities, and simulations delivered by professors from Politecnico di Milano and business executives from multinational enterprises and consulting firms. Through these activities, participants will benefit from the direct experience and expertise of academics and practitioners with extensive international business backgrounds.
In addition, students will further develop their practical and managerial skills through a team-based project. This project will enable them to apply the concepts, tools, and capabilities acquired during the Lab by developing an international business plan for an actual company. The project will be carried out in international teams comprising students from Politecnico di Milano and partner universities worldwide through the X-Culture Challenge ( http://x-culture.org/ ).
The course contributes to the overall learning objectives of the degree programme by fostering the following competencies:
Apply scientific, analytical, and engineering approaches to design effective solutions for complex business and industrial challenges.
Develop innovative ideas and managerial solutions in dynamic international business environments.
Work effectively in multicultural teams, interacting professionally, responsibly, and constructively while contributing to the achievement of shared objectives.

At the end of the course, students will be able to:
Select international business strategies that are appropriate for different global competitive environments.
Design an international business plan for a company seeking to expand into foreign markets.
Assess and mitigate cross-border risks.
Develop international digital marketing and e-commerce strategies.
Design organizational structures aligned with international business strategies.
Evaluate and select appropriate foreign market entry modes.
Manage international human resources in multicultural environments.
Understand the challenges involved in launching and financing a born-global start-up.
Negotiate the legal framework of international outsourcing agreements.
Identify opportunities arising from partnerships between multinational enterprises (MNEs) and non-governmental organizations (NGOs).
Integrate sustainability and circular economy principles into international production networks and global value chains.
Learn from the experiences of senior managers of multinational enterprises through direct interaction.
Evaluate how artificial intelligence can support international business decision-making.
Collaborate effectively with peers to develop solutions to international business challenges.

The Invest in Foreign Markets Lab is organized into six modules.
Module 1 – International Business Strategies
Main topics include:
International business strategies
International business planning
International digital marketing strategies
Cross-border e-commerce
International pricing strategies
International entrepreneurship
Legal aspects of international business negotiations
Partnerships between multinational enterprises (MNEs) and NGOs: business opportunities and local development
Sustainable international business
Artificial intelligence for international business
Module 2 – Corporate Finance and Financial Support for International Business
Main topics include:
Valuation methodologies for cross-border mergers and acquisitions
Managing country risk in international business
International funding for SMEs and entrepreneurial ventures
Module 3 – International Logistics and Distribution
Main topics include:
Foreign market entry modes
International transportation systems
Customs procedures and tariff classification
Module 4 – International Organization and Human Resource Management
Main topics include:
Organizational structures of multinational enterprises
Managing multicultural teams
International recruitment and talent management
Module 5 – Meet the Managers
Students will meet senior managers from multinational enterprises and policymakers involved in promoting internationalization and foreign direct investment, gaining first-hand insights into international business practice.
Module 6 – Group Project
Students will participate in a real internationalization project for an Italian company by developing an international business plan. The project is carried out in collaboration with the X-Culture Challenge ( http://x-culture.org/ ), an international experiential learning initiative involving more than 6,000 students from over 170 business schools across 53 countries. Participants work in multicultural teams on real business challenges proposed by companies, supported throughout the project by dedicated tutors.
The course concludes with a final presentation of the project.

Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua facoltativa (a scelta dello studente)
Altro
The final assessment for the INVEST IN FOREIGN MARKETS LAB consists of three components:
Project work: 50%
Project presentation: 25%
Average score obtained in the in-class group assignments (for attending students only), or a short final exam covering the course lectures (for students who choose this alternative assessment option): 25%
Students will work on the project throughout March and April, while the in-class group assignments will take place during March, April, and May. The project presentations (for all students) and the short final exam (for students who choose this alternative assessment option instead of completing the in-class group assignments) will take place at the end of the semester.

Charles Hill, Thomas Hult, "International Business: competing in the global Marketplace", Editore: McGraw-Hill Higher Education; 12 edition (February 20, 2018), Anno edizione: 2018
Note: The course material will be uploaded either before or immediately after each lecture (based on lecturers' requests). The book is optional.

The course aims to equip students with basic knowledge of digital information management systems in the construction sector for architectural and engineering works and infrastructures: fundamentals of BIM (Building Information Management).
The training is structured so as to allow the student to understand the main digital information problems, to acquire techniques for an organic approach to their solution, to be able to effectively interact with the technologies and skills involved in the digital management of information during the strategy, design, construction and operation phases.
The course provides the student with knowledge about: 1) digital information management flows; 2) digital information management systems and tools; 3) national and international standards of digital information management.

Students will be able to understand the economic and production issues related to the construction and infrastructure sector through digital data management tools and information models.
They will acquire the basic notions of the reference standards and will be able to develop procedural flows of information management applied to the design, production and operation phases in construction

Knowledge management & infrastructure projects: data space and digital platform; knowledge net in construction sector; AI and industry 4.0 in construction sector; Building Information Modelling (BIM)
BIM principles and standards: BIM story; international practice UK and USA; principle of digitization in construction sector; politics and laws for digitization of construction sector; International standard ISO; European standard CEN; National standard UNI
Digital Information management flow: actors and organization; strategy and design phase; purchasing phase; construction phase; operation phase (life cycle management). Project, inter and intra organization perspectives for collaboration and data uses.
Digital Information management system and tools: Digital platform for constructions; Common Data Environment (CDE); BIM Authoring 3D tools; Time Management 4D scheduling tools; Cost management 5D tools; Asset management 6D tools
Digital information request and delivery: GIS model for infrastructures, Asset and Project information models; Organization, Asset and Project Information Requirement; Exchange Information Requirement; BIM Execution Plan; Information Delivery Plan
Digital information analysis: digital and circular economy, cost-benefit analysis, market and use value, BIM review tools for clash detection, code and quality checking

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
Course organization and assignment review
Submission of a project work assignment that will be framed during the course and then developed by teams composed by min 3 people with different academic backgrounds. Students'll have 3 meetings review vithout intermediate evaluation
Final exam
Oral disussion about the course themes, starting from the resoults of the project work assignment, delivered in the end of the course

A.Pavan, C.Mirarchi and others, BIM-Based Collaborative Building Process Management, Editore: Springer, Anno edizione: 2019, ISBN: 978-3-030-32888-7

The course will provide students with models to understand how (and why) money and financial variables matter from a macroeconomic perspective. The importance of credit and financial market imperfections for the conduct of monetary policy and for real economic activity will be stressed. At the end of the course the student should be able to understand macroeconomic stabilization policies, the main monetary policy operating procedures, the role of financial intermediation and the effects of financial fragility on the economic system.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

The student:

• understands the financial/monetary context and knows how the different transmission mechanisms of financail/monetary shocks to the real economy operate;
• knows which are the implications and the possible evolving trends of imperfections in credit markets on firms' borrowing possibilities and, in general, on the macroeconomic outcomes;
• knows how to design new economic scenarios and/or the effects of monetary policies on economic agents' behavior by simplyfing and proper modeling the economic context;
• can identify the effetcs of financial fragility on the economic system.

Overview
The aim of the course is to stress the importance and the effects of financial choices and of monetary policy decisions on real economic activity. After introducing some basics macroeconomic concepts, useful to understand the real effects of economic policies and the functioning of monetary policy, we study credit market imperfections and how they can cause financial fragility phenomena that can lead to financial and real crises.
Main topics
Block 1. Basic macroeconomic concepts (neo-classical model, IS-LM model, the liquidity trap, the AD-AS model, the Phillips curve, the yield curve);
Block 2. Monetary policy operating procedures (the money multiplier, the central bank balance sheet, the ECB's monetary policy c orridor, the Taylor rule, inflation targeting, post-crisis non conventional policies);
Block 3. Asymmetric information and financial intermediation; credit market imperfections and their effects on economic activity (from Modigliani-Miller to the financial hierarchy; credit rationing: Stiglitz e Weiss (1981), bank runs and financial panics: Diamond e Dybvig (1984));
Block 4. Financial fragility and monetary policy transmission mechanisms to real activity (the traditional interest rate channel (money view), asymmetric information effects and the credit channel ( credit view ): lending view (Bernanke and Blinder (1988)) and the financial accelerator).

Prova scritta obbligatoria, senza prove in itinere
Valutazione continua facoltativa (a scelta dello studente)
The course will include traditional lectures and practice session. Newspapers' articles on the topics of the course will be suggested and active partecipation to their discussion will be welcome. The final evaluation will be based on a final written test that includes one or two questions on the first part (Blocks 1 and 2) and one or two questions on the second part (Blocks 3 and 4). In order to pass the exam the student must obtain a sufficient mark both in the first and in the second part.
The final grade will be composed of the grade you receive on your final (written) exam, plus any supplementary points you earn partecipating in certain activities presented during the course (e.g., forum discussion on webeep, homework/in class exercises and acting as a teacher in the course). More details will be provided during the course. Please n ote that since these activities are optional, even if you choose not to participate, you can still achieve the maximum final grade.
The final test will be based both on numerical and qualitative questions in order to assess if the student:

• knows how to solve an economic problem and how to measure the effects of monetary and fiscal shocks on the economic equilibrium;
• is able to identify different trends in the main economic variables as agents' expectations change;
• knows how the central bank takes and implements monetary policy decisions both in standard and non-standard times;
• can discuss critically a newspaper article on the topics covered in the course adapting the adequate theoetical model to the practical problem at hand.

Blanchard, Amighini, Giavazzi, Macroeconomics-A European Perspective, Editore: Pearson
Xavier Freixas, Jean-Charles Rochet, Microeconomics of Banking
Mishkin, Frederic S., Economics of Money, Banking, and Financial Markets, Editore: Pearson, ISBN: 978-0-321-58471-7

L'insegnamento fornisce una visione d'assieme unitamente alle corrispondenti metodologie quantitative e competenze per progettare i sistemi produttivi e gestirne la continua modifica in relazione all'evoluzione del mix di prodotti e ai cambiamenti nelle tecnologie. Sono proposte metodologie per considerare congiuntamente aspetti tangibili e intangibili che determinano le scelte di configurazione, metodologie che consentono di tenere conto dell'incertezza degli scenari futuri e metodologie per la configurazione ottimale dei sistemi. Gli strumenti e le metodologie studiati nell'insegnamento sono anche applicate ad un caso realistico nell'ambito di un laboratorio progettuale. Il laboratorio progettuale è parte del programma di innovazione della didattica del Politecnico di Milano.

The course intends to introduce top-notch analytical approaches for data-driven marketing.
The course will adopt a hands-on approach based on a recursive pattern:

• Introduction to the marketing problem to be addressed through analytics
• Introduction of the analytical/statistical method(s) suited to solve the problem
• Practical application of the method(s) and exercises
• Discussion of the actual adoption of the method(s) in practice
  In the course, students will be engaged in exercises and group works aimed at strenghtening their teamwork and practical implementation.
  By doing so, the course will aim to foster the three following objectives:
• Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
• Identify trends,technologies,key methodologies and stakeholder needs in analytics for business
• D esign solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment

Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society: understand how companies approach marketing analytics, the underlying organizational and technological processes and their impact on company activities
Identify trends,technologies,key methodologies and stakeholder needs in marketing analytics: students will be able to understand and identify the top-notch challenges in marketing analytics and to understand what are the challenges related to their introduction. They will know methodologies and technologies to process marketing data in a profficient way.
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment: the course will challenge students in developing solutions to real-life cases, identifying proper methods to address them and developing suited models to extract insights from marketing datasets

1. Introduction to marketing analytics: the need for a data culture in marketing, the data available for marketers and the ability to read them effectively
2. Marketing research methods: how to conduct a marketing research and how to design surveys that are reliable and valid
3. Multivariate statistics for marketing: dimensional reduction, cluster analysis and discriminant analysis for segmentation and marketing research. Cases and interpretations
4. CRM analytics: analysis of the lifetime and the problem of churn in contractual and non-contractual settings. Random forest, decision trees and survival analysis for churn prediction and prevention
5. Methods for customer (e)valuation: customer lifetime value (CLV) estimation and the customer lifetime as a stochastic process
6. Attribution modelling in omnichannel, multitouchpoint contexts and marketing mix modelling (marketing effort optimization)
7. AI prompting for marketing analytics

Prova scritta obbligatoria, con prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i condizionato (a scelta del docente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua condizionata (a scelta del docente)
Altro
The exam will consist of three blocks, that student must pass in order to pass the exam:

• Written exam on exercises (with an optional in itinere call besides the regular exam sessions)
• Written test about theory: during the regular exam sessions in the form of multiple choice and/or open ended questions
• Assignment
  For the assignment block, students can choose one among three alternative formats, subject to the availability of topics for each format as determined by the teacher:
• Project assignment to be carried out during the course
• Integrative written exam with multiple choices and exercises
• Flipped class by the students, with the teacher evaluating the quality of the output

Stephan Sorger, Marketing Analytics: Strategic Models and Metrics, Editore: Admirall Press, Anno edizione: 2016
Blanchard, Debasish, Pranshu, Data Science for Marketing Analytics: Achieve your marketing goals with the data analytics power of Python, Editore: Packt Publishing, Anno edizione: 2019
Hermann, Burbary, Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World, Editore: Que Publishing, Anno edizione: 2018

The goal of the course is to provide students the understanding of future work and organizations scenarios and to enable them to design new forms of work and organization that are aligned with the new competitive and social environment, exploiting the opportunities offered by digital technologies. In particular, the course will contribute to the following Learning Goals:
LG2 – Identify future trends, technologies and key methodologies in a specific domain (work and organization design)
LG3 - Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
LG5 – Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members

Lectures and case discussions will allow students to be able to:
understand the different scenarios of the future of work and organizations
analyse the changes in the society and the competitive environment that influence work and organizations
appraise the challenges and opportunities offered by digital technologies in designing work and organizations
appraise the main characteristics of emerging organizational models and the new approaches to organizational innovation
design new forms of work and organization
be an effective leader in the different new organizational scenarios
apply people management practices that are aligned with the new organization models
effectively drive organizational change.

The course covers the main challenges and future scenarios of work and organizations, the main characteristics of emerging organizational models and the new approaches to organizational innovation and change. All the topics are treated both theoretically and through company cases and guest speakers. In addition, group project work or an individual assignment (depending on student's choice) stimulates the in-depth understanding, discussion and application of some of the models presented in class to one or more cases.
The course will cover the following topics:
Emerging challenges for the future of work and organizations: society, competitive environment, new digital technologies
Future scenarios of work and organizations
The Agile Organization:
Agile principles
The Agile organization in practice: tools and methods
People leadership and management in agile organizations
The boundary-less organization:
From outsourcing to crowdsourcing
Platform work and organizations
People leadership and management in boundaryless organizations
Smart, virtual and technology-enabled organization:
Advanced technology adoption/Industry 5.0
Smart and virtual work principles, methods and tools
People leadership and management in smart and virtual work context
The purposeful organization
The role of purpose in new forms of work and organization
Leadership and people management in purposeful organizations
Organizational innovation and change
New approaches to organizational innovation and change
Agile and design thinking principles for organizational innovation

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente) o condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The assessment will be based on two components: an assignment and a written exam. The content of the assignment depends on students' choice of how to participate in the course, namely in one of the following two different modalities: through a group work modality, or in an individual modality.
Group work modality (standard):

• During the classes in which new forms of organization and work are introduced, students will be asked to work in teams to have the opportunity to further deepen and better understand from a critical perspective the new forms of work and organization that are presented in class. This form of active engagement with the course content allows students to develop deep insights and offers a good preparation for the written exam.
• The teamwork might differ from one class to the other but generally consists of a team discussion of a real case (either presented by a guest speaker or described in a written case study) and a plenary presentation and discussion by some teams. In preparation of the discussion, teams might be asked to look for information on both academic and grey literature papers or secondary sources before the class.
• Each team will be asked to share and present their teamwork and to act as main discussant several times during the course. Both the presentations and the discussions will be evaluated.
• Active discussion in class by all students and effective teamwork is also envisaged and evaluated through a bonus/malus system.
  Students in the group project work modality can choose to do an additional (optional) oral exam after the written exam, to potentially earn extra points to their final grade.
  Individual modality:
• Students who are not able to participate in the classes and course activities regularly have to accomplish an individual project work at the end of the course
• The individual project work has to be delivered one week before the written exam
  The lecturer can decide to add an obligatory oral exam in case there are questions about the individual assignment. This oral exam needs to be passed in order to be given access to the written exam.
  All students participate in a written exam, during which students should demonstrate:
  to know the most important future scenarios and the main characteristics of new forms of work and organization
  to be able to analyse a specific competitive setting to design the most appropriate form of work and organization
  to choose the correct approach to people leadership and management in the context of the new organization
  to be able to define the appropriate strategy to organizational change and innovation required by the new form of work or organization introduced
  All examination components need to be passed in order to receive a final grade (this applies to both students in the group project and the individual modality).

Understand the nature and peculiarities of projects, programme and portfolios. Understand role of projects in society and workplace and the difference between project management success and project success. Understand the sustainability and unsustainability aspects of project management.
Identify, in the context of projects: stakeholders, cost elements, risk and opportunities, options to plan and deliver projects.
Design strategies to engage stakeholders, financial structures, risk management frameworks.
Develop the scope of the project, project plans, strategies to plan and deliver sustainable projects.

After successful completion of this module students:
Will gain a holistic understanding of project business and project ecology (Knowledge and understanding);
Will be able to understand key project management concepts, their evaluation and application (Knowledge and understanding);
Will be able to select and apply proper qualitative and quantitative project management tools, processes and methods at the different project and system life cycle stages (Applying knowledge and evaluating);
Will be able to critically assess projects and programmes considering scope, risk, stakeholders, sustainability (Applying knowledge and evaluating)
Will be able to propose delivery models considering the different dimensions of project success. (Evaluating and creating)

Projects are the key elements of our time; they are needed to plan and deliver infrastructure, address a global pandemic like COVID-19, or deal with climate change. Projects span across industries and economic sectors, including construction projects, the development of new major software, making movies, but also humanitarian projects. This course aims at transferring to students theoretical and practical knowledge about Project Management, Business, and Ecology. The course addresses the state-of-the-art approaches, methods and models for deciding, planning, and delivery projects and programmes. Including traditional “Project Management” topics, the course covers the essentials of project business (e.g. the governance of the organisations involved in projects) and the most recent elements of the project ecology. More specifically:
Introduction to Project Management, Project Business and Project Ecology: Introduction of key concepts such as project, programme, portfolio, project-based company. Managing for stakeholders, stakeholders relationship maps, project governance and project Ecology
Traditional Project Management models, tools and techniques: Scope management including WBS and other structures, Economic and Financial (with exercise on NPV, IRR, Project Balance), Planning and scheduling, Critical Path Method and its limitations (with numerical exercises), Cost Estimating, Project Controlling and its implications for re-planning; Risk Management (definition, identification, evaluation, mitigation, contingency, reporting),
Modern topics of Project management: Mega and complex project, human biases, Project management success vs project success, Sustainability (including SDG) & Dark side (modern slavery, corruption, sexism etc.),
This module's learning experience includes face-to-face lectures, numerical exercises, case discussions, real examples.

Prova scritta obbligatoria, senza prove in itinere
Written test: focused on assessing the learning outcomes. It will include a mix of theoretical questions and numerical exercises. Exemples of test and solutions are available in WeBeep

Jeffery Pinto, Project Management: Achieving Competitive Advantage - 5th edition, Anno edizione: 2019

The course enables students to address authentic industrial challenges in manufacturing through the application and integration of smart manufacturing methods. Working in teams and in collaboration with an industrial partner, students analyse a company problem, formulate it as an engineering and management problem, select appropriate methods, develop and validate a solution, and communicate their findings to both technical and managerial audiences.
The projects may concern products, production processes, manufacturing systems and their evolution over time. Depending on the industrial case, topics may include manufacturing-system design and reconfiguration, sustainable and zero-waste production, product–process integration for customisation, planning and scheduling under uncertainty, digital twins, prognostics and health management, and the improvement of system reliability and availability.
The course adopts a project-based and experiential-learning approach. Activities may include lectures and seminars, laboratory work, analysis of industrial data, meetings with company representatives, visits or periods at company premises, and independent team project work.
In addition to technical and analytical capabilities, the course develops students’ ability to work responsibly in multidisciplinary teams, organise project activities, manage interactions with an industrial partner, respond to changes in project requirements and communicate evidence-based recommendations.
The course contributes to the following general programme learning goals:

• analysing complex industrial problems using rigorous scientific, engineering and management methods;
• developing and evaluating innovative solutions for evolving industrial contexts;
• integrating technical, organisational, economic and sustainability considerations;
• collaborating effectively and responsibly in a professional environment;
• communicating methods, results, assumptions and limitations to different stakeholders.

By the end of the course, students will be able to:
1. Analyse and formulate an industrial challenge by identifying relevant stakeholders, objectives, constraints, performance indicators, data requirements and sources of uncertainty.
2. Develop an appropriate representation of the problem, defining and justifying assumptions, selecting a suitable level of abstraction, and assessing the quality and limitations of the available data.
3. Select, adapt and apply smart manufacturing methods to develop alternative solutions, using appropriate engineering, analytical and digital tools.
4. Evaluate and validate the proposed solution using industrial evidence, considering technical performance, feasibility, economic implications, organisational impact and sustainability.
5. Plan and manage a team-based industrial project, allocating responsibilities, monitoring progress, documenting decisions and adapting the work plan to intermediate results and changes in the project context.
6. Collaborate professionally with team members and company representatives, incorporating feedback and managing communication, responsibilities and deadlines.
7. Communicate project results effectively through technical documentation, visual material and oral presentations, explaining the rationale, assumptions, results, limitations and recommendations.

The course is organised around an industrial challenge proposed by a partner company. Students work in teams to understand the industrial context, formulate the problem, collect and analyse relevant information, develop and evaluate alternative solutions, and present evidence-based recommendations.
The project may address one or more interconnected aspects of manufacturing, including product design, production-process design, manufacturing-system configuration, production planning and control, maintenance, quality, logistics, digitalisation and sustainability.
The course includes the following activities:
Industrial project and company interaction
Students collaborate with the industrial partner throughout the project. Depending on the case, collaboration may include work at the company premises, production-site visits, periodic meetings with company representatives, remote interaction and the use of industrial data provided by the company. The company supports the definition of the project objectives, provides relevant contextual information and contributes feedback during the project.
Lectures and seminars
Lectures and seminars introduce or consolidate the technological, analytical and managerial concepts required to address the industrial challenge. Additional seminars may be delivered by company specialists or external experts.
Laboratory and modelling activities
Students use appropriate laboratories, software tools, datasets and experimental facilities to develop, test or validate their proposed solutions. Facilities may be provided by the Department of Mechanical Engineering, the Department of Management, Economics and Industrial Engineering, other departments of Politecnico di Milano, or partner organisations.
Industrial-data analysis
Students work with data collected in industrial settings. Activities may include data preparation, quality assessment, modelling, simulation, optimisation, statistical analysis, machine learning and validation, depending on the project requirements.
Project reviews
Periodic reviews are conducted with the teaching staff and, when possible, company representatives. Reviews are used to evaluate progress, discuss assumptions and intermediate findings, identify risks and agree on subsequent project activities.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Assessment is based on the quality of the industrial project and on each student’s individual contribution and understanding.
Group assessment – 70%
The group assessment considers the quality of the problem formulation, methodological rigour, appropriate use of data, validity of the results, feasibility of the proposed solution, consideration of economic and sustainability implications, and clarity of the documentation.
Individual assessment – 30%
Although presentations may be organised at group level, students are assessed individually on their contribution, command of the complete project, ability to justify methodological choices and capacity to answer questions. The company supervisor may provide feedback on each student’s professionalism, participation, reliability and interaction. The final academic assessment remains the responsibility of the course instructors.
To pass the course, students must participate in the required project activities, submit the final deliverables, present the work carried out, and demonstrate an adequate individual understanding of the project.

Lecture slides and tutorials https://webeep.polimi.it

Over the last decade, a new breed of entrepreneurial ferment has gained traction around the globe, inspired by the search for novel, sustainable solutions to complex social challenges. Adopters of this approach, labelled as social entrepreneurs, develop and deploy innovative solutions to improve living conditions in their communities and address the needs of the society, simultaneously combining the pursuit of purpose and profit. In other words, they attempt to solve a societal problem through innovation in a financially sustainable manner. This paradigm represents a new generation of businesses forged by the need to respond to major social and environmental challenges.
Students in the course will learn how entrepreneurs can identify and exploit opportunities to develop solutions aimed at solving social and environmental problems and the peculiar challenges of managing an enterprise that realizes a dual process of value creation, both social and economic.
The course will offer to students the opportunity to practice their critical thinking applied to real-world situations.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:

• Understand the concept of social entrepreneurship, how an entrepreneurial process for social change unfolds and the peculiar challenges of dual, social and economic, mission management;
• Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to transform a system-changing idea into a long-term sustainable entrepreneurial initiative;
• Interpret real-world situations of managing socially-oriented hybrid organizations that strive to create systemic change in society;
• Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members.

At the end of the course, the students will be able to:
understand the process of opportunity identification and opportunity exploitation apply to the search of solutions for social and environmental problems;
analyze the possible tensions peculiar of the management of social venture;
apply theory and empirical evidence to envision and realize solutions to the potentially destructive and constructive trade-off situation experience in managing social enterprises.
design the different elements of a hybrid socially-oriented business model;
analyze funding needs and sources for different types of social enterprises;
assessing the readiness of a social entrepreneurial project to be scaled and identify possible challenges;
select the scaling strategy given the specific characteristics of the social venture;
describe the main concepts and frameworks to measure the firm's performance in terms of the social and environmental impact generated;
understand team working dynamics, develop leadership, negotiation skills, and conflict management ability (case study teamwork assignment);
develop communication skills and communicate the key concepts in a public context as well as in a written document (in-class case discussion and case study teamwork assignment);
be aware of how they might apply social entrepreneurial skills in their future careers opportunities.

The course includes:
Lecture sessions: they aim to outline and discuss conceptual frameworks, tools and empirical evidence.
In-class case study discussions: they aim to help students apply the insights from theory and empirics to understand the challenges of managing a venture with a hybrid social and economic purpose. Students must read case study materials in advance of the class sections.
Testimonials: guest speakers will be invited to share their practical experiences with the class.
COURSE DETAILED PROGRAM
I. UNDERSTANDING THE PROBLEM AND OPPORTUNITIES
1.1 The current trends and societal challenges and the quest for a new capitalism
1.2 Becoming a Social Entrepreneur: Unfolding the process
II. ENVISIONING YOUR SOLUTION AND ORGANIZATION
4. Combining profit and purpose: hybridity and social impact
5. A definition and taxonomy of socially oriented hybrid organisations
6. Managing hybridity in social ventures
7. Technology, innovation and management of Social-Tech Ventures
III. BUILDING A BUSINESS STRATEGY FOR SOCIAL CHANGE
8. Designing a socially-oriented business model
9. Funding social enterprises: challenges, opportunities and novel approaches
10. Reinterpreting the notion of firm growth: scaling social impact through multi-stakeholder partnerships, social franchising, advocacy and dissemination

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The assessment is based on:
Impact Challenge project (teamwork) — Teamwork will allow students to experience a social entrepreneurial journey, from identifying a system-change idea to solve a societal challenge to translating it into a prototype for a viable, sustainable entrepreneurial project. The output will consist of two assignments: the first, to be delivered during the course, will involve an analysis of the context and the preliminary value proposition of the solution, with feedback provided throughout the course by designated tutors; the second, to be delivered and presented at the end of the course, will describe the final results and how the idea has been turned into a social enterprise capable of generating societal and economic value.
Case study analysis (individual assignment) — During the course, the students will be supported in the preparation of a case study analysis: the case will be discussed in class and the collective discussion will help to students to get a full understand of the case. To prepare for the exam, students must thoroughly review the case study materials, reflect on the main challenges discussed in class, consider how they relate to the case specifics, and connect the case to the theoretical concepts addressed during the course. The students will take a written exam expressing their critical point of view on the case during the officially scheduled exam. Students must complete this activity in person.

Slides provided by the Professor; Readings materials provided during the course; Text of case studies

The aim of this Laboratory is to expose students to the most adopted tools in managing their relationships with suppliers. In particular, participants will study and apply tools to manage suppliers and to optimize procurement performances. All these tools are discussed with a panel of Chief Procurement Officers during the semester and are applied to different real cases in small working groups.
This laboratory will focus on managing relationships with suppliers, along the whole relationship lifecycle: market analysis, suppliers scouting and qualification, negotiation, spending analysis, vendor rating. It will enhance students’ capabilities to:

• negotiate with suppliers and manage the relationships;
• compare and select suppliers;
• use digital tools to optimize procurement.

At the end of the course, the student has the following skills:

• Is able to read a real business problem and identify appropriate and valuable solutions, through a quantitative assessment of the options and a critical review of the results
• Is able to apply different procurement models in specific business contexts, to improve the performance of the purchasing department and to face new challenges of the business
• Is able to undestand a business scenarios and develop solutions to improve the processes and competences of the procurement department in an innovative way, through the application of structured models and with an assessment of the implications in the short and long term
• Is able to present solutions and ideas in a professional and constructive way, fostering the value of the teamwork, and using a language adequate to both managers and fellow students

During the course, the following topics related to Supplier Relationship Management will be discussed:

• Strategic impact of procurement
• Supply chain finance
• Financial risk heding and purchasing of commodities in the financial market
• Supplier selection and Total Cost of Ownership
• Supplier negotiation
• Supplier selection tools (auction and tender) and supplier selection methods
• Supplier monitoring and planning
• Digital tools to support purchasing process
  Course organization
  The course is practice-oriented, classes are managed either through case studies and simulations or through a direct interaction with purchasing managers.
  Students will be divided into groups of 4-5 people from the beginning.
  Each group will be assigned to a specific problem/challenge within a company and will work on this problem during the semester. To face the challenge, students will apply a set of different tools and methodologies applied by companies in that specific field.
  Groupwork might be performed in two different ways, according to each specific case:
• Synchronous: groups will work on group activities in class all together.
• Asynchronous: groups will work on their own on the case.
  Moreover, groups will be involved into a Procurement Bootcamp, to design an overall category strategy, with the real application of all the tools learned during the semester.
  Finally, several Chief Procurement Officers will be involved during the course to present and discuss with students their professional daily life.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Altro
The evalution is multiple:

• In depth analysis of a business case, developed in group, to identify appropriate and valuable solutions in a specific purchasing context - MANDATORY
• In class participation to specific business cases and simulations, developed in group, to apply different engineering models in specific business contexts- OPTIONAL
• Peer evaluation of the group activities, to demonstrate to be able to present ideas to fellow colleagues in a professional way - MANDATORY
• Development of a project work with a specific company, working in a pre-defined task, to comprehend a procurement business scenarios and develop solutions to improve the procurement processes and competences, through a real discussion with companies - MANDATORY
• Presentation of the solution of the project work in front of the class, to present a group solution in a professional and constructive way - MANDATORY
• Oral individual exam, to demonstrate the understanding of how to apply different procurement models in specific business contexts - MANDATORY

Federico Caniato, Davide Luzzini, Antonella Moretto, Andrea Patrucco, Stefano Ronchi, Procurement Management. Strategy, organization and tools

The Supply Chain Management course enables students to get a comprehensive understanding of the structure, dynamics, and mangement of modern supply chains. It provides a high-level perspective on key challenges, current trends, and emerging issues faced by the supply chain. In addition to coonceptual understanding, the course aims at conveying a set of practical tools and analytical approaches that support professionals in better interpreting and managing supply chain challenges in real-world contexts. The course enables students to develop the following capabilities:
To understand the supply chain processes, as well as the context, in which these processes operate.
To identify and analyze the major challenges affecting the supply chain prcesses.
To d esign solutions using a scientific and engineering-based approach that is grounded in analysis, critical thinking, and modeling to respond to complex supply chain problems.

Having completed this course, the students are expected to show an elevated ability in:
Identifying trends and analysing their impact on supply chain decisions
Designing SCM strategies and solutions
Making relevant decisions in SCM by leveraging important tools and frameworks
Developing new concepts to deal with future supply challenges and trend
Interacting with colleagues and professionals from different disciplinary areas in complex problem settings and enabling them to highlight SCM issues and explaining the impact of external decisions on SC performance

The Supply Chain Management Course consists of the following contents:
Supply Chain Introduction
Supply Chain Strategies / Supply Chain Integration
The Value of Information for Supply Chain Management
Network Design in the Supply Chain
Basics of Supply Chain Planning and Inventory Models for Supply Chains
Product Design and Supply Chain Management
Supply Chain Metrics for Performance Measurement
Supply Chain Management and Sustainability
Supply Chains and Risk Management
Supply Chains, Information Technology, and Business Models

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Students will be assessed on their understanding of the course content by means of a group project assignment and one written exam. The group assignment is composed of two parts: (1) the first part consists of a presentation that is evaluated during the semester. (2) The second part is a short written report that is due by the end of the teaching period. The written report elaborates on the contents of the presentation. This group assignment is mandatory to pass the course and can be performed only during the semester when the lectures are taking place (Particular attention should be paid to the deadlines related to the group assignment that are presented during the first lecture)

Caridi, M., Moretto, A., Perego, A., & Tumino, A., The benefits of supply chain visibility: A value assessment model, Journal of Production Economics, Anno edizione: 2014, Fascicolo: 151, 1–19.
Chopra, Sunil / Meindl, Peter (2016): Supply Chain Management: Strategy, Planning, and Operation, 6th Edition, Essex: Pearson 2016.
Feitzinger, E., & Lee, H. L., Mass customization at Hewlett-Packard: The power of postponement, Harvard Business Review., Anno edizione: 1997, Fascicolo: January–February
Fisher, M., What is the right supply chain for your product? Harvard Business Review, Anno edizione: 1997, Fascicolo: March–April
Johnsen, T., Miemczyk, J., Marques, L., & Howard, M., Procurement and Supply Chain Management: A Sustainability Perspective, Editore: Routeledge, Anno edizione: 2026, ISBN: 9781032813912
Lee, H. L., Aligning supply chain strategies with product uncertainties, California Management Review, Anno edizione: 2002, Fascicolo: 44(3), 105–119.
Lee, H. L., & Tang, C. S., Variability reduction through operations reversal, Management Science, Anno edizione: 1998, Fascicolo: 44(2), 162–172
Markoff, R., & Magnani, F., The Launch of the Century: a supply chain novel, Anno edizione: 2024, ISBN: 979-8340198815
Sheffi, Yossi (2015): The Power of Resilience - How the Best Companies Manage the Unexpected, Cambridge/London: MIT Press 2015.
Sheffi, Yossi (2018): Balancing Green - When to Embrace Sustainability in a Business (and when not to), Cambridge/London: MIT Press.
Simchi-Levi, David (2010): Operations Rules - Delivering Customer Value through Flexible Operations, Cambridge/London: MIT Press 2010.
Simchi-Levi, David / Kaminsky, Philip / Simchi-Levi, Edith (2003): Managing the Supply Chain - The Definitive Guide for the Business Professional, New York et al.: McGraw-Hill 2003.

The course aims to make students understand how the automation and digital technologies (e.g. Industry 4.0) can contribute to the sustainable and circular transition of the manufacturing sector, both in the process industry and in the discrete manufacturing systems. The students will learn how to analyse the context to select the best technology, the best application scenario and the proper approach to involve in a balanced manner the entire workforce, giving equal opportunities to all, ensuring a sustainable transition of manufacturing companies. The impact evaluation will also be investigated to give students the know-how on how to understand the sustainable related-impacts of their decisions (e.g. energy efficiency and LCA). Among all, the topics tackled will the human-centric manufacturing, the energy efficiency, the life cycle assessment (LCA), the circular manufacturing paradigm, urban factory, waste management and end-of-life management practices. The course, hence, fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on sustainable business performance
Analyse trends, technologies and key methodologies empowering the transition of manufacturing companies towards circular and sustainable processes
Apply solutions based on a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment to face the sustainable development required
Evaluate the solutions applied to make students be aware about the impact of specific decisions.

The main expected learning outcomes for each of the following capabilities are:
Understand: the students will learn how the automation and digital technologies (e.g. Industry 4.0) can contribute to the sustainable and circular transition of the manufacturing sector, both in the process industry as well as in the discrete manufacturing systems
Analyse: the students will learn how analyse the context to select the best technology, the best application scenario and the proper approach to involve the workforce in order to ensure a sustainable transition of a manufacturing company
Apply: the students will apply the knowledge gathered from the lectures and the industrial cases to manufacturing systems in order to design sustainable systems. Quantitative and qualitative techniques will be explained
Evaluation: the impact evaluation will also be assessed in order to give students the know-how on how to understand the sustainable related-impacts of their decisions.

Introduction to Sustainable Manufacturing
Global societal challenges;
Sustainability megatrends;
International frameworks (EU Green Deal, WMF, UN SDGs).
Advanced and Sustainable Manufacturing Strategies
Servitization,
PSS;
Mass customisation;
Hurban factory;
Reshoring;
Strategic role of sustainability.
Sustainability and AI for Sustainability
Digital twins,
Data analytics,
AI for optimisation and predictive maintenance,
sustainability KPIs;
Participatory workshop: digital and sustainability maturity assessment of a manufacturing system.
Human-Centric and Inclusive Manufacturing
Human-centric and social sustainability concepts;
inclusion-by-design;
AI and automation for safe,
Equitable workplaces;
Participatory activity: human-centric system/workstation design exercise.
Energy-Efficient Manufacturing
Energy efficiency frameworks (EU 20-20-20, ISO 50001);
Energy audits;
KPIs;
Lean energy management;
Holistic factory assessment.
Participatory hands-on: simplified Energy Management exercise.
Life Cycle Assessment (LCA)
LCA methodology: functional unit, system boundaries, impact categories;
Participatory hands-on: simplified LCA exercise.
Circular Manufacturing and Circular Economy
Transition to circular systems;
Circularity indicators,
Drivers, barriers;
Waste management.
Visit to MADE Competence Center

Prova orale obbligatoria
The achievements of the students after the attendance to the sustainable manufacturing course will be assessed through an oral exam which will cover all the topics tackled during the lectures to understand their acquired knowledge.

Technology-driven businesses are nowadays struggling to keep up with the rapid pace of technology innovation and change, such as the increasing complexity of modern cyber-physical systems. In this context, Technology Risk Governance (TRG) comprises the set of strategies, methods and organisational models that different organisations put in place for understanding, assessing and managing technology-related risks. This course aims at transferring to students theoretical and practical knowledge on TRG through in class discussion of real cases and testimonials from companies, which will cover a wide spectrum of industrial and service systems (e.g. manufacturing, energy, transport).
The course addresses the state-of-the-art approaches, methods and models for supporting risk-informed decisions in managing complex socio-technical systems, from technology selection to system design, from organisational risk factors to regulation and governance.

After successful completion of this course module students:
Will demonstrate the ability of identifying and analysing technology risks in cyber-physical systems, eventually discussing alternative mitigation options (Knowledge and understanding);
Will be able to select and apply proper qualitative and quantitative technology risk assessment methods at different system life cycle stages (Applying Knowledge and understanding);
Will be able to identify and critically discuss emerging relevant challenges to the governance of technology risks in cyber-physical systems, leveraging on state-of-the art knowledge (Making Judgements and Learning skills), and prepare a technical report on technology risk assessment (Communication).

The course addresses the state-of-the-art approaches, methods and models for supporting risk-informed decisions in managing complex socio-technical systems, from technology selection to system design, from organisational risk factors to regulation and governance. More specifically:
Risk governance of new and emerging technologies. Technology outlook and risk assessment methods for technology foresight and selection. Discussion of application cases.
Risk analysis of complex socio-technical systems. Risk definition, modelling and reporting under the precautionary principle; Risk engineering methods (with exercises on FMECA, FTA-ETA, PRA). Safety and information security analysis of cyber-physical systems: differences and relationships.
Human and Organisational risks in complex socio-technical systems. Modelling and analysis of human and organisational risk factors; Risk Management of safety-critical and mission-critical systems (the High Reliability Organisation theory). Critical incident analysis case discussion. Discussion of industrial practices; Testimonials.
Risk governance of interdependent systems. Characteristics of networked cyber-physical systems. Types of interdependencies. Modelling tools for vulnerability and interdependency analysis. Risk governance models and processes, discussion of cases and testimonials from companies.
The learning experience of this course includes, in addition to face-to-face lectures, numerical exercises, case discussions, a group project, real examples and interactions with guest speakers from industry.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
Group Assignment: Groups of students (max 3 students/group) will be engaged in actively applying risk management principles, models and methods by means of a major assignment. The assignment may take the form of a Technology Risk Assessment study, or an ex-post systematic analysis of a technology-driven industrial accident, by making use of the methods and tools presented in class. The assignment is intended to evaluate the student’s ability to: i) choose and apply the most appropriate approach and methods given the key features of the complex socio-technical system at stake; ii) examine and assessing the suitability of an organization’s technology risk governance model; iii) preparing a technical report on technology risk governance. The deliverable consists of a final written report;
During classes some minor assignments will be suggested, as an extension of in-class exercises, to be completed in groups on a voluntary basis.
Written test: focuses on analytical problems in technology risk assessment, aiming at evaluating the student’s ability of using proper methods and correctly interpreting results.
Grading: Student evaluation will be based on course assignments:
Group assignment: 50%;
Written test: 50%;
The submission of minor assignments may award the student with max 0.5/30 point each.

Course instructor, Teaching notes, Case texts and suggested readings
Note: Available on Beep course web page
Bedford, Tim & Cooke, Roger M, Probabilistic risk analysis: foundations and methods, Editore: Cambridge University Press, Anno edizione: 2012 https://www.cambridge.org/core/books/probabilistic-risk-analysis/E7AB7D462EA12249CA33D828B6A44ECF
Reason J. T., Managing the risks of organizational accidents, Editore: Routledge-Ashgate, Anno edizione: 1997

Processi di Lavorazione Additivi
La produzione mediante processi tradizionali di lotti poco numerosi o al limite unitari di prodotti con geometrie ad alta complessità è sempre stata considerata come economicamente svantaggiosa. La situazione sta ora modificandosi grazie all'introduzione dei processi basati su tecnologie additive (Additive Manufacturing - AM), spesso comunemente note come tecnologie di stampa 3D. Dopo essere stati utilizzati per più di vent'anni nell'ambito dei processi di sviluppo prodotto come tecnologie per la fabbricazione rapida di prototipi, utensili e attrezzature, le tecnologie additive sono sempre più utilizzate per la produzione di singoli prodotti o prodotti personalizzati in molti settori industriali. Il corso fornirà un'introduzione alle tecnologie di produzione additiva, discutendone le loro applicazioni e le implicazioni tecniche e gestionali in riferimento a tutti i possibili utilizzi di tale innovativa tecnologia di produzione.

The course will offer a unique opportunity to acquire a deep understanding of all currently state of the art Additive Manufacturing technologies used on high-end industrial sectors. Each manufacturing process used on metals (conventional and non-conventional), polymers, composite materials, ceramics and glasses, living cells/human organs will be described in detail. Every process will be analysed in terms of main applications for which the process offers the ideal performances as well as all associated benefits, advantages and drawbacks.
The course will subsequently address all currently open technical challenges. In fact, Additive Manufacturing is showing great potential on a very large number of space and aerospace applications, however open challenges have been identified. These include design aspects and associated design rules for AM. Manufacturing challenges start with the raw material procurement and control (powder-screening methods, procurement specification and verification requirements). On the manufacturing process itself, process stability and its monitoring/controlling, the understanding of changes of process and parameters impact on final product play the major role. Moreover, space qualification and validation routes will be addressed. Lastly, standardisation will be presented in order to facilitate the market uptake of 3D printing and promote its innovation potential to industrial competitiveness.
Once the student will be fully aware of all currently available technologies their benefits and drawback as well as the main open challenges, real life case studies (mainly from the space and aerospace domain) will be presented. The objective of this part of the course is to provide the student with a current industrial implementation approach of Additive Manufacturing on high quality products. Real spacecraft, satellites, rockets or aircraft parts end-to-end design/manufacturing process will be shown. Starting with the design/topology optimisation (bionic design), moving to the selection of the ideal Additive Manufacturing technology up to the optimisation of the process parameters, the mechanical characterisation (static, fatigue, microstructure, NDI, computer tomography, eddy current, etc.) and the production of a breadboard to be full scale tested and then flown in orbit. Moreover, the course will also provide case studies and examples of failure investigations on real components.
Lastly, the course will provide an outlook on the future developments related to Additive Manufacturing, including the 4D printing as well as the industry 4.0 developments.

After succesfully completing the course, the student will be able to:
Identify trends, technologies and key methodologies related with digital and additive manufacturing for high-value-added products ( Applying Knowledge).
Develop new ideas and solutions in emerging industrial businesses. In fact, Additive manufacturing is one of the more active playground for new solutions, innovative ideas and start-ups. ( Applying knowledge and making judgements)
Interact in a professional, responsible, effective and constructive way in a working environment. The project work will allow all the students to interact in a multi-disciplinary environment. In fact the project team will mix students in management, mechanical, design, automation and physics engineering ( Team-working and communication abilities ).

Additive Manufacturing (AM or 3D Printing) is changing the industrial landscape worldwide, particularly in high-end technology sectors, including space, aerospace, racing and medical applications. The course will provide the student with a very deep understanding of the different Additive Manufacturing technologies and their industrial applications with focus on space and aerospace. A wide range of materials will be presented ranging from conventional and non-conventional metals, polymers, ceramics and geopolymers (e. g. moon regolith) and even covering living cells and human organs. All the currently open technical challenges will be presented. Moreover, the course will be complemented with “real-life” case studies from the aerospace sector. The case studies will cover real design developments from concept phase to in-orbit space flight as well as failure investigations on real components and units.
Detailed Program:
Detailed overview of all AM Technologies used on:
o Metals
o Polymers
o Composite Materials
o Ceramics and Glasses
o Living Cells/Human Organs
Description of all benefits per domain of application of the above mentioned technologies
Detailed overview of the open technical challenges, including:
o Dimensional Challenges
o Design Challenges
o Manufacturing Challenges (starting from materials supply chain up to manufacturing stability, pre-/in-/post-processing, etc.)
o Qualification/Verification challenges (mechanical characterisation, Non-Destructive Investigation, in-situ monitoring, etc.)
o Standardisation challenges
Case studies (2 to 3) providing deep understanding of the end-to-end design/manufacturing process:
o Design/topology optimisation
o AM technology selection and parameters optimisation
o Mechanical characterisation (static, fatigue, microstructure, NDI, computer tomography, eddy current, etc.)
o Manufacturing of the breadboard
o Full scale testing
o In-flight verification
What happens when it goes wrong?:
o Failure investigation case studies (2 to 3)
o Usual “illnesses” of Additive Manufacturing
What’s next:
o The future developments in Additive Manufacturing
Course timetable - please check WeBeep for the detailed schedule
*Please check the news on webeep for latest news on rooms and locations.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Grading will be based on a written examination, which include open questions. During the exam, the students will be asked to show the acquired knowledge on AM processes, techniques and methods and and their skills to identify current AM trends, the existing technologies and key methodologies ( Knowledge and understanding and Applying Knowledge and understanding abilities)
A team project will be carried out using the teaching lab of the AddMe lab of the Department of Mechanical Engineering. The project will check the acquired ability to develop new ideas and solutions and their capability of multidisciplinary team-working ( Making Judgements, Learning skills and Communication abilities ).

The course will allow the student to
design an asset management strategy;
understand equilibrium and no arbitrage pricing techniques;
understand mathematical models for risk management.

After the course the student will
build the portfolio frontier and define an asset management strategy;
know equilibrium and no arbitrage pricing techniques;
know the main concepts of stochastic calculus, which are essential in quantitative finance;
know how to price and hedge a financial derivative;
know how to solve analytically (if possible) a financial problem (asset management, pricing, hedging), exploiting the developed theoretical competencies;
know how to find proper modeling assumption to describe a financial asset (stock, interest rate, volatility, commodities, etc.);
know how to manage risk of financial derivatives.

Decisions in a risky environment: Portfolio selection
Portfolio frontier
Asset management: from theory to practice
Capital market models: CAPM & APT
Introduction to stochastic processes
Derivatives evaluation
Basic Interest rate products (Bonds, Repos, FRA, STIR, Swaps)
Option pricing
Numerical techniques: MonteCarlo and Tree (CRR)
Risk management of derivatives
The course includes sessions with examples and applications of the general theory to specific concrete cases, working also on real data.

Prova orale obbligatoria
The exam is based on an oral exam.

Roy E. Bailey, The Economics of Financial Markets, Editore: Cambridge University Press, Anno edizione: 2005, ISBN: 9780521612807
John C. Hull, Options, Futures, and Other Derivatives, Editore: Pearson, Anno edizione: 2009
Teaching notes

The course aims to provide students with the capabilities to master advanced modeling for operations in order to face management problems in different systems of interest. It will lead to the virtualization of the studied systems into different types of simulation models through which the decision-makers can conduct experiments, thus learning about the complex systems and helping the design of more effective decision-making structures and operating policies.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members

Understand the different concepts of simulation for analyzing operations problems and foster the introduction of innovation solutions and practices in complex systems and real-life business contexts [Understand]
Understand the use of simulation tools exploiting general programming languages or mathematical and simulation environments which allows improving analytical skill and mindset [Understand]
Apply criteria, models and tools to operations problems in order to provide the decision-making support considering different types of decisions (strategic, tactical and operational), various scopes (e.g. supply chain and single node of a logistics and production network), and multiple objectives (e.g. efficiency, sustainability, resilience) [Design]
Model and design innovative solutions in new fields (e.g. Industry and Logistics 4.0) [Design]
Improve team-working skills [Interact]

Simulation technique. Types and paradigm of simulation. Simulation objectives. Design and development of a simulation model. Generating probability distributions (Monte Carlo simulation). Design of experiment campaigns.
Event-oriented simulation. Modeling, analysis and design of complex systems (e.g. production systems) through event-oriented simulation paradigm.
Object-oriented simulation. Modeling, analysis and design of complex systems (e.g. supply chain and logistics systems) through object-oriented simulation paradigm.
Simulation-based intelligent support systems for decision-making. Use of simulation to develop decision support systems in smart processes (e.g. synchronized use of simulation with physical operations according to the Digital Twin approach).
Each topic is treated both theoretically and above all practically. In particular, the course intends to provide the skills to develop simulation models using the Python general programming language.
The course leverages the following teaching methodologies:
Theoretical lessons, to provide the students with both knowledge on the modelling of complex systems and criteria, methodologies, models, and tools to design and manage operations problems (ILOs 1, 2)
Practical lessons, to go through structured exercises to let the students apply what they learnt during the theoretical lessons (ILOs 2, 3 and 4)
Laboratory sessions, to go through assignments to let the students apply what they learnt during the theoretical lessons and work in small groups (ILOs 2, 3, 4 and 5)
Seminars, i.e. lectures given by external guests (managers and consultants to present the use of simulation to solve real-life business problems ) to provide the students with strong connections with the real applications of what has been learnt during the lessons (ILOs 1, 2, 4)

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
The final exam consists of an assignment (70% of the final mark) and a written exam (30% of the final mark).
Group assignment.
The assignment is carried out in small groups. The assignment will be assigned through the semester. Students are required to apply the models and tools discussed in the course (ILOs 1, 2, 3, 4, and 5) and summarise their output. The evaluation of the assignment is based on the developed summary.
Written exam.
The written exam is individual and made of theoretical questions: open and close questions where the students have to prove to be able to both describe and apply concepts learnt during the course to specific contexts/problems (ILOs 1, 3, and 4).
The teaching material consists of: (i) set of slides supporting the in-class lectures; (ii) practical lessons/exercises; (iii) selected references (selection of papers and chapters of relevant books, etc.). All the material will be available before the related lesson on https://beep.metid.polimi.it.

The course aims at providing students knowledge and tools to understand some fundamental concepts regarding agri-food systems, including food supply chains as well as society, environment, and other public and private stakeholders. Agri-food supply chains are introduced and analyzed under a strategic design lens, with focus on supply chain strategies, configurations and main processes.
The course also identify key trends for modern agri-food supply chain referring to sustainability and quality.
Moreover, students will be introduced to examples of real supply chains in different food industrial segments, in which relevant and specific sustainability challenges and transformation will be analyzed from a theoretical as well as from a practical perspective, through seminars by companies' speakers.
Teaching is delivered by a mix of:
Lectures and introduction of theoretical frameworks
Discussion of case studies
Seminars from companies and academic experts in specific domains
Recorded video-lectures to provide bases for in-class discussion

At the end of the course the students will be able to:
Understand the concept of supply chain and supply chain management
Describe the main typologies of food supply chains in terms of industry overview, main actors, key processes, main sustainability challenges and related innovations
Understand, describe and analyze the type of supply chain strategies and the main models for global supply chain configurations (for non-food and food products)
Understand and describe the main trends and challenges connected to sustainable development and the grand challenges connected to the food industry
Understand principles of the circular economy paradigm for the food system, main business models and main enablers of food waste prevention and management
Understand the key principles and challenges connected to food traceability and their implications for the agri-food supply chains
Apply knowledge and analyse paradoxical issues regarding sustainability in food, devoleping and defending arguments while also communicating the main results.

Introduction to the concept of supply chain, supply chain management
Supply chain management processes
Push/pull view of supply chain processes
The SCOR model
The impact of complexity and uncertainty
Strategic network design
Supply chain strategies and strategic fit: Fisher (1997) and Hau Lee (2002) models (discussion of case studies)
Global supply chain: drivers and different global supply chain configurations
Risk and resilience in food supply chains
Sustainability in the agri-food supply chain
Definition of sustainability: grand sustainability challenges for the agri-food industry
The role of the supply chain: threats and opportunities
How to accelerate sustainability transitions in the agri-food supply chain:
Collaborations for sustainable value creation
Short food supply chains (discussion of a case study)
Traceability in the agri-food supply chain
Circular economy principles and business models
The food waste hierarchy framework
Technologies and solutions for food waste reduction and valorization
Supply chain configurations, managerial and sustainability challenges and related innovation for various industrial segments and products.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale

• Mandatory written exam (weighting 70% of the final grade), consisting of multiple-choice and open-ended questions.
• Mandatory debate session (weighting 30% of the final grade). Students work in groups to prepare for and participate in a debate on an assigned topic.
  As part of the debate, each group is required to prepare:
• a PowerPoint presentation;
• a short written summary paper.
  During the debate session, students present and defend their arguments while taking part in the different phases of the debate process.

Samir Dani, Food Supply Chain Management and Logistics - From Farm to Fork, Editore: Kogan Page, Anno edizione: 2015
Sunil Chopra, Supply Chain Management - Strategy, Planning and Operations, Editore: Pearson, Anno edizione: 2019
Note: (Only chapters from 1 to 6 and chapter 17)

This course presents the major principles and applications of industrial economics. The course provides models of firms’ competition and of the functioning of industries. Students will acquire knowledge on theories of the firm, competitive structures, entry barriers, market failures and frictions, externalities, economics of technological change, industrial and competition policy. The concepts will be presented from the double point of view of firms competing on the markets and of policymakers who supervise and regulate their strategies and operations in the interest of society. Such an approach will teach students to make sense of the heterogeneity of real-world industries’ structures and of the consequences of this heterogeneity on firms’ profits, competitive dynamics, and, more generally, social welfare.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities.

• Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance.
• Develop new ideas and solutions in business and industrial scenarios evolving over time.
• Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members.

Main expected learning outcomes.

• Know concepts and definitions about the components and impacts of business and institutional contexts on firms' conducts and perfomance
• Understand models and economic theories that explain how the business context causes business conducts, firm performance and social welfare
• Apply the instruments provided in the course to the analysis of real-world cases and industries to enhance managerial and policy decision-making

Efficiency, coordination, and economic organization
Why do firms and industries exist? The role of specialization, exchange, coordination; Social welfare and the efficient allocation of resources; Coordination mechanisms: the invisible hand of markets and the visible hand of firms and institutions.
Competitive structures
Insights into different market forms; Concentration and concentration indices; Regulation of natural monopoly.
Market failures
Market power: Allocative inefficiency; Externalities: consumption and production externalities, remedies to externalities including environmental policy, network externalities; Public goods; Information asymmetries: moral hazard and adverse selection, remedies to information asymmetries: signals and incentives; Transaction costs: bounded rationality, specific investments, opportunistic behavior; Transaction costs and governance of transactions.
Oligopolistic markets
Strategic interdependence and duopolistic models; Entry barriers, entry deterrence and limit pricing; Price discrimination; The theory of contestable markets.
Theories of the firm and their implications
The neo-classical profit maximization assumption: critiques and alternatives; Theories of the firm: managerial theories, contractual perspectives (agency theory, property rights theory), resource- and knowledge-based theories; Determinants and insights into firm boundaries: horizontal and vertical integration, diversification, mergers & acquisitions, alliances and other intermediate forms between firm and market; Determinants of internationalization and the multinational corporation.
Technological change
Theories of technological change: the legacy of Schumpeter; Market structure and innovation; The economics of standards: hardware/software paradigm, winner-takes-all-markets and technological standard wars.
Industrial and competition policy
Classification of policies: industrial policy, regulation and antitrust; The economics of anti-trust (market power analysis, mergers, collusion and cartels, abuse of dominance); The economics of ex-ante regulation; Industrial policy: approaches and experiences.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Altro
Assessment of

• Compulsory written exam at the end of the course
• Voluntary participation in interactive activities
• Oral exam at the lecturer's discretion

Climate change, environmental pollution, resource scarcity are the contemporary challenges that call for urgent transition of the industry from the traditional paradigm of production and consumption towards circular economy and sustainable development. This course is designed to provide students with concepts and instruments necessary for analysing industrial practices in terms of their environmental performance, and for identification of relevant circular economy strategies for decoupling economic growth from environmental degradation, increasing resource efficiency and promoting sustainable lifestyles. The emphasis is given to the systemic perspective in examination of circular economy approaches at company and industrial system levels.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
Identify trends, technologies, key methodologies and stakeholder needs related to circular economy at company and industrial system levels
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and social environment

A student that has successfully attended the course is expected to:
Understand the role of circular economy in enabling the decoupling of economic activities from negative environmental impacts and fostering the transition towards sustainable development
Know and explain circular economy strategies and their limitations at company and industrial system levels
Identify and apply appropriate instruments for analyzing circularity and environmental impact of industrial operations
Critically analyse industrial practices and identify opportunities for improving their circularity

Basics of circular economy: industrial ecology, sustainable development, principles of circular economy, limitations of circular economy, circular economy strategies
Circular economy at the company level: circular product design, product/material end-of-life management: reuse, remanufacturing, recycling
Circular economy at the industrial system level: circular supply chain management, industrial symbiosis
Circularity and environmental impact analysis instruments: circularity indicators, environmental key performance indicators, material flow analysis, life cycle assessment
The course is organised in lectures (traditional and flipped classroom formats), seminars with guest speakers, exercises, business game sessions.
The lectrues will be streamlined online via Webex and recorded.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation of the course is based on a group assignment and an oral exam. The group assignment aims to evaluate student's ability to identify and apply appropriate instruments to develop a circular transition pathway in a specific industrial context. The oral exam aims to evaluate knowledge of the course materials, ability to indicate interconnections of discussed concepts and instruments and their limitations. During the semester, three self-assessment tests will be available for students to evaluate their understanding of the course content and preparation for the oral exam.

Slides and other classroom materials will be available on the WeBeep website of the course https://webeep.polimi.it/

The aim of the course is to discuss from the perspective of sustainable development the great environmental, economic and social challenges that humanity is facing in the contemporary era. The verb "discuss" is utilized deliberately to emphasize the interactive mode used throughout the course. Each and all of the problems are treated up to a global (planetary) scale and over long (from decennial to secular or even millennial) temporal scales. Particular attention is given to climate change and its consequences along many directions claiming for sustainable solutions, from agricultural and ecological dynamics to human and Earth health. Given the high level of complexity of the proposed issues, no univocal solutions are provided. Rather, the active research performed by the students during individual and group work, based on the most up-to-date literature and under the guidance of instructors, will let them deepen both the knowledge and the understanding about some specific, elective topics.

The specific learning skills acquired by the students are
Knowledge and understanding of the most important global changes that require the design of a sustainable path toward development, with particular and special focus on climate change. These include economic issues (indicators other than GDP, inequalities and poverty, the possibility of development without growth), environmental issues (such as biodiversity conservation, resources availability and urban resilience) and social issues (such as education and health). In particular, the scales of reasoning in students' minds are widened by the large geopolitical and the long temporal scales that are considered in the course. [Dublin Descriptor 1]
Ability of contextualizing and applying the concepts and tools learned to specific problems, going beyond the single-issue simplistic view of sustainable development that is typical of basic courses on the subject. [Dublin Descriptors 2 and 3]
Capacity of autonomously navigating through the pertinent, up-to-date international literature so as to argue pros and cons of potential solutions to specific problems. [Dublin Descriptor 3 and 5]
Group work attitude in preparing a dissertation to be presented to (and defended with) the whole class, as well as a short report to be submitted at the beginning of the exam session (communication skills) [Dublin Descriptor 4].

The course consists of two modules. The first module is specifically focused on Climate change, while the other is mainly devoted to implications of global changes to sustainable development. The two modules are not delivered sequentially, but in parallel because their contents are not separated but intertwined. Climate change is in fact seen here as one of the major global challenges to be faced by humanity in the present era.
Topics of the first module (Climate change) are the following:
Introduction to global environmental change: Understanding environmental change, Historical approaches to environmental change, Current approaches to environmental change, Contemporary patterns of global environmental change
The Earth system - The climate system (radiation and radiative balance- the equilibrium temperature of a planet)
Natural climate change and the ice ages: Milankovich theory. Climate dynamics and the general circulation of the atmosphere
Natural and anthropogenic climate drivers
Deep Decarbonization Pathway Planning and Mid-Century Strategies- The Three Pillars of Decarbonization
GCM scenarios - Downscaling methods for Climate change impacts evaluation
The second module of the course (Sustainable Development) is delivered using the flipped class methodology. Video-lectures are taken from the MOOC (Massive Open Online Course) entitled "The Age of Sustainable Development" by Prof. Jeffrey Sachs (Columbia University), freely available on Coursera. Each week, the students are requested to watch one video and/or study one chapter of the course book, so as to be ready for discussion during the class.
Lectures of the second module (Sustainable development) are
Introduction to sustainable development
An unequal world
A brief history of economic development
Why some countries developed while others stayed poor
Ending extreme poverty
Planetary boundaries
Social inclusion
Education for all
Health for all
Food security
Resilient cities
Saving biodiversity and protecting ecosystem services
Sustainable development goals

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The exam consists of two parts: an oral presentation (talk) with discussion during the course (group work), followed by the submission of a short report at the end of the course, and written tests plus a possible discussion on the paper (individual work). The students will be organized in groups (tentatively of three people). A list of topics of interest, as possibly resulting from discussion during lectures, will emerge during the classes. The group will perform research on the selected topics based on the available literature, will organize a talk (tentatively 15 minutes) and write a short report (Scientific Reports style, around 4000 words). The instructors reserve the right to discuss individually with each student the report they have written in groups, in order to ensure the personal contribution to the original research presented.The quality of the work done and the ability of the group to keep the class discussion vivid and alive, as well as the feedback provided to other groups, are part of the evaluation. The written tests will be performed individually and consist of answering questions and/or solving simple exercises so as to prove the familiarity of the student with the topics of the course. The final grade results from a combination of individual and group work. The individual portion (written tests plus optional oral exam at the teachers’ discretion) and the group portion (oral presentation and short report) each contribute 15 points (out of 32) to the final score, with up to 2 bonus points being given for active participation. The exam will be considered as passed with a final grade >= 18 and individual/group grades >= 8.

MOOC available at Coursera.org https://www.coursera.org/learn/sustainable-development
Jeffrey Sachs, The Age of Sustainable Development, Editore: Columbia University Press, Anno edizione: 2015, ISBN: 978-0-231-53900-5 https://cup.columbia.edu/book/the-age-of-sustainable-development/9780231173155

This course aims at achieving the following learning goals:

• LG1: Understand sustainability related context, functions, processes in a business and industrial environment and the impact of those factors on business performance
• LG2: Identify future trends, technologies and key methodologies in the domain of sustainable innovation

At the end of the course, students will be able to:

• LO1.1: Understand the relevance of sustainable innovation for the long-term success of a firm
• LO1.2: Understand the importance to work in a collaborative way with the involvement of a set of key stakeholders to effectivelly implement a sustainable oriented innovation
• LO2.1: Identify the role played by technologies and new approaches for the implementation of a sustainable oriented innovation

The first module aims at presenting the role of collaborative innovation to achieve sustainable impact. This module will cover the following topics:
Understand the need for sustainability-oriented innovation.
Understand the what sustainability-oriented innovoation is.
Understand the need for collaboration to achieve sustainability-oriented innovations.
The second module focuses on sustainable business models and on innovation promotion and impact. This module will cover the following topics
Sustainable business model innovation
Sustainable behaivior and innovation adoption
Assessing the sustainable impact.
The third module aims to apply the concepts of the first two modules to the main sustainable innovation models, including:
Base of Pyramid innovation.
Circular economy and industrial symbiosis.
Certification
Shared models
A project work is integral part of the course. The objective of projects is to help students in applying the approaches and principles we teach in class.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
In this course, two assessment methods will be considered:

• group work assignment: in the group work assignment, students will be asked to exploit the value of collaborations for sustainability for a specific company. The group work will be delivered at the end of the course by means of a report and a final presentation. During the course, there are no intermediate deliveries, but there are moments dedicated to feedback integrated in the course schedule.
• individual exam: in the individual exam, the students will be requested to demonstrate their understanding of the phenomenon of innovation for sustainability.

Rüdiger Hahn, Sustainability Management - Concepts, Instruments, and Stakeholders from a Global Perspective, Editore: Pearson, Anno edizione: 2025, ISBN: 9781292482576
Lüdeke-Freund, F., Breuer, H., & Massa, L., Sustainable Business Model Design - 45 Patterns., Anno edizione: 2022, ISBN: 978-3-9824003-3
Note: https://www.sustainablebusiness.design/

Objective of the course is to introduce the basic principles and design instruments for collaborative robotic devices, when coupled with a human being, to assist, rehabilitate, or augment movement capabilities. The main steps of the design of collaborative robotics in the healthcare domain are the definition of functional and technical requirements following a user-centered approach, the identification of a proper mechatronic framework, the identification of a sensor network for proprioception, and the definition of low level and high-level collaborative control framework.
A technical and functional evaluation with tests on a testbench and human subjects are finally needed.
Specific objectives of the course are:
to learn the methodology to define user specifications and technical requirements;
to learn the knowledge needed to understand and design the mechatronics system;
to learn the knowledge needed to understand and design the cooperative control framework;
to learn the knowledge needed to understand and design the sensor network for user’s intention detection and proprioception layer;
to understand how to perform Verification and Validation (V&V) of the integrated system.
The course has a strong practical and laboratory-based approach.

Lectures will be delivered by the lecturers followed by practical guided examples and open discussions. This will allow students to (DdD 1):
Analyze and understand the goals, assumptions and requirements associated to a collaborative robot, and model them formally;
Define the architecture of a collaborative robot mechatronic and control framework, and model them formally;
Identify and define the verification and validation activities needed for a collaborative robot.
The laboratory activities and the project work will allow students to (DdD2 and DdD3):
Simulate in Matlab environment kinematic, dynamic and path planning of a collaborative robot;
Design, build and control a simple collaborative robot;
Learn how to solve problems not strictly faced within the Course.

Introduction to the collaborative robotics problem - what is a collaborative robot for human augmentation; typical applications and trend for collaborative robots in healthcare (e.g., assistive robots, rehabilitation robots, service robots); a Short History of collaborative robots; robot classification (interaction modalities, end-effectors/rigid exoskeletons/soft exoskeletons, active/passive, etc.); different types of joints.
Definition of technical and functional requirements following a user-centered approach.
Kinematics of collaborative robots - forward and inverse kinematic problem; position, velocity and acceleration, joints and task space description.
Dynamics of collaborative robots, specifically related to robots worn by human subjects.
Basics of hardware-level designs for compliance.
Basics of low-Level Robot-Assisted Control Strategies (e.g. impedance, admittance).
Introduction to high-Level interaction Modalities (e.g. passive, active-assisted, active-resisted, error-augmentation).
Trajectory/motion planning for a collaborative robot.
Overview of strategies for user’s intention detection, including the selection of proper sensors to detect user’s intention of movement (e.g. inertial sensors, EMG sensors, eye tracking, Brain-computer interface) and basics of signal processing of biological signals.
Verification and Validation process.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
During the course, the students will work in small teams under the supervision of a lecturer and of a tutor.
Each group will be assigned with a specific assignment involving the definition of the functional specifications of a collaborative robot for healthcare applications and the use of a dedicated hardware. Students will be required to define the technical requirements, design the mechatronic system, integrate the sensors needed to detect the user’s intention, develop the control system, and perform preliminary functional tests.
A one-degree-of-freedom exoskeleton for educational purposes will be used to to carry out the assignment (EduExo Pro, AUXIVO).
The two course modules share a single final assessment, consisting of the following components:
Interim project presentation (6%): each group will present the progress of the project according to the schedule introduced by the lecturers during the first class and published on the course WeBeep page.
Project submission and demonstration (25%): during the final class of the semester, each group will submit the project code and present a practical demonstration of the developed system, according to the schedule published on WeBeep.
Individual examination (69%): during the official examination sessions, each student will be assessed individually through:
a written exercise covering the course topics (19%);
an individual discussion of the project (37.5%);
an oral examination on the course content (12.5%).
Please note that the grade awarded for the project component cannot be rejected or repeated within the same academic year.

Etienne Burdet, David W. Franklin, Theodore E. Milner., Human Robotics: Neuromechanics and Motor Control., Editore: The MIT Press, Cambridge, Massachusetts, London (UK).
Books of industrial robotics

Modern large-scale datacenters require the seamless integration of different components - applications, computation nodes, storage devices, and networks - into one computing infrastructure. The course covers the basics of current datacenters architectures, ranging from the analysis of the single components to the global infrastructure. The focus is on the foundations required to understand the design of computing infrastructures that are scalable, available, secure and flexible at the same time. Virtualization, container-based technology, cloud computing and storage systems are analyzed in depth to show how they can be used to support challenging tasks such as machine-learning applications and high-performance computing.

Knowledge and understanding (DD1):

• The student will acquire knowledge about the Computing Infrastructure field. In particular, the students will learn the essential elements that are part of a scalable data center and the basic concepts of reliability, performance evaluations, virtualization, and cloud computing.
  Applying knowledge and understanding (DD2):
• The student will be able to understand the design choices done within a large-scale computing infrastructure.
• The student will be able to design both computational and storage components of a data center, to satisfy specific service-level requirements
• The student will be able to apply performance and reliability analysis to the data center and to other complex systems, even outside the computer engineering domain
  Making judgements (DD3):
• The student will be able to explore alternative solutions within a data center, in terms of computing architectures and service models.
• The student will be able to analyze and discuss the trade-offs between reliability, performance, and costs of different hardware and software technologies within a data center.
  Communication skills (DD4):
• The student will be able to use the data center terminology appropriately.
• The student will be able to illustrate the characteristics and functionality of a data center infrastructure and related service models.
  Learning skills (DD5):
• The student will develop learning skills necessary to autonomously extend performance and reliability analysis to other types of components in a data center, and to autonomously understand novel technologies within computing infrastructures together with their impact.

Hardware infrastructure of datacenters:

• Basic components, Rack structure, Cooling
• Hard Disk Drive and Solid State Disks
• RAID architectures
• Hardware Accelerators
  Software infrastructure of datacenters:
• Virtualization: basic concepts, technologies, hypervisors and containers
• Computing Architecture: Cloud, Edge and Fog Computing
• Infrastructure-, platform- and software-as-a-service
  Methods:
• Scalability and performance of datacenters: definitions, fundamental laws, queuing network theory basics
• Reliability and availability of datacenters: definitions, fundamental laws, reliability block diagrams
  Exercises to apply the knowledge in simple examples or to more complicated scenarios will be used especially considering the parts related to reliability, storage system design, and performance analysis.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The evaluation consists of a written exam on the topics covered in the course. The exam will include both theoretical questions and numerical problems.
More in detail the written exam includes:

• Close-ended questions on course topics to verify the capacity to recognize the basic concept behind the design of a large-scale computing infrastructure; (DD1, DD2)
• Open-ended theoretical questions on course topics to verify the capacity to describe the key concepts related to the design of a large-scale computing infrastructure; (DD1, DD2, DD3, DD4, DD5)
• Numerical problem resolutions regarding analysis and design of data center and data center components, virtualization, storage systems, dependability, and performance modeling. (DD1, DD2, DD3)
  An oral test could be requested by the lecturer to deepen specific questions of the written test and further verify the capacity of the student to describe the key concepts related to the design of a large-scale computing infrastructure and develop links between the various topics of the course (DD1, DD2, DD3, DD4, DD5)

Course Web Site webeep.polimi.it
Luiz André Barroso and Urs Hölzle, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
Edward D. Lazowska, John Zahorjan,G. Scott Graham, Kenneth C. Sevcik, Quantitative System Performance: Computer System Analysis Using Queueing Network Models
Note: (Open Access Book) (chapters 1-4)
James Smith and Ravi Nair, "Virtual Machines" Versatile Platforms for Systems and Processes
Caesar Wu and Rajkumar Buyya, Cloud Data Centers and Cost Modeling

This course aims at providing the fundamentals of creative thinking and its stimulation in order to optimize the use of natural resources (raw materials and energy) in design and decision making activities. To this purpose, the course includes the execution of exercises and other design activities that require the application of methods, tools and techniques for the analysis of technical problems and the synthesis of solutions. These will be generated by means of a holistic approach that considers the relationship between the technical solution and other social/biological/technical systems and aims at minimizing the potentially harmful effects on the environment during the whole life cycle of the solution.

Theoretical and practice lectures will make it possible to:
Remember and Understand:
The creativity metrics;
The constructs of modelling techniques for the representation of products and processes in their life cycle;
The phases of a Life Cycle Assessment;
The approaches for problem reformulation and the identification of design solution opportunities;
Heuristics for the creative solution to technical problems of sustainability;
The primary sources of creative stimulation and their intrinsic organization
Apply, Analyse, Evaluate and Create:
Analyse an industrial context of reference to define challenges and objectives for environmental sustainability;
Evaluate their own design processes to estimate the effectiveness and the efficiency of creative thinking;
Analyse existing/competing solutions' environmental impact along their life cycle for the identification of problems of environmental sustainability that require creative solutions;
Analyse technical problems and create alternative formulations of the same for the identification of more convenient and environmentally sustainable solving strategies;
Evaluate the relevance of multiple sources of inspiration to stimulate the creative generation of original solutions;
Apply problem-solving heuristics to create solutions that overcome the analysed problems of environmental sustainability.

Approaches to highlight problems of environmental sustainability (Definition of sustainability, sustainable development goals and related targets; Linear to Circular economy transition – Identification of supply chain development opportunities; Life Cycle Assessment (LCA) for the identification of environmental problems; Life Cycle Assessment (LCA) to compare competing solutions)
Technological opportunities (materials and processes) for the development of more sustainable solutions (Eco-profiles of raw materials of industrial relevance; Sources of information and selection criteria for raw materials; Manufacturing processes and related environmental impacts; Sources of information and selection criteria for manufacturing processes)

Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The course is organized into theoretical and practice lectures that also include co-creative sessions to address simple design topics of industrial relevance. The theoretical lectures present all the topics of the course. The practice lectures enable the application of the contents taught during the theoretical lecture to practical problems of industrial relevance for in-class activities, both individually and in teams. The evaluation of the achievement of the intended learning outcomes will require the execution of a group project, where the team members will need to play a variety of design roles.

M. F. Ashby, Materials and the Environment. Eco-informed material Choice, Editore: Elsevier, Anno edizione: 2021, ISBN: 978-0-12-821521-0

See the program of the module in the master course

See the program of the module in the master course

L'insegnamento affronta il tema della creatività, in particolare nel campo della scienza e della tecnologia, con l'obiettivo di stimolare negli studenti la consapevolezza del fatto che esistono alcuni fattori chiave per creare ambienti di lavoro e modi di agire e pensare maggiormente creativi. Dopo una base teorica sulla creatività in generale e della creatività negli ambiti della scienza e della tecnologia, con particolare riferimento alle opere di Kuhn e Popper, vengono proposte una serie di metodologie da sperimentare in maniera laboratoriale, ispirate degli studi di Resnick, De Bono, Kelley e altri autori. L'approccio viene validato praticamente attraverso lo svolgimento di progetti di gruppo su temi dati, da affrontare in gruppi interdisciplinari.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua obbligatoria
See the program of the module in the master course

Data-driven and algorithmic technologies increasingly support or automate decisions in engineering, business, science, public policy and everyday life. Their outcomes, however, are not determined by technical performance alone: they also depend on how data are generated, selected and represented, on the objectives and constraints embedded in algorithms, and on the social contexts in which technological systems are designed and deployed.
The course provides students with an interdisciplinary framework for understanding, analysing and addressing fairness-related issues in data-driven technologies. It combines a sociological perspective on data, datafication and algorithmic processes with technical methods for identifying bias, evaluating different notions of fairness and designing fairness-aware technological and decision-making solutions.
The course is intended for students from different engineering backgrounds. It aims to show that data and algorithmic fairness is not a specialised topic limited to diversity and inclusion, but a central engineering challenge concerning the quality, reliability, legitimacy and societal impact of technological systems.
The sociological module introduces students to the relationship between data and society, considering the production and use of data as both a technological activity and a socio-political process. The technical module focuses on the mechanisms through which unfair outcomes may arise in data, algorithms and decision-making processes, and on methods and frameworks for evaluating and mitigating them.
Through lectures, discussions, case studies, exercises and a group project, students will learn to connect sociological interpretation, technical analysis and engineering design.

Upon successful completion of the course, students will be able to:
Explain and critically interpret how data and algorithmic systems are shaped by social, cultural, political and technological processes, and how their design and deployment may reproduce or transform existing inequalities.
Dublin Descriptor 1 — Knowledge and understanding
Analyse data-driven and algorithmic systems from a fairness perspective, identifying potential sources of bias across the different stages of the technological lifecycle and applying suitable concepts, criteria and methods to assess their outcomes.
Dublin Descriptor 2 — Applying knowledge and understanding
Formulate and justify fairness-aware design or policy choices, critically discussing alternative solutions, conflicting objectives, limitations and trade-offs, and clearly communicating the results of the analysis to audiences with different disciplinary backgrounds.
Dublin Descriptors 3 and 4 — Making judgements and communication skills
Class activities, independent study and project work will also support students in integrating technical and sociological perspectives, using feedback constructively and autonomously extending the course concepts to new application domains.
Dublin Descriptor 5 — Learning skills

The course is organised into two closely integrated modules.
Module A — Data and society: sociological perspectives
2 CFU
The first module introduces a sociological perspective on data and algorithmic processes. Data are considered not only as technical objects, but also as the result of social choices, classifications, institutional practices and power relations.
Topics include:
introduction to sociology and to the relationship between society and technology;
data, society and processes of datafication;
the social construction of data, categories and classifications;
identity, culture and technological systems;
the relationship between technology, power and inequality;
the role of gender, race and ethnicity, age, disability and socioeconomic conditions in the production and use of data;
historical and contemporary case studies concerning data-driven technologies;
data feminism and design justice;
epistemic injustice and its relevance to data production, technological design and decision-making;
the social, cultural and political implications of algorithmic systems in scientific, business, policy, healthcare and everyday-life contexts.
The module combines lectures with in-class discussions, exercises and case-study activities. This reflects the approach proposed for the sociological module, in which data production and application are treated as both technological and socio-political phenomena.

Prova scritta obbligatoria, senza prove in itinere
Valutazione continua obbligatoria
The course adopts an interdisciplinary and student-centred approach. Teaching activities combine:
lectures introducing sociological concepts, technical methods and analytical frameworks;
guided discussions on scientific literature, technological applications and controversial cases;
individual and small-group exercises;
analysis of real or realistic case studies;
activities requiring students to compare alternative definitions and approaches to fairness;
supervised development of a group project;
final presentation and discussion of project results.
The group project requires students to select or analyse a data-driven or algorithmic application and examine it from both a sociological and a technical fairness perspective. Depending on the selected case, students may analyse data generation, model assumptions, performance across population groups, decision rules, deployment conditions, affected stakeholders and possible mitigation strategies.
The project is intended to develop the ability to integrate perspectives from different disciplines and to formulate technically informed and socially aware design recommendations.
Indicative teaching mix
Teaching activity
Hours
Didattica trasmissiva/frontale
28
Didattica interattiva/partecipativa
12
Didattica laboratoriale
4
Didattica progettuale
6
Didattica valutativa
0
Total assisted teaching
50
Independent study and project work
75
Assisted teaching hours per CFU
10
This classification is consistent with the current distinction between transmissive teaching, interactive activities, laboratory work and project-based teaching. In particular, discussions, guided exercises and case-study activities fall within interactive teaching, while the supervised development and revision of the group assignment are appropriately classified as project-based teaching.

Il corso "Data Intelligence Applications" propone l'adozione di tecniche di machine learning, principalmente nel campo dell'online learning in applicazioni reali. In particolare, il corso si focalizza su quattro applicazioni di grande interesse per il mercato: pricing in scenari di commercio elettronico, applicazioni di matching online, advertising digitale e influenza sociale. Inoltre, il corso fornisce tecniche non banali di learning, come algoritmi bandit non stazionari, bandit combinatori, bandit basati su processi Gaussiani, regressione tramite processi Gaussiani, apprendimento da dati generati da processi bandit. Agli studenti è richiesto di produrre dei prototipi di algoritmi capaci di lavorare su dati molti vicini ad applicazioni reali.

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a circular business and industrial environment and the impact of those factors on business and technical performance measures.
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a circular business case, focusing on demanufacturing and remanufacturing processes for recoverying and reuse functions and materials from high-value, post-use products in multiple sectors.
Develop new ideas and solutions in circular business cases, grounding on the knowledge of the available technological solutions supporting demanufacturing and remanufacturing and evolving in line with the general technological, business and regulatory framework.

Understand: The students will learn the key definitions of circular economy business cases, the underlying motivations, and the boundary conditions affecting the successful industrial transition to this sustainable production-consumption model. Moreover, they will learn the key role of advanced de-and remanufacturing systems in view of the development and implementation of circular economy business models at industrial scale. Several real-life examples will be discussed in order to support the in-depth understanding of business practices.
Design: The students will learn scientific and engineering methods in support of an efficient design and management of advanced demanufacturing and remanufacturing systems.
Develop: The students will learn the most relevant circular economy problems of the future and will be challenged with the analysis of future technology and business innovations to support these emerging needs.

The economical and environmentally sustainable treatment of end-of-life products and industrial waste by de-manufacturing processes is the core topic of this course. De-manufacturing includes the set of technologies, tools and knowledge-based methods to remanufacture and re-use functions and to recover materials from industrial waste and post-consumer high-tech products, under a circular economy perspective. This course provides competences related to mechanical de-manufacturing processes and systems, with the objective to design and operate these technologies in environmental and economical sustainable way, in different industrial settings.
The course will be structured to cover the following topics:

• De-manufacturing paradigm: definition of de-manufacturing systems and examples of industrial applications; De-manufacturing performance measures; Integrated process and system view of the problem; recent trends in de-manufacturing system and the role of the Digital Product Passport.
• De-manufacturing technologies: description of mechanical de-manufacturing processes, including disassembly, re-manufacturing and recycling technologies; mechanical size-reduction and separation processes; the role of hybrid data-driven and physics-based models in the design and operation of de-manufacturing and remanufacturing processes; advanced de-manufacturing technologies based on automated and semi-automated systems.
• De-manufacturing systems: features of de-manufacturing systems; material mixtures and granular flow models; multi-stage de-manufacturing systems modeling; performance evaluation and design of de-manufacturing systems; flexibility in de-manufacturing systems.
  The students will carry out laboratory activities to develop hands-on knowledge on specific processes and process-chains.
  Detailed Lectures Plan (32h)
  Introduction (6h)
  De-manufacturing paradigm: definitions and context.
  Integrated view of disassembly, remanufacturing, recycling, and recovery.
  Overview of de-manufacturing processes and systems.
  Examples:
  Remanufacturing of mechatronic components in the automotive industry: Electronic Control Units (ECUs), starters, alternators, engines.
  Recycling systems for End of Life Vehicles (ELVs): workflow and ASR (Automotive Shredding Residue) problem.
  Recycling systems for WEEE: focus on Printed Circuit Boards (PCBs).
  Recovery of key-metals from Lamps, hard drives, and PCBs.
  Performance Measures: grade/recovery trade-off.
  Integrated process and system view of the problem.
  De-manufacturing processes and technologies (13h)
  Mechanical disassembly and remanufacturing processes. Disassembly graphs and disassembly planning.
  Mechanical recycling processes: size-reduction and separation.
  Mechanical size-reduction processes:
  Overview of the cutting mechanisms and shredding machines;
  Population Based Models for size reduction processes;
  Experimental analysis;
  Application and analysis of the results.
  Mechanical Separation processes:
  Separation principles, physics and mechanisms;
  Overview of technologies: eddy current separation, electrostatic separation, magnetic separation, floatation, sieving, jigging, separation by air, optical sorting technologies (NIR, VIS, SWIR). Comparison of technologies and criteria for the selection of the most suitable process/technology.
  Modeling and simulation of separation processes;
  Analysis of the output and use of the models for process parameters optimization.
  Thermal and chemical processes: characteristics and requirements on the upstream processes (hints).
  De-manufacturing systems (13h):
  De-manufacturing systems architectures and material transportation technologies.
  Modeling material mixtures and granular flows.
  Performance Evaluation of de-manufacturing systems:
  Mass Balance Equations;
  Analytical modeling of de-manufacturing systems dynamics.
  Design of de-manufacturing systems;
  Flexibility and modularity in de-manufacturing systems.
  Detailed Classworks and Labs Plan (21h)
  De-manufacturing process planning (4h):
  Exercise: given a set of electronic and mechatronic products, the student will analyze their structure, their materials, their joints and will decide upon the best possible de-manufacturing process sequence, also through practical sessions.
  Exercises: calculation of performance measures.
  De-manufacturing processes and technologies (9h):
  Exercises: disassembly processes optimization.
  Exercises: disassembly line balancing (both deterministic and stochastic).
  Exercises: use of the size reduction simulation model for process parameters’ selection.
  Visit to the CIRC-eV lab.
  De-manufacturing systems (8h):
  Exercises: analytical modeling of de-manufacturing system.
  Exercise: use of the separation models for the analysis of the recovery and grade in different operating conditions.
  Exercises: reconfiguration of recycling systems; impact of different flow control logics.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The course is based on lectures, integrated with exercise sessions, also using laptops, as well as laboratory sessions with hands-on and experimental activities at lab scale. Moreover, optional industrial visits will be organized. The exam includes a written part, focused on exercises, and an oral part, with questions dealing with the whole program. To access the oral part, the written part has to be approved with a sufficient mark. Both parts have to be approved during the same exam session. Optional seminars and small projects will also be offered to deeply analyze specific topics of the course in small teams along with the course development. The results of these optional project works have to be presented before the end of the semester. The quality of this integrative work will be reflected in the final mark.

L'insegnamento fornisce strumenti per meglio comprendere l'articolazione che le tematiche di genere assumono nell'ambito del design. Si intende affrontare l'oggetto di studio a partire dal contributo disciplinare del Design della comunicazione e dei possibili spazi di relazione e integrazione tra i domini delle Culture visive (Design della comunicazione) e del Design e quello delle Scienze sociali, rappresentato dai Gender Studies (Culture di Genere). Verranno sviluppati studi e riflessioni critiche per indagare, in particolare, le forme di rappresentazione dell'identità femminile nel sistema dei media (attraverso i diversi artefatti comunicativi: dai supporti della grafica editoriale, al manifesto, al packaging, agli spot ecc.), così come le forme espressive dei prodotti industriali là dove assumono il ruolo di marcatori di genere.

Il corso fornisce le competenze in materia di sostenibilità necessari a trasformare la comunicazione di contenuti complessi in un'informazione chiara, trasparente, reale e diffusa. Le lezioni introdurranno una metodologia di progettazione specifica per raccontare le strategie, gli obiettivi e i progetti legati alla sostenibilità, basata sull'utilizzo integrato di contributi visivi, mappe concettuali e infografiche che completano ed enfatizzano le informazioni principali presenti nel testo. Lo studente acquisirà gli elementi necessari a contestualizzare i processi creativi, rendendo così più accessibili tematiche articolate e sistemiche anche a coloro che non sono gli addetti ai lavori.

Questo corso introduce i concetti di progettazione e analisi degli esperimenti insieme alla teoria dei modelli lineari. Il corso parte dai principi di base di progettazione della sperimentazione e si introduce il concetto di ANOVA a singolo fattore nell'approccio parametrico e non parametrico. Si tratta anche il tema dell'ANOVA a effetti casuali. Successivamente si introduce il concetto di design a blocchi randomizzati, quadrati greci/latini e design a blocchi bilanciati incompleti. Successivamente si affrontano i piani fattoriali 2k e l'utilizzo dei punti centrali per la stima della curvatura. Si parla di regressione lineare semplice e multipla, di verificare le ipotesi utilizzando test diagnostici, inferenza e selezione modello/variabile.

The principle of development economics are key to understanding how we got to where we are, and why many development problems are so difficult to solve, and to the design of successful development policy and programs.
The first goal of this course is to ensure that students understand real conditions and institutions across the developing world. The second is to help students develop analytic skills while broadening their perspectives of the wide scope of the field. The third is to provide students with the resources to draw independent conclusions as they confront development problems, their sometimes ambiguous evidence, and real-life development policy choice.

On successful completion of this course, students will be able to: 1. Demonstrate familiarity with some central themes and issues of economic development. 2. Demonstrate the understanding of the difference between growth and development, major growth theories, the measurement of inequality, significance of poverty, international trade, and role of foreign investments. 3. Discuss competing theories of economic development; 4. Analyse empirical evidence on the patterns of economic development. 5. Read critically the journal literature and draw independent conclusions as they confront development problems, their sometimes ambiguous evidence, and real-life development policy choice (also thanks to some ad hoc seminars from the United Nations and/or World Bank).

Introducing Global Development
Traditional economic measures and the new economic view of development. The Millennium Development Goals.
Textbooks: Todaro M.P., Smith S.C. Economic Development, 12 th Edition. Addison Wesley, ch.1-2
De Janvry A., Saudolet E. (2016). Development Economics: Theory and Practice. Routledge, ch. 1.
Readings
Sachs JD, Mellinger AD, Gallup JL. 2001. The geography of poverty and wealth. Scientific American. March; 284(3):70-5.
Poverty, inequality and development
Measuring inequality and poverty.
Textbook: Todaro M.P., Smith S.C. Economic Development, 12th Edition. Addison Wesley, ch. 5
Readings
Foster J., Seth S., Lokshin M., Sajaia Z. 2013. A unified approach to measuring poverty and inequality. Theory and practice. The World Bank.
Deaton A. 2021, Covid-19 and global income inequality. Working Paper 28392. February 2021 http://www.nber.org/papers/w28392
Rao Fu, Gui Jin, Jinyue Chen, Yuyao Ye (2021). The effects of poverty alleviation investment on carbon emissions in China based on the multiregional input–output model, Technological Forecasting and Social Change, 10.1016/j.techfore.2020.120344, 162.
Classic Theories of Economic Growth and Development
Development as growth and the linear stages theories. Structural change models. The international-dependence revolution, and the neoclassical counterrevolution.
Textbook: Todaro M.P., Smith S.C. Economic Development, 12th Edition. Addison Wesley, ch. 3
Readings
Diao X., Ellis M. McMillan M.S., Rodrik D. 2021. Africa's Manufacturing Puzzle: Evidence from Tanzanian and Ethiopian Firms. DOI 10.3386/w28344. NBER Working Paper 283 44. January 2021
Korinek A., Stiglitz J.E. 2021. Artificial Intelligence, Globalization, and Strategies for Economic Development. NBER Working Paper 28453 http://www.nber.org/papers/w28453
Contemporary Models of Development and Underdevelopment
Underdevelopment as a coordination failure. The Big-Push. Amartya Sen: The capability approach.
Textbook: Todaro M.P., Smith S.C. Economic Development, 12th Edition. Addison Wesley, ch. 4
Readings
Easterly W. 2006. Reliving the 1950s: the big push, poverty traps, and takeoffs in economic development, Journal of Economic Growth, Volume 11, Issue 4, pp 289–318
Institutions and development
Textbook: De Janvry A., Saudolet E. (2016). Development Economics: Theory and Practice. Routledge, chapter 20.
Readings
Abramovitz, M. (1986). Catching Up, Forging Ahead, and Falling Behind. Journal of Economic History, 46:2, pp. 385-406.
Acemoglu D., Smith J. The role of institutions in growth and development, Review of Economics and Institutions, 2010, vol. 1, no. 2, pp. 1-33.
Acemoglu D., Johnson S., Robinson J. 2001. The colonial origins of Comparative Development: An Empirical Investigation, American Economic Review, Vol. 91, No. 5 (Dec., 2001), pp. 1369-1401.
International Trade Theory and Development Strategy
Traditional trade strategies for development: Export promotion vs. import substitution. South-south trade and economic integration
Textbook: Todaro M.P., Smith S.C. Economic Development, 12th Edition. Addison Wesley, chapter 12
Readings
Harrison A. 1996. Openness and growth: A time-series, cross-country analysis for developing countries, Journal of Development Economics 48 (2), 419-447
Hanson GH, Harrison A. 1999. Trade liberalization and wage inequality in Mexico, ILR Review 52 (2), 271-288.
Multinational Enterprises, Global Value Chains, and local development.
Textbook: Todaro M.P., Smith S.C. Economic Development, 12th Edition. Addison Wesley, chapter 14
Readings
Aitken B.J., Harrison A.E. 1999. "Do Domestic Firms Benefit from Direct Foreign Investment? Evidence from Venezuela," American Economic Review, vol. 89(3), pages 605-618.
Amendolagine V., Boly A., Coniglio N.D., Prota F., Seric A., 2013. FDI and Local Linkages in Developing Countries: Evidence from Sub-Saharan Africa. World Development, Volume 50, pp. 41-56.
Haddad M, Harrison A. 1993. Are there positive spillovers from direct foreign investment? Evidence from panel data for Morocco, Journal of Development Economics, 42 (1), 51-74.
Eskeland GS, Harrison AE. 2003. Moving to greener pastures? Multinationals and the pollution haven hypothesis, Journal of Development Economics, 70 (1), 1-23.
Impact evaluation of development policies and programs
Textbook: De Janvry A., Saudolet E. (2016). Development Economics: Theory and Practice. Routledge, ch. 4.
Readings
Galiani S., Gertler P., Schargrodsky E. (2005), Water for life: The impact of the privatization of water services on child mortality, Journal of Political Economy 113(1): 83-120.
Guidolin M., La Ferrara E. 2007, Diamonds are forever, wars are not: is conflict bad for private firms?, American Economic Review, 97(5): 1978-93.
New advances in behavioral economics and development
Textbook: De Janvry A., Saudolet E. (2016). Development Economics: Theory and Practice. Routledge, ch. 4.
Readings
Duflo E. 2020. Field Experiments and the Practice of Policy. American Economic Review, 110(7): 1952–1973
Servet J-M., Tinel B., (2020). The behavioral and neoliberal foundations of randomizations, Strategic Change, 10.1002/jsc.2328, 29, 3, (293-299).

Prova scritta facoltativa (a scelta dello studente), senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
Assessment:
The exam could be undertaken with two different modalities
Type 1:
The exam is constituted by two parts:
Group assignment with intermediate and final oral presentation (50%)
Final Test (50%)
Type 2:
(Oral) Exam in the regular sessions (June, July, September).
Type 1 is more likely to be chosen by attending students; however, as attendance is not compulsory, any student can in principle select either type 1 or type 2.

Please see the references to each subject in the dedicated field

Digital technologies are increasingly used to support the design, operation and control of manufacturing systems. In industrial environments, effective decision-making requires models that represent the current state of the system, account for variability and uncertainty, and incorporate the interaction between human operators and digital technologies.
The course introduces methods and tools for developing and using digital models of manufacturing systems, with particular emphasis on Digital Twins and human-centred production environments. Students will learn how to represent manufacturing resources, processes, products and human activities, and how to use these representations to support monitoring, analysis and short-term operational decisions.
Within the Management Engineering curriculum, the course contributes to the development of the ability to:
analyse the functions, processes and interactions of business and industrial systems, considering their economic, environmental and social implications;
formulate and solve industrial problems using scientific and engineering methods;
integrate data, models and digital technologies to support decisions in complex manufacturing environments;
evaluate the role of human operators in digitally enabled production systems.
The course supports these programme-level capabilities through the modelling, analysis and control of human-centred manufacturing systems.

By the end of the course, students will be able to:
model the main elements and behaviour of a manufacturing system using Digital Twin concepts;
select and apply appropriate digital and AI-based methods to a manufacturing problem;
integrate models, data and software tools into a coherent application;
analyse results and assess the assumptions, limitations and industrial value of the proposed solution;
communicate the methodology and results of a technical project.
Each student will complete an individual project on one of the topics covered in the course.
The specific knowledge and technical skills developed will therefore depend partly on the selected project.
Students may exchange general methodological information and use shared software components or datasets when authorised by the instructor, but the submitted analysis, implementation, results and report must be individual.

1. Digital representations of manufacturing systems
Digital Factory, Digital Twin and AI-enabled manufacturing concepts.
Digital representation of resources, processes, products and their interactions.
Manufacturing data models, standards, ontologies and Digital Twin architectures.
Behavioural modelling, data integration and AI-supported model updating.
Use of machine learning and immersive technologies for system analysis, visualisation and operator support.
2. Modelling and monitoring human activities
Representation of human operators, human–machine interactions and manually executed processes.
Computer-vision and deep-learning methods for pose estimation, object detection and activity recognition.
Modelling and monitoring of manual operations using multimodal data.
Detection of deviations, errors and unsafe conditions in human-executed tasks.
Technical, organisational, ethical and privacy aspects of AI-based human monitoring.
3. Digital Twin-based analysis and operational control
Synchronisation between physical systems, Digital Twins and AI models.
State estimation, prediction and monitoring of manufacturing operations.
Use of Digital Twins and machine learning for simulation, forecasting and what-if analysis.
AI-supported planning, scheduling and operational decision-making.
Validation and assessment of robustness, uncertainty, explainability and industrial applicability.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, individuale, con revisioni periodiche, con presentazione/discussione finale
Assessment is based on:
an individual project developed throughout the semester;
a written project report and the related software or digital models;
an oral presentation and discussion of the project;
a written test covering the theoretical and methodological topics of the course.
The project will be evaluated on the basis of:
correctness and coherence of the proposed methodology;
quality of modeling hypotheses and implementation;
appropriate use and integration of digital tools;
quality of the experimental analysis and interpretation of results;
awareness of assumptions and limitations;
clarity and reproducibility of the submitted work;
quality of the oral presentation and discussion.
Weighting:
project, implementation and report: 55%;
oral presentation and discussion: 20%;
written theoretical test: 25%.

The course Digital Security Management addresses the fundamental management and technical aspects of security and privacy in organizations, emphasizing the need for good security management practices. The goal of this course is to provide concepts and practical methods about the management of security policies, methods, tools, services, and responsibilites in organizations.
The knowldege that will be acquired can enable an aware communication between those who speak the language of security and those who are acquainted with the language of enterprise, so supporting informed conversations between technology teams and organization managers.
More precisely, the course aims are to: i) identify the problems and concepts of security and privacy management in organizations; ii) show how these problems can be solved through organizational and technical measures. Therefore, it describes the policies, methods, tools, and resources to set in place in private and public organizations towards these aims.

The course is organized in two parts: 1) an introduction to the definitions and problems of security, fundamentals and management, in particular; 2) the description of technical measure that can be adopted to deploy security management.
Security and privacy of enterprise systems is focused, with a view of new applications, such as data science and big data, streaming from IoT systems, Datawarehouse systems, and cybersecurity.
The GDPR and the legislation at the Europena level for security, privacy and AI an its application are analyzed through descriptions of guidelines to security plans formulation. Testimonials of security management will give cases and experiences in practical application of measures for data privacy, security plans, management of security services for privacy protection, and other security management in enterprises.

PART I SECURITY MANAGEMENT CONCEPTS
Introduction to Security Management Concepts.

• Fundamentals of security: Physical, Organizational and Technical Security, threats, attacks, defenses,
  principles of cryptography, network security, audit, definition of Cybersecurity.
• Security Properties (Confidentiality-Privacy, Integrity, Authenticity, Availability)
• Attacks, vulnerabilites, countermeasures.
  Security as a Non-Functional Requirement.
• Security as a Quality of Service (QoS) parameter: information security and security information (costs of maintenance and
  hidden costs).
• Security specifications: description of what/where/when/how to monitor and control, languages and tools for specification.
• Security impact on organization structures: analysis methods (business, organization, architecture, technology cycle.
• Resource Management and Security: Security by Design, organization and technical measures. Security Policies.
• The GDPR for privacy and its application.
• Policies in Europe, US and other Countries (DoD, NIST Criteria, Standardization Agencies).
  PART II TECHNICAL ISSUES FOR SECURITY MANAGEMENT
  Services for Security Management.
• Smart access and authentication model and services.
• Organizational services (policies, plans, security charts, etc.).
• Access, authorization, user profiles management.
• Decision Making in dynamic, agile and distributed organizations.
• Security services for Certification, Authorities, trust systems, PKI, evolution of cryptography management.
  Data Security
  Policies and models.
  Security management in the DBMS, role of the Security Officer.
  New trends: security of Big Data, security of the Data Warehouse, Cybersecurity.
  Security Plans Management
  Data Protection Plans.
  Guidelines to formulation, continuous monitoring and adequacy.
  Ethics, privacy, governance
  Examples in several domains: Banking, Healthcare, Insurance, Industry, Manufacturing, Government
  Security and AI: issues, legislation, technical aspects, ethical aspects.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, individuale, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua obbligatoria
Presentation of a project developed in class. The project (by individual or groups of 2 students) is developed during the teaching time in class, and through home work. A set of project themes is proposed by the teacher. The students can also propose a case they know or they are already working at in other classes or in their personal life.
The project develops the description of an anlyzed AS-IS enterprise security status, and proposes a set of guidelines to improve security be putting into evidence the security lacks in data, machines, networks, organigram and so on. The ISO 27001 standars is the guide during risk analysis and security measures deployment. The case is illustrated in the final classes as a presentation given by the student in simulation of a company presentation. The project documentation (between 40 and 60 pages, formatted according to a teachedr-defined index) is to be uploaded on WEBEEP 10 days before the exam. The evaluation of the project sums up to 16 points.
Written or oral exam on security issues presented in class is the second part of the exam, grading to a maximum of 16 points.
Additional points can be gained by the students by selecting a reading set on topics proposed by the teacher. A summary of reading work is presented in class using slides prepared by the student. This part is optional and gives 1 or 2 additional points.

Stallings, William, and Lawrie Brown., Computer security: principles and practice., Editore: Pearson, Anno edizione: 2015
Castano, S., Fugini, M., Martella, G., Samarati, P, Database Security, Editore: Addison-Wesley, Anno edizione: 1995
M.FUGINI, Security Management Notes, Anno edizione: 2024 https://fugini.faculty.polimi.it/
Note: avalable as pdf
Trim, P. R., & Lee, Y. I. (2023), Managing cybersecurity threats and increasing organizational resilience., Anno edizione: 2023 Big Data and Cognitive Computing, 7(4), 177

The course is aimed at providing the Students with practical concepts and instruments for modelling complex systems in their operative environment or asset, potentially simulating the entire life-cycle of an industrial system (including degradation phenomena) through its Digital-Twin.
The course will merge the multidisciplinary inputs from energy, mechanical, electrical, control and management engineering in a unique and coherent virtual framework that can be used for design, operation and monitoring optimizations.
The course will introduce students to the field of industrial system monitoring, specifically focusing on the role of models (and Digital-Twins) in the diagnosis and prognosis of industrial systems and components, exploiting statistical pattern recognition and machine learning to interpret changes in their measured features.
The course will provide additional insight to the modelling of energy plant systems, with laboratory experiences focused on realistic application scenarios, also involving national and/or international industrial representatives.

By the end of the course, students will learn contents and practices according to what defined in the leaning objectives.
In terms of acquired knowledge and understanding, students will be able to:
Examine scenarios where Digital-Twin models can bring benefits
Predict benefits and drawbacks of modelling methods in the framework of industrial system design, operation and monitoring optimization
Interpret existing application studies in the literature and implement methodologies appropriate for solving complex problems, both systematically and creatively.
Concerning the ability to apply the acquired knowledge and understanding, students will be able to:
Apply the methods covered during the course on realistic scenarios
Demonstrate the pros and cons of the modelling strategy in relation to the application scenario
Critically, independently and creatively solve problems with some originality in new or unfamiliar environments within the multidisciplinary context of Digital-Twins
Through a schedule of hands-on practices and laboratories, students will also acquire the skills to formulate a judgment, meaning to
Analyse the modelling framework
Formulate subjective expectations on the results
Judge the results as a comparison with prior expectations
Provide a sound judgments even on the basis of incomplete or restricted information
Furthermore, through the group laboratories, students will gain the ability to autonomously take initiative to identify and address learning needs for further knowledge, leveraging on the multidisciplinary background of the group. Additionally the students will improve their management and relational soft skills by working as a group of experts.
Finally, students will improve their communication skills, being able to communicate their conclusions and recommendations with the argumentation of the knowledge and rationale underpinning these, to both specialist and non-specialist audiences clearly and unambiguously.

The course contents are delivered through lectures and hands-on computer laboratory practices with professors and/or a tutor.
The course covers the following topics divided in modules as per the description below:
Module 1 - Introduction
Topic 1.1 - Introduction and motivation for the rapid growth of Digital-Twins for industrial applications. Real case examples will be provided as input to the students, thus setting the motivation and goal of the course. Specific attention will be devoted to the application of Digital-Twins for system health management and maintenance optimization.
Topic 1.2 - Design and maintenance criteria evolution (from safe life to damage tolerant design, from fault driven to predictive maintenance). Introduction of Health and Usage Monitoring Systems as a means toward process automatization.
Module 2 – Physics-based modelling
Topic 2.1 - Physics-based modelling: application of time-based simulation with MATLAB SIMULINK-SIMSCAPE. Hand-on practices on energy system simulation.
Topic 2.2 - Degradation and failure mechanisms: an overview of different degradation and failure mechanisms occurring on the most widely used components in the energy field of application is provided, including fatigue, creep, corrosion, pitting, lubricant degradation, battery State of Charge, including an overview of failure and degradation mechanisms. The students will particularly focus on the analytical and numerical modelling strategies for predicting damage progression.
Topic 2.3 - Time-based modelling of system degradation: simulation is used to predict in a virtual environment the effect of a potential damage over the system features observed by a sensor.
Module 3 – Event-based modelling
Topic 3.1 - Event-based modelling: Discrete Event Simulation (DES) is introduced as a means to simulate systems depending on discrete time, with particular focus on event-based degradation modelling. Practical laboratories using MATLAB SimEvents (in combination to Simulink) will be provided, e.g. modelling scenarios typical of the operation research discipline.
Topic 3.2 - Decision logic modelling: concepts and instruments will be provided to simulate the decision logics in an operative framework. Practical laboratories using MATLAB State-Flow will be provided, simulating realistic scenarios of industrial systems’ management, e.g. the battery management system and the operation and monitoring of energy systems.
Module 4 – Surrogate modelling
Topic 4.1 – Surrogate modelling: for most application, the Digital-Twin should be fast enough to be run in real-time. This is not feasible with direct simulation, while surrogate models can be used for approximating input-output relations. Different methods based on Machine Learning (e.g. Artificial Neural Networks, Gaussian Processes, etc.) will be considered for the definition of surrogate models.
Module 5 – Model updating
Topic 5.1 - Basics of Monte-Carlo sampling: the concept of Monte-Carlo sampling will be recalled as a mean to implement repeated and efficient (forced sampling) simulation of the Digital-Twin.
Topic 5.2 – Digital-Twin updating: the Digital-Twin must be updated during service life based on observations by sensors. Various methods for parameter identification and tracking based on Bayesian inference and Monte-Carlo sampling will be implemented in the framework of damage identification and operation optimization, including the Metropolis-Hastings Monte-Carlo Markov Chain and the Particle Filter.
The theoretical aspects introduced in the course will be correlated with laboratories, for a direct implementation of the methods, e.g. including the implementation of a digital-twin for the Health and Usage Monitoring and Prognostic Health Management of energy systems and components, e.g. including pressure vessels, pumps, batteries, etc..
The students will apply the concepts developed during the course to real-case studies.
Students will analyze the industrial system, modelling its components in their operative scenario, including potential degradation and failure mechanisms and the logistic support to guarantee their operability.
Students will perform trade-off analysis to support management decisions
Finally, the students will provide a report in the form of a presentation of their results, that will be evaluated as part of their final score.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Students will pass the course after delivering a report of the practices and laboratories developed together with a tutor and a written examination intended to assess the understanding of both the theory aspects and the concepts delivered through the reports.
[Report]
Via this exam, it will be possible to test students’ acquired knowledge and understanding, their capability to apply the acquired knowledge and understanding, and their capacity to synthetise them through short reports. A 4-page report is required for some specific practices and laboratories, including a short summary of the topic goal, the method used with boundary hypothesis for its application to the case study, the results and comments on the results. Groups of 2 students are allowed in making the reports.
[Written exam]
Theory questions will allow to test the student command on the main aspects treated during the course. It will also be possible to test students’ contribute in the reporting, asking to provide comments on particular aspects, decisions, hypothesis, etc. made in the context of the practices.
Final Grading
Reports will be assessed based on a +3 to -5 scale. To pass the course, students must successfully pass the written test (grade higher or equal to 18/30) and the total score summing the written test and the report assessment must be higher or equal to 18/30.

C.M. Bishop, Pattern recognition and machine learning
N. Khaled, B. Pattel, A. Siddiqui, Digital-twin development and deployment on the cloud

L'utilizzo di modelli in ambito industriale è ad oggi sempre più diffuso, spesso sotto forma di un Digital-Twin che simuli l'intero ciclo vita di un sistema nel suo ambiente operativo. Tali modelli, simulando l'evoluzione di variabili continue nel tempo e l'occorrenza di eventi discreti, possono essere utilizzati per l'ottimizzazione della gestione del sistema e del processo decisionale, attraverso opportune analisi del rapporto tra costi e benefici.
A seguito di un breve richiamo degli aspetti fondamentali relativi alla gestione del ciclo vita, alle strategie di manutenzione e ai meccanismi di degrado e guasto tipici di un sistema industriale, lo studente imparerà a simulare un ambiente operativo industriale mediante diverse strategie di modellazione di fenomeni continui nel tempo, eventi discreti, e logiche decisionali. Ciascun argomento sarà affiancato da esercitazioni pratiche su casi realistici.
Il corso prevede infine un'esperienza di laboratorio informatico in cui gli studenti, con l'ausilio di un tutor, impareranno a modellare e simulare lo scenario operativo di un vero sistema industriale.

Il corso si concentra sui gemelli digitali dei sistemi di produzione, che sono repliche digitali di sistemi fisici utilizzati per supportare la presa di decisioni durante le fasi di progettazione, produzione e operazione degli impianti industriali. L'aspetto centrale del corso è la modellazione e le tecniche di analisi della simulazione ad eventi discreti che costituiscono il nucleo della tecnologia dei gemelli digitali.

Lo scopo del corso è rendere gli studenti consapevoli delle responsabilità penali connesse alla progettazione e conduzione degli impianti industriali.
L'insegnamento - mediante l'analisi di casi aziendali e di sentenze in materia antinfortunistica - fornirà una descrizione dei più diffusi problemi tecnici, organizzativi, comportamentali che interessano i contesti produttivi, soffermandosi in particolare sulle criticità attinenti la relazione uomo - macchina.
Verranno quindi illustrate alcune soluzioni tecnico/organizzative - conformi agli attuali standard giurisprudenziali - per risolvere dette criticità e prevenire così efficacemente infortuni e reati negli stabilimenti industriali.
Sarà infine offerto un dettagliato quadro degli strumenti difensivi che le aziende possono utilizzare in caso di contestazioni da parte dell'Autorità Giudiziaria.

To provide the main tools in dynamical systems and mathematical control theory, enabling students to address control problems of interest in applied sciences, by using the concepts learned during the course.
This course explores the fundamental mathematical principles and methods used to analyze and design control systems which are necessary tools in the design and management of systems that stem from sciences, technology, industry, or services.
Control theory analyzes properties of controlled systems, i.e., dynamic systems which can be acted upon by means of a control (or command).
The aim is to transform the system from an initial state to a particular end-state, respecting certain criteria, we might aim to stabilize the system in order to make it resistant to certain disruptions or to determine optimal solutions for a particular optimization criterion (optimal control).
Students of this course can profit of their training both in academic and in modern industry, in specialized fields such as aeronautics, aerospace, robotics, but also in life sciences, where the knowledge of the mathematical tools employed in control could help to better understand problems encountered to design, build, and optimize, or at least improve existing methods. From the mathematical point of view, due to the wide range of applications of control systems, both models involving ODEs and models involving PDEs are needed. The main part of the course deals with dynamical systems of ODEs. Control theory for PDEs is a wide field of study and research. Students will be introduced in this framework by means of some specific examples, as diffusion problems and vibrating phenomena, where they can exploit the main techniques employed to study controlled PDEs, largely used in applied sciences.

By the end of the course, students know classical problems of control theory governed by ordinary differential equations (ODEs). They also know examples of control problems involving partial differential equations (PDEs), of very large interest in various applied sciences.
Applications studied during the course include: fuel optimal landing of a space vehicle, minimum drag nose shape problem, boat guidance in a river, reproductive strategies in social insects (in the framework of controlled ODEs), heating or cooling a building in an optimal way, stabilization and controllability of a string (in the PDEs framework).
In reference to the Dublin indicators, the course emphasises:
DD1 – Knowledge and Understanding
The student will be able to clearly explain, using rigorous mathematical language, the definitions and theorems related to the course syllabus provided by the instructor.
DD2 – Applying Knowledge and Understanding
The student will be able to:
analytically use tools from control theory to various types of differential equations and systems;
set up an optimisation problem.
DD5 – Learning Skills
The nature of the subject, together with the structure of the course and the examination, is designed to foster and assess the student's learning abilities. In addition, the teaching approach adopted encourages students to develop independent learning skills and become more autonomous learners.

1. Dynamical systems. Linear systems of ODEs: general results and structure, exponential matrix. Asymptotic behavior of dynamical systems, stability (linearization, Lyapunov method), phase portraits.
2. Control Systems and asymptotic stabilization. Examples, reachable sets, linear systems, local controllability of nonlinear systems, bang-bang theorem. Stabilization of linear and nonlinear control systems.
3. Optimal control. Existence of Optimal Controls for Mayer problems and the problem of Bolza. Necessary conditions for the optimality: the Pontryagin Maximum Principle. Linear quadratic optimal control. Sufficient Conditions. Dynamic Programming. The linear quadratic case.
4. An introduction to control for partial differential equations. Controllability and stabilization of the wave and the heat equations. Optimal control for PDE’s, an introduction.
5. Further topics. Seminar of experts and students on recent advances in mathematical control theory, dealing e.g., with control problems for multiagent systems, traffic models, moving sets.
The 5cfu version of the course consists in the points 1, 2, 3, 5 of the above program.

Altro
In dependence of the number of students, several options are possibile:
Evaluation during lectures, depending on their participation. The students will be asked to contribute actively by preparing expositions and solving exercises.
Oral examination with, possibly, a preliminary presentation of some specific topic of the course or written exercises.
These options will be clarified during the first week of the course.

Bressan, Piccoli, Introduction to Mathematical Theory of Control, AIMS Book Series, 2007
Cannarsa, Gazzola, Dynamic Optimization for Beginners, EMS Press
Evans, An introduction to mathematical control theory, Berkley, Lecture notes
Li, Yong, Optimal Control Theory for Infinite-Dimensional Systems, Birkhäuser, Boston, 199

L'interazione tra l'uomo e i sistemi ambientali solleva conflitti originati dall'opposizione di prospettive contrastanti. La ricerca di un percorso verso la sostenibilità (concetto complesso e sfaccettato, riassunto dalle Nazioni Unite nei 17 Sustainable Development Goals dell'Agenda 2030) richiede un approccio fortemente interdisciplinare in grado di integrare le diverse dimensioni (economica, sociale, ambientale) del problema. L'approccio non deve celare i conflitti di interesse, ma piuttosto consentire un confronto trasparente tra punti di vista differenti. In quest'ottica, l'insegnamento si propone, da una parte, di fornire allo studente una panoramica delle grandi problematiche ambientali su scala globale, con particolare riguardo agli effetti delle attività umane sui sistemi ecologici. Dall'altra, l'insegnamento affronterà il tema della valutazione ambientale su scala locale, fornendo le conoscenze di base per la valutazione dell'impatto dei progetti e della pianificazione territoriale sulle diverse matrici ambientali e sul sistema socioeconomico. Si analizzeranno infine criticamente i principali strumenti di supporto alle decisioni in contesti caratterizzati dalla presenza di obiettivi multipli.

DdD1 (conoscenza e comprensione)
Lo studente

• conosce le principali problematiche ambientali su scala globale e comprende i principali meccanismi di impatto delle attività umane sulla struttura e il funzionamento dei sistemi ecologici
• conosce i principali metodi multicriteriali, comprendendo le ipotesi di fondo, i vantaggi e i limiti dei diversi metodi e le condizioni necessarie per la loro applicabilità
• conosce i principali approcci alla sostenibilità nelle sue differenti dimensioni (ambientale, sociale, economica)
  DdD2 (capacità di applicare conoscenza e comprensione)
  Lo studente
• è capace di analizzare criticamente un problema ambientale, identificando i principali portatori di interesse e i loro obiettivi, e individuando i potenziali conflitti
• sa identificare gli indicatori più appropriati per caratterizzare lo stato attuale dell'ambiente e le sue variazioni previste, nonché per quantificare il livello di perseguimento degli obiettivi di sostenibilità
• sa rappresentare in modo formale un problema decisionale a molti obiettivi, valutando l'approccio tecnico più adeguato per la ricerca del miglior compromesso
  DdD3 (autonomia di giudizio), DdD4 (abilità comunicative)
  Lo studente
• sa leggere e comprendere la struttura e i contenuti principali di uno studio di impatto ambientale, identificandone i principali punti di forza e di debolezza, nonché approfondire in modo autonomo gli aspetti di contesto politico e socioeconomico, imparando a integrare fonti di informazione complementari
• è in grado di comunicare in modo efficace i risultati del suo lavoro, trovando il giusto equilibrio tra analisi e sintesi, utilizzando forme di comunicazione appropriate per interagire con professionisti di discipline differenti e con un pubblico generico

Introduzione: Sviluppo, ambiente e conflitti sociali. Esempi di problematiche e ricerca di soluzioni condivise.
L'ecologia nell'Antropocene: Biomi naturali e biomi antropogenici. Novel ecosystems, disturbo antropico e dinamica degli ecosistemi.
Strumenti per il processo decisionale pubblico: Analisi Costi-Benefici. Teoria del valore. Metodi di valutazione monetaria. Analisi Costi-Efficacia. Analisi a Molti Obiettivi. Criterio di efficienza di Pareto. Scelta delle alternative. Valutazione di Impatto Ambientale.
Valutazione di impatto ambientale (VIA) e Valutazione ambientale strategica (VAS): Storia e quadro normativo. Aspetti metodologici. Iter procedurale. Strumenti per l'analisi e la stima degli impatti.
Metodi di supporto alle decisioni: Schema processuale. Classificazione dei metodi decisionali. Analisi a molti attributi. Analisi gerarchica. Metodi Electre.
Sviluppo e sostenibilità: Concetti di sostenibilità. Limiti dello sviluppo. Il rapporto Brundtland. Sostenibilità debole e sostenibilità forte. Approccio economico alla sostenibilità. Servizi ecosistemici e loro valutazione monetaria. Limiti dell'approccio monetario. Indicatori di sostenibilità ambientale: impronta ecologica, planetary boundaries. Integrazione delle dimensioni ambientale e sociale: l'economia della ciambella.
Ecologia industriale: Flussi di materia nei sistemi produttivi: l'analisi dei flussi materiali. Il ciclo di vita dei prodotti: Life cycle thinking e Life cycle assessment (LCA). Fasi di un'analisi LCA. Indicatori di impatto. Approccio LCA alla valutazione di piani e programmi
Ecologia del paesaggio: Elementi strutturali del paesaggio: patch, corridoi, matrici. Connettività e frammentazione del paesaggio. Reti ecologiche. Landscape metrics.
Ecologia urbana: Effetti dell'urbanizzazione sull'ambiente fisico. Risposte biotiche all'urbanizzazione. Urbanizzazione e biodiversità.
Nell'ambito del corso verranno svolte attività laboratoriali sui temi dei conflitti e della negoziazione nei processi di progettazione e sull'utilizzo di strumenti informatici per la quantificazione dei servizi ecosistemici. Verranno inoltre proposte uscite didattiche finalizzate ad approfondire i legami tra gestione del verde urbano, biodiversità e servizi ecosistemici.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
L'esame è costituito da una parte individuale e da una di gruppo.
I lavori di gruppo (valutati per un massimo complessivo di 8/30) consistono nell'analisi di casi di studio e nella loro presentazione alla classe. La valutazione tiene conto della capacità di analisi (livello di approfondimento della trattazione), della capacità di sintesi (livello di completezza della trattazione), dell’efficacia comunicativa (compresi gli aspetti grafici e estetici), del rispetto dei tempi assegnati, della qualità dell’interazione tra gruppi.
La parte individuale (valutata per un massimo di 22/30) consiste in un esame scritto che comprende domande multiple, domande aperte e esercizi su tutti gli argomenti affrontati a lezione. La valutazione tiene conto della capacità di esporre i concetti in modo chiaro, conciso e tecnicamente appropriato, di interpretare dati socio-economico-ambientali alla luce dei concetti discussi nel corso, di applicare le conoscenze acquisite alla soluzione di semplici problemi quantitativi e di argomentare in modo completo e convincente i possibili approcci per la soluzione di problemi articolati e complessi.
Il voto finale integra inoltre eventuali punti (o frazioni di punto) aggiuntivi accumulabili attraverso la partecipazione a quiz, la stesura di report sulle attività laboratoriali svolte durante il corso, la condivisione di appunti.

Presentazioni delle lezioni e materiale supplementare https://webeep.polimi.it
Note: Le presentazioni utilizzate in aula saranno condivise dopo ogni lezione sulla piattaforma Webeep. Nello spazio Webeep dell'insegnamento sarà reso disponibile materiale didattico supplementare (articoli scientifici e rapporti tecnici) ad integrazione delle presentazioni.

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members

Students will be able to:
Understand and describe the different measures of inputs, outputs and outcomes related to the activities of the healthcare sector, the purposes of each type of measure and how performance measurement can be a useful information tool for healthcare policies and managerial decisions
Critically analyze and appraise the results of performance measurement for improving the outcome of policy and managerial decision-making, at the healthcare system level as well as at the healthcare providers level, understanding the key success factors and the challenges to its successful use

SETTING THE CONTEXT OF PERFORMANCE MEASUREMENT: A BRIEF INTRODUCTION TO THE FUNCTIONING OF HEALTHCARE SYSTEMS
The architecture of healthcare systems
Organization, financing, and delivery of healthcare services
ISSUES, METHODOLOGIES AND USE OF PERFORMANCE MEASUREMENT IN HEALTHCARE
A framework for the measurement of performance in healthcare
The different dimensions of performance
Health
Clinical quality and appropriateness
Financial protection
Equity
Efficiency
To provide students with the necessary skills to operationalize the theoretical concepts related to performance measurement, their presentation in the lectures will be followed by a practice class discussion of applied work related to the different measures. Special attention will be devoted to the data to be used, to their sources and to their appropriate treatment for the application of the different methodologies.
A detailed schedule with the dates and the topics dealt with in the lectures and in the practice classes will be provided before the beginning of the course on the WeBeep platform.

Altro
1) Students regularly attending the course will be assessed as follows:
Essay 65%
Oral exam 35%
Essay
Each student will be assigned a topic related to a specific area of healthcare performance measurement or a specific indicator, selected from those discussed during lectures. Based on relevant academic and policy literature, the student will write an individual essay critically evaluating the strengths and weaknesses of the measurement approach and discussing its main implications for policy and managerial decision-making.
The essay aims to assess the student’s ability to critically interpret and appraise performance measurement results. Guidelines for the structure and content of the essay will be provided in advance.
Oral exam
The oral examination will cover all the topics presented during the lectures. It is designed to assess students’ comprehension and integration of the course material.
A detailed schedule, including key deadlines for all assignments and the date of topic assignment for the essay, will be published on the WeBeep platform before the start of the course. The full assessment process—including the submission of the essay and the oral exam—will be completed within approximately two weeks after the end of the teaching period, and before the official exam dates.
2) Assessment for Non-Attending Students
Students who do not attend classes will be assessed through a written examination (open-ended questions) during the regular exam sessions. The written exam will have a duration of 90 minutes.
At the instructor’s discretion, an oral exam may be required in addition to the written test, particularly when the written responses do not provide sufficient evidence of mastery of the course content. When applicable, the oral exam will take place within seven days of the written test.

Irene Papanicolas and Peter C. Smith (eds), Health system performance comparison, Editore: Open University Press McGraw-Hill Education, Anno edizione: 2013, ISBN: 978-0-33-524726-4 https://www.euro.who.int/__data/assets/pdf_file/0009/244836/Health-System-Performance-Comparison.pdf
Note: Relevant chapters: 5, 6, 7, 8, 9, 10

Learning goals
The course fits into the overall program curriculum in Management Engineering by contributing to achieve its general learning goals. Specifically, the course develops the following learning objectives:

• Undestand the context, functions, processes of innovation in a business and industrial environment
• Undestand the threats and opportunities posed by innovation on the a business and industrial environment
• Undestand the issues of innovation appropriability and their impact on business performance.

DdD 1 Knowledge and understanding
Understand the economic rationales that drive firms’ innovation decisions, thus being able to make sense of firms’ innovation investments and, ultimately, of the impact of these investments on firms’ performances.
Understand the economic rationales that guide policymakers (and institutions in general) to support innovation, thus being able to make sense of innovation policies and, ultimately, of their impact on the innovation performances of firms, industries, and economic systems.
DdD 2 Applied knowledge and understanding
Develop company advisory skills regarding how to orient their innovation investments to maximize efficiency and the impact on performances.
Develop policymakers advisory skills on how to design innovation policies to effectively stimulate innovation
DdD 3 Authonomy of judgement
Design solutions to case studies of real-world situations, by applying theoretical and empirical knowledge on economics of innovation.
Identify trends and design solutions in teams

Topics
Nowadays, new technologies emerge one after the other and technological knowledge advances at full speed. In this context, everybody agrees that innovation is the main leverage through which firms can gain a sustainable competitive advantage and achieve superior performance. Accordingly, understanding the economic antecedents and consequences behind firms’ innovation decisions, and being able to maximize the outcomes of these decisions is a key capability for succeeding on the labour market. Likewise, innovation is the main engine of economic growth and policymakers (and institutions in general) actively engage in supporting it. Hence, it is of paramount importance to develop awareness on the economic rationales behind this support so as to take advantage of the associated policy schemes. Moving from these premises, this course illustrates conceptual foundations and real-world evidence about
The role of innovation and new technologies in modern economic systems and the drivers of adoption of new technologies, with a focus on uncertainty and limited rationality as barriers to this adoption.
The relation between firms’ innovation and competition, with a focus on appropriability regimes, market structures, and market imperfections.
The antecedents and economics consequences of inter-firm agreements for innovation, with a focus on alliances and acquisitions.
The role of institutions in innovation, with a focus on public support to innovation and policy schemes for stimulating innovation.
Course materials
The course does not base on a unique textbook. Course materials consist of a collection of slides, case studies, scientific papers, book chapters, videos, etcetera, which the teachers make available through the EINT page on WeBeep.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Evaluation
The final grade results by summing students’ scores in the
MANDATORY - Individual written exam. Each student takes an unseen written test in one of the exam dates scheduled by the school. The test lasts 80 minutes and consists of multiple-choice and/or open-ended questions. The written exam revolves around the topics seen in class. The individual written exam grants a maximum of 30/30 points of the grade.
OPTIONAL - Students may also complete an optional group assignment during the course. The assignment will consist of a written report (about 3000 words) on a content to be explained in more detail during the course (end of October). The assignment can be completed and submitted only as part of this year course (deadline by the beginning of December 2026 and graded before the start of the exam session). Groups should consist of 4-5 students. The optional assignment awards up to 4 extra points, which will be added to the final exam score.

Il corso di Progettazione della Tecnologia Educativa combina competenze tecnologiche con teoria dell'istruzione per formare professionisti nella creazione di strumenti EdTech efficaci. Offre formazione pratica in design, prototipazione e valutazione, con attività pratiche come lavori di progetto e discussioni di gruppo. Il corso non richiede competenze di programmazione o analisi dati pregresse. Gli studenti lavoreranno in gruppi per sviluppare e valutare prototipi innovativi EdTech, in base alle loro competenze tecniche. Gli obiettivi principali di apprendimento includono la comprensione delle teorie dell'istruzione, il design centrato sull'utente, i metodi di valutazione e le tendenze attuali dell'EdTech. Gli studenti impareranno anche come comunicare efficacemente le proprie idee. Gli argomenti trattati includono teorie pedagogiche, design centrato sull'utente, tecnologia nell'istruzione, metodi di valutazione e studi di caso.

SISTEMI ELETTRICI PER I TRASPORTI
Il corso tratta dei sistemi elettrici dedicati ai trasporti con particolare riferimento ai trasporti collettivi di persone e a quelli merci. In particolare viene approfondita la trazione elettrica per sistemi ferroviari e metropolitani con riferimento alla alimentazione in corrente continua e quella per sistemi ferroviari con riferimento alla alimentazione in corrente alternata sia a frequenza ferroviaria che a frequenza industriale. Vengono dapprima illustrati gli aspetti tecnici e le problematiche legate agli impianti fissi e successivamente, nella seconda parte del corso, vengono approfondite le apparecchiature e i dispositivi a bordo dei materiali rotabili. Un elaborato progettuale sul dimensionamento elettrico di un sistema di trasporto urbano è previsto come attività di esercitazione.
Sono infine accennati i sistemi elettrici a bordo degli aerei e delle navi

The course deals with electric power systems for transportation with particular reference to ground transportation systems for people, goods and merchandises. Electric traction installation for rail and urban services are described in detail with reference to the DC supply and the AC one, this latter considering both industrial and rail frequency.
In the second part of the course the devices and the systems on board of the trains are presented and a written project on the urban electric transportation system design is performed during the exercise activity of the course.
Basic notions on modern electric road vehicles will be provided.
Electric systems for road electric vehicles (charging stations, charging modes, etc.) are also developed and discussed.

The course will allow the Students to know (DdD1):
The advantages of electric traction systems, mainly for terrestrial transportation systems;
DC supply infrastructures for urban and regional tramway, subway and railway systems;
AC supply infrastructures for heavy-duty and high-speed railway systems;
AC and DC motor drives for vehicle propulsion;
Multi-system electric vehicles for their interoperability across the borders;
Self-propelled railway vehicles (diesel-electric and fuel cell);
Architectures of powertrains of different hybrid and plug-in electric road vehicles;
AC and DC charging infrastructures for electric road vehicles.
The training lessons will allow the Students to design an urban or regional transportation system analyzing technical, economic, and environmental aspects (DdD2 and DdD3).
Technical visits to real high power systems will show to the Students the practical application of the theoretical subjects (DdD2).
Class seminars with industries of the transportation sector will allow the Student to know actual and future trends of the electric technologies in the transportation systems (DdD2) and interact with experts of this field (DdD4).

1.: Electric Traction: overview of electrified transportation systems and economical evaluation of electrified railroad lines.
2.: Direct Current Supply: DC power generation, rectifiers and power converters, electric substation, voltage and current harmonics and filters, line voltage drops, disturbances, the problem of stray currents and related corrosion.
3.: Alternate Current Supply: single phase AC supply at rail frequency, single phase AC supply at industrial frequency, the electric substations, problems related to the connection at AC three-phase power supply transmission network; electric and electromagnetics disturbances.
4.: DC Rolling Stock: Traction circuits, the line current absorption devices, motors and protection systems, the speed control, the auxiliary services.
5.: AC Rolling Stock: Traction circuits, motors and protection systems, the speed control, the auxiliary services.
6.: Self-propelled Rolling Stock: General description of the operation.
7.: High Speed Rail Lines: System operation and control.
8.: Electric Road Vehicles: Connection of the charging stations to the mains, AC and DC charging modes, base structure of an electric road vehicle.
Room exercise lessons are dedicated to the design of an urban or regional transportation system.
Class seminars with industries of the transportation sectors (railway and automotive) will show the actual and future trends of the technologies in this field.
Technical visits on real power systems complete the course.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), individuale, con revisioni periodiche, senza presentazione/discussione finale
Final exam at the end of the course will be in written form.
Some questions on specific subjects will be asked to assess the knowledge of the theoretical aspects of the course (DdD1).
Moreover, a written test will assess the ability of the Student to link the theoretical subjects to the practical aspects (DdD2).
During this test, the Student will have to integrate the different aspects of the topics of the course to find the correct solution (DdD3).
A design project carried out during the training lessons will contribute to the final evaluation (DdD2 and DdD4).
Final exam will be written
It consists in 24 T/F questions + 4 written questions (1 point for every correct answer, 0 if wrong or not aswered)
+
Short project on the training part, not mandatory but can give up to 3 points on the final mark (mandatory for the final mark with honors)

Morris Brenna, Federica Foiadelli, Dario Zaninelli, Electrical Railway Transportation Systems, Editore: Wiley-IEEE Press, Anno edizione: 2018, ISBN: 978-1-119-38680-3

The course aims to provide a deep understanding regarding the liberalization process of the electricity sector and its evolution in a liberalized environment.
In the first part, tools to understand the process of liberalization of the electricity sector, the requirements and the conditions necessary for an efficient electricity market will be provided. Different market structure are compared and analyzed. Afterwards, models for price and power market analysis will be introduced.
In the second part, emphasis will be given to the European electricity market: the problem of the market coupling in Europe is analyzed and the evolution and the projects regarding the integration of the different market sections (day ahead electricity markets, intraday markets, and ancillary services markets) is analyzed.
Finally, starting from the liberalization of the Italian electricity market, due to the Bersani Decree, the complex framework that characterizes this market and its rules will be described and critically analyzed.
The subjects are organized in theoretical lessons and practical (numerical) lessons.
Then, a project related to the simulation and analysis of the electricity markets will be organized and the students will follow the project organized in teams.

The course will allow the students to know ( DdD1, DdD4 ):
what are the prerequisites for the liberalization of the electricity market;
what are the market structures in the electricity sector;
how the technical constraints (due to the generation plants and the electricity grid) influence the design of the electricity market;
what are the different approaches to represent the network in the market models;
the evolution of the market paradigms due to the penetration of the non-programmable renewable energy sources;
to evolution of the market coupling project in Europe;
the Cross-Border Redispatch Cost-Sharing problem among different Countries.
The practical (numerical) lessons and the project work will allow the students to ( DdD2, DdD4 ):
understand how it is possible to implement (from a mathematical point of view) an electricity market model;
apply the optimization theory and algorithms for modelling electricity markets.

Electrical systems management in liberalized markets environment: liberalization process from vertically integrated structures to liberalized markets, the players and their role.
Main electricity markets paradigms: bilateral contracts and pool market models.
Power electricity exchange (PX) and the role of the Transmission System Operator (TSO): electricity market models and congestion management. Transmission capacity value.
Ancillary Services and Ancillary Services Market: description of ancillary services and their management in special market (ancillary services markets).
The evolution of the ancillary services markets.
Capacity market.
Imperfect competition; market power and promotion of competition: tools for market power analysis, game theory. Strategic interaction between day-ahead market and the ancillary services markets.
The Italian spot electricity market (MPE: mercato a pronti): structure and rules. MGP (Mercato del Giorno Prima), MI (Mercato Infragiornaliero), MSD (Mercato dei Servizi di Dispacciamento) and MB (Mercato di Bilanciamento).
The Italian Forward Electricity Market (MTE: mercato a termine): characteristics and rules. Interaction with the spot market.
Market coupling project in Europe.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The final mark of the exam is split between the project (25%) and the final examination (75%). Both will be evaluated with a score of up to 30p and the student is considered promoted if the written test is passed with minimum 18p and if the resulting final mark is also 18p.
After the end of the course, students participate to one of the available final examinations.
The examination consists of a written part and of an oral part.
The written part contains the numerical applications and it will be scored with a maximum of 15p.
If the student provides a satisfactory answer in the written part, i.e. if it obtains at least 60% of the score (9p/15p), the student will have access to the oral part. Otherwise, the student exam is considered RIMANDATO/POSTPONED to the next exam sessions.
The oral part generally consists in one question on all the theoretical topics covered by the course and it will be scored with a maximum of 15p.
The mark of the final exam will be made by the sum of the two parts. The student passes the final exam if it obtains at least 18p out of 30p.
Students should demonstrate full comprehension of the subjects and the usage of the appropriate technical language ( DdD1, DdD2 and DdD4 ).

Chris Harris, Electricity Markets: Pricing, Structures and Economics, Editore: John Wiley & Sons Ltd, Anno edizione: 2013, ISBN: 9780470011584 https://onlinelibrary.wiley.com/doi/book/10.1002/9781118673409
Allen J. Wood, Bruce F. Wollenberg, Gerald B. Sheblé, Power Generation, Operation, and Control, 3rd Edition, Editore: Wiley, New York, Anno edizione: 2013, ISBN: 978-0-471-79055-6 https://www.wiley.com/en-us/Power+Generation%2C+Operation%2C+and+Control%2C+3rd+Edition-p-9780471790556

Il corso affronta le principali questioni teoriche relative all'innovazione socio-tecnica (quali i concetti di base dell'innovazione tecnologica, le dinamiche di diffusione delle innovazioni, i limiti del determinismo tecnologico, l'agency degli oggetti tecnologici, la flessibilità interpretativa della tecnologia, genere e tecnologia) e analizza esempi rilevanti di tecnologie d'avanguardia che hanno un impatto sulla società e sulla vita umana, come l'Internet delle cose, la fabbricazione digitale, la realtà aumentata e l'intelligenza artificiale. Anziché focalizzarsi sul loro funzionamento, le prestazioni e i problemi tecnici, il corso affronterà le questioni etiche che esse sollevano e gli impatti sociali che producono.

The main goal of the course is to introduce students to the fundamentals of quantitative impact assessment methods and models. These quantitative models are specifically aimed at assessing the prospective environmental and economic impacts resulting from the application of technological or policy interventions at meso- and macro-scale, comprehensively including supply-chain effects in a Life Cycle perspective.
First, basic principles of systems modelling, quantitative impact assessment and Industrial Ecology are introduced and discussed also based on real life examples and case studies. In the second part of the course mathematical basis of impact assessment models are introduced, focusing on Leontief’s Input-Output framework. The third part of the course is devoted to the analysis of energy, environmental and economic national accounting frameworks, mapping the structure of national supply chains, hence usually adopted as databases for impact assessment models. In the fourth part of the course, the introduced methods and datasets are adopted to define basic and advanced impact assessment models.

Knowledge and understanding. The students learn basic concepts of Impact assessment methods, Life Cycle Assessment and Industrial Ecology. They understand how physical and monetary flows of goods and services are produced and consumed within a generic productive system, and how they are accounted in standard accounting frameworks. They learn basics of impact assessment and LCA modelling.
Applying knowledge and understanding. The students are able to setup an impact assessment model from scratch to perform quantitative analyses of shocks at meso- and macro-scale. They are able to define the appropriate approach and to select complexities to be modelled based on the type of policy/technology shock to be analyzed
Making judgements. The students are able to quantify policy/technology shock at the meso- and large-scale based on different impact indicators (energy, environmental, economic dimensions). They will be able to perform scenario analysis based on the reference production system at country level, evaluating the effect of a different technology deployment.

Topic 1 – Principles of Quantitative Sustainability Assessment (QSA). Current challenges in quantitative sustainability assessment, approaches to model productive systems, principles of Industrial Ecology and Life Cycle Assessment. Impact assessment: practical examples and real case studies.
Topic 2 – Computational structure of impact assessment models. The Leontief’s Input-Output framework. Supply and Use models: nomenclature, balance equations, setup and application for impact assessment and LCA. Modelling productive systems and handling systems’ complexities.
Topic 3 – Fundamentals of energy, environmental and economic accountings. Overview of national accounting frameworks, standard classification of products and activities. Single-region and Multi-regional accounting tables. Handling and transforming national accountings to perform impact assessment and LCA.
Topic 4 – Applications of impact assessment models. Review and taxonomy of available modelling approaches. Definition and use of Process-based models, Input-Output based models, Hybrid models. Application of attributional and consequential LCA and impact assessment. Application to a real case study based on a model built from scratch.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The lectures are provided ex cathedra, nevertheless a participatory approach is always envisaged. Part of the course is devoted to practical exercises about the definition and use of impact assessment models. A project work is carried out working in team, focusing on the application of methods and models to a real case study.
The final exam is composed by a written test and the evaluation of a project work. The written test provides rating 0-25 (80%) and it allows the assessment of:
Knowledge and understanding, since the students must reply to a set of theoretical questions.
Applying knowledge and understanding, since the students must solve conceptual exercises with the support of the laptop.
The project work provides rating 0-6 (20%). It is not mandatory but highly recommended. Project work is based on the presentation of the work done and an individual discussion of the project. It allows the assessment of:
Applying knowledge and understanding. Students are applying impact assessment models to a case study.
Making judgement. Students are analyzing and providing a critical discussion of the obtained case study results.
Communication, the students are working in team and communicate each other, finally preparing a presentation of the oral examination.

Slides, tutorials and hands on provided during the course
Miller, Ronald E., and Peter D. Blair, Input-output analysis: foundations and extensions, Editore: Cambridge university press, Anno edizione: 2009
Leimkuhler, Ferdinand F., Introduction to operations research, Editore: McGraw Hill, Anno edizione: 2015
Eurostat, Eurostat manual of supply, use and input-output tables, Editore: Eurostat methodologies and working papers, Anno edizione: 2008
Scientific papers provided during the course

The main objective of the course is to study the climate change challenge using quantitative, numerical tools. Specifically, the aim is to learn the basic elements of the global energy and climate problems, evaluate the solutions with a focus on the energy sector, and use optimization and simulation models to evaluate the emission reduction and adaptation strategies.
To do so, a discussion of the fundamentals of the global economy, energy, land and climate systems will be complemented by development and applications of mathematical models integrating these key components. The course will also involve programming languages used in energy-climate planning, such as AMPL and python, among others.
The course uses innovative teaching methods, in particular, it is a flipped classroom course: students will form groups of 4-5 and work on projects to improve one or more numerical models to deal with climate change solutions, either on mitigation or adaptation.
Students based in Leonardo (e.g., Mathematical Engineers) may attend part of the course virtually.

At the end of course, students will be able to:

• Explain the foundations of climate science / climate change and how climate change affects energy and economic systems
• Describe the main historical landmarks of climate- energy policy (IPCC)
• Explain the link between climate change and energy systems
• Discuss advantages and limitations of the different mitigation and adaptation strategies
• Describe the different components of an energy system
• Distinguish between major modeling paradigms (IAMs, bottom-up and top-down energy models, etc.) and choose the appropriate type of model for a given question
• Answer specific questions using optimization models and critically interpret / analyse results
• Translate a real-world problem into an optimization formulation
• Write a mathematical model in a specific programming language
• Identify the main sources of uncertainty and calculate their impact on model outcomes
• Present a project in class, and thus create a presentation and be able to communicate it properly

The specific list of topics is as follows
Topic 1: Introduction to the climate change challenge: physics and causes of climate change, consequences and impacts.
Topic 2: Global energy and climate policies and agreements
Topic 3: The role of technology in climate change mitigation
Topic 4: Fundamentals of continuous and discrete optimization
Topic 5: Mathematical modeling and optimization using AMPL
Topic 6: Fundamentals of climate economics
Topic 7: Introducing the tools of Integrated Assessment Models
Topic 8: The simplest integrated energy-economy-climate model: the DICE model
Topic 9: Introduction to energy systems
Topic 10: Energy models: EnergyScope and PyPSA
Topic 11: Climate risks, adaptation and climate engineering
Topic 12: Accounting for risks and uncertainty: sensitivity and uncertainty analysis methods, stochastic and robust optimization

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Final grade will be based on two main components. A group project which involves model development and presentation during the course lectures. An additional written exam which will be done during the standard exams timeline.
1) Model development and group presentation (2/3): This will be done in class during the course, and we will evaluate both the modeling work as well as the communication skills. In particular, the teacher will assess the relevance of the chosen project, the validity of the software development (also looking at the code) as well as the presentation and oral skills.
2) Written exam (1/3): This will test knowledge of programming and of the theoretical concepts. The theoretical questions will cover the topics examined in class.

Global Energy Assessment - Toward a Sustainable Future, Editore: Cambridge University Press, Anno edizione: 2012 http://www.globalenergyassessment.org/
IPCC 6th assessment report, Anno edizione: 2023 https://www.ipcc.ch/assessment-report/ar6/
DICE 2013 http://www.econ.yale.edu/~nordhaus/homepage/documents/DICE_Manual_100413r1.pdf
The AMPL Book https://ampl.com/resources/books/ampl-book/

Il corso tratta gli impianti di produzione di potenza elettrica, con particolare attenzione all'intrinseca relazione tra i fluidi di lavoro, i cicli termodinamici e le apparecchiature principali (turbomacchine e scambiatori di calore). Sebbene la maggior parte del corso sia dedicata ai grandi impianti a combustibili fossili, altre tecnologie, quali i motori a fluido organico e le microturbine a gas, sono ivi presentate; in ogni caso, i concetti sviluppati nel corso possono essere facilmente estesi anche a generici processi industriali. Il corso è strutturato su tre argomenti principali: le proprietà termodinamiche dei fluidi di lavoro; l'analisi di secondo principio dei cicli di potenza Rankine e Joule; l'analisi monodimensionale dei turboespansori.

In an era of transformation of the energy sectors, this course describe the functioning of energy markets and the economic principles that have guided their design. Through a blend of economic theorethical models, pracitical evidence, and academic research, students gain comprehensive understanding of the dynamics, principles, and motivaitions shaping global energy markets.
Key topics include the theorethical frameworks, models, and the practical tools essential for understanding energy markets. Emphasis is placed on elucidating the rationale behind public intervention in the market, navigating competitive wholesale markets, and analyzing the impact of environmental externalities on market dynamics.
Real-world case studies and guest speakers enrich the learning experience, fostering critical thinking and application of theoretical constructs to practical scenarios.

Describe the functioning of energy markets.
Identify natural monopolies (e.g., transmission/distribution) and explain why regulation is needed to improve welfare.
Explain the motivations for public intervention in energy markets (efficiency, security of supply, externalities).
Describe competitive wholesale electricity markets and the main design challenges.
Explain how environmental externalities affect energy markets and evaluate major regulatory instruments (ETS, taxes, standards).
Apply energy economics tools to real-world cases and policy/market design problems.

Topics:
Market structure, economic principles and models: Competition, Monopololy, Deadweight Loss, and Natural Monopoly
Regulation of Natural Monopolies: Models with perfect information, Models with information asymmetries, Regulation of Natural Monopoly in practice
Energy and the Enviorment: Negative Externalities, Technological adoption, NIMBY, Policy solution in the energy markets
Energy Sources: Cartels, Dominant-producer model, Hold-up problems and Long Term Contracts
Electricity Markets
Natural Gas Market
Topics will be discussed through: Lecture sessions: they aim at illustrating, sharing and discussing models, conceptual frameworks, tools and empirical evidence In-class case study discussions: they aim at making students apply the insights from theory and empirics to real world situations. Students have to read case study materials in advance of the class sections.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The final exam aims at testing student's:
Level of understanding of the theories and empirics presented in class
Ability to apply the theories and empirics presented in class to real cases
Ability to interpret correctly the regulatory intervention as well as the choices of the players in the energy markets in light of the theory and empirics presented in class
Ability to calculate a market equilibrium
Exam format
Written exam
The exam consists of 31 multiple-choice questions, each worth 1 point. For each incorrect answer, 1 point will be deducted (malus). Unanswered questions receive 0 points (no penalty).
The exam will be administered on paper. Students must clearly mark their answers on the official answer sheet, which is the only document that will be evaluated. Any ambiguous or multiple markings will be considered incorrect.
Oral Exam
Students whose final written score is higher than 26 are required to take a mandatory oral examination. The purpose of the oral examination is to confirm and, where appropriate, adjust the final grade, which may therefore be either increased or decreased.
Students may choose not to attend the oral examination. In this case, a final grade of 26 will be automatically recorded.
For all other scores, the result of the written examination is considered final. Students are not entitled to request an oral examination.

The interest of the international community in the multiple interconnections among energy, environment, and society is fully recognised, as is the close link between energy and development. The 2030 Agenda and the 17 Sustainable Development Goals confirm that the world is increasingly interconnected and that social challenges are becoming more and more complex and unpredictable. With regard to energy, Goal 7 identifies energy availability as a necessary precondition for human and social development, as well as a key enabler in the fight against poverty, in line with the broad concept of “development as freedom” defined by Amartya Sen. Nevertheless, access to sufficient, affordable, efficient, reliable, safe, and clean energy is not yet available to everyone. In developing countries, the problem is critical, but increasing challenges have also emerged in emerging countries and, more recently, even in developed countries. Innovative solutions and strategies to match economic growth with the multidimensional targets of sustainability, including environmental preservation and social inclusion, need to be developed. The many geopolitical tensions of recent years have hampered efforts to address the complexity of the energy challenge, putting the concept of justice in the energy transition under threat, particularly with reference to vulnerable groups and regions.
By widening the multidisciplinary vision of students and by evaluating the many implications that sustainable energy may have on development at the global and local levels, the course aims to provide a general overview of the various aspects of cooperation and development, analysed from a project-oriented perspective, with the goal of designing solutions that meet local needs and developing policy recommendations stemming from the engineering planning process. To achieve these multifaceted goals, after recalling the main models of cooperation and development, science diplomacy will also be introduced, with a particular focus on how evidence-based policymaking can be informed.
Project Cycle Management (PCM) will then be introduced as a tool for the appropriate design of cooperation actions, particularly with regard to the logic of cause-and-effect relationships. Given that the energy sector represents the main field of application, after detailing the multidimensional nexus between Energy and Development, a planning methodology to guide engineering design towards meeting local needs and making the best use of local resources will be introduced. The peer-reviewed methodology, Comprehensive Energy Solution Planning (CESP), addresses this challenge by combining a cyclic approach consisting of: (i) a set of traditional engineering-oriented phases (the current standard for energy solution planning), and (ii) complementary social science-based phases that integrate holistic aspects into project planning. Some of the course topics will be delivered through a blended learning approach, making use of MOOCs, web resources, and role-playing simulation debates. The project work is primarily based on the application of the flipped classroom approach.

The learning outcomes may be aggregated into five areas of knowledge
1 The students will learn the foundation and the evolution of the main development models from the Marshal plan to the new paradigm of Sustainable Development; they will learn the trends of the energy situation in emerging countries with special reference to the African continent. The will learn the principles of energy planning and solution design by deepening the main renewable or hybrid technological solutions and will understand the basic principle of Decision support Systems. Students will also understand the main implication among energy and development, energy and human right as well as their policy implication at national and regional scale.
2. The student will be able to apply the Project Cycle Management and the methodological approach to define appropriate energy solutions for rural and off grid areas by defining load curves and selecting technologies. They will be also able to draft business models and to adopt strategy for long term sustainability of the given solution. They will also be able to evaluate the expected impact of the energy solution onto the socio economic asset of the target community.
3. the students will learn how to make choice and provide judgement, given a number of energy strategies for the same problem, they will be autonomous in identifying and defining a set of priority by adopting appropriate Decision support tools and deducting from scientific result, policy recommendation in the form of policy brief
4. t he students will learn how to prepare a project proposal according to standard methods (like PCM) and how to present it, given a certain time and audience, including policy makers
5. the students will learn by doing and will take profit of work group.

Topic 1 — History of Development Cooperation, Development Models, and Science Diplomacy
From conflict to cooperation. The evolution of development cooperation from the 1950s to the present. Colonialism and neo-colonialism. The theoretical foundations of international cooperation and the evolution of development models. The role of scientists in development processes. The growing importance of Science Diplomacy: Diplomacy for Science, Science for Diplomacy, and Science in Diplomacy. Providing scientific advice to policymakers. Decision-making processes: principles, assessment methods, and tools. The policy brief: purpose, structure, and drafting guidelines.
Topic 2 — The Energy–Development Nexus: Affordable and clean Energy for Africa
The global energy landscape: historical trends and projections based on World Bank and International Energy Agency data. OECD countries, emerging economies, and countries facing critical energy challenges. The relationship between energy and development. Energy and human rights: the Energy Justice framework. Africa’s energy landscape and the continent’s main challenges. Africa’s strategic relevance in the global energy transition.
Topic 3 — Project Cycle Management: Planning the Intervention
The European Commission’s Project Cycle Management framework as a tool for development cooperation. The identification and analysis phase: problem analysis, objective analysis, stakeholder analysis, and strategy analysis. The formulation and planning phase: the Logical Framework Approach, Gantt charts, and budgeting. Output, outcome, and impact indicators. SMART indicators and Objectively Verifiable Indicators (OVIs). The relationship between Project Cycle Management and the Theory of Change.
Topic 4 — Comprehensive Energy Solution Planning: Designing the Energy Solution
The Comprehensive Energy Solution Planning methodology will be presented through the six interconnected and interdisciplinary steps embedding counterfactual analysis. Context Analysis: assessment of the regulatory, institutional, socioeconomic, and local energy context. Resource and Demand Assessment: analysis of available energy resources and current and projected energy demand. Technical Solution Design: identification, sizing, and, where possible, optimisation of appropriate technical solutions. A Python-based tool will also be introduced to design hybrid minigrdi for access to energy. Business Model Design: development of a coherent business model to ensure the long-term economic and operational sustainability of the selected energy solution. Complementary Activities: identification of supporting measures required to create an effective enabling environment. Impact Analysis: assessment of the solution’s expected social, economic, environmental, and developmental impacts.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Lectures are a mix of ex-cathedra, blended/flipped where a participatory approach is envisaged via open discussion. Part of the course is devoted to a methodological project work about: project cycle management, application of the comprehensive energy solution planning. One project work will be carried out in team and it will be about “Rural electrification in Sub-Saharan Africa”. The project work including an executive summary for policy maker as policy brief is highly recommended and will allow the assessment of the following learning outcomes
The student will apply knowledge since the students will apply the CESP methodology to a real case, they will be able to define load curves, select appropriate technologies, propose business models and evaluate the expected impact of the energy solution on the local community.
The students will be able to make judgements since they will select strategies base on a set of given information and using appropriate decision support mathematics.
The students will be able to communicate their achievements since they will work in team and will prepare a written proposal for the solution of the project work and will finally present the achievement via an oral presentation.
The project work provides a rating (0-10) and consist of a team and individual evaluation. It will be added to the evaluation of the written text. The written test (0-23) will assess individually the following learning outcomes
an improved knowledge and understanding of the subject since the students will have to respond to a set of theoretical questions
a further assessment of their capacity to apply knowledge and understanding since the students will have to solve quantitative exercises
The written exam work will assess:
Knowledge and understanding since the students will have to respond to a set of theoretical questions
Applying knowledge and understanding since the students will have to solve some exercises
The oral will be applied for international students (incoming or outgoing) that will attend the exam on line due to their abroad period or in case any use the Professo may wish to check any non authorised used of AI.

Colombo, S. Bologna, D. Masera, Renewable Energy for Unleashing, Sustainable Development,, Editore: Springer International Publishing Switzerland, Anno edizione: 2014
Note: DOI:10.1007/978-3-319-00284-2_1
Monique Kremer, Peter van Lieshout and Robert Went,, Doing Good or Doing Better development policies in a globalizing world,, Editore: Amsterdam University Press, Anno edizione: 2009
Note: Chapter 1,2,3,5
EU commission, Project Cycle Management, Anno edizione: 2004 http://ec.europa.eu/europeaid/multimedia/publications/publications/manuals-tools/t101_en.htm
TRANSFORMING OUR WORLD: THE 2030 AGENDA FOR SUSTAINABLE DEVELOPMENT, Editore: Nazioni Unite, Anno edizione: 2015
Directorate-General for Research and Innovation, Open Innovation, Open Science, Open to the World - a vision for Europe, Editore: European Commission B-1049 Brussels, Anno edizione: 2016 https://digital-strategy.ec.europa.eu/en/library/open-innovation-open-science-open-world#:~:text=The%20Three%20Os%20%E2%80%93%20Open%20Innovation%2C%20Open%20Science%2C,science%20and%20innovation%20more%20open%2C%20collaborative%20and%20global.

Develop a comprehensive understanding of management consulting and enterprise transformation, including the main consulting domains, methodologies, tools, and the role of consultants in supporting strategic, organisational, operational, and digital change.
Strengthen students' ability to analyse and solve complex business challenges by integrating managerial knowledge from different disciplines and applying structured problem-solving, critical thinking, and holistic analysis to real-world scenarios.
Prepare students to contribute effectively to cross-functional transformation initiatives by combining theoretical frameworks with practical consulting experience through case studies, enabling them to address market, organisational, and technology-driven challenges.

Familiarize with typical pillars of consulting support: M&A, post merger integration, enterprise organization, operational excellence and WFM, ICT governance, data management and AI.
Support students to combine their managerial learnings from previous courses and to face market, organization and technology challenges through real case studies.
Guide students along cross-enterprise transformation projects, as example of consulting role in the real world.
Explain the main topics of consulting industry: methodologies, tools, process, economics, and management
Improve problem solving, holistic analysis and lateral thinking
Blend theory with real cases studies

History of Management Consulting
Consulting business model, players, key success factors, trend, economics and KPI, financials
Consulting carrier, performance evaluation, incentive schemes
M&A: goals and different models, asset evaluation, type of deal, deal structure, Financing, Leverage BuyOut, business planning, process steps from scouting to closing, main actors (PE, Industrial, Advisors, lawyers), legal docs, PE and VC, start upo evaluation.
Post merger integration: day-one integration topics, synergies identification and implementation, new business and operational models enabled by M&A, organization post deal, cultural integration, integration process.
Organizational models from traditional to agile, competencies evolution, how to design an organizational structure, microstructure, integraiton and corporate governance.
Operational Excellence: Zero Based Budget, Business Process Reengineering, process mapping and BPM.
Workforce Management
Enterprise Technology Architecture and functionalities: from Industry specific to new trends and evolution
Data Center Management (physical, virtual, cloud, private cloud, public cloud, Cloud strategy)
ICT Governance: Organization Model, Contract management, Investment management and monitoring, System Development Life Cycle
Data-driven culture, decision making and productivity
Data management, value chain
AI: traditional and generative
Case studies on each of the subjects

Prova scritta obbligatoria, con prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Valutazione continua facoltativa (a scelta dello studente)
On Course Exam: 6 short-exams of 30’, every 2 weeks, following each of the 6 Modules, in order to test the learning of the students and give grade time by time. Average grade of te 6 exams will be the final grade.
Working groups on specific business cases may replace one or two of on course exams
Regular exam calls: 2 hour exams for 6 exercises (1 per module)

The course aims at providing students with a comprehensive understanding of key issues relating to the creation of new firms, the determinants of their performance, their impact on society, and the reasons and schemes for public support to entrepreneurship.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance;
design solutions by applying the scientific and engineering approach in addressing problems and opportunities in business and industry;
interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members.

By the end of the course, students will be
aware of the key determinants of new venture creation and performance;
able to make decisions concerning several crucial issues (entrepreneurial team creation, new venture organization, alliance formation and management, access to public financing, entry into an incubator), taking into account the specificities of the new venture;
able to develop a business case aimed at stimulating discussion on specific contents of the course.

o Introduction to entrepreneurship
o Entrepreneurial entry
The entrepreneur-specific factors: demographic characteristics, psychological traits, and motivations
The context of entrepreneurship: technological, industry, institutional, and local determinants of entrepreneurship
o Business model development and business model patterns
o The performance of new ventures and the impact on society
Survival: the liability of newness and smallness
Innovation: the role of new firms in innovation systems
Growth: growth theories, effects of new ventures on economic growth
o The determinants of new venture growth
The entrepreneurial team: formation and evolution
Access to resources: hiring vs. team enlargement, alliances, incubation
Public support to entrepreneurship
The organization of new ventures
o The heterogeneity of new ventures
Academic entrepreneurship
Family entrepreneurship
Entrepreneurship by minorities: female and ethnic entrepreneurship
o Wrap up and example of exam questions

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Grades will be assigned by combining the evaluations of:
a written exam to test the knowledge acquired by students and the ability developed by students to use theory in practical cases (up to 23 points);
a case study writing exercise (up to 10 points) to be developed in groups between November and December.
The written exam may be replaced by an oral exam if the number of candidates registered for the written exam is very low. The knowledge required to take the oral exam will be the same as that required for the written exam.
More details on the two parts of the final exam will be provided during the first lecture and will be summarized in the slides that will be made available on the WeBeep platform.

Parker S.C., The Economics of Entrepreneurship

This course is designed to provide the students with a comprehensive set of knowledge and tools to understand the current worldwide Economy evolution in the light of Environmental, Social and Governance (ESG) principles.
First, a review of the macro-economic context, with a focus on the relevant policies and regulations driving the energy transition, will be introduced.
Afterwards, the evolution of ESG topics will be covered with focus on companies acting in the most relevant sectors exposed to the transition. Sectors subject to specific analysis are Banking, Automotive and its value chain, Steel and Energy. With a focus on these sectors, the course will provide insights with reference to: i) strategy and business portfolio evolution, ii) sustainable finance, iii) corporate governance, iv) new management performance metrics, v) sustainable rating, vi) social sustainability initiatives and vii) financial and non-financial disclosures.
Lectures will be complemented by case histories presented by sectors leading companies as well as talks with other relevant Market players.
Students will be required to play an active role by developing business cases on ESG Strategy/initiatives adopted by a selected set of leading Companies.
The course contribute to the following programme objectives:
Identify trends, technologies, key methodologies and stakeholder needs in a specific domain
Identify risks and opportunities induced by the above
Develop new ideas and transformative solutions to deliver positive impact on business, industrial and societal scenarios evolving over time

The main expected learning outcomes for students are:
to understand the drivers of the current ESG market trend and to forecast further evolutions
to evaluate the different ESG strategies implemented by leading companies in different sectors
to learn how to govern a new ESG company's strategy from design to implementation and public disclosure

The course is designed to introduce key concepts and tools for understanding and evaluating the evolution of companies’ strategies in the ESG transition to counteract the rising risks and take advantage from the new opportunities
The course will benefit from a balanced mix of lectures, case histories presented by the industry senior management, talks with other relevant Market players and business cases presented by students.
Overall, interaction and active participation are key elements for a profound understanding of the covered topics.
The main topics covered during the course are:
Global energy scenarios and focus on international and national energy policies.
Analysis of i) the world energy scenarios in accordance with the latest forecasts provided by IPCC, IEA and NGFS; ii) evolution of energy supply and demand; iii) focus and benchmarking of existing mechanisms implemented at supranational as well as national level (subsidies, carbon certificates trading, border tax)
Corporate strategies evolution
Strategic impact of ESG principles over the most exposed Economy Sectors including Banking, Automotive and supply chain, Steel and Energy
Sustainable finance
Sustainable finance and tools aiming at funding corporate activities connected to ESG principles. Climate related financial risk: the perspective of different parties (companies vs financing parties vs Regulators)
Corporate governance
Introduction to the corporate governance basic principles and description of their very recent evolution induced by the ESG influence. Role of Active Shareholders and evolution of Directors’ risk profile. Implications of ESG strategies on the management performance measurement.
Social strategies
Overview of Social sustainability practices in different Economy Sectors.
ESG rating
The global evolving context of ESG rating: consolidated standards and emerging trends
Financial/Non Financial Disclosure
Overview of existing standards for climate-related financial and non-financial information.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The overall final grade will be based on the following criteria:
Evaluation of the oral exam (60% of the final grade). Each student will be tested orally on the course subjects (Bibliography). The active/constructive student participation to each lesson will be an additional evaluation element (with potential additional scoring points)
Evaluation of teamwork business case (40% of the final grade). Students will work in teams to deploy a real business case detecting, describing and finally commenting/challenging how the assigned Company implemented each ESG topic covered during the course. The companies available for business cases are large companies

Il corso fornisce competenze avanzate nel campo della teoria della stima, con particolare riferimento ai problemi legati all'ingegneria industriale. In particolare, vengono presentati i seguenti argomenti: introduzione alla teoria della stima; stima a massima verosimiglianza; identificazione parametrica per modelli lineari e non lineari; introduzione ai metodi di analisi dei dati (regressione lineare, analisi a componenti principali, classificazione); introduzione ai processi stocastici stazionari; identificazione non parametrica nel dominio delle frequenze; stima bayesiana.

This course deals with the application of ethical theories to problems created, aggravated, or transformed by technology (broadly construed). It aims at showing how the processes of technology design, development, management, control, and production are i nherently moral. It intends to give students a chance, and the proper conceptual resources, to reflect on the ethical, social, and cultural impact of technological applications.
The course includes lectures by the instructor, workshops, and student presentations. Class participation is warmly encouraged. Students are expected to critically reflect on what they learn during the course, share ideas and insights during class discussions and activities, and put theory into practice.

Dublin Descriptors
Expected learning outcomes
Knowledge and understanding
Students will:
Acquire a broad perspective on the ethical and social impacts and implications of science and technology;
Be acquainted with normative ethics and normative argumentation;
Learn how to recognize and analyze ethical and social aspects and issues inherent in some technological applications;
Be able to understand how technical problems are inherently connected to a social dimension within a socio-technical perspective.
Applying knowledge and understanding
Students will:
Be able to use critical skills in clarifying and ethically analyzing case-studies involving technology;
Be able to apply ethical theories to problems created, aggravated or transformed by current technologies;
Be able to explore and assess possibilities for solving or diminishing existing and emerging ethical and social problems.
Making judgements
Students will be able:
To autonomously and critically analyze the ethical issues raised by a given technology;
To evaluate and select the appropriate knowledge in the effort of elaborating and justifying a philosophical argument on a topic autonomously selected.
Communication
Students will learn to:
Exercise and improve their skills in a critical writing;
Present in an effective way the results of their research, being able to justify their choices.
Lifelong learning skills
Students will:
Be better prepared to their future professional life in an ethically and socially responsible way;
Be able to analyze problems through an ethical lens.

The course will cover different topics both from a theoretical and a more practical point of view. After a broad introduction on the ethical significance of Technology and Engineering, the course will first discuss traditional topics in Engineering Ethics, such as Professional Ethics, the notion of Responsibility, the Problem of Many Hands, and Whistleblowing. Secondly, the course will focus on Technology Ethics by analyzing the Non-Neutrality of Technology, Value Mediation, and Design Ethics. Once the ethical significance of Engineering and Technology is clarified, the course will provide tools to appropriately discuss moral problems by introducing Normative Ethical Theories (Consequentialism, Deontology, Virtue Ethics) and specifying their function in Applied Ethics. As a conclusive step, the overarching value of Sustainability will be examined, its main components investigated, and related ethical challenges debated.
Workshop activities held throughout the course will explore the most fundamental notion of Technological Mediation.
Class sessions will be dedicated to supervise students in the development of the individual final essay in order for it to meet the standards required by scientific publications.

Progetto/i - Elaborato/i obbligatorio, individuale, con revisioni periodiche, senza presentazione/discussione finale
Altro
Type of assessment
Description
Dublin descriptor
Collective presentations
[Mandatory only for 5 CFU]
Students are encouraged to:
Develop an argument in which the presented claims are justified by the use of ethical argumentation and the relevant literature;
Discuss this argument in an oral presentation in class in front of the instructor and their student colleagues.
1, 3
4, 5
Individual written essay
The individual final essay must show that the student has the capacity to read and carefully study the suggested bibliography and the ability to apply it to case-studies or relevant topics;
The individual final essay requires students to have developed critical skills in analyzing technical problems with the tools provided by ethical theories and argumentation.
1, 2
3, 4, 5

Ibo van de Poel, Lambèr Royakkers, Ethics and Engineering: An Introduction, Editore: Wiley-Blackwell, Anno edizione: 2011
Sven Ove Hansson (Ed.), The Ethics of Technology. Methods and Approaches., Editore: Rowman & Littlefield, Anno edizione: 2017
Batya Friedman, David G. Hendry, Value Sensitive Design: Shaping Technology with Moral Imagination, Editore: The MIT Press, Anno edizione: 2019
Behnam Taebi, Ethics and Engineering. An Introduction., Editore: Cambridge University Press, Anno edizione: 2021
Sven Nyholm, This is Technology Ethics: An Introduction., Editore: Wiley-Blackwell, Anno edizione: 2023

This course aims at raising critical awareness on the most important ethical issues pertaining to the design, development, deployment, and use of transportation tecnologies (broadly construed). Through the in-depth study of such issues, it intends to support students in the exercise of ethical thinking skills and to promote responsible engineering practices. In addition, the course aims at offering useful conceptual tools to identify, analyze, and responsibly manage the moral impacts of mobility engineering. Finally, it intends to stimulate reflections and debates on key transportation ethics values such as safety, privacy, autonomy, inclusivity, justice, and sustainability by encouraging students to support moral claims with adequate justifications, solid arguments, and clear language, while listening to and taking the arguments of others seriously.

Dublin Descriptors
Expected learning outcomes
Knowledge and understanding
Students will:
Acquire a broad perspective on the ethical and social impacts and implications of transportation technologies;
Be acquainted with normative ethics and normative argumentation;
Learn how to recognize and analyze ethical and social aspects and issues inherent in some transport technologies;
Be able to understand how technical problems are inherently connected to a social dimension within a socio-technical perspective.
Applying knowledge and understanding
Students will:
Be able to use critical skills in clarifying and ethically analyzing case-studies involving transportation technologies;
Be able to apply ethical theories to problems created, aggravated or transformed by current transportation technologies;
Be able to explore and assess possibilities for solving or diminishing existing and emerging ethical and social problems.
Making judgements
Students will be able:
To autonomously and critically analyze the ethical issues raised by transportation technologies;
To evaluate and select the appropriate knowledge in the effort of elaborating and justifying a philosophical argument on issues relevant to Transportation Ethics;
To prepare a small research of critical analysis of an ethical, legal or societal issue related to a technical case-study.
Communication
Students will learn to:
Exercise and improve their skills in critical thinking and writing;
Present in an effective way the results of their research, being able to rationally justify their choices.
Lifelong learning skills
Students will:
Be better prepared to their future professional life in an ethically and socially responsible way;
Be able to analyze transportation problems through an ethical lens.

The course explores the most relevant ethical, political, and societal aspects and problems related to the design, development, management, and use of transportation systems, with particular attention to urban transport. It is divided into two parts.
The first part examines Transportation Ethics against the background of Technology and Engineering Ethics in order to develop a clear picture of its components, importance, and difficulty. Moreover, it draws on Philosophical Ethics to show how Normative Theories such as Consequentialism, Deontology, and Virtue Ethics can offer useful tools to identify, analyze, study, and manage moral problems raised by transportation systems.
The second part of the course takes a closer look at these problems by discussing issues surrounding 1) Sustainability, 2) Safety and Autonomy, 3) Justice and Inclusivity, and 4) Privacy and Freedom.
Students will work in groups to learn first-hand how to apply these values to engineering practices in the transportation domain.

Progetto/i - Elaborato/i obbligatorio, individuale, con revisioni periodiche, senza presentazione/discussione finale
Altro
Type of assessment
Description
Dublin descriptor
Collective Presentations
Develop an argument in which the presented claims are justified by the use of ethical argumentation and the relevant literature;
Present the work in class discussions and written reports on which the instructor will provide feedbacks before the final evaluation.
1, 3
4, 5
Individual Written Essay
The individual final essay must show that the student has the capacity to read and carefully study the suggested bibliography and the ability to apply it to relevant topics;
The individual final essay requires students to have developed critical skills in analyzing technical problems with the tools provided by ethical theories and argumentation.
1, 2
3, 4, 5

Barbara Richardson, Transportation Ethics, Anno edizione: 1995
David Banister, The Sustainable Mobility Paradigm, Anno edizione: 2007
Karel Martens, A People-Based Approach to Accessibility, Anno edizione: 2019
Karen Lucas, Transport and Social Exclusion, Anno edizione: 2012
Matts-Ake Belin et al, Vision Zero, Anno edizione: 2012
Jilles Smids, The Moral Case for Intelligent Speed Adaptation, Anno edizione: 2018
Jeffrey Reiman, Driving to the Panopticon, Anno edizione: 1995
Karel Martens, Transport Justice. Designing Fair Transportation Systems., Editore: Routledge, Anno edizione: 2016
Wes Marshall, Killed by a Traffic Engineer: Shattering the Delusion that Science Underlies our Transportation System, Editore: Island Press, Anno edizione: 2024
Peter Norton, Fighting Traffic. The Dawn of the Motor Age in the American City., Editore: The MIT Press, Anno edizione: 2008
Fabio Fossa, Ethics of Driving Automation. Artificial Agency and Human Values., Editore: Springer, Anno edizione: 2023
Karin Edvardsson Björnberg et al. (Eds), The Vision Zero Handbook. Theory, Technology and Management for a Zero Casualty Policy., Editore: Springer

This course will be useful to students who plan to take empirically oriented finance courses as well as students who want to get a solid understanding of the tools required to analyze and model financial asset prices and, more generally, economic time series related to any field of economics and management. The link between statistical models and their implementation is emphasized.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

With respect to the first learning goal, at the end of the course students will be able to:
Understand the key aspects of statistical time series models, and how these models can be used to forecast economic variables and analyze their relationship
Understand the differences between univariate and multivariate time series models
Understand the importance of confidence intervals associated to point forecasts
Understand the notion and relevance of stationarity in time series analysis
Understand the key aspects of dynamic volatility models
With respect to the second learning goal, at the end of the course students will be able to:
Select the appropriate time series model to apply in practical economic situations.
Interpret the output of econometric packages implementing time series models
Use time series models for forecasting economic and financial time series
Use time series models to support economic decisions

Overview
The course introduces students to financial econometrics, providing them with appropriate techniques for empirical investigation in finance. The emphasis will be on understanding and applying a set of econometric tools that are widely used by academics and practitioners working in quantitative areas such as risk management, investment management, and financial engineering (although most of the techniques are widely used also in empirical macro and monetary economics). After a quick review of the multiple linear regression model, the course will illustrate univariate and multivariate models for time series analysis and forecasting. The analysis of non-stationary time series will be discussed, illustrating the theoretical and empirical relevance of the notion of integration and cointegration. The course also covers dynamic models for volatility analysis (ARCH and GARCH models) and one topic, possibly varied from year to year (event studies, Markov switching models, Factor models,...). Providing the students with the ability to use the models is one of the goals: to this aim, problem sets with both analytical and computer-exercise components will be a relevant part of the course.
Main topics
0. Refresher on the linear multiple regression model: estimation through Ordinary Least Squares, checking assumptions (functional form, multicollinearity, heteroskedasticity, autocorrelation, non-normality)
1. Univariate analysis of time series: Stochastic processes and their properties. AR, MA and ARMA models. Analysis of trend, cycle and seasonality.
2. Multivariate analysis of time series: ARX models and VAR models
3. Analysis of nonstationary univariate and multivariate time series: integration and cointegration
4. Models for the analysis of volatility: ARCH and GARCH models.
5. One of the following topics: Event studies, econometric aspects of the CAPM, econometrics of the efficient frontier, econometrics of derivatives, analysis of ultra-high frequency financial data, long memory processes, Markov switching models,... The topic will be chosen at the beginning of the course. Students willing to deepen autonomously, for some reason, a different topic instead of the chosen one, may propose it.

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), individuale, senza revisioni periodiche, con presentazione/discussione finale
(i) Written exam (80 minutes, weight 60%). The written exam is based on two exercises (the first is on the topics 1, 2 and 3 illustrated above; the second is on the topics 4 and 5). The main purpose of the written exam is to assess the achievement of the second learning goal and the associated learning objectives (ability to select the appropriate model to answer research questions, to read the output of time series packages, to forecast economic time series based on time series model, to use the models to support economic decisions)
(ii) Oral exam (15 minutes, weight 40%). The main purpose of the oral exam is to assess the achievement of the first learning goal and the associated learning objectives (understanding of the main theoretical aspects of time series models). The oral exam has to be taken after the written exam, not necessarily in the same call.
(iii) Non-compulsory team project work (2 students): a paper about 10/15 pages long, where some of the techniques illustrated in the course is applied to a real problem; the paper has to be illustrated in a 30 minutes presentation, possibly via skype; the project work may increase the final mark by at most 2/30. The project work gives you the opportunity to get an hands-on perspective on the discipline. Highly recommended if you plan to include some time series analysis in your final thesis, or if you think that a deep understanding of statistics in general and time series analysis in particular is a valuable asset for your future.

Chris Brooks, Introductory Econometrics for Finance, Editore: Cambridge University Press, Anno edizione: 2014, ISBN: 9781107661455 http://www.cambridge.org/features/economics/brooks/
Note: Chapters 1 to 8

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and financial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Develop new ideas and solutions in business and financial scenarios evolving over time

Indicate the importance of risk management practices inside financial institutions and the drivers that made this topic particularly relevant; understand the role of risk management in preventing issues and difficulties coming from credit, market, liquidity and operational risks. Discuss the importance of the relation between risk and capital. Illustrate a taxonomy of risks and possible strategies to manage them. Express the causes and effects of the last decades financial crisis. Show the main regulatory frameworks and the rationale behind them. Discuss the difference between regulatory capital and economic capital.
Summarize the main financial instruments and the principles of CAPM; explain the key methodologies applied in risk management, in particular VaR, ES, Credimetrics, Credit Risk Plus, Vasicek’s model and all the tools suggested by the regulator in Basel regulation for risk assessment, from the concept of Risk Weighted Assets to LCR and NSFR. Illustrate the main instruments for the estimate of default probabilities.
Illustrate the emerging new business models of the financial institutions and relate each one of them to the risk management activity. Evaluate the connections among risks and business models, expecially during the digital transformation phase.

OVERVIEW
The course focuses on financial risks topics. Financial risks became on the last decade among the most important value drivers. It’s a key issue for a company and for a financial institution to face them in order to create value and to optimize capital allocation in coherency with the expected results and risks. In particular, it concentrates on the main financial risks. For each one of them the course focuses on the measurement and on the main solutions and techniques in order to manage them. At the end of the course, students will be able to understand in detail most of the current debate on financial institutions through a better understanding of Basel regulation, its requirements and its main outcomes and implications.
CONTENTS DESCRIPTION
Financial Risk Management (FRM): process and main areas
FRM and digital transformation
Risk and return
Asset pricing: Capital Asset Pricing Model & portfolio theory
Mutual funds and hedge funds
Trading in financial markets
The financial crisis
Basel I, II and III
Credit risk and probability of default
Operational risk
Liquidity risk
VaR
Scenario analysis and stress testing
Economic capital
ORGANIZATIONAL ISSUES
The contents are provided through class lectures, which consist in both theoretical lessons and exercises. Lectures have a strong correspondence with the suggested textbook. Students should attend class regularly and actively participate, contributing to class learning and discussion. Some sessions will be given through practitioners coming from the most important and highly-reputed financial risk management departments.

Prova scritta obbligatoria, senza prove in itinere
Individual written test at regular calls.
Students may re-take the exam in any regular exam session, as many times as they wish; doing so requires formally rejecting the previous grade.

HULL, J., RISK MANAGEMENT AND FINANCIAL INSTITUTIONS, Editore: WILEY, ISBN: 978-1118955949

The course aims to provide the students with the theoretical knowledge of physics and engineering to understand, model and design different technologies, ranging from traditional energy conversion systems to electrochemical devices, like batteries and fuel cells, that occupy a growing role in energy conversion and storage sector.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in energy technologies and the impact of those factors on energy technologies development
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in energy technologies

The main expected learning outcomes consist in:
Identify the physical processes regulating and limiting the operation of conventional and electrochemical energy technologies
Point out requirements of energy technologies in function of different applications
Identify and understand the main technological issues regarding electrochemical devices and their impact on technology development and costs
Determine performance and efficiency of conventional and electrochemical energy technologies in different operating conditions
Calculate efficiency losses occurring in physical processes of energy technologies and assess room for improvement
Design energy technologies for both stationary and automotive applications, focusing on the trade-off between performance and cost

The course provides the basis of thermodynamics to deal with the design criteria of different energy technologies. Then, after a technological assessment, the features of some traditional and electrochemical conversion and storage systems for automotive and stationary applications are analyzed in depth, focusing on performance, efficiency, technological issues and off-design conditions.
Traditional energy conversion systems
Physics:
Review of the 1 st and 2 nd principle of thermodynamics.
Introduction to exergy and exergy analysis.
Review of heat and mass transfer in heat exchangers.
Technologies:
Joule-Brayton and Rankine cycles for stationary applications: operating principle, efficiency, technological issues and limits, off-design conditions, combined cycle.
Otto and Diesel cycles for automotive applications: operating principle, efficiency, technological issues and limits, off-design conditions, market analysis.
Introduction to renewable energy sources (hydro, solar, windmill) and their effect on worldwide energy consumption, electricity price and electric grid stability, focus on Italian scenario.
Electrochemical conversion and storage systems
Physics:
Working principles of batteries and fuel cells.
Thermodynamics and exergy analysis of electrochemical cells.
Mass transport phenomena and kinetics of electrochemical cells.
Technologies:
Historical overview of electrochemical devices, state of art of electrochemical energy conversion and storage technology for automotive, stationary and portable applications.
Batteries with aqueous and non aqueous electrolyte: general features, efficiency, charging and discharging issues, technological limits, lithium ion battery, flow batteries.
Water electrolyser for energy storage: general features, efficiency, technological issues and limits, off-design conditions.
Polymer electrolyte fuel cell for stationary and automotive applications: general features, efficiency, technological issues and limits, off-design conditions.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The students will be evaluated through:

• a final oral exam about the whole course program;
• an optional project homework regarding the application of studied technologies.

Michael J. Moran, Howard N. Shapiro, Fundamentals of Engineering Thermodynamics, Editore: Wiley & Sons

Access to sustainable and affordable water, energy, and food stands among the greatest technological challenges of the 21st century. How can we manage scarce and valuable subsurface resources while minimizing pollution? How do we maximize recovery from our remaining reserves of conventional oil and gas? Is it possible to capture and store carbon dioxide underground to limit atmospheric emissions and mitigate dangerous climate change?
Addressing these questions requires an understanding of multiphase flow in porous media, the movement of water, oil, gas through geological formations.

Upon successful completion of the course, students will be able to:
Knowledge and understanding: Demonstrate a thorough understanding of the physical principles governing multiphase flow in porous media, reservoir characterization methods, fluid–rock interactions, and the mechanisms controlling hydrocarbon recovery and geological CO₂ storage.
Applying knowledge and understanding: Apply analytical methods and principles to characterize reservoir systems at laboratory and field scales, evaluate reservoir performance, estimate hydrocarbons in place and recovery factors, and analyze displacement processes governing oil and gas production.
Making judgements: Critically assess production data and select appropriate conceptual and analytical approaches for reservoir evaluation and management.

This course provides a comprehensive introduction to the theory and modeling of multiphase fluid flow in porous media, with particular emphasis on hydrocarbon reservoirs. It covers the fundamental principles governing fluid flow in the subsurface, the constitutive relationships describing fluid–rock interactions, and analytical and numerical approaches for modeling multiphase flow in geological formations.
The course covers the following topics:
Reservoir characterization: main geological features and heterogeneity, Oil terminology and definitions
Scale problem: pore scale and continuum scale, representative elementary volume (REV)
Reservoir characterization at the laboratory and field scale
Flow in porous media: governing equations for single-phase and multiphase (oil-water-gas) flow
Fluid and rock properties: porosity, absolute and relative permeability, wettability and wettability alteration, interfacial tension, capillary pressure, fluid saturation, and fluid properties.
Pore-scale displacement processes: fluid configuration in the pore space, drainage and imbibition processes, trapping, and displacement mechanisms.
Analytical methods for immiscible displacement: fractional flow theory, Buckley–Leverett analysis, Welge's method, and estimation of oil recovery efficiency.
Hydrocarbon distribution and behavior: phase behavior, reservoir drive mechanisms, and fluid distribution within subsurface reservoirs.
Geologic CO2 Storage, moving and trapping of CO2 in the subsurface, CO2 storage efficiency

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The examination consists of a written examination covering both the theoretical concepts and their practical applications.
Students who obtain a minimum score of 25/30 in the written examination may choose to take an optional oral examination.
The instructor also reserves the right to require a student to attend an oral examination, regardless of the written examination score, whenever clarification is deemed necessary or when inconsistencies emerge during the evaluation of the written examination.

M J Blunt, Multiphase flow in permeable media: a pore-scale perspective, Editore: Cambrdige University Press, Anno edizione: 2017
L. P. Dake, Fundamentals of Reservoir Engineering, Editore: Elsevier, Anno edizione: 1991, ISBN: 0-444-41830-X

The course provides a comprehensive overview of the fundamentals of signals and transmission systems and serves as a prerequisite for advanced coursework in communications. The course provides students with the tools to analyse deterministic signals and random processes, including a thorough treatment of Fourier analysis, practical examples, and real-world communications and signal-processing problems. Each topic is treated both theoretically and practically. The ability to apply the knowledge gained will be continuously assessed through recurring class exercises, homework, and simulation activities. The students are supported by a tutor in their understanding.

Knowledge and understanding (DD1)
Students will gain a solid background on signals, probability, and stochastic processes, as well as the understanding of the main functionality of digital communications.
Applying knowledge and understanding (DD2)
Students can apply the principles and tools of signals and systems acquired during the course to various disciplines. Linear systems, signal operations, and Fourier Transforms are widely used in mathematics, modeling, problem-solving, and advanced courses in data analytics. The students will be able to see connections among theoretical concepts and recognize how to apply them to telecommunication engineering.
Communication (DD4)
Students will learn to present course topics using the specialized vocabulary required for advanced studies in communications. They will develop the ability to communicate concepts through graphical and symbolic representations of signals and systems, as well as through appropriate formats for statistical analysis (e.g., histograms and word clouds). Furthermore, they will learn to express ideas and procedures using formal signal notation and terminology.

Deterministic signals.
Elementary signals & operations, continuous and discrete. Linear time-invariant systems: convolution, correlation and their applciations. Fourier analysis: properties, bandwidth and energy spectrum, sampling theorem, periodic signals, and the Discrete Fourier Transform. Examples and applications: sampling and aliasing, harmonic distortion, IQ modulation and complex baseband representation.
Probability.
Review of the basic elements of probability: definition, experiment & events, distribution, and densities: histograms. Conditioned probability & Bayes rules, some distributions (Normal, uniform, exponential). Moments (mean, variance, and correlation) and elements of statistics.
Stochastic random processes.
Introduction to processes: realisations and ensemble statistics - stationarity & ergodicity, cross-correlation & power spectrum density. Stochastic processes through a linear time-invariant system. Examples and applications: thermal and quantisation noise, delay estimation, time-correlated processes, signal restoration from noisy observations.
Digital communication.
Principle of baseband transmission of digital signals

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
The assessment is based on a written and an oral exam at the end of the course. The written exam consists of numerical exercises covering the course topics. During the course, students will engage in live test sessions, laboratories, and exercises in a flipped-classroom format that can replace the written component. The oral exam focused on theoretical questions and discussions of exercises.
In particular, students will be evaluated for the following aspects:
1) understanding the basic notations, formalisms and operations of signals, probability and processes ( DD1,DD4 )
2) understand the probabilistic structures of stochastic processes, as well as the use and misude of probability (DD1)
3) applying the basics of signals, systems and stochastic processes in real-life problems - though simplified ( DD2 )

Overview of the Course
In recent years, both scholarly and practitioner communities have shown growing interest in innovative approaches to future making. In an increasingly complex and fast-changing world, predicting the future has become a daunting challenge. Organizations often struggle to make informed decisions about where to invest resources and which initiatives to pursue. Unpredictable market conditions and geopolitical instability further complicate strategic decision-making, leaving many organizations ill-equipped to respond effectively. As a result, mastering future making skills is more important than ever. To remain competitive and resilient, organizations must cultivate future thinking capabilities that enable them to proactively design strategies in response to emerging change. This means not only evaluating current options but also imagining and shaping possible futures when developing novel strategic directions.
Future making has been defined as the way organizational actors envision, construct, and enact the future. This process calls for a new set of organizational capabilities, practices, and routines to give meaning and structure to future possibilities. The Future Making course is designed to:
Enhance participants’ skills and abilities in imagining and crafting distant futures;
Introduce pioneering methodologies for identifying and interpreting weak signals of potential change;
Empower participants’ moral imagination in proactively addressing grand societal challenges;
Stimulate a critical and reflective mindset in designing meaningful and desirable future life experiences.

Intended Learning Outcomes
Identify trends, technologies, key methodologies and stakeholder needs in a specific domain;
Understand and interpret technological and socio-cultural trends, recognize weak signals of change, and consider the moral foundations that may influence possible futures [Team Future Making Project; Individual Written Exam];
Develop new ideas and transformative solutions to deliver positive impact on business, industrial and societal scenarios evolving over time:
Imagine and craft meaningful and desirable future life experiences, grounded in a deep understanding of emerging societal and technological trends [Team Future Making Project; Team Reflexive Diary].

Premise
The course actively engages students in an experiential learning process: in addition to conceptual inputs, the faculty will use case study discussion, workshop, teamworking sessions and team presentations. For this reason, it requires that participants:
Attend class regularly and contribute to class discussions;
Be fully prepared for class (by accomplishing the pre-assigned tasks);
Actively participate in team projects and activities outside of class, and contribute to team learning.
The main educational process is thought for students who will actively participate in class and who will engage in team-bases activities. The course allows some students, who are not able to provide this form of active participation, an alternative educational process.
Attending Students
The course is based on both individual and team activities. The lectures manly aim at illustrating and sharing frameworks, models and tools. In order to facilitate the understanding, case studies are presented and discussed along the lectures. During the course, participants develop the Team Future Making Project to face the brief proposed by the Faculty. Participants are engaged in creating the teams by their own. The teams are averagely composed by 6 members. The Team Future Making Project is based on three main phases:
Framing: The Framing phase establishes the foundation by defining the scope and boundaries of the studied societal challenge. This involves critically analysing emerging future forces and identifying signals of change that may affect the proposed challenge. By setting these parameters, participants can achieve a structured understanding of the current landscape and anticipate potential challenges and opportunities. The first phase is based on Desk Research autonomously developed by each team and on the Framing Factory, workshop facilitated by the Faculty and supported by Generative AI Tools (see Sections 4 and 5 for further details);
Reframing: Building on the insights gained during the Framing, the Reframing phase involves collective efforts to think creatively and ethically, exploring new possibilities and perspectives. By challenging existing assumptions, meaningful and desirable futures can be envisioned. Reframing aims at destroying preconcepts, bias and evaluate new information that might better make the future. The second phase is based on the Reframing Factory, workshop facilitated by the Faculty and supported by Generative AI Tools (see Sections 4 and 5 for further details);
Leading: The Leading phase is dedicated to refining the scenarios developed in the previous phases and translating them into future experiences of life and actionable strategies. This involves addressing the practical aspects of implementing meaningful and desirable futures within real-life contexts. This phase is in line with the aim of research in management and strategic implementation that underscores the necessity of practical strategies and actionable plans to realize future visions. The third phase is based on the Leading Factory, workshop facilitated by the Faculty and supported by Generative AI Tools (see Sections 4 and 5 for further details).
Team Future Making Projects are presented on 17th December 2026. Teams have to upload the Presentations on WeBeep no later than 16th December 2026 h22.00. Detailed guidelines about the Team Future Making Projects are provided during the introductive session (see Sections 4 and 5 for further details).
The Team Reflexive Diary is an account of the learning journey developed throughout the course. It should focus on connecting individual and team learning with the theories discussed and the insights gained from the activities carried out. Detailed guidelines about the Team Reflexive Diary are provided during the introductive session (see Sections 4 and 5 for further details).
The Individual Written Exam, scheduled at the beginning of the off-term period ( 1 st Call), is composed by small case studies to be critically discussed, closed and open questions (see Sections 4 and 5 for further details).
Not-Attending Students
Not attending Students are those who—for some major constraints [1] that should be clearly explained to the Faculty via email or dedicated meeting—are not able to participate to the great portion of classes and/or team activities ( no more than two absences are allowed in relation to Team Future Making Projects session highlighted in orange in Section 5). Students with overlapping classes should commit in participating to Future Making activities within the above mentioned limit or follow the course as not-attending students.
The exam is oral and scheduled in the off-lectures period. Not-attending students will not be included in teams and have to develop the Individual Future Making Project: this activity substitutes the Team Future Making Project that attending students accomplish in teams. The Individual Future Making Project is about the same challenge proposed to the teams along the course. Individual Future Making Projects are presented during the oral exam. Not-attending students have to prepare only a PowerPoint presentation about the project to be presented during the oral exam in a maximum of 15 minutes. Not-attending students have to send one week before the oral exam ([email protected]) the Presentation.
The Individual Reflexive Diary is an account of the learning journey developed throughout the course. It should focus on connecting individual learning with the theories discussed and the insights gained from the activities carried out. Not-attending students have to send one week before the oral exam ([email protected]) the Presentation.
The Individual Oral Exam, scheduled during the off-term period, is composed by small case studies to be critically discussed, closed and open questions.
The Faculty strongly suggest to attend classes and to engage in team activities. An active participation to the course not only improves the effectiveness of the learning process, but also reduces the overall effort that the student has to put in the preparation of the final exam characterising the course.
N
Topic
Key References
Faculty
01
Introduction to the Course
Learning Goals; Educational Process; Evaluation; Team Future Making Project
Introduction to the Challenge
Human Capital Growth and People Wellbeing in the Gen/Agentic AI Era (2035)
Dell’Era + Luciano
02
Future Making: Near and Distant Futures
Foresight: Prediction and Preparation
Futures and Democracy
Laura Bechthold, Professor for Technology Assessment & Cultural Management @ Bavarian Foresight-Institute
Jan Oliver Schwartz, Head of Institute & Co-Founder @ Bavarian Foresight-Institute
Augustine et al. (2019)
Fergnani (2022)
Marinkovic et al. (2022)
Dell’Era
Bechthold & Schwartz
03
Making Distant Futures
Innovative Abduction and Moral Imagination
Future-led Transformations
Chiara Diana, VP and Chief Design Offices @ Frog
Veronika Ji, Strategy Director @ Frog
Comi et al. (2025)
Durante et al. (2024)
Gümüsay and Reinecke (2022)
Dell’Era
Diana & Ji
04
FRAMING Factory (1/2)
Empathizing with the Near Future | Trajectories and Future Forces
Discussing Surprising Signals of Change | Cues
Sense Breaking | Creative Hypotheses
Reinterpreting Future Forces | Future Engines
Dell’Era + Luciano
05
FRAMING Factory (2/2)
Discussing Moral Bases | Tensions
Sense Giving | Meaningful Desires
Contrasting Future Forces | Future Wills
Dell’Era + Luciano
06
World Building
Worlds, Stories and Conversations. Games as Design Catalyst
REFLEXIVE Diary | Sharing Experiences and Insights about FRAMING activities
Boni (2017)
Zaidi (2017)
Luciano
Dell’Era + Luciano
07
REFRAMING Factory (1/2)
Conceiving Distant Future | Trajectories of the Future
Building the Future World | Memories of the Future
Dell’Era + Luciano
08
REFRAMING Factory (2/2)
Imagining Distant Futures | Manifesto of the Future
Shaping the Future Experience | People, Generative Applications and Context
Dell’Era + Luciano
09
Designing Corporate Transition
Thinking Futureback. Leading Systemic Transformation within Organizations
REFLEXIVE Diary | Sharing Experiences and Insights about REFRAMING activities
Luciano
Dell’Era + Luciano
10
LEADING Factory (1/2)
Scoping the Future Boundaries | Organization
Crafting the Future Experience | Future Space and Interactions
Dell’Era + Luciano
11
LEADING Factory (2/2)
Reflecting on Corporate Transformations | Opportunities and Threats
Roadmapping Corporate Transformations | Meaningful Strategic, Organizational, and Technological Initiatives
Dell’Era + Luciano
12
TEAMWORKING Session
Preparing Final Presentations
REFLEXIVE Diary | Sharing Experiences and Insights about LEADING activities
Dell’Era + Luciano
13
Final PRESENTATIONS
Performing Final Presentations
Dell’Era + Luciano
Slides / Case Studies / Videos
Slides, case studies and videos will be made available through the course website on WeBeep (https://webeep.polimi.it).
Suggested Books and Articles
There is not a unique reference textbook, but rather a collection of book chapters / articles from different sources that complement an active participation during classes.
Key Articles:
Augustine, G., Soderstrom, S., Milner, D., & Weber, K. (2019). Constructing a distant future: Imaginaries in geoengineering. Academy of Management Journal, 62(6), 1930–1960.
Durante, I., Dell'Era, C., Magistretti, S., & Pham, C. T. A. (2024). Predictive or imaginative futures? Experimenting with alternative future-making approaches. Creativity and Innovation Management, 33(3), 496–517.
Gümüsay, A. A., & Reinecke, J. (2022). Researching for desirable futures: From real utopias to imagining alternatives. Journal of Management Studies, 59(1), 236-242.
Wenzel, M., Krämer, H., Koch, J., & Reckwitz, A. (2020). Future and organization studies: On the rediscovery of a problematic temporal category in organizations. Organization Studies, 41(10), 1441-1455.
Wenzel, M. (2022). Taking the future more seriously: From corporate foresight to future-making. Academy of Management Perspectives, 36(2), 845-850.
Wenzel, M., Cabantous, L., & Koch, J. (2025). Future making: Towards a practice perspective. Journal of Management Studies. Advance online publication. https://doi.org/10.1111/joms.13222
Whyte, J., Comi, A., & Mosca, L. (2022). Making futures that matter: Future making, online working and organizing remotely. Organization Theory, 3(1), 1-20.
[1] E.g. Interns, Erasmus, etc.

Prova scritta facoltativa (a scelta dello studente), senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
The final evaluation of the course is different for attending and not-attending students.
Attending Students
The evaluation is based on the following elements:
Team Future Making Project: teams are engaged in designing a new meaningful and desirable future highlighting a possible future experience of life. Presentation sent on 16th December 2026 must be performed on 17th December 2026;
Team Reflexive Diary: The reflexive diary is an account of the learning journey developed throughout the course. It should focus on connecting individual and team learning with the theories discussed and the insights gained from the activities carried out. Three sub-sessions are devoted to sharing the reflexive diaries developed by the teams; each sub-session focuses on a specific phase of the team future-making project: Framing, Reframing, or Leading. Each team joins only one of the three sessions and, accordingly, focuses on one specific phase of the project. Each team will have 10 minutes to present the lessons learned, focusing on key and specific episodes, as well as on the most relevant contents explored or imagined during the activities. Team members are invited to reflect deeply on the different perceptions and experiences lived within the team;
Individual Written Exam: open questions about case studies and theoretical contents; the individual written exam is based on the content included in the course slides, class discussion, and guest speeches.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Team
Future Making Project
Team
Reflexive Diary
Individual
Written Exam
Attending Students
18
4
10
In order to pass the exam:
Sum must be >= 18;
Team Future Making Project >= 10;
Team Reflexive Diary >= 2;
Individual Written Exam >= 6.
Peer evaluations among team members will be performed to guarantee a balanced commitment (they can determine incremental variations: +1 or -1). The Team Future Making Project is valid for the entire academic year, so for all the calls the students that attend the course will keep that mark.
Not-Attending Students
The evaluation is based on the following elements:
Individual Future Making Project: individuals are engaged in designing a new meaningful and desirable future highlighting a possible future experience of life. Presentation sent one week before the oral exam ([email protected]) and delivered during the oral exam;
Individual Reflexive Diary: The reflexive diary is an account of the learning journey developed throughout the course. It should focus on connecting individual learning with the theories discussed and the insights gained from the activities carried out. Non-attending students may autonomously select one specific phase of the team future making project: Framing, Reframing, or Leading. The diary should focus on the lessons learned through the development of the project. The reflexive diary, consisting of a maximum of 10 slides, must be sent to [email protected] one week before the oral exam.
Individual Oral Exam: open questions about case studies and theoretical contents; the individual oral exam is based on the content included in the course slides, case studies, textbooks, guest speakers’ presentations.
The specific elements in the grading system and the points assigned to them are depicted in the following table.
Individual
Future Making Project
Individual
Reflexive Diary
Individual
Oral Exam
Not Attending Students
14
4
14
In order to pass the exam:
Sum must be >= 18;
Individual Future Making Project >= 8;
Individual Reflexive Diary >= 2;
Individual Written Exam >= 8.

The course is aimed at illustrating the fundamentals of the mathematical theory of interactions between agents. It starts with the discussion of the main assumptions underlying the theory, and it continues by considering the possible description of the games: the extensive and the strategic form. Both the cooperative and non cooperative theory will be considered. The goal is to explain how rationality can explain and/or predict and/or suggest the behavior of interacting agents. This is not limited to human being, it can also be applied to animals, networks of computers and so on.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance.
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment.

Knowledge and understanding
1) To know the fundamentals of interactive decision theory.
2) To know some of the proofs of fundamental theorems in non cooperative game theory.
3) To know some of the proofs of fundamental theorems in cooperative game theory.
Ability in applying knowledge and understanding
1) To be able to modelize simple interactive situations as games.
2) To be able to state and explain the proofs of fundamental theorems in game theory.
3) To solve exercises.
Making judgements
1) To be able to state translate a problem in a game and analyze it.
Communication skills
1) To be able to explain and illustrate (in written form) a definition, the text of a theorem, its proof.

1) The main assumptions of the theory. Main differences between the decision theory and the interactive decision theory.
2) The Nash non cooperative model, Nash equilibrium and existence of (mixed) equilibria in finite games. Examples. Potential games, how to find a potential. Examples: congestion games, routing games, network games, location games. Price of stability and of anarchy. Zero sum games. Games in estensive form. Games with perfect information, backward induction. From the extensive to the strategic form. Combinatorial games.
5) Cooperative games, definitions, examples. Core, nucleolus, the Shapley value and power indices.
6) Problems of matching.
7) Mechanism design
8) Basic of Social choice and Arrow’s theorem.
9) The bargaining problem: the Nash and the Rosenthal approaches.
The last topics will be proposed if time suffices.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
There will be five exam sessions, in dates fixed by the School: two in the exam session of June-July, one in September (or at the end of August), and two in the session of January-February.
The exam is written and it consists of both exercises and theory questions. Each exercise and theory question is assigned a maximum score, in such a way that they sum up to a maximum of 35 points in total (30 points for the exercises + 5 points for the theory questions).
The exercise part of the exam aims to evaluate methodological skills of the students and their ability to apply knowledge and understanding of the course contents to specific problems (as indicated in the expected learning outcomes). In particular, the ability to model simple interactive situations as games and solve them.
The theory part of the exam aims to assess the student's level of knowledge and understanding of the conceptual aspects of the course. In particular, it is aimed at checking that the students are able to explain and illustrate (in written form) definitions, statements of theorems/results and proofs.
Final evaluation:
The overall grade is calculated by adding the scores obtained in the exercises and theory questions. The exam is passed if the student achieves an overall grade of at least 18. Students getting at least 32 points are graded with 30 e lode.
At the instructor's discretion, a student may be required to take an oral exam.
During each exam, students may not consult or carry with them textbooks, notes, calculators, cell phones, smartphones or other electronic devices not explicitly approved by the instructor. Students who violate this rule will be removed from the exam room and their performance will be assessed as failing.

M. Maschler, E. Solan, S. Zamir,, Game theory, Editore: Cambridge University Press, Anno edizione: 2013
R. Lucchetti, A primer in game theory, Editore: Esculapio, Anno edizione: 2011

L'obiettivo principale di questo corso è fornire una valutazione quantitativa delle maggiori sfide ambientali e delle loro ripercussioni sul funzionamento dei sistemi economici e umani. Un focus particolare sarà dato a due sfide ambientali globali che rappresentano due tra i maggiori rischi affrontati dalle nostre società: il cambiamento climatico e l'inquinamento atmosferico. Il corso presenta il loro impatto su diverse sfere economico-sociali e individuerà politiche e soluzioni per mitigare la loro influenza, dal punto di vista dei governi, delle aziende private e dei cittadini. Il focus geografico sarà globale, analizzando sia le economie industrializzate che i paesi in via di sviluppo. Il corso mira anche a trasmettere metodologie di econometria e data science per analizzare le relazioni causali tra le sfide ambientali globali e gli esiti socio-economici. Durante il corso, gli studenti impareranno l'applicazione di metodi sperimentali (ovvero studi randomizzati controllati) e non sperimentali (Dif-in-Dif, dati panel, Regression Discontinuity Design) per la valutazione dell'impatto. Si discuterà anche di come i big data provenienti da sensori intelligenti, osservazioni satellitari, ecc. possano aiutare a identificare le cause del cambiamento ambientale globale e mitigare il loro impatto. Ciò avverrà principalmente attraverso la presentazione di articoli accademici e casi di studio e lavori di gruppo applicati.

Learning Objectives. The course fits into the concentration in Supply Chain (SC) Management of the overall curriculum in Management Engineering, and it contributes to some general learning goals. The course focuses on developing the following capabilities. To identify trends, technologies and key methodologies in the realm of SC Planning. To design approaches, tools and methodologies grounded on a scientific and engineering-based approach (analysis, learning, reasoning, and modeling skills coming from a solid and rigorous multidisciplinary background) to face SC planning problems and opportunities in service-related and industrial environments.
To interact in a professional, responsible, effective and constructive way in a working environment, motivating also team members.

Expected Learning Outcomes Upon completion of this course, the students are expected to demonstrate ability: To identify trends, by assessing the impact of planning activities over SC decisions, in the light of the increasingly growing need to deliver bold SC plans to react to a continuously changing competitive scenario; To design and develop effective global SC plans aligned to corporate strategic plans and critical success factors of the addressed business area. The students will be able to contribute to the main SC decisions ranging from SC configuration to short-term delivery plans for the different SC partners. To successfully interact with professionals from different disciplines and various backgrounds, by identifying the main planning issues and outlining the cause-effect relationships that drive SC performance.

Topics Covered
Amazon, Apple, McDonald's, Procter and Gamble (P&G), Unilever. What do they have in common?
Most of them share outstanding places in Fortune 500 ranking, and all of them – according to Gartner [1] – represent the Masters category, which recognizes sustained SC excellence. The Masters continue to demonstrate advanced lessons for the SC community, and they highlight the accomplishments and capabilities of long-term SC leadership. While the wave of Covid pandemic was sweeping the world, SC disruptions and resilience gained attention in daily news. However, behind resilience and agility – to navigate turmoil effectively and successfully – SC Masters have been restructuring their organizations, transforming business models and redefining markets by blending well-established capabilities with emerging innovations. In the end, SC masters have succeeded in reshaping their own SCs through tremendously effective planning initiatives.
How should we care about SC planning?
In a search for competitive differential advantage, many managers of world–class organizations around the globe have come to realize that differentiating on processes is more sustainable than differentiating on products. Indeed, SC planning is the forward-looking process of coordinating assets to optimize the delivery of goods, services and information from supplier to customer, balancing supply and demand [2]. SC planning looks after current processes – including the ones originated in pure service industries – and determine methods for orchestrating the execution flow, the information flow and the financial flow in SCs.
Who are SC planners?
SC planners have the ability to look at the whole SC from upstream to downstream with both short- and long-term mindset. They also troubleshoot breakdowns along the SC and respond fluidly to unexpected events. We now live in the age of the digital SC, which makes it easier than ever before to understand the intricacies of SCs. SC planners are tech-savvy and they feel comfortable working alongside the world of “machines”: they combine technical and business knowledge (for example the ability to handle forecasting and logistics) with collaboration and communication skills in writing and verbal conversation with a wide range of characters from dock workers to high-level executives and business owners. SC planners do not work in a silo and they do not wait for someone else to do what needs to be done. They are proactive, and they bring out the same drive in others. In the end, SC planners are leaders in the seminal meaning of people who cause others to want to travel with them [3]: they show the way to themselves, to others and to teams.
How should we train the SC planners of the future?
When it comes to SC planning, CEOs typically feel in the dark and they take a back seat, thus overlooking that if an organization really nails its SC planning, it can react to disruptions before they even happen, and quickly transform strategy into execution. We must train SC planners in such a way that they are able to steer their organizations to respond more quickly to market development, and they can lead their organizations on a journey toward prolonged success by forging a greater synergy with their CEOs.
There are at least three major topics SC planners should make their CEOs aware of, before dipping their toes into SC planning: (i) whether company’s SC has been consciously established and improved through a decision-making process, or it has merely evolved, which reveals that probably SC configuration has not received enough attention and your logistics managers do not know why warehouses are located where they are; (ii) whether business and SC strategies are misaligned, as SC plans have much more to do with customers and service than suppliers and cost, which means that a growth business strategy and an aggressive cost-cutting SC strategy do not match; (iii) whether some customers are over-serviced – and then less profitable – as service levels are based on perceived customer needs, but you failed to check whether the reality matches that perception.
What SC planners should bring in their toolboxes?
Some widespread gossip whispers that SC planners are ideal positions for analytical nerds who spend their idle time at work playing Tetris and who would rather solve a Rubik’s cube at the weekend than do anything else. On the other hand, the SC planners of the future are outgoing leaders with outstanding ability to steer effective SC designs: they keep SC plans aligned to business plans, and they improve service levels while reducing costs at once. Hence, a typical SC planning toolbox include: Sales and Operations Planning (S&OP), Collaborative Planning Forecasting and Replenishment (CPFR), Vendor–Managed Inventory (VMI), Direct Delivery Systems (DDS), Available and Capable to Promise (ATP/CTP), multi-plant capacity planning, demand and inventory planning and factory planning.
Syllabus
To properly match the requirements of both Management Engineering (ME) and Management of Built Environment (MBE) courses of study, classes have been arranged into 14 main sessions with a typical format of 3 – 4 hours in a row once a week (typically on Monday morning). The course syllabus has been built around the best path we should set out to properly train the SC planners of the future.
Students will be confronted with various real-life, real-time dilemmas that require cross-functional understanding, collaboration, and leadership.
Sessions L1 to L11 are related to lectures and each of them matches with several case studies, to be practiced in the corresponding session in a flipped mode fashion. Case-studies play a pivotal role in achieving a relevant portion of learning objectives [1], and they will be corroborated by some guest speeches of industrial directors and planners.
The introductory session (L1) is devoted to SCs and SC planning and the presentation of SCOR model (Source, Make, Deliver and Return), while Sessions L2-L4 refer to sustainable, strategic and global SC configuration. L5 refers to the evolution of S&OP through IBP. Then, Session L6 is related to emerging trends and recent advances in make vs. buy SC strategy and the role of SC finance supporting decisions of corporate strategy.
Session L7 is releted to risk mitigation strategies aimed at making SCs resilient to economic and geopolitical disruptions. Session L8 and L9 focus on the impact of customer service and marketing strategies on SC planning process. Session L10 addresses the role of “x”-shoring strategies (like re-, back-, near-) as a response to economic and geopolitical risks.Session L11 outlines the impact of product design on SCs and the interactions between NPD process ad SC management process.
Finally, sessions T1 and T2 include additional practice respectively on sessions L1-L6 and L7-L11, and (upon request) they can be graded as Mid-term exam and Early-bird exam.
The course in a nutshell
L1 Execution, information and financial planning. SCOR model
L2 Strategic SC planning in action: Fisher & Hau Lee Models
L3 Using AI for SC planning
L4 Integrating SC planning and marketing
L5 Global SC planning & distribution networks
L6 SC planning via IBP
L7 S&OP Game
L8 Upsteam SC planning & SC finance
L9 Sustainabile SC planning for circular economy
L10 Mitigating SC risks and creating resilience
L11 Aligning SC planning and NPD process
[1] To see how a typical case-based session should look like, try: https://www.youtube.com/watch?v=p7iwXvBnbIE.
The instructor’s standpoint is well highlighted here: https://www.youtube.com/watch?v=eA5R41F7d9Q&t=44s.
[1] https://www.gartner.com/en/supply-chain/research/supply-chain-top-25
[2] https://www.gartner.com/en/information-technology/glossary/scp-supply-chain-planning
[3] The leadership role is more about the destination, vision, engagement, emotion. To capture a glimpse of leadership, try: https://www.youtube.com/watch?v=pxBQLFLei70 (2014 commencement speech at UT Austin). A footage is available also with subtitles (and ads): https://www.youtube.com/watch?v=TBuIGBCF9jc.
[4] To see how a typical case-based session should look like, try: https://www.youtube.com/watch?v=p7iwXvBnbIE.
The instructor’s standpoint is well highlighted here: https://www.youtube.com/watch?v=eA5R41F7d9Q&t=44s.

Prova scritta facoltativa (a scelta dello studente), con prove in itinere
Prova orale facoltativa (a scelta dello studente)
Valutazione continua facoltativa (a scelta dello studente)
Grading
All assignments are due by 11:59 PM CET on the due date, usually the day before the corresponding session. For example, when a session is scheduled on Friday, assignments are due by Wednesday at midnight. When a session is scheduled on Monday, assignments are due by Thursday at midnight To accomplish our learning objectives, we use a variety of techniques: readings, written assignments, videos, and discussion. We will often refer to and apply the tools and frameworks from the class when analyzing cases, discussing issues, and treating SC planning problems. One of the real benefits of the course is that you can enhance your learning through productive discussion with peers in the classroom. Contributions are evaluated on the basis on your willingness to constructively challenge and discuss the concepts of SC planning through presentations, case assignments and in-class exercises.
Case discussions are useful as you are supposed to put yourself in the shoes of the executives and take a position on what you would do. Questions have been provided that lead you through important issues to examine. For every question, always consider the pros and cons of each answer, as there are no easy solutions in SC planning. Considering both sides will push you to reconsider the assumptions that often are embedded in each problem setting. Another important part of case analysis is to look at any numerical information provided. The numbers can and should guide you towards both the successes and failures of the company. This portion of the class may involve breakout sessions for teams to generate strategies and tactics from individual analysis for class discussion. Whenever you provide an assessment, try to frame your thinking about the criteria of interest. My experience taught me that disagreements arise since the basis for the decision was predicated on different criteria and therefore agreement became impossible. Being articulate about criteria allows you to speak with each other rather than past each other.
Class participation is scored as a function of the quality of your contributions (i.e. does your comment move the class discussion forward) rather than the quantity of comments. Students are encouraged to refrain from prolonged or misdirected monologues, statements of common knowledge, and confrontations that are not directed at the issue at hand.
The table below summarizes all assignments along with the corresponding grade points. Any item missing will be treated via an oral test taken after the end of the course, by absorbing the corresponding weight.
Item Type Weight Mode
Mid-term Exam Individual 30% Computer aided test
Early bird Exam Individual 30% Computer aided test
Alternatively,
One-shot final exam Individual 60% Comprehensive oral exam (*)
Participation and In teams 40% Content 25%
case discussions Presentations 15%
(*) 100% for students who did not embark into developing their own case and/or did not participate in the sessions devoted to case discussions
Bibliography
Main textbooks
Jacobs, F.R., Chase, R. B., 2018, “Operations and SC Management”, McGraw-Hill.
Cigolini, R., Franceschetto, S., 2021, “Cases in SC Management”, Mondadori
Additional textbooks (in alphabetical order)
Christopher, M., 2016, “Logistics and SC management”, Pearson Education.
Correa, H.G., 2014, “Global SC management”, Atlas
Gattorna, J., Ellis, D., 2019, “Transforming supply chains: realign your business to better serve customers in a disruptive world”, FT Series
Harrison, A., Van Hoek, R., 2014, “Logistics management and strategy: competing through the SC”, Pearson
Ivanov, D., Tsipoulanidis, A., Schoenberger, J., 2019, “Global SC and operations management”, Springer
Johnsen, T., Howard, M., Miemczyk, J., 2014, “Purchasing and SC management. A sustainability perspective”, Routledge.
Mangan J., Lalwani, C., 2016, “Logistics and SC integration”, Wiley
Rushton, A., Oxley, J., Croucher, P., 2017, “Handbook of logistics and distribution management: understanding the SC”, Kogan
I., 2007, “Logistics and SC integration”, Sage
Shah, J., 2016, “SC management: text and cases”, Pearson
Shapiro, J.F., 2007, “Modelling the SC”, Brooks/Cole, Cengage Learning.
Stadtler, H., Kilger, C., 2005, “SC management and advanced planning”, Springer
Waters, D., Rinsler, S., 2014, “Global logistics: new directions in SC management”, Kogan
Videos
The next few videos may represent a thoughtful introduction to some key topics of the course:
SC Planning @ Starbucks: https://www.youtube.com/watch?v=ElYNhGbOTOQ
SC planning via SCOR model: https://www.youtube.com/watch?v=VrX2Qf0OT2M
SC planning via SCOR again: https://www.youtube.com/watch?v=sL0vKtpwWP0
What supply planning is: https://www.youtube.com/watch?v=4iI6La7-U2o
Integrated SC Planning: https://www.youtube.com/watch?v=fM4xKfLZhFI
A digital SC for the future: https://www.youtube.com/watch?v=HKnpiDiCe2s
Then, just for the sake of warming you up before starting, you might as well take a glance here.
A look around the notion of SCs & SC Management:
https://www.youtube.com/watch?v=Mi1QBxVjZAw&t=11s
https://www.youtube.com/watch?v=lZPO5RclZEo&t=2s
https://www.youtube.com/watch?v=4-QU7WiVxh8
https://www.youtube.com/watch?v=ZuQ200JAViA&list=PLCD3E338A3E58E906&index=7
https://www.youtube.com/watch?v=YbM_LydRlnM
SC strategies & the service sector: https://www.youtube.com/watch?v=mPkgkwb08GU
SC transformation @Intel: https://www.youtube.com/watch?v=3bE4bHBVB6k
SC-related positions, jobs, roles etc.:
https://www.youtube.com/watch?v=Mh8KCRcQtRM
https://www.youtube.com/watch?v=HN5dDOGgKVA
https://www.youtube.com/watch?v=7qGAIaKqAuE
https://www.youtube.com/watch?v=bQKE5Uu5TNo
https://www.youtube.com/watch?v=O6ry5U9pHqE
https://www.youtube.com/watch?v=kkbc2PUxpY0
Some meaningful examples:
Amazon (old) SC: https://www.youtube.com/watch?v=Y-lBvI6u_hw
IKEA (unique) Supply Chain: https://www.youtube.com/watch?v=DBrl356VhqQ
Walmart SC: https://www.youtube.com/watch?v=yZC4neLax5o
Relevant journals for further readings (in alphabetical order)
IJLDM: https://www.emerald.com/insight/publication/issn/0960-0035
IJOPM: https://www.emeraldgrouppublishing.com/journal/ijopm
IJPE: https://www.journals.elsevier.com/international-journal-of-production-economics
IJPR: https://www.tandfonline.com/toc/tprs20/current
JOM: https://onlinelibrary.wiley.com/journal/18731317
JPSM: https://www.journals.elsevier.com/journal-of-purchasing-and-supply-management
JSCM: https://onlinelibrary.wiley.com/journal/1745493x
PP&C: https://www.tandfonline.com/loi/tppc20
SCM: https://www.emerald.com/insight/publication/issn/1359-8546
Related Institutions other than Universities
APICS: http://www.apics.org/
CIPS: https://www.cips.org/

With increasing quantities of goods moving across the globe, growing environmental regulatory pressures and increasing customers’ expectations, sustainable logistics has now become one of the key business areas for companies to compete, be successful and thrive in nowadays business environment. The course aims to provide students with the capabilities to master advanced managerial issues related to Sustainable Logistics operations. Understanding the environmental impact of complex logistics systems, identifying the practices and actions that can be undertaken by managers to embrace more sustainable logistics strategies and design greener logistics networks, becoming aware of the tools and methods for sustainability quantification, analysing the company’s green logistics performance over a set of relevant KPIs will be among the key topics.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

Understand and describe:
the main green logistics strategies and their consistency with the general company strategy
the main practices and actions that can be undertaken in the arena of green logistics, with reference to key aspects such as network design, transport, warehousing, and logistics innovation
the main methodologies for sustainability quantification and company’s green logistics performance analysis
Apply the theories, models, principles and criteria to understand and address real-world problems related to green logistics
Design and illustrate innovative sustainable logistics solutions in new fields (e.g. sustainable B2c eCommerce and last mile delivery)

Sustainability in Logistics as a strategic priority for companies. Definition of Green Logistics. Evolution of the concept over time. Triple Bottom Line (TBL) and SDG frameworks. Types of environmental impact. Green logistics and corporate strategy.
Assessing Green Logistics: frameworks and quantification methods. Guidelines, metrics and measures. GHG Protocol, ISO standards, GLEC framework. The carbon footprint of logistics activities.
Sustainable logistics network and green transport. Design and management of green logistics networks. The role of transport in greening logistics networks and types of sustainable transport solutions. Cost, service and sustainability performance. Sustainability performance quantification.
Green warehousing. Energy-efficient solutions for warehousing. Best practices and impacts on corporate performance. Assessment of the environmental impact of logistics sites. Systems for monitoring green performances (e.g. ‘Green IT’).
Sustainability strategies for city logistics and last mile deliveries. Innovative last mile delivery solutions. Impacts on efficiency, effectiveness and environmental sustainability. City logistics networks. Crowdsourcing logistics in urban environment. Relationship between service level and sustainability.
New models of collaboration towards sustainability. Collaborative practices. The role of logistics service providers (LSPs) in improving sustainability.
The impact of logistics on social sustainability. Logistics solutions for reducing food waste.
Innovation in logistics and sustainability implications. B2c eCommerce. Sustainable packaging. Reverse Logistics. Logistics 4.0 and sustainability.
The Green Logistics course leverages the following teaching methodologies:
Theoretical lessons, i.e. “traditional” lessons to provide the students with both a deep knowledge on green logistics systems/processes and criteria, methods and tools to design and manage sustainable logistics systems (ILOs 1, 2)
Practical lessons, i.e. lessons going through structured exercises to let the students apply what has learnt been during the theoretical lessons (ILO 2)
Seminars, i.e. lectures given by external guests (top managers from multinational companies and international experts) to provide the students with strong connections with the real applications of what has been learnt during the lessons (ILOs 1, 2, 3)

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The final exam consists of a written examination (mandatory) and a group assignment (optional/on a voluntary basis).
Written exam
The written exam is individual and structured into:
Theoretical Questions: open questions where the students have to be able to both present/describe green logistics strategies/solutions and apply them to specific contexts/problems (ILOs 1, 2, 3)
Quantitative Exercises: practical exercises with numbers where students are required to apply the methods learnt during the course (ILOs 1, 2)
Group assignment
The group assignment is optional (not mandatory) and can be carried out in small groups. It consists of a real business case to be discussed in terms of as-is process analysis and identification/ proposal of logistics strategies and solutions for improving the overall sustainability performance. The evaluation of the assignment is between 0-3 points to be added to the final mark of the written exam (ILOs 1, 2, 3).
The teaching material consists of: (i) a set of slides supporting the in-class lectures; (ii) practical lessons/exercises; (iii) selected references (e.g. selection of papers and book chapters). All the material will be available before the related lesson on WeBeep.

A. McKinnon, M. Browne, M. Piecyk, A. Whiteing, Green logistics: improving the environmental sustainability of logistics, Editore: Kogan Page, Anno edizione: 2015, ISBN: 978-0749471859
D.B. Grant, A. Trautrims, C.Y. Wong, Sustainable logistics and supply chain management: principles and practices for sustainable operations and management, Editore: Kogan Page, Anno edizione: 2017, ISBN: 978-0749468668

The present course is designed in collaboration with Altagamma to illustrate the fundamentals of the luxury sector while creating concrete links between theory and practice in the key processes along the value chain of high-end and luxury goods companies. Several case studies will be discussed, with particular emphasis on leading luxury companies, to understand the most relevant, critical, and future-facing perspectives. The course approach will be based on dynamic conversations, real case discussions, and interactive industrial relations to allow participants to visualize the key principles of High-End and Luxury Management applied in practice.
A note on Altagamma:
Since 1992, Altagamma Foundation gathers High-End Italian Cultural and Creative Companies, recognized globally as authentic ambassadors of Italian style. The mission of the Foundation is to increase the competitiveness of the High-End industry, contributing to Italy’s economic growth. Altagamma members operate in multiple sectors among which fashion, design, jewellery, food, hospitality, automotive, yachts and wellness.

Specifically, by the end of the course, participants are expected to have reached the following learning objectives:
To know the fundamentals of the premium and luxury market today, as well as luxury Critical Success Factors, and to be familiar with recent and future market trends in high-end and luxury sectors.
To understand the key theoretical principles behind luxury strategy and management and to see how such principles are transformed into action in real cases across various sectors in luxury.
To evaluate the strategy of a brand, identifying strengths and weaknesses, and be able to clearly communicate to different audiences the points of parity and points of difference of a specific brand in a given market.
To acquire basic definitions (e.g. Manufacturing, Production Process, Supply Chain) as well as an overview of the paramount actors and processes along the supply chain for luxury firms.
To understand the link between (product-related) Luxury Critical Success Factors and the way customer requests are handled and to be able to design a customer-oriented strategy in a luxury company.
To elaborate, with elements of critical and reflective thinking, on the concepts of social and environmental sustainability, such as decarbonisation and just transition, to understand how they can be weaved into luxury.
To be able to apply the contents of the course to a real problem and deliver an effective presentation to industrial stakeholders.

The Luxury Sector Fundamentals:
The origins of the concept of luxury
Facts & Figures: 20 years of Altagamma Monitor
Academic definitions and national approaches (Altagamma, Comité Colbert, Meisterkreis, the Walpole Society)
Where and how is “value” created? Critical Success Factors of a luxury brand; symbolic vs technical brands; from the Veblen effect (never scientifically demonstrated) to Bandwagon and Snob effect; different customer profiles for luxury and high-end products and services.
Anatomy of the Luxury Value Chain:
New Product Development:
Focus on Personal Luxury Goods – Apparel/Footwear/Accessories: New Collection Development; timing and critical aspects
Focus on complex products (cars, yachts, design/furniture): co-design and other collaborations with suppliers
Supply Chain Management (SCM):
Luxury supply chain management: do consolidated models and theories apply?
Make or Buy; sourcing strategies; manufacturing: craftsmanship at the origin of true luxury
Luxury and Sustainable Supply Chain Management
Production and Distribution Planning:
Distribution channels and retail formats; distribution agreements; selecting the most appropriate format
Choice of number of echelons and Order Penetration Point positioning; optimal management of trade-off between stock-out and over-stock (application of the Newsvendor model to the case of Personal Luxury Goods distribution)
Sustainability and Digital Transitions:
Various cases and discussions on the future of luxury amidst trade-offs and tensions at the intersection of sustainability, innovation and operational aspects of luxury.
Future Trends and Change Management in the Context of Luxury:
Various cases and discussions on the future of luxury amidst trade-offs and tensions to build more resilient an future-oriented business and operational strategies.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
Valutazione continua condizionata (a scelta del docente)
One groupwork (on cases or assignments addressed during the semester): 30%
Active classroom participation: 20%
Final written exam ( a case study, to be discussed from a qualitative and quantitative point of view, open book): 5 0%

Brun Alessandro and Cecilia Castelli, Supply chain strategy in the fashion industry: Developing a portfolio model depending on product, retail channel and brand." International Journal of Production Economics, Anno edizione: 2013
Brun Alessandro and Antonella Moretto, "Contract design and supply chain management in the luxury jewellery industry." International Journal of Retail & Distribution Management, Anno edizione: 2012
Brun Alessandro and Moretto Antonella, Organisation and supply chain for quality control in luxury companies. Journal of Fashion Marketing and Management., Anno edizione: 2014
Karaosman Hakan, Marshall Donna and Ward Irene, For the many not the few: introducing just transition for supply chain management, Editore: INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT, Anno edizione: 2023
Karaosman Hakan and Marshall Donna, Impact pathways: just transition in fashion operations and supply chain management, Editore: INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT, Anno edizione: 2023
Karaosman Hakan, Marshall Donna and Villena Veronica, Chrysalis of crisis: Covid-19 as a catalyst for awakening power and justice in a luxury fashion supply chain, Editore: INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT, Anno edizione: 2023
Karaosman, Hakan, Perry, Patsy, Brun, Alessandro and Morales-Alonso, Gustavo, Behind the runway: Extending sustainability in luxury fashion supply chains, Editore: JOURNAL OF BUSINESS RESEARCH, Anno edizione: 2020
Brun Alessandro and Karaosman Hakan, Customer influence on supply chain management strategies: An exploratory investigation in the yacht industry, Editore: BUSINESS PROCESS MANAGEMENT JOURNAL, Anno edizione: 2019
Love Ranga, The Ghost of Luxury
Kapferer, Bastien, The Luxury Strategy: break the rules of marketing to build luxury brands
Chevalier, Gutsatz, Luxury Retail Management: how the world's top brands provide quality product & service support
Rigaud, Pini, New Luxury Management: Creating and managing sustainable value across the organization

Hence the relationship between environmental factors and human health has been known for years, there is now more attention from both the general public and different stakeholders (industry, healthcare professionals, policy makers) in addressing this matter. This fact generates the need to provide multidisciplinary competences, related to both environmental and biomedical engineering, to collect, organize, analyze, and visualize the multisource data available to generate quantitative data and actionable information that could serve as basis for decision makers.
This Lab module aims course is intended to provide the student with competences about how the environment may affect human well-being and health, and to provide the skills needed to access and process available geo-localized multi-source environmental and health data to support public health management decision-making.
Students will also learn the principles and concepts of air quality and dispersion and will be able to implement and perform air dispersion modelling, presenting appropriately the air pollution results and understanding their implications in terms of exposure and potential health effects.
The course is structured in two modules:
Through Module 1, students will acquire the basic knowledge to retrieve and manage open access environmental data, collected both through measuring stations and satellite imagery, allowing to generate scenario analysis to assess the exposure to environmental pollution. Students will also learn how to retrieve geo-localized disease-related data and how to develop descriptive and predictive epidemiological data-driven models to ultimately support decision-making.
Through Module 2, students will learn the principles and concepts of air quality and atmospheric dispersion modelling, presenting appropriately the air pollution results and understanding their implications in terms of exposure and potential health effects.

Module I
Knowledge and understanding
Students will learn how to:
Understand basic principles of data geo-localization, and the usage of Geographic Information Systems
Interpret the theories and principles of the impact of environmental factors on human health
Applying knowledge and understanding
Given specific project cases, students will be able to:
Detail the corresponding requirements
Analyze and comment on specific design choices
Project spatially explicit models for analysis of georeferenced data
Making judgements
Given a relatively complex problem, students will be able to:
Evaluate correctness of proposed solutions
Understand which factors are important and which limitations the proposed solution could have bases on temporal and spatial resolution of the input data
What are the usable tools for care professionals, the role of patient and of the engineer
Communication
Students will learn to:
Build maps for effective visualization of georeferenced information with Geographic Information Systems (GIS)
Present their work in front of their colleagues during project lab
Write a report to describe the design and implementation choice
Lifelong learning skills
Students will learn how to be able to:
Manage the execution of group projects related to coding with the support of informatics tools (GitHub)
Query and pre-process georeferenced data
Implement frameworks for the execution of modelling tasks with python programming language
Module II

• knowledge on air quality issues and human health-related implications (DD1)
• knowledge on air quality data sources and features (DD1)
• basic knowledge on air quality modelling (DD1 & DD2)

Module I covers the following topics:
· Geo-referenced data and Geographic Information Systems (GIS): coordinates reference systems, management of geographic data in vector format through GIS (QGIS), management and conversion of raster files, basics of geo-processing functions
· Most commonly used open-data sources: how to access, download and process geo-referenced data such as Copernicus, OpenStreetMap, ISTAT, regional geo-portal, ARPA, land-use database (DUSAF), Milan topographic database (etc.)
· Health and health-care related data, contextualization with environmental perspective
· Python programming language, PyCharm IDE, QGIS console, QGIS-based programming in Python
· Geo-referenced custom structured databases (focus on data types)
· Data pre-processing and features selection: missing data, outliers, principal component analysis
· Explorative analysis: variables distribution, correlation analysis, logistic regression, geographically weighted regression
· Explanatory/predictive modelling through machine learning techniques (interpretable machine learning)
· Coding projects with GitHub
Module II covers the fundamentals of atmospheric pollution, with particular reference to:

• Air quality: pollutant features, air quality indicators and reference levels, adverse effects on human health
• Air quality phaenomena and related spatial scales: global, regional and local air quality issues • Air quality data: spatial and temporal resolution, averaging time, regulatory limits.
• Atmospheric pollution sources: primary and secondary pollutants.
• Features of air quality models: scope of air quality modelling, local scale models, regional scale models, statistical models.

Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The achievement of the expected learning outcomes of both Module 1 and 2 will be evaluated through the assignment of a project work to be developed and discussed in its conceptual scheme and operational implementation. Along with a final report and presentation, the evaluation process will also take into account the activities held during laboratory hours.

Modulo 2: materiali a cura del docente disponibili sul portale WeBeep www.webeep.polimi.it
Note: I materiali forniti coprono tutti gli argomenti trattati nell'ambito dell'insegnamento. Gli altri testi di seguito elencati possono fornire ulteriori approfondimenti e possono costituire riferimenti utili per l'attività professionale.
C. D. Cooper, F.C. Alley, Air Pollution Control, Editore: Waveland. Press Inc., Anno edizione: 2011, ISBN: 1-57766-678-X
Theodore L., Air pollution control equipment calculations, Editore: Wiley-Interscience, Anno edizione: 2008, ISBN: 0470209674

The course aims to introduce students to the theory, principles, methods, and tools of human-centred design, a multidisciplinary area integrating engineering, design, and social sciences to improve how humans interact with digital technologies.
Digital transformation is reshaping the way humans interact with digital artefacts at work. While technologies such as AI, IoT, and automation enable new forms of efficiency, they also raise complex challenges regarding human roles, usability, trust, ethics, and inclusivity. This course focuses on designing digital experiences that are effective, responsible, and meaningful for the people involved, workers, managers, and end-users alike.
Students will explore theoretical frameworks and methodological approaches from human–computer interaction (HCI) and Participatory Design. Through lectures, discussions, and project-based learning, they will develop the ability to design, analyse, and evaluate digital operational systems that prioritise human values, well-being, and agency.
Specifically, the course contributes to the development of the following general capabilities:
Understanding socio-technical contexts, functions, and processes.
Identifying human, organisational, and technological factors affecting performance and innovation.
Applying design and research methods to envision and prototype human-centric digital solutions.
Collaborating effectively in multidisciplinary teams and reflecting critically on design outcomes.

By the end of the course, students will be able to:
Identify and apply human-centred design principles
Analyse socio-technical systems, recognising interdependencies between humans, technologies, and organisational processes.
Plan and manage participatory design activities, including stakeholder engagement and co-design workshops.
Select and apply research and evaluation methods to assess usability and user experience.
Design interventions or prototypes that enhance human experience and operational value within digital ecosystems.
Reflect critically on the ethical, social, and sustainability implications of digital transformation.
Attendance in class is mandatory, as active participation and engagement are essential components for achieving the learning objectives of the course.

The course is organised around five thematic areas combining theoretical insights and hands-on exploration:
Introduction to Human-Computer Interaction and Human-Centric Design
Definitions and theories
The evolution of digital artefacts and the human factor.
Key frameworks: Human-Centred Design, Participatory Design, and Sociotechnical Systems.
Design Methods for Human-Centric Design
Design thinking for digital environments
Participatory and co-design methods: stakeholder mapping, personas, and scenarios
Prototyping: from mock-ups to simulation environments.
Human–Technology Interaction in Complex Systems
Designing for usability, safety, and trust in complex systems.
Cognitive load, automation bias, and decision support in digital environments.
Designing interfaces and control systems for Complex Systems.
Desiging Digital Transformation process for Equality, Diversity and Inclusion:
Responsible innovation and ethical design frameworks.
Diversity and inclusion in digital work environments.
Human sustainability and meaningful work in the age of automation.
Evaluation and Impact Assessment
Methods for evaluating human–system interaction: usability testing, field studies, and ethnographic analysis.
Metrics for human-centric performance and organisational resilience.
Synthesising insights into actionable design recommendations.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Valutazione continua condizionata (a scelta del docente)
Altro
The course is structured to engage students in simulated professional challenges that reflect real-world contexts, fostering the integration of theoretical knowledge with practical application. This experiential approach aims to enhance students’ analytical, collaborative, and problem-solving capabilities, equipping them with competencies relevant to contemporary professional environments. Teamwork constitutes the core pedagogical framework of the course, mirroring the collaborative dynamics commonly adopted within organisations. Accordingly, the assessment will primarily be based on the quality of the outputs produced and presented during class activities. Furthermore, students will be required to complete a final individual assignment to demonstrate their capacity for independent critical reflection and synthesis.
Attendance in class is mandatory, as active participation and engagement are essential components for achieving the learning objectives of the course.
Student performance will be evaluated through a combination of group and individual assignments, designed to assess both collaborative design capabilities and individual critical reflection.
Oral (80%)
The group assignment will take the form of a poster and/or oral presentation, synthesising the outcomes of a collaborative design activity. The assessment will consider the rigour, coherence, and originality of the work presented. The poster must include:
A description of the project context and the specific challenges addressed.
A justification of the selected design and research methodologies.
The application and results of the proposed methodological approach.
A critical reflection on potential improvements, unresolved issues, and ethical considerations related to the project.
Written (20%)
Each student will submit a written essay (approximately 600–800 words) reflecting on how human-centric design principles and methods can be applied within their own research or professional context. The essay should demonstrate analytical depth, methodological awareness, and a capacity for critical synthesis.
If generative AI tools are employed in the preparation of the essay, students are required to explicitly declare the prompts used and the nature of the generated outputs.
Following the completion of the course, subsequent examination sessions will be structured as follows:
Written: 20% – Submission of a new individual written assignment.
Oral: 80% – Oral examination aimed at assessing the student’s understanding of the theoretical frameworks, methodologies, and critical perspectives addressed during the course.

Norman, D. A., The Design of Everyday Things, Editore: MIT press

Learning Goals (Obiettivi dell'insegnamento)
This course aims at outlining relevant developments in manufacturing and service industries with regard to automation and digitalization developments. This is especially tailored towards the new Industry 5.0 (I50) concept of human-centered operations systems. Therefore, the course wants to address the challenge of Human-System Interaction ( HSI ) and the design of successful human-centered systems. HSI is critical in modern operations and supply chain management due to the increasing use of automated and digital systems. Counter-intuitively during automation and Artificial Intelligence (AI) applications, the human factor is increasing in importance in terms of operational performance and business success. In most empirical evidence studies within operations management we find that hybrid systems are performing best, combining the strengths of automated and computer systems with human workers.
Consistently with premise, the course has the following structure: This course aims to provide the main methodologies and criteria for analysing, designing and managing hybrid, i.e. human-digital work systems in logistics, manufacturing and supply chain systems. After an overview on the strategic importance of human-centered operations systems, the course addresses the 3 main pillars of hybrid work systems from a human perspective: Safety, Efficiency and Trust. The last section of the course is dedicated to application examples and blueprints for successful human-centered operations systems. The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities for the participants:
Understand context, functions, processes in a hybrid (human-technology interaction) operations system and the impact on business performance
Identify trends, technologies and key methodologies in a specific application domain (specialization streams like manufacturing, retail logistics or healthcare services)
Design solutions applying a scientific approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face challenges and opportunities in business, service and industrial environments with HSI

Intended Learning Outcomes (ILO, Risultati di apprendimento attesi)
Understand and describe the main challenges in hybrid systems for digital operations systems and their interaction with the general company strategy [Understand]
Define an evolving HSI operations strategy of a company, based on both its operations processes and the its general digitalization and business strategy [Understand and Identify]
Understand and describe: the main HIS stages of Safety, Efficiency and Trust (SET) the following exemplary fields: manufacturing, transport, inhouse logistics (storage and picking), and service processes like for example healthcare [Understand and Identify]
Identify and present innovative HSI solutions in new fields (e.g. service processes, after sales or maintenance processes) [Identify and Design]
Apply criteria, methodologies and models to hybrid operations / HSI challenges in order to: design and manage digital operations systems with AI / ML / Robotics applications in a service and industry contexts [Design]

Topics (Argomenti trattati)
Operations automation and artificial intelligence (AI). Definition of technology adoption in operations systems. Implications of the use of automation and artificial intelligence in operations. The importance of process re-design and digital transformation contexts.
Challenges for digital transformation and AI business models. The human factor as the bottleneck explained. System and supply chain perspectives instead of workplace or corporate perspectives for success. Digital transfer from private to corporate systems.
Analyzing cognitive workload. Stress analysis in digital operations with the MESTAT concept. Differentiating operations tasks and supervising tasks on the rise. Analyzing new required competencies for human workers in future operations systems e.g. gold collar.
Design principles for I50. Discourse how to design human-centered operations systems with tools like design thinking and employee integration. Kaizen and TQM instruments to be used in I50 digital transformation settings.
I50 strategy design. Business model analysis and business canvass methods for I50 purposes in manufacturing and service industries. Strategy by design with human worker integration for competitive advantages.
I50 research update. Latest research outline regarding I50 and human-centered supply chain operations. Examples from different manufacturing and service industries explained.
Case study. Example case study on the empirical analysis of digital operations. E.g. retail logistics, manufacturing or healthcare services innovation cases.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
Assessment (modalità di valutazione)
The final exam consists of a written part and an oral part. The written exam is made of:
3 Written Assignments: Theory Abstract, Method Abstract & Experiment Abstract where students are required to design a HSI operations system (e.g. a warehouse, a picking system, service process) applying the models learnt during the course (ILO 4)
Oral presentation exam: Presentation session on Dec 19 where student groups report about own designed and implemented experiments in human-centric systems analysis (ILOs 1, 2, 3)
The teaching material consists of: (i) set of slides supporting the in-class lectures; (ii) practical lessons/exercises; (iii) supplementary exercises; (iv) selected references (selection of papers and chapters of relevant books, videos, etc.). All the material will be available before the related lesson on https://beep.metid.polimi.it.

This course provides a comprehensive examination of the psychological aspects that shape human behavior within contemporary organizations. Integrating foundational theories with current research and practice, the course explores mindsets, job analysis and design, and the mechanisms underlying motivation and performance. It also addresses pressing priorities in modern organizations, including occupational well-being, and workforce diversity and inclusion.
Emphasizing the dynamic interplay between people and technology, students will critically analyze the challenges and opportunities involved in leading and managing a diverse workforce in the digital era.

Through the integration of scientific frameworks, empirical research, real-world case studies, and applied perspectives, students will develop the analytical insight and practical tools necessary to:
Understand and critically evaluate how beliefs, assumptions, and mindsets influence individual behavior
Assess jobs and adapt work design to navigate evolving technological, demographic, and ecological landscapes
Analyze and refine the psychological drivers of motivation and productivity
Promote psychological well-being in the workplace
Leverage diversity as a strategic asset to drive innovation and equity.

Key Topics
Mindset
This module examines the role of beliefs and cognitive frameworks in shaping learning, performance, and behavior. Students will explore fixed and growth mindsets, along with other forms of mindset (e.g., digital mindset), analyzing how these psychological constructs influence resilience, feedback-seeking, adaptability, and performance.
Job Analysis and Design
This section focuses on how to design work to enhance motivation, engagement, performance, and well-being, considering rapid technological, demographic, and environmental shifts. Drawing on foundational theories, students will understand how job characteristics affect workplace outcomes at the individual, team, and organizational levels.
Work Motivation and Performance
This module provides a comprehensive analysis of work motivation theories, tracing their development from foundational classical models to modern, evidence-based frameworks. Students will critically assess the impact of motivational dynamics on organizational behavior and performance.
Well-Being and Occupational Health Psychology
This module examines workplace well-being through the lens of occupational health psychology, focusing on its key antecedents, mechanisms, and outcomes at the individual and organizational levels. Emphasis is placed on evidence-based interventions and organizational practices designed to foster resilient, healthy, and sustainable work environments.
Diversity, Equity, and Inclusion
This module examines diversity as a psychological, social, and strategic organizational dynamic. Students will explore the impact of stereotypes and biases (both implicit and explicit), as well as the mechanisms of inclusion, belonging, and intergroup processes. Emphasis is placed on leveraging diversity as a catalyst for innovation and a sustainable competitive advantage.

Prova scritta obbligatoria, senza prove in itinere
Assessment:
Final Written Exam: Students will be evaluated through a written exam at the end of the course. This individual assessment is designed to test their theoretical understanding, ability to apply concepts to practical contexts, and capacity for critical analysis and independent thinking.
Coursework & Participation: While assignments given during the course are not formally graded, active participation in these activities and class discussions is strongly expected.

The course gives the students an overview of the hybrid and electric powertrain commonly used in the automotive sector. The main objective is to analyze the hybrid/electric vehicle at system level, therefore analyzing how different solutions in the powertrain component sizing affects the whole vehicle performances. Scenarios and perspectives for the electrification will be discussed considering especially the European market before detailing the main important technical aspects: vehicle architecture, electrical motor/converter, on board storage system, energy management algorithms and charging infrastructures.

Lectures will provide the basis for basic knowledge to understand all the key aspect involved in the design of a hybrid / electric powertrain ( Knowledge and understanding ). Furthermore, in order to give the student an industrial picture of electrification, seminars given by engineers from automotive companies will be organized. In this way students will understand both the research and the industrial approach to the electric/hybrid vehicle.
A project regarding the hybridization/electrification of a powertrain, will be used to let the student to acquire the knowlodge to face some engineering problem as the sizing of hybrid powertrain, of battery or hybrid storage system. Students will work in groups (3-4 person) during th whole semester in order to apply the acquired knowledge on a specific vehicle to be analyzed, proposing a hybridization/electrification solution. During the course the project development will be discussed with the lecturer/tutors. This project will be presented during the final exam.

The main topics of the course are listed in the following bullets.
Scenarios and perspectives for the electrification in road transport: market prenetration of hybrid and electric vehicles, requirements for mass production, forecasts especially considering the European market;
Hybrid and electric vehicles’ architectures: overview of the different mechanical layouts of hybrid and electric powertrains, influence on the powertrain performance and complexity, evaluation of the overall efficiency and the related pollutant emissions;
Electric motors and power converters: basic working principles and fundamental equations of the principal electric machines (Permanent Magnet brushless DC, PM brushless AC, axial flux synchronous motors, …) used in battery/hybrid electric vehicles, sizing and thermal issues, overview on power electronic technologies used for on board power converters (Mosfets, IGBTs,...);
On board storage systems: different battery chemistries and technologies, overview of other on board storage systems, forecast of future battery performances, Battery Management System, hybrid storage systems, battery testing;
Energy management algorithms: overview of energy management algorithms, optimization algorithms;
Electric Vehicles Battery Charging Systems: different kinds of charging modes, standards for BEV charging infrastructure, connector typologies for quick/fast/ultrafast charging, communication protocols between vehicle and charging infrastructures, impact of charging infrastructures on electric distribution grids;
CAN bus communication protocol: physical frame, database structure, devices and show cases;
Laboratory visits and company presentations.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The final assessment of the course consists in an oral test in which the project work will be discussed and analyzed.
Students are requested to merge in small group and together will re-design the powertrain of an existing vehicle, transforming it into an hybrid or full electric one (project work).
The aim of the oral discussion is to verify that students:
have acquired a sufficient level of knowledge and understanding of the course topics;
are able to apply knowledge in solving engineering problem with specific reference to the project the student worked on during the course;
are able to communicate with a proper technical language.

Mehrdad Ehsani, Yimin Gao, Stefano Longo, Modern Electric, Hybrid Electric, and Fuel Cell Vehicles, Editore: Taylor & Francis Ltd, Anno edizione: 2018, ISBN: 9781138330498
Sheldon S. Williamson, Energy Management Strategies for Electric and Plug-in Hybrid Electric Vehicles, Editore: Springer, ISBN: 978-1-4614-7710-5

The course fits into the overall program curriculum, pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment, and the impact of those factors on business performance.
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment.
Interact in a professional, responsible, effective, and constructive way in a working environment, also motivating group members.

The student successfully taking this course is expected to:
Understand the context and the problem to solve or the opportunity to improve.
Apply scientific methods and tools to collect data, analyse them in a structured way to find the root causes of the problem, creatively design innovative countermeasures, implement them, check the results, and take consequent actions.
Interact with other members of the team who are working on the problem and with the other people involved in a constructive way.
Thus, developing strong analytical skills, and the ability to generate innovative solutions, all this by addressing real companies problems with real data, thus practicing to work in an improvement-prone environment with a strong innovative mindset.

TOOLBOX
To provide analytical and problem-solving tools to manage the improvement and innovation activities in a company:
A framework for problem setting and problem-solving: the famous A3 of Toyota Business Practice.
Measurement System Analysis
Analysis and graphical representation of a data set
Design of Experiment (DOE)
Simulation and Digital Twins
Data Analytics, Clustering, Factor Analysis, ANOVA
Creative Thinking
Multicriteria decision making, AHP
Test of Hypothesis

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Mandatory group (2 members) assignment due about 8 weeks after the course starts (30% of the final grade).
Mandatory individual written exam at the end of the course (during the exam session) using a computer and software (70% of the final grade).
The exam will be on tools and methods. It consists of multiple-choice questions and 2-3 exercises that present the quantitative analysis of a current company situation. The student is required to understand the problem, identify the correct analytical tools to use, apply them to find the causes of the problem, and discuss the findings. One or more questions may be related to: a) proposing a solution (countermeasures to solve the problem) and discussing it, or b) an open question on the topics presented in the course.

Module 2 aims to inform students about the content of Accessible Graphic Design, providing a basis in the organisation and design of accessible digital interfaces.
Main contents are: Principles of Universal Design; The design of Information; Use of colours, typography and icons; Ideal contrasts; Responsive design.
Moreover, the module aims to support and revise, from a pure Communication Design point of view, the annual projects developed within the Course of Inclusive Digital Technologies.

Dublin Descriptors
Expected learning outcomes
1. Knowledge and understanding
The students will learn how to:
master the different phases in a human-centered approach to the design of innovative, interactive technologies sustaining inclusive digital services
analyze the system’s users and context of use, and recognize specific needs (e.g., related to physical abilities, gender, socio-economic status)
consider the users’ needs in the design of digital technologies that behave respecting users’ diversity
evaluate design artifacts with a focus on inclusivity
prototype new technological solutions for conducting iterative design-and-evaluation cycles.
2. Applying knowledge and understanding
Given specific project cases, students will be able to:
Detail the corresponding requirements
Analyze conceptual and architectural choices
Apply the learned principles to identify technological solutions addressing inclusivity
Build interactive prototypes fulfilling the high-level and design specifications.
3. Making judgments
Students will be able to:
Analyze and model the goals, assumptions and requirements associated with identified problems for inclusivity
Identify the most adequate design principles and methods
Select the most adequate interactive paradigms and technologies
4. Communication
The students will learn how to explain design decisions at the correct level of abstraction, to highlight the strength of their design while motivating possible weaknesses.
5. Lifelong learning skills
The students will learn how to design inclusive interactive systems based on a human-centered approach.

Course lectures will cover the key principles and methods for the design of inclusive technologies and services:
Human-centered design: user research, participatory design and co-design, user-based evaluation
Interaction, UX and user interface design
Usability and Accessibility: principles, standards, evaluation methods and tools
Principles for Inclusive Design
Human-centered, inclusive AI: recognizing bias and exclusion in AI
Emerging technologies for inclusive digital services, e.g.: Conversational AI, IoT and tangible computing, gesture-based interaction, AR/VR.

Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The teaching and learning approach is project-based: students will learn by developing a project in which they apply the methodological and theoretical concepts introduced during the lectures.
Project activities will begin after the initial lectures presenting the methodological framework of inclusive and human-centred design. Companies, associations, and researchers working in the field of accessibility and inclusion will be invited to give seminars and propose relevant application domains and challenges for the students’ projects. The teachers and teaching assistants will supervise the project work through weekly reviews, supporting students in the progressive refinement of their analysis, design choices, prototypes, and evaluation activities.
The final assessment will be based on:
the quality of the intermediate project deliverables, including the analysis of users, needs, barriers, and contexts of use, as well as the appropriate application of inclusive and human-centred design methods;
the quality of the proposed solution and, where applicable, of the developed prototype, considering its coherence with the identified requirements and its accessibility, usability, inclusiveness, and technical feasibility;
the quality of the technical and design documentation, including the clarity of the adopted process, the justification of the design decisions, and the critical discussion of the strengths, limitations, and possible improvements of the proposed solution;
the final presentation and discussion of the project, which will assess the students’ ability to communicate the work effectively, use appropriate disciplinary terminology, justify their choices, and demonstrate an individual understanding of the project.
In relation to the learning objectives, the assessment activities will evaluate:
knowledge and understanding, through the correct use of concepts, principles, and methods related to accessibility, inclusive design, and the development of digital technologies for diverse users;
applying knowledge and understanding, through the ability to analyse accessibility and inclusion challenges, identify user requirements, and design, prototype, and evaluate appropriate technological solutions;
making judgments, through the ability to select suitable methods, compare alternative design solutions, critically interpret evidence and feedback, and reflect on the ethical and social implications of the proposed technologies;
communication skills, through the quality of the project documentation, the representation of the design process and results, and the final presentation and discussion;
learning skills, through the ability to incorporate feedback from the weekly reviews, autonomously investigate unfamiliar user needs, methods, standards, and technologies, and progressively improve the proposed solution.
The overall evaluation will consider both the quality of the final outcomes and the methodological rigour, critical awareness, and inclusiveness of the process followed to achieve them. The final discussion will also make it possible to assess the individual contribution and learning of each group member.

Course slides (available on WeBeep) https://webeep.polimi.it/login/index.php

The goal of the course is to enable students to master the configuration and the design of production systems according to the required characteristics (flexibility, reconfigurability, productivity, responsiveness, sustainability) and related performances. The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes, and impacts on operational and business performances resulting from factors decided when defining the configuration and the design of production systems;
Identify and analyze some industrial technologies and the related managerial and organizational issues;
Design solutions within different configurations of production systems based on the application of a scientific and engineering approach to face problems and opportunities in a business and industrial environment.

The main expected learning outcomes of the course, achievable through lectures and exercise/case study sessions, consist of knowledge and comprehension of the main criteria and methods for the design of production systems, as well as of the practical abilities to analyze the features of different configurations and industrial technologies and to, correspondingly, synthesize design solutions. In particular, the course will allow students to achieve knowledge and comprehension, in order to:
Name, with precise terminology, context, functions and processes implied within different configurations and design of production systems;
Describe and explain the general features, strengths and weaknesses pertaining to different configurations of production systems, while relating, in each configuration, to different functions, processes and impacts on operational and business performances;
Describe and explain the main criteria, approaches, methods and mathematical formulations to provide rough design solutions for different configurations of production systems;
Describe and explain the modelling criteria and methods to provide detailed design solutions after performance assessment and verification in view of the stochastic nature of activities in production systems;
Identify, describe and analyze the main features of some industrial technologies and their implications in terms of managerial and organizational issues.
The course will also allow students to be able to practically apply the acquired knowledge and comprehension in specific problem settings, proposed during the exercise/case study sessions and requiring abilities of analysis and synthesis, leading to:
Distinguish different contexts and requirements identified in specific problem settings, eventually being able to understand problems and opportunities in a given business and industrial environment and to formulate the goals in terms of performance targets and main design variables;
Analyze the data sets provided within specific problem settings, to estimate the achievable performances and costs;
Design solutions within different configurations of production systems, considering the contexts and the requirements due to specific problem settings, and the achievable performances and costs.

The following topics are presented during the course:
analysis of the characteristics, scope, design, management and organizational issues of the different configurations of production systems;
innovative approaches for design and management based on the virtualization of production systems (from traditional simulation to digital twin);
criteria and methods for performance assessment and verification of design solutions in view of the stochastic nature of production systems (factory physics principles and laws, Monte Carlo and Discrete Event simulation applied to manufacturing processes and systems, Digital twins of manufacturing systems);
criteria, approaches and methods for the design of manufacturing systems (job shop, manufacturing cells, transfer lines);
criteria, approaches and methods for the design of manual assembly systems (fixed position assembly, paced and un-paced lines, continuous flow lines, multi-model and mixed-model lines, assembly shop, assembly cells);
criteria, approaches and methods for the design of automated assembly systems (lines, flexible assembly systems);
criteria, approaches and methods for the design of process plants;
analysis of some industrial technologies (e.g.: food, paper, cement, ceramics, glass, semiconductors) and related management and organizational issues.

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The examination consists of a written examination on the content of the lectures and exercise sessions and an oral examination, which is conditional. In order to access the examination, a manufacturing system design case will also be required; the case will consist of an extended exercise in the form of a project providing a specific problem setting that the student will have to face through the analysis and synthesis of possible design solutions, also integrating insights on management and control (using simulation/digital twin).
Overall, the students will have to demonstrate, during the exam, his/her learning outcomes as proper knowledge and comprehension of the main criteria and methods for the design of production systems, as well as of the practical abilities required to analyze the features of different configurations and industrial technologies and to, correspondingly, synthesize proper design solutions.
During the exam, the students will have to:
be able to introduce, with precise terminology, the context, functions and processes implied within different configurations of production systems;
be able to describe and explain the general features, strengths and weaknesses of different configurations of production systems, showing an understanding of the motivations at the background;
be able to describe and explain, in each configuration of production system, the different functions and processes as well as the expected impacts on operational and business performances of different design solutions;
be able to describe and explain the main criteria, approaches, methods and mathematical formulations, and their usage to provide rough design solutions for different configurations of production systems;
be able to describe and explain the modelling criteria and methods, and their usage to provide detailed design solutions after performance assessment and verification in view of the stochastic nature of activities in production systems;
be able to identify, describe and analyze the main features of some industrial technologies and their implications in terms of managerial and organizational issues;
be able to distinguish different contexts and requirements identified in specific problem settings as well as to analyze the data sets provided to estimate the achievable performances and costs;
be able to provide design solutions within different configurations of production systems, considering the requirements due to specific problem settings, and the achievable performances and costs.

A. Portioli Staudacher, A. Pozzetti,, Progettazione dei sistemi produttivi, Editore: Hoepli, Anno edizione: 2003, ISBN: 8820331985
Hopp, Wallace J., and Mark L. Spearman, Factory Physics. 3rd ed., Editore: Illinois: Waveland Press, Anno edizione: 2011
M. Macchi, E. Negri, Digital Twins of Manufacturing Systems - Enhancing Collaborative Decision-Making in Manufacturing, Editore: Springer Cham, Anno edizione: 2026, ISBN: 978-3-032-31750-6
Lecture slides and tutorial webeep.polimi.it
Note: Webpage of the course

The course focuses on structuring, valuing, and financing large infrastructure investments. Students will learn how public sources, debt, equity, and hybrid instruments can be combined to sustain infrastructure projects. In particular, students will establish a link between sound theoretical references in corporate finance and the concrete funding of infrastructure projects. The analysis of risks at different stages of project development and the investigation of expected rewards will be complemented by the identification of sources of funding. Students will understand the main contractual arrangements underlying credit agreements, while different roles and perspectives will be covered, from financial and structuring advisors to investment banks, and infrastructure equity sponsors. The course, for which no specific background in finance is required, will consist of lectures and talks by guest speakers from NPBs, investment funds, and National/Regional authorities.

This course provides students with the knowledge and skills to understand and manage innovation in the Life Science and Health and Social Care Ecosystem. By combining theoretical perspectives with practical insights, it examines how innovation can create and capture value while addressing pressing challenges of equity, quality, and sustainability. Through highly interactive sessions and contributions from senior managers, leading professionals, and international experts, students will gain a well-rounded understanding of emerging approaches and develop a forward-looking perspective on the future of healthcare innovation.

Students are expected to meet the following Learning Goals:
Understand the main challenges, processes, and dynamics in the Life Science and Health and Social Care Ecosystem, with particular attention to value-based and responsible approaches (DdD 1)
Apply conceptual frameworks and analytical tools explained in class to identify trends, assess technologies, and address real-world needs of healthcare stakeholders through hands-on experiential activities such as interviews and hackathon-like group work (DdD 2)
Strengthen communication skills to engage effectively and persuasively with diverse stakeholders, presenting insights, ideas, and project outcomes in a clear, impactful, and professional way (DdD 4)
Foster critical thinking and autonomous, continuous learning, generating innovative and transformative solutions that create positive impact across rapidly evolving business, industrial, and social contexts. This will enable students to transfer their knowledge and competencies to new and complex challenges in healthcare innovation (DdD 3,5)

The course is organized as an experiential learning space around different topics whose in-depth understanding is fundamental for those professionals who are interested in developing value-oriented and sustainable innovations, technologies, services, and business models in the healthcare field.
Co-creation and co-production in healthcare Students will explore methods and practices that actively involve patients, caregivers, healthcare professionals, and other stakeholders in the joint design and delivery of healthcare solutions, fostering a culture of shared responsibility and collaborative innovation.
Responsible and frugal innovation in healthcare The course examines how healthcare innovation can mobilize diverse resources to deliver affordable, effective, and scalable solutions, while embedding ethical, social, and sustainability considerations at every stage of the innovation process.
Value-based healthcare and assessment of innovation The course will address frameworks and tools for evaluating healthcare innovations in terms of the value they generate for different stakeholders (e.g. patients, caregivers, hospitals, environment). Students will understand how to assess their potential impact, and prioritize those innovations that contribute to improved value generation and value capture.
Hospitals’ strategy about new technologies Recognizing hospitals as the primary gateways for healthcare technologies, the course investigates how they identify, assess, and integrate emerging innovations, evaluating their value through an overarching perspective.
Innovation pathways for health technologies
Students will explore how healthcare technologies move from research to market and clinical adoption, focusing on how to identify promising innovations and assess their technological maturity, clinical value, regulatory pathway, economic sustainability, and organizational feasibility.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, con presentazione/discussione finale
This course combines face-to-face lectures with group activities organized into two complementary challenges: the “Learn from the Experts” Challenge and the “Hackathon-like” Challenge. Together, these activities will address the key topics of the course, such as co-creation, responsible and frugal innovation, value-based healthcare, technology scanning and assessment and innovation pathways for healthcare technologies. Group work will involve active collaboration with relevant stakeholders from the Life Science and Health and Social Care Ecosystem, including companies, startups, hospitals, and consultancy firms.

• The “Learn from the Experts” Challenge will offer students direct engagement with key actors in the Life Science and Health and Social Care Ecosystem. By listening to and interacting with these professionals, students will deepen their understanding of real-world dynamics and strengthen their ability to critically analyze and reflect on the complexities of healthcare innovation.
• The "Hackathon-like" challenge will engage students in collaborative problem-solving, applying theoretical knowledge to real-world healthcare challenges. Delivered in class, the challenge will benefit from the active involvement of professionals from the field, who will offer guidance, clarify students’ questions, and contribute valuable feedback to enhance the learning experience. Given the interactive and experiential nature of the course, attendance in presence to hackathon-like group activities is highly recommended, as active participation is essential for achieving the learning objectives.
  Students will be asked to produce short deliverables about the two challenges that will account for 60% of the final grade. Students with motivated needs can ask for an individual essay instead of group activities. Finally, Students will demonstrate their understanding of the subject through an oral test about either the content of the group activities or the face-to-face lectures, which will account for the remaining 40% of the final grade.

The goal of the course is to provide students with knowledge to tackle the challenges and to assess the benefits of integrating renewable energy sources with nuclear to effectively support the transition towards a carbon-neutral power grid.
The aim of this module is to provide a general overview of the role of nuclear energy in carbon neutral scenario, highlighting the benefit and challenges of the presence of the nuclear option in the energy mix. The module will focus on the technical aspects of the integration among advanced nuclear plants, renewable energy sources, storage solutions, enhanced grid networks, load-shifting, and flexible backup options.
This module will focus on the use of Modelica code for the modelling and the technical evaluation of the integrated energy systems for the project work.

The students will know and comprehend:
The challenges of the transitions towards a carbon-neutral world and the implications on the power grid
The features of the integration among the different low carbon energy sources
The characteristics of the nuclear reactor concepts for hybrid systems (e.g., Small Modular Reactors and Generation-IV reactors) and the technical challenges from a control and safety point of view
The students will be able to:
Analyze needs and address the challenges of power generation planning and dispatchment in the green energy transition
Use and develop models for the study of low carbon energy sources
Perform a simplified techno-economic analysis of systems characterized by the presence of advanced nuclear reactors, renewables power plant, storage and other components
Exhibit fluency in technical communications with use of accurate scientific terminology.

Introduction to nuclear technology for integrated systems: basic principles of nuclear power plant production with a particular focus to the most promising concepts to be used in the integration with renewables (e.g., Small Modular Reactors and Generation-IV reactors), key plant components involved in the integration with other energy sources and their interface with the electrical grid.
Role of nuclear energy in the energy mix: base load, load-following and frequency control, GHG emissions, environmental footprint and grid stability. Non electrical applications: hydrogen production, district heating, thermal storage, desalination.
Nuclear technical challenges for the integration: principles and goals of nuclear safety, impact of the integration on safety, analysis of the daily regulation on the main power plant parameters, control issues coming from the integration with non-programmable renewable energy sources.
Fundamentals of electricity market: forward/short term market, formation of market price, wholesale market models, zonal vs nodal market, ancillary service & balancing market, capacity market.
Seminar from experts coming from industry, research center and intergovernmental agencies (OECD/NEA, IAEA, …): outlook on the current worldwide situation toward the decarbonization and role of the nuclear/renewable integration.
Techno-economic analysis of a real-world case: use of Modelica language to analyze feasibility and impact of the low-carbon sources integration.

Prova orale obbligatoria
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The evaluation consists in an oral examination aimed at verifying the knowledge of the course topics. In particular, the ability to explain the current challenges of the transition towards a carbon-neutral power grid, the ability in analyzing the problem with the proper tools – both from the technical and economic point of view - and the capacity to understand and comment the outcomes of the models are tested and evaluated. In addition, the examination requires also the preparation and the discussion of a scientific report regarding the real-world study case analyzed in the project work. The report should be prepared in advance and sent at least one week before the oral examination.

In recent years the international trade has grown significantly. Assuming a company perspective, the course aims at examining International Distribution in terms of logistics channel and trade channel design. The main international logistics variables underpinning the international distribution are deepened. Special attention is given to emerging markets and company size (medium company vs. multinational company).
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

Understand and describe the main strategies for setting a global logistics network and their consistency with the general company strategy [Understand]
Understand and describe: the main solutions/alternatives in the following fields: transport modes, customs, outsourcing in a global context, trade channel, planning of logistics flows, management of financial flows and incoterms [Understand and Identify]
Apply criteria, methodologies and models to distribution problems in order to: design and manage global distribution networks [Design]
Identify innovative solutions in managing global networks (e.g. entering new markets) [Identify]

International transportation.Features of the main transportation modes (ocean shipping, air shipping); types of services (e.g. FCL, LCL, groupage airfreight, charter airfreight); transportation networks (e.g. hub and spoke, multi – port calling), types of companies (freight forwarders, carrier, NVOCC, etc.); transportation unit loads (e.g. containers) and cost structure of international transportation (ocean freight, additional charges, positioning, detention, demurrage).
The Order cycle in a global context. Terms of trade/incoterms, main criteria for the selection of terms of trade and implications on costs structure; analysis of the shipping process in the international context and of examination of the role of main actors (supplier, client, freight forwarders, banks, insurance companies). Customs clearance process and classification of duties.
Internationalisation process of the distribution channel. General framework for distribution internationalisation; main methods for entry in a new market, both indirect exporting (e.g. export trading companies, distributors) and active exporting (e.g. agents, subsidiaries, Ecommerce B2C); main configurations of logistics networks in terms of type of warehouses (e.g. consolidation hub, international warehouse, merge in transit warehouse) and number of echelons; main logistics strategies (i.e. International sale, International outpost and International network).
The management of financial flows in a global context. The impact of duties, taxes (e.g. value added tax) and currency fluctuations; the logistics tools for the management of financial flows: VAT warehouses, bonded warehouses, free trade zones (FTZ), triangulations.
Logistics outsourcing in a global context, as a strategic lever for internationalisation. Study of the main actors and advanced services (e.g. representative office tax, management of logistics flows and payments); the role of 4PL (Four party logistics).
The risk management in a global context. Main risk factors in international flows; main approaches towards risk management (buffers tock, contingency plans, mitigation), models to assess global risk, insurance policies to manage the risk.
Planning of logistics flows in a global context. The design of relationship between subsidiaries and headquarter (forecasting, replenishment, production planning); setting of a collaborative planning with distributors (VMI on global scale)); advanced planning tools (e.g. DRP); the value and the tools of visibility in a global context.
The International Distribution course leverages the following teaching methodologies:
Theoretical lessons, i.e. “traditional” lessons to provide the students with both a deep knowledge on international distribution systems/processes and criteria, methodologies, models, tools to design and manage logistics systems (ILOS 1, 2, 3)
Practical lessons, i.e. lessons going through structured exercises to let the students apply what they learnt during the theoretical lessons (ILOS 2, 4)
Seminars. i.e. lectures given by external guests (top managers from multinational companies) to provide the students with strong connections with the real applications of what has been learnt during the lessons (ILOS 1, 2, 3)
R eal visits, i.e. in-company visits to show the students the logistics systems and processes of multinational companies (ILOS 1, 3, 4)

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The final exam consists of a written part and an assignment (group work, not mandatory ).
The Written Exam is made of:
Quantitative Exercises: practical exercises with numbers where students are required to design a specific solution (e.g. choice of transportation mode, global logistics network, …) applying the models learnt during the course (ILO 4)
Theoretical Questions: open questions where the students have to prove to be able to both present/describe logistics strategies/solutions and apply them to specific contexts/problems (ILOs 1, 2, 3)
The assignment work consists in studying international distribution system of a company. More in detail, focussing on a small number of linkages (e.g. flows from Italy to US) students are required to perform: as is analysis of the process (by using all elements developed in the course), highlighting pros/cons of the current setting; to be scenario: proposal of some alternatives/solutions to improve the AS IS situation. The company to be analysed will be proposed by students. The assigmnet must be submitted 2 days before the first call (in June), it will be graded on a scale of 0-3 points and the score will be added to the score of the written exam.
The teaching material consists of: (i) set of slides supporting the in-class lectures; (ii) practical lessons/exercises; (iii) supplementary exercises; (iv) selected references (selection of papers and chapters of relevant books, videos, etc.). All the material will be available before the related lesson on https://beep.metid.polimi.it.

Lee E., A guide to International Trading: Professionals Tools and Practice Insights for Successful Operations, Editore: Springer, ISBN: 978-3031399763
David P., International Logistics, Anno edizione: 2013, ISBN: 978-0-9894906-0-3
Dornier P., Ernst R., Fender M., Kouvelis P., Global operations and logistics, Editore: John Wiley and sons, Anno edizione: 1998, ISBN: 978-0471120360
Hult T., Closs D., Frayer D, Global Supply chain management, Editore: McGraw Hill Education, Anno edizione: 2014, ISBN: 978-0-07-182742-3

The course provides analytical models to understand the determinants of exchange rates, the dynamics of the balance of payments and the interaction between monetary policy, fiscal policy and international financial markets. The goal is to develop the ability to evaluate policy choices in an open economy and to interpret major global macro‑economic phenomena.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

Lectures and in‑class discussions will allow students to:

• Master the main open‑economy macro models and balance‑of‑payments accounting
• Evaluate the impact of monetary and fiscal shocks under different exchange‑rate regimes
• Interpret real‑world international crises and policy debates through these analytical tools
  Forum, quizzes and individual presentations will allow students to:
• Quantify policy effects on exchange rates, inflation and output with real data
• Test key international‑finance relationships (and models) and summarize results in short discussions/presentations
• Draft and present a data‑driven policy brief diagnosing external challenges and recommending macro‑policy actions

The course examines international economics with an emphasis on exchange rates, monetary policy and financial integration. After laying theoretical foundations, empirical applications and recent case studies (real world events) are discussed.
Block 1. International accounts: balance of payments and foreign‑exchange market.
Block 2. Exchange‑rate theories: PPP, UIP, overshooting model and carry trade.
Block 3. Monetary and fiscal policy in an open economy: IS‑LM‑BP and Mundell‑Fleming models.
Block 4. Exchange‑rate regimes and currency crises: first‑, second‑ and third‑generation models.
Block 5. Optimum currency areas and the Eurozone experience.
Block 6. International monetary system, global imbalances and net international investment position.

Prova scritta obbligatoria, senza prove in itinere
Valutazione continua facoltativa (a scelta dello studente)
The course will include traditional lectures and practice sessions. Newspaper articles on the topics of the course will be suggested and active participation in their discussion will be welcome. The final evaluation will be based on a final written test that includes two questions on the first part (Blocks 1-4) and one question on the second part (Blocks 5-6). In order to pass the exam, the student must obtain a sufficient mark in the final exam.
The final grade will consist of the grade received on the final (written) exam, plus any supplementary points earned by participating in certain activities presented during the course (i.e.: individual assignments (problem sets), quizzes and group assignment (acting as a teacher in the course/presentations)). More details will be provided during the course. Please note that these activities are optional: students can still achieve the maximum final grade without them.
The final exam will combine numerical exercises and conceptual questions to verify that the student:

• can solve open‑economy macro problems, quantifying how monetary‑ and fiscal‑policy shocks affect output, prices, exchange rates and the balance‑of‑payments position;
• can trace and interpret the behaviour of key international variables—exchange rates, interest‑rate differentials, current‑account balances—as market expectations and policy stances evolve;
• understands how a central bank designs and implements monetary policy in an open economy and be able to critically analyse a press or policy article on international‑economics issues, selecting and applying the most appropriate theoretical framework from the course.

Paul R. Krugman, Maurice Obstfeld and Marc Melitz, International Economics: Theory and Policy - 12th edition, Editore: Pearson, Anno edizione: 2021, ISBN: 9780135766859

At the end of the course the students will be able to:
-anlyze and design complex telecommunication systems based on Internet of Things
-understand and apply complex communication technologies at the very heart of IoT systems
-design communication networks of tiny and constrained devices to enable IoT applications and services
-design IoT systems interconnected with the Internet

1 - Knowledge and understanding
Students will learn how to:
-Analyze complex communication technologies for IoT systems
-Analyze application layer protocols for the IoT
-Analyze management platforms for the IoT
-Identify IoT system components and their relations
-Use operative systems for the IoT
-Use prototyping platforms for the IoT
2 - Applying knowledge and understanding
Students will be able to:
-Dimension and optimize the energy consumption of sensor nodes
-Evaluate the performance of communication technologies for the IoT
-Evaluate the performance of application layer protocols for the IoT
-Evaluate the performance of management platforms for the IoT
-Develop simple applications based on IoT
3 - Making judgements
Students will learn to:
-Understand the fundamental tradeoffs that govern the energy management of battery-operated sensor nodes
-Identify how the fundamental system limitations impact the design of the IoT systems
-Recognize the design space and its degrees of freedom that can be exploited to define communication technologies for the IoT
4 - Communication
Students will learn to:
-describe complex network technologies at different levels of detail

The course will provide the basics on the four major building blocks of the Internet of Things: the reference hardware, the communication technologies, the management platforms and the data storage/processing solutions. The course will start off by overviewing the most common hardware components of sensor nodes, and will then move to addressing the challenges which have to be faced to interconnect and manage such tiny devices. In this field, low power short rannge and long range communication technologies will be reviewd. Finally, the course will describe the main features and requirements of management platform commonly used to orchestrate IoT systems.
Program at a Glance
1-Introduction: the vision of ambient intelligence, application examples, enabling Technologies (Sensor Networks, RFID), networking Building Blocks and Abstractions
2-Hardware Components & Abstractions: sensor node hardware architectures, basics of ADC, energy consumption models for sensor nodes
3-Application layer protocols for the IoT: networking basics, the Constrained Application Layer Protocol (COAP), the Message Queuing Telemetry (MQTT)
4-Communication technologies for the Internet of Things long range solutions: evolution of the mobile radio network to support IoT traffic (LTE-CatM, NB-IoT), examples of Low Power Wide Area Networks (LoraWAN),
5-Communication technologies for the Internet of Things - short range solutions: introduction to capillary network infrastructures, the ZigBee protocol stack (IEEE 802.15.4 PHY/MAC layer, ZigBee Network layer, ZigBee application layer and profiles), Bluetooth and BLE, overview of THREAD and MATTER
6-Radio Frequency Identification: application Scenarios, the Physical Layers of RFID (operation band, transmission fundamentals), Collision Arbitration Standards and Solutions (Tree-based arbitration, frame-aloha based arbitration, the Q-Algorithm, performance evaluation of arbitration protocols)
7-Hands-On Activities: management and prototyping platforms (ThingSpeak, NodeRed, WokWi), analysis of IoT traffic via Wireshark

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The students will be evaluated through two mutually exclusive ways:
(i) in-course challenges
or
(ii) a final written exam on the topics of the course
The students can decide which type of evaluation is the most appropriate for them,
The written exam includes three exercises and a set of questions on the topics of the course. The students may refer to the course web site to check for templates and sample exams from past year's editions of the course.
The in-course challenges consist in developing mini-projects with fixed delivery deadlines throughout the course. The mini-projects will be organized as follows: one written homework with quantitative/qualitative exercises (similar to those discussed during exercises sessions), three practical mini-projects on the development of IoT applications by leveraging the software tools presented during lectures and lab sessions.
The final grade is
-the grade obtained in the final exam, for those students attending the final exam
-the average gade of the 4 in-course challenges, for those students clearing the course with the challenges. In this case, a short final written exam up to 3 additional points can be given to increase the final grade
The mini-projects can be developed by groups of up 2 students.
The written homework must be done singularly
The students will have to prove in the written exam and in the in-course challenges:
-to have clearly understood and acquired to the topics of the course
-to be able to qualitatively assess all the building blocks of a IoT system (hardware, communication technologies, management platforms and data storage/processing)
-to be able to assess the energy consumption of IoT devices
-to be able to dimension and optimize IEEE 802.15.4 networks
-to be able to evaluate the performances of RFID arbitration systems based on Frame ALOHA and binary trees
-to have acquired and understood the working details of short range (ZigBee, Bluetooth/BLE) and long range (LoraWAN, NB-IoT) communication technologies for the IoT
-to have acquired and understood the working details of IoT application layer protocols (COAP, MQTT)
-to be able to manage the reference software (Node-Red, Thingspeak)
-to be able to analyze IoT traffic
-to be able to build up working IoT application or networking solutions leveraging the aforementioned software
-to be able to produce clear and comprehensive documentaion describing the developed project

Green Chemistry (also known as Chemistry for Sustainability) and Green Engineering are a set of knowledge useful in designing the construction of products, materials, and plants in a manner that has minimal impact on human health and the environment. The course introduce the principles of of these disciplines, providing the tools necessary to quantitatively evaluate different synthetic procedures (chemical and biochemical), industrial risk, and toxicity. Examples from industry, including reaction conditions, alternative solvents, feedstock and intermediates selection, optimization of performance materials, will be discussed as well as emerging trends in bioprocesses and catalysis.
Upon completion of this course you will be able to:
recognize and discuss the major issues related to sustainability
understand the basics of green chemistry/green engineering and recognize green chemical processes and products
understand fundamental considerations on alternative energy sources
understand the nature, reactivity, and environmental fates of toxic organic chemicals
undestand the biochemical basis of biological organisms and the importance of biomass as source of chemicals and energy
undestand the recent trends in industry issues related to sustainability and safety with enphasis on national and international regulations.
understand the societal implications of some environmental problems and the green chemistry proposed solutions

The course is intended to provide students in Engineering Chemistry, Environmental Engineering, Safety Engineering and Material Engineering with an overview of the fundamentals of pollution prevention, green chemistry and green engineering. Students should gain a greater appreciation of how improvements and modifications are being made in both research and manufacturing to maintain and even enhance environmental quality, preventing risks connected with the production and use of harmful or toxic chemicals. It may also assist students and laureates in choosing a professional career in chemical industries and in the environmental-safety sectors. The course includes recent trends in the fundamental re-engineering of chemical process, i.e. process intensification, use of catalysis and non-traditional media and energy sources, green metrics and LCA criteria to evaluate alternative processes and products, etc.. A section is devoted to the role of biomasses as renewable sources that are capable to "green up" the chemical industry and to support sustainable development of the human society, satisfying the demand in energy and materials.At the end of the course, students will have the knowledge to address green and sustainability issues described in the objectives.
In terms of knowledge and understanding (Dublin Descriptor 1), students will be able to:
recognize and discuss the major issues related to sustainability
understand the basics of green chemistry/green engineering and recognize green chemical processes and products
understand fundamental considerations on alternative energy sources
understand the nature, reactivity, and environmental fates of toxic organic chemicals
undestand the biochemical basis of biological organisms and the importance of biomass as source of chemicals and energy
undestand the recent trends in industry issues related to sustainability and safety with enphasis on national and international regulations.
understand the societal implications of some environmental problems and the green chemistry proposed solutions
Regarding the application of the knowledge and understanding acquired (Dulino Descriptor 2), students will be able to:
perform simple green metric calculations on simple chemical reactions
have a broad vision about the issues related to a chemical process and how to move in a more green and sustainable direction
have a broad vision about the issues related to the use of natural resources (fossil and sustainable) and how yo reduce the environmental impact related to their use
Through classroom exercises, students will acquire the ability to make independent judgments (Dublin Descriptor 3), and in particular to:
determine the mass balance and the related green metrics through stoichiometric calculations
formulate hypotheses on how to improve a process or how to choos the best on depending on the effect of experimental variables such as temperature, pressure, solvents, reaction times
evaluate the reasonableness of the result of numerical calculations, based on estimates of the orders of magnitude involved.
Furthermore, students will have improved their communication skills (Dublin 4 Descriptor), using correct technical-scientific terminology to describe green and sustainable materials, their transformations, and energy production.
Finally, students will be able to independently rework, select and summarize (Dublin 5 Descriptor) the concepts relating to the information contained in basic and advanced textbooks, scientific and technical literarure in the field of chemical technologies, in particular in green and sustainable chemistry.

The course is organized in several sections:
1) Sustainability and Principles of Green Chemistry
2) Control of Environmental impact of chemical processes and products,
3) Toxicity,
4) Green metrics,
5) Biopolymers and Natural products,
6) Biotransformation and Biotechnology,
7) Energy Efficiency and Emerging Technologies,
8) Process Intensification,
9) Solvent and feedstock selection,
10) Catalysis for Sustainable Chemistry,
11) Product and Process Alternatives
Description of topics
1) Sustainability of raw materials and energy sources: renewable and not renewable resources – survey of main concerns – 12 Principles of Green Chemistry and Green Engineering – tools and methodologies for the assessment of chemical, toxicological and environmental risk – life cycle analysis of products and processes, indicators – green design of chemicals, polymers, and materials.
2) Toxicology – hazard and exposure – toxicity risk assessment
3) Improvement of environmental performance of existing industrial processes – green metrics – greener production of chemical commodities, materials, and fine chemicals from industry
4) Energy – sources, efficiency, safety: fuel types and their environmental impact – hydrogen economy – unconventional energy sources: microwave, ultrasounds, photochemistry and electrochemistry.
5) Biomasses and Cn building blocks – biopolymers and composites.
6) Bio-refinery: transformation of conventional raw materials into commodities – biocatalysis – energy crops – biofuels – solvents and molecular specialties – biotechnological applications.
7) Catalysis in green chemistry: heterogeneous catalysis (acid, metal, micellar, phase transfer) – supported reagents – homogeneous catalysis – biocatalysis.
8) Alternative solvents for Green Chemistry: VOC – supercritical fluids – ionic/eutectic liquids – gas expanded liquids – polymeric liquids.
9) Mechanical, thermal and chemical recycling: effluent and waste minimization and control – durability of products and materials – recycle of plastics.

Prova scritta obbligatoria, con prove in itinere
Exams consist in the evaluation of how the topics discussed during the course are approached by the student, and includes exercises on green metrics, question about the organic chemistry concepts important in green chemistry, and open questions. There is an intermediate exam in november (written) regarding the first part of the course and the second part (written), together with the full exam (written) in january. The students that pass the first part can do the second part, the other students they will do the full exam. It is a choice of the student, to refuse the first part even if positive (>= 18) an do the full exam. All the other written exames will cover the full program of the course. The student that pass the first part in november can take the second part in january, or february, or june, or july, or september; to pass the whole exam, aslo the grade of the second part has to be >=18, if it is lower, the student has to repeat the full exam.

P.T. Anastas, J.C. Warner, Green Chemistry: Theory and Practice, Editore: Oxford Un. Press, Anno edizione: 2000
Note: Testo Introsuttivo
L. Constable, D. Constable,, Green Chemistry Metrics: Measuring and Monitoring Sustainable Processes, Editore: Wiley, Anno edizione: 2009
Note: testo generale
M. Doble, A.Kumar, Green Chemistry and Engineering, Editore: Academic Press, Anno edizione: 2007, ISBN: 0123725321
Handbook of Green Chemistry, Editore: Wiley VCH, Weinheim, Anno edizione: 2013, ISBN: 978-3-527-33710-1
Note: Set I: Green Catalysis, (Vol. 1: Homogeneous - 2: Heterogeneous - 3: Biocatalysis);
II: Green Solvents (- Vol. 4: Supercritical Solvents -: Reactions in Water - 6: Ionic Liquids);
III: Green Processes (Vol. 7: Green Synthesis - 8: Green Nanoscience - 9: Designing Safer Chemicals)

Cenni storici sulla tecnologia nucleare e il suo sviluppo industriale, ruolo dell'energia nucleare. Concetti di Fisica del Reattore: reazione a catena, proprietà nucleari fondamentali dei materiali del reattore per combustibile -refrigerante -moderatore. Reattore ad acqua pressurizzata (PWR): tecnologia e sistemi, strutture e componenti principali. Principali differenze con reattori ad acqua bollente (BWR) e reattori veloci (FBR). Ciclo del combustibile nucleare: risorse, conversione, arricchimento, fabbricazione, gestione combustibile esaurito e rifiuti radioattivi, riprocessamento. Aspetti economici del sistema nucleare.

This course covers empirical strategies aimed at answering economic research questions. The course illustrates several applied econometric models, and develops the skills needed to plan and carry on empirical research projects. Since most applied economic research examines questions with direct policy or managerial implications, this course will clarify the difference between correlation and causal links. Purely predictive methods, grounded in correlation and regression analysis will be presented and compared with alternative estimation techniques (such as instrumental variables) more focused on the analysis of causal effects. The goal of the course is to provide valuable econometric tools for students majoring in several fields, from micro/macro/international/industrial economics to finance, and management.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

With respect to the first learning goal, at the end of the course students will be able to:
Understand in depth the key aspects of the linear regression model and the relevance of the underlying standard assumptions
Understand the variants of the linear regression model to be used when the standard assumptions do not hold
Understand why the linear regression model is not appropriate when the dependent variable is discrete, truncated or censored and which are the appropriate models to be used in those cases
With respect to the second learning goal, at the end of the course students will be able to:
Select the appropriate econometric model to be applied in practical economic situations.
Interpret the output of econometric packages implementing econometric models
Test the validity of the underlying assumptions for each model
Use econometric models to support economic decisions

Overview
The agenda includes regression, instrumental variables, differences-in-differences, probit, logit, tobit, survival analysis. One of the goals is to equip students with working knowledge of the tools of probability and statistics, skills in data handling and statistical programming, and an understanding of the models and methods of applied econometrics. To this aim, problem sets with both analytical and computer-exercise components will be a relevant part of the course. The cases will be illustrated and discussed using the open source econometric package Gretl ( gretl.sourceforge.net ).
Main topics
0. Basics refresher: estimation and testing theory, matrix algebra
1. The linear multiple regression model under standard assumptions: estimation through Ordinary Least Squares, reading and interpreting the regression output, using the model for prediction.
2. Checking assumptions of the regression model: functional form, multicollinearity, heteroskedasticity, autocorrelation, non-normality
3. Using the model to investigate causal relationships: omitted variables, endogenous regressors and the method of instrumental variables
4. Using the model to analyze the effectiveness of policies and managerial choice: the differences-in-differences method
5. Analysis of binary variables (probit and logit models)
6. Analysis of categorical variables (multinomial logit models)
7. Analysis of ordinal variables (ordered probit models)
8. Analysis of count variables (Poisson regression)
9. Analysis of truncated and censored variables (Tobit models)
10. Analysis of durations (survival model

Prova scritta obbligatoria, senza prove in itinere
Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), individuale, senza revisioni periodiche, con presentazione/discussione finale
(i) Written exam (80 minutes, weight 60%). The written exam is based on two exercises (the first is on the topics 1 to 4 illustrated above; the second is on the topics 5 to 10). The main purpose of the written exam is to assess the achievement of the second learning goal and the associated learning objectives (ability to select the appropriate model to answer research questions, to read the output of econometric packages, to perfom the appropriate tests, to use the models to support economic decisions)
(ii) Oral exam (15 minutes, weight 40%). The main purpose of the oral exam is to assess the achievement of the first learning goal and the associated learning objectives (understanding of the main theoretical aspects of econometric models). The oral exam has to be taken after the written exam, not necessarily in the same call.
(iii) Non-compulsory team project work (2 students): a paper about 10/15 pages long, where some of the techniques illustrated in the course is applied to a real problem; the paper has to be illustrated in a 30 minutes presentation, possibly via skype; the project work may increase the final mark by at most 2/30. The project work gives you the opportunity to get an hands-on perspective on the discipline. Highly recommended if you plan to include econometric models in your final thesis, or if you think that a deep understanding of statistics in general and econometrics in particular is a valuable asset for your future.

William Greene, Econometric Analysis, 7th Ed., Editore: Pearson, Anno edizione: 2012, ISBN: 9780131395381 http://pages.stern.nyu.edu/~wgreene/Text/econometricanalysis.htm
Note: selected chapters

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand the Investment Banking context, its functions and processes within the business and industrial environment
Identify the most common methods for company valuation and their practical adoption
Understand the strategy and identify the technicalities of various extraordinary deals (e.g. M&A, restructuring, private equity,...)

Students will be able to:
Learn and apply most used valuation methodologies and practices and discuss trends in complex areas of financial management
Understand and explain investment banking activities, discussing features of extraordinary deals (e.g. IPOs, M&A, LBOs, restructuring)
Recognize the different features of IB in real deals / activity and in the news
Frame different solutions (and their suitability and implications) according to corporation needs and market conditions
Develop a critical mindset to analyze past deals / activities and/or propose suggestions for new ones
In general, students will be well prepared for job interviews in the IB / finance / strategic or financial consulting segments

OVERVIEW:
The course focuses on Investment Banking (IB) topics. In particular, it concentrates on the valuation issues through the explanation of the different methodologies developed and used within the industry, along different kinds of deals and needs. In addition, it focuses on the way in which financial intermediaries can arrange and support companies’ fund raising processes on the market and through private placements. Finally, some lectures will provide insights about some extraordinary deals and assets and debts restructuring processes.
CONTENTS DESCRIPTION:
The course includes the following lectures:
Valuation
o Company value: introduction to equity and enterprise value, aim of valuation
o Analytical and empirical methodologies: asset approach, earnings approach, cash flow approach, relative valuation approach, mixed methodologies (e.g. EVA)
o Equity Research
Capital Markets
o Debt fund raising: structured bonds, ABS
o Equity fund raising
o Private equity
o Project finance
o Structured operations: complex derivatives, CDS
o Corporate Banking: short- and mid-term financing
Extraordinary deals
o Mergers & Acquisitions (M&A) and LBOs
o Company crises and company restructuring, Asset restructuring and Debt restructuring
ORGANIZATIONAL ISSUES:
The contents are provided through class lectures, which consist in both theoretical lessons and exercises. Students should attend class regularly and actively participate, contributing to class learning and discussion. Some practical sessions or case studies will be discussed with outstanding practitioners coming from the most important and highly-reputed investment banks.
During the course, a limited number of students may have the opportunity to participate in selected Challenges, such as the CFA Research Challenge. Participation will be voluntary and subject to the availability of places.

Prova scritta obbligatoria, senza prove in itinere
The assessment of learning is conducted through exams during the sessions specifically scheduled in the Academic Calendar.
The exam consists of two parts:
Part A, which is mandatory, covers basic concepts (e.g. Beta). Only passing Part A allows access to Part B.
Part B covers relevant issues and advanced discussion based on the competencies you acquired during the course.

Joshua Pearl, Joshua Rosenbaum, Investment Banking: Valuation, Leveraged Buyouts, and Mergers and Acquisitions, Editore: Wiley

The course is focused on the Life Cycle Assessment (LCA) methodology.
The aim is twofold: to introduce students to the theoretical fundamentals of the methodology and then to apply them to evaluate the environmental sustainability of materials and industrial processes.
A significant portion of the course will be devoted to applying the LCA methodology to representative real-life cases, mainly taken from chemical, food, and materials industries.
The course is organised as a computer laboratory. The open-source software, OpenLCA, is the tool adopted.
Lectures will be held in classrooms with electrical connections at every desk, and students are required to bring their own laptop computer.

Upon successful completion of the course, students will be able to:
explain the principles and methodological framework of Life Cycle Assessment (DdD1);
use OpenLCA software to perform Life Cycle Assessment studies (DdD2);
select appropriate environmental impact assessment methods and indicators for different assessment goals (DdD2);
apply the LCA methodology to simplified industrial case studies (DdD2);
interpret and critically discuss the results of Life Cycle Assessment studies (DdD2);
critically interpret and evaluate published LCA studies (DdD3).

Sustainability assessment: introductory concepts.
Fundamentals of Life Cycle Thinking (LCT) and Life Cycle Management (LCM)
Life Cycle Assessment (LCA): historical background, ISO standards, procedures, applications, data quality and data sources.
Eco-indicators: measurement methods, environmental and damage impact categories, impact quantification; carbon footprint and climate change.
Materials End-of-Life: open and closed-loop recycling, re-use, waste-to-energy, waste-to-materials, waste-to-chemicals, waste management processes.
Use of the software OpenLCA

Prova scritta obbligatoria, senza prove in itinere
The final assessment consists solely of a written examination, organised in two sections:
Part A: closed questions on theory fundamentals and one case study (half an hour)
Part B: numerical application of the LCA methodology to a simplified case study using the software OpenLCA (2 hours)
The final grade (maximum 33 points) is obtained by combining the scores of Part A (maximum 9 points) and Part B (maximum 24 points). Final grades are then converted to the Italian grading scale, with scores strictly higher than 31.5 awarded 30 cum Laude.
The test will last two and a half hours, with a short 15-minute interval between Part A and Part B.
Part A consists of multiple-choice questions and short-answer questions covering theoretical concepts and one simplified case study. During Part A, no electronic support or any other type of support is allowed.
In Part B, students will perform a simplified Life Cycle Assessment using OpenLCA and answer quantitative questions based on the obtained results. During Part B, students must use their own notebook computer. Printed notes, textbooks and other reference materials are permitted. Students may access online resources during Part B. Mobile phones are not allowed.
There is no limit to the number of examination sessions students may take, and there is no oral examination.
At the end of the course, students may take a voluntary mock examination under exam conditions. The simulation replicates the structure and timing of the official examination and offers an opportunity for self-assessment.
Students are required to bring their own notebook computer for the practical laboratory sessions and for Part B of the final examination.

Walter Klopffer and Birgit Grahl, Life Cycle Assessment (LCA) - A Guide to Best Practice, Editore: Wiley-VCH, Anno edizione: 2014, ISBN: 978-3-527-32986-1
Note: Textbook available in the Polimi library as e-book
Michael Z. Hauschild Ralph K. Rosenbaum Stig Irving Olsen, Life Cycle Assessment Theory and Practice, Editore: Springer, Anno edizione: 2018, ISBN: 978-3-319-56474-6 DOI 10.1007/978-3-319-56475-3
Reinout Heijungs - Sangwon Suh, The Computational Structure of Life Cycle Assessment, Editore: Springer, Anno edizione: 2002, ISBN: 978-94-015-9900-9

This course aims to provide the main methodologies and criteria for analysing, designing and managing Logistics Systems and Processes. After an overview on the strategic importance of Logistics and on the Performance Measurement Framework, the course addresses the 3 main layers of Logistics Management: Execution, Advanced Planning, System Design. The last section of the course is dedicated to Innovation in Logistics. The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

1. Understand and describe
the main logistics strategies and their consistency with the general company strategy
the main logistic solutions in the fields of distribution, warehousing (storage and picking), transportation, inventory management
the main models/methodologies that are intended to convey the key principles and criteria to design and manage logistics systems
2. Apply the theories, models, principles and criteria to solve complex "likely logistics problems" and to understand and address "real-world logistics problems"
3. Design and illustrate innovative logistics solutions in new fields (e.g. B2c eCommerce)

The strategic role of Logistics Management. Definition of Logistics Management. Evolution of the concept of Logistics. Logistics and Supply Chain Management. The 3-layer model: execution, planning, design. The role of Logistics in the corporate strategy. Types of Logistics Strategies.
Logistics Performance Measurement System. Logistic costs measurement and analysis. Customer service KPIs. “Cost-Service” relationship.
Logistics Execution. Warehouse Design and Management: objectives, criteria, methodologies, quantitative decision-support models. Automated warehouses: performance indicators, technical features, management policies, application fields, design methods. Order Picking: technological solutions, design methods, management policies. Transportation Management. Transportation modes (road, ship, train, air, multimodal/intermodal): features and application fields. Optimization of road transportation.
Advanced Inventory Planning. Inventory planning in a multi-item multi-node logistic system. Collaborative Planning: Information sharing, Central coordination models (e.g. Vendor Managed Inventory -VMI), Collaboration models (e.g. Collaborative Planning Forecasting and Replenishment-CPFR). Impacts of inventory management on order cycle time.
Logistics System Design. Logistic network design and management. Distribution network typologies: single and multi echelon, hub and spoke, mixed structures. Design methodologies and quantitative decision support tools. Outsourcing of Logistics: objectives, logistic service providers, selection criteria. Basics of inventory planning and impacts of inventory management on order cycle time and costs.
Innovation in Logistics. eCommerce and Omni-channel Logistics. Logistics 4.0. Sustainable Logistics (intended in its threefold meaning, i.e. economic, environmental and social). Reverse Logistics in a circular economy context. IA and Logistics.
The Logistics Management course leverages the following teaching methodologies:
Theoretical lessons, i.e. “traditional” lessons to provide the students with both a deep knowledge on logistics systems/processes and criteria, methodologies, models, tools to design and manage logistics systems (Intended Learning Outcomes - ILOS - 1, 2, 3)
Practical lessons, i.e. lessons going through structured exercises to let the students apply what they learnt during the theoretical lessons (ILOS 2, 4)
Seminars. i.e. lectures given by external guests (top managers from multinational companies) to provide the students with strong connections with the real applications of what has been learnt during the lessons (ILOS 1, 2, 3)
Virtual/real visits, i.e. in-class (with videos) and or in-company visits to show the students the logistics systems and processes of multinational companies (ILOS 1, 3, 4)

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, senza presentazione/discussione finale
The final exam consists of a written part and an oral part.
The Written Exam is made of:
Quantitative Exercises: practical exercises with numbers where students are required to design a logistics system (e.g. a warehouse, a picking system, …) applying the models learnt during the course (ILOs 1, 2)
Theoretical Questions: open questions where the students have to prove to be able to both present/describe logistics strategies/solutions and apply them to specific contexts/problems (ILOs 1, 2, 3)
The oral assessment is made of questions that might span all the topics of the course and can modify the overall score from “minus infinite” to around “plus 2 points” in the 0-30 scale (ILOs 1, 2, 3). Access to the oral examination is allowed only if the written exam is sufficient. Oral exam is mandatory for students who got a mark equal to or higher than 28. It is elective for all the other students. The oral assessment must be taken in the same session of the written exam. In addition, a non-mandatory assignment can be completed by small groups of students (e.g. 3-4 students) and must be submitted 2 days before the first call ( in January ). The assignment will involve applying some of the methods and topics studied during the course (e.g., digitalization and automation in logistics) to a real-world scenario. The assignment will be graded on a scale of 0-3 points, which will be added to the score of the written exam.
The teaching material consists of: (i) set of slides supporting the in-class lectures; (ii) practical lessons/exercises; (iii) supplementary exercises; (iv) selected references (selection of papers and chapters of relevant books, videos, etc.). All the material will be available before the related lesson on https://webeep.polimi.it.

Coyle, Langley, Gibson, Novack, Bardi, Supply Chain Management: A Logistics Perspective. (from 8th edition, 2008), Editore: South-Western College Publications, ISBN: 9780324376920
Ballou, R.H., Business Logistics Management (from 5th Edition, 2003), Editore: Prentice Hall, ISBN: 9780130661845
Chopra S., Meindl P., Supply Chain Management: strategic, planning and operation, Editore: Prentice Hall, Anno edizione: 2004, ISBN: 0131217453

This course gives an overview of techniques and algorithms in machine learning and pattern recognition. It provides students with the basic ideas and intuition behind modern machine learning methods as well as a more detailed coverage of most techniques.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Identify trends, technologies and key methodologies in a specific domain (specialization streams)
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

By the end of the module, students should:
Have a good understanding of the fundamental issues and challenges of machine learning: data, model selection, model complexity.
Develop an appreciation for what is involved in learning from data.
Understand a wide variety of machine learning algorithms.
Understand how to apply a variety of learning algorithms to data.
Understand how to perform evaluation of learning algorithms and model selection.
Have an understanding of the strengths and weaknesses of many popular machine learning approaches.
Appreciate the underlying mathematical relationships within and across machine learning algorithms and the paradigms of supervised and unsupervised learning.
Apply the algorithms to a real-world problem, optimize the models learned and report on the expected accuracy that can be achieved by applying the models.
Be able to design and implement various machine learning algorithms in a range of real-world applications.
Be able to write code in Python programming language to use machine learning algorithms.

Introduction to Machine Learning
Motivations of machine learning. Machine learning, artificial intelligence and big data. Applications of machine learning. Representation of input data. Machine learning process.
Exploratory data analysis
Data validation and cleansing, outlier and missing values detection. Data transformation. Data reduction. Sampling. Feature selection. Features extraction by filtering. Principal component analysis. Data discretization. Univariate analysis: graphical analysis, measures of central tendency, dispersion, relative location, heterogeneity, analysis of the empirical density. Bivariate analysis: graphical analysis, measures of correlation, contingency tables. Multivariate analysis: graphical analysis, measures of correlation.
Supervised learning: classification and regression
Taxonomy of supervised methods. Evaluation of classification models: holdout, cross-validation, confusion matrix and derived metrics, ROC curve, cumulative gain and lift. Treatment of categorical attributes. Nearest neighbor. Classification and regression trees: splitting, stopping and pruning. Bayesian methods: naive methods, Bayesian networks. Logistic regression. Neural networks: Rosenblatt perceptron, multi-level feed-forward networks. Support vector machines: structural risk minimization, maximal margin hyperplane for linear separation, nonlinear separation. Simple and multiple linear regression. Assumptions on residuals. Least square regression: normality and independence of residuals, significance of coefficients, analysis of variance, coefficients of determination and linear correlation, multicollinearity, confidence and prediction limits. Selection of predictive variables. Ridge regression. Generalized linear regression.
Association rules
Motivation and evaluation of association rules. Single-dimension association rules. Apriori algorithm. Generation of frequent itemsets, generation of strong rules. General association rules.
Clustering
Taxonomy of clustering methods. Affinity measures. Partition methods: K-means, K-medoids. Hierarchical methods: agglomerative methods, divisive methods. Evaluation of clustering models.
Applications and use cases
Introduction to Python programming language and its main libraries for machine learning (Scikit-learn, Keras). Applications in relational marketing using Python: lifetime value analysis, acquisition, retention, cross-selling, market basket analysis. Web mining. Social market analysis. Speech recognition. Text mining. Fraud and anomaly detection. Bioinformatics.

Prova scritta obbligatoria, senza prove in itinere
The final mark is determined by a written test based on open and closed form answers. Theoretical questions aim at assessing knowledge acquisition with respect to tasks, methods and algorithms. Applied questions aim at assessing the ability to apply methods and algorithms, to properly understand the outputs and to derive the implications for the application domain.
Notice that only students officially registered for a given session will be allowed to take the examination in that session.

C. Vercellis, Business intelligence: data mining and optimization for decision making, Editore: Wiley, Anno edizione: 2009
T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, Editore: Springer, Anno edizione: 2011
E. Alpaydin, Introduction to Machine Learning, Editore: MIT press, Anno edizione: 2014
A. Geron, Hands-On Machine Learning With Scikit-Learn and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems, Editore: O'Reilly, Anno edizione: 2017

This course is designed to equip students with the concepts and tools of sustainability and impact management in a world increasingly shaped by complex and interdependent challenges. In this evolving context, economic actors are rethinking their strategies, operations, and impact in response to sustainability imperatives that can no longer be addressed through traditional approaches alone. Students will develop radical management mindset and capabilities to engage with the enabling infrastructures, such as regulatory frameworks, measurement systems, technology, and finance mechanisms, that support and guide sustainable transformations. The course provides an updated lens to reinterpret core managerial concepts, including strategy, technology management, finance, and performance measurement, within the context of impact-driven business models and emerging economic paradigms. The course explores evolving market dynamics, corporate models, and entrepreneurial approaches explicitly designed to tackle societal issues while generating positive impact. Through a combination of theoretical insights, case studies, and practical tools, students will learn how strategy, innovation, finance, and impact management systems can be reshaped to serve both social purpose ventures and mainstream organizations committed to sustainability.
By the end of the course, students will be able to interpret the complex and systemic interrelations among societal challenges, technological innovation, market disruptions, and purpose-driven corporate and entrepreneurial models. In particular, the course contributes to the development of the following capabilities:
Understanding the concept of impact and sustainability management and the foundations of purpose-driven corporate and entrepreneurial models. The distinguishing feature of such models is the proactive pursuit of solutions to societal problems along with economic sustainability and profit.
Designing innovative solutions through the application of scientific approaches (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face societal challenges and seizing related opportunities, developing system-changing ideas, scaling solutions and translating them into long-term oriented, sustainable business models;
Interpreting real-world situations and learning from case studies;
Interacting in a professional, responsible, effective and constructive way in a working environment, also motivating group members.

On completion of the course, students will be able to:
Understand the concept of impact and sustainability management, and how purpose-driven corporate and entrepreneurial models respond to emerging societal challenges and opportunities within the impact economy.
Grasp the foundations and real-world applications of impact and sustainability management as a key driver of systemic transformation.
Reinterpret core managerial notions, such as strategy, technology, performance measurement, and finance, through the lens of purpose, sustainability and impact.
Design innovative, impact-oriented business models for ventures addressing societal challenges, and develop coherent management strategies.
Apply managerial tools and develop competencies to face the specific challenges that characterize organizations committed to tackling societal issues.
Understand the role of technology as an enabler of systemic change and as a strategic asset in sustainability-driven transformation.
Use frameworks and tools to measure and manage organizational performance in relation to societal impacts.
Analyze and compare financial instruments and approaches that aim to generate measurable societal impact alongside financial returns.
Learn how to scale ventures oriented toward societal impact by leveraging ESG criteria, impact finance, and hybrid growth strategies.
Communicate ideas and concepts effectively in both oral and written form, through case study discussions, presentations, and assessments.

I – THE EMERGENCE OF THE IMPACT ECONOMY
Societal challenges and the pursuit of a new form of capitalism
The evolution of management theory and practice through successive waves of capitalism
Emerging infrastructures enabling innovation and management: purpose, sustainability, and impact
Fundamental principles of the impact economy
II – CORPORATE AND ENTREPRENEURIAL APPROACHES TO SUSTAINABILITY AND IMPACT
The role of companies in the transition to an impact economy
Redefining corporate purpose: aligning business with societal value
Legal and organizational frameworks for impact-oriented enterprises
Sustainable and impact-driven business models
Strategies for scaling purpose-driven companies
Technology and innovation as enablers of impact
Impact measurement and management in the corporate context
III – FINANCE FOR SUSTAINABILITY AND IMPACT
The emergence of novel purpose-driven financial approaches
Disintermediation, ethics, and values: alternative finance models
Applying ESG criteria for long-term risk protection: responsible finance
Value-based financial approaches and instruments: sustainable finance
Investing in solutions: microfinance and impact finance
IV – ECOSYSTEMS AND POLICIES FOR SUSTAINABILITY AND IMPACT
The emerging role of the Entrepreneurial State
New forms of Public-Private Partnerships for impact
Social Innovation Ecosystems as enabler of impact

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
Altro
The final test will be:
a MANDATORY written exam for ALL students and it covers the slides, primer, case studies (including testimonials) discussed in class
an OPTIONAL oral exam where students are asked to critically discuss the theoretical concepts and show an original interpretation of the additional readings provided by the Professor.
The assessment is based on the knowledge of the theories and on the student’s ability to prove their understanding of their application in real-world situations.

A Primer in Management for Sustainability and Impact
Note: During the course, a Primer will be provided as well as additional readings and case studies.

The course aims at providing knowledge, skills and tools needed for analyzing, understanding, and assessing strategic decisions about energy management. The course provides students with methods and tools to analyse the context, understand the main trends and phenomena affecting the energy industry, assess the different alternatives a company has in the management of energy, in the light of the ongoing decarbonization path.
The course starts by providing a global framework of the current scenarios characterizing the energy sector and the main evolutionary trends enabling its decarbonization. Then, it focuses on the market and industry dynamics related to “traditional” sources ( oil&gas and electricity sectors ), as well as renewable energy sources (such as photovoltaic and wind energy ). Energy efficiency and the emerging paradigms (also enabled by the spread of digital technologies ) such as smart buildings, energy communities, and smart mobility are further investigated. Finally, two of the most promising emerging options to decarbonize the energy sector are addressed, i.e. energy storage systems and hydrogen. Across the different topics mentioned above, the role of technological innovation and regulatory framework is assessed, as well as the current and emerging market opportunities for companies, to provide students with a comprehensive view and understanding of the phenomena.
The discussion of business cases, together with guest lectures held by executives and managers, will encourage students to examine and get familiar with the abovementioned topics as well as their strategic and practical implications for companies.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:

• Understand context, global framework, market and industry dynamics in the energy field and their mutual effects on business, economy, environment and society
• Identify trends, technologies, key methodologies and stakeholders needs in the energy domain

EXPECTED LEARNING OUTCOMES
Dublin Descriptors
MsC Learning goals – Management Engineering
Expected learning outcomes
DdD 1: Knowledge and understanding
Understand context, global framework, market and industry dynamics in the energy field and their mutual effects on business, economy, environment and society
Students will:
Understand and interpret the role of energy management in the current competitive environment and its evolution
Understand the market and industry dynamics in the energy industry
Understand the impact of the technological innovation and of the regulatory framework in the energy field
DdD 2: Applying knowledge and understanding
Identify trends, technologies, key methodologies and stakeholders needs in the energy domain
Students will:
Apply the appropriate tools to analyze the competitive environment in the energy industry
Identify the critical decisions in the management of energy by firms
Discern and select the appropriate strategic approaches to energy management
Identify the main opportunities to launch new businesses in energy domain

Basics of energy & sustainability. The current scenarios characterizing the energy sector.Energy sources and uses at global level; Top Countries in production and use of energy; Evolutionary trends enabling its decarbonization; Emission Trading Scheme (ETS) and other enabling mechanisms.
Market and industry dynamics in the electricity sector. Electricity industry value chain; Electricity markets overview; Power generation technologies: technical and economic performance.
Market and industry dynamics in the Oil&Gas sector. Global Market dynamics; Technologies & Business Models (Revenues, Margins, Organization) in the oil&gas industry; Analysis of top players at global and European level; Decarbonization trends in the Oil&Gas industry.
Market and industry dynamics in the renewable energy sector. Global Market dynamics; Renewable energy technologies overview (e.g., PV, Wind, Hydropower); The evolution of the regulatory framework in Europe related to energy production from renewable energy sources and its impact on industry dynamics; Existing and emerging Business Models (Revenues, Margins, Organization) in the renewable energy industry (e.g., Power Purchase Agreement, Power-to-gas).
Market and industry dynamics in the energy efficiency sector. Global Market dynamics; Energy efficiency technologies overview (e.g.,electric engines, VSDs, building insulation) for buildings and industrial processes. The evolution of the regulatory framework in Europe related to energy consumption and energy efficiency (incentives, obligations, certifications) and its impact on industry dynamics; Existing and emerging Business Models (Revenues, Margins, Organization) in the energy efficiency industry (e.g., Energy Performance Contracts).
Smart Ecosystems. The role of digital technologies in the energy domain; Integrating new technologies for producing, using and storing energy in local environments (energy communities) as well as in buildings (smart buildings). Business cases and examples of energy communities and smart buildings.
E-mobility. Emerging trends (e.g., electrification, sharing, autonomous driving) that are reshaping "traditional" mobility towards "smart mobility"; e-mobility enabling technologies overview (e.g., e-cars, charging infrastructure); the evolution of the regulatory framework in Europe related to electric vehicles and its impact on industry dynamics; Existing and emerging Business Models (Revenues, Margins, Organization) in the electric vehicles charging services (e.g., Charging Point Operators, Mobility Service Providers).
Cross-sectoral decarbonization enablers. Hydrogen and energy storage systems: global market dynamics; technologies and production processes overview (e.g., blue hydrogen via CCUS, green hydrogen via electrolizer); the evolution of the regulatory framework in Europe related to hydrogen and its impact on industry dynamics; existing and emerging business models.
The course leverages the following teaching methodologies:
Traditional lessons, providing theoretical background
Seminars with company guest speakers
Group work on a company problem (project work)

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The final course evaluation is based on:
Oral exam: it is based on the topics of the course and is intended to evaluate a student’s ability to discuss and link different topics.
Project work: The project should take the form of a systematic analysis of one of the topic covered in the course (or close to the ones covered in the course), by making use of the methods and tools introduced and discussed in class; it is to be implemented in a group of 4-5 students. The project is intended to evaluate a student’s ability to critically analyse a novel problem and discuss possible alternative solutions, by integrating different perspectives and contributions emerging within the team. The project work output is evaluated at the end of the semester (no intermediate evaluations).
Composition of the final grade: Oral exam = 100%; Project work report and presentation (optional) from -2 to +2 on the grade of the oral exam.

The design and management of manufacturing and de-manufacturing systems call for methods devoted to the performance evaluation and optimization of system configuration and control. In the scope of the new needs dictated by the twin transition digital and ecological, this course deals with mathematical models of manufacturing/de-manufacturing systems aimed at evaluating their performance and optimizing their configuration and control. Different mathematical models are studied and applied based on the characteristics of various systems.
The goals of the course are:
Identify trends, technologies and key methodologies in the industrial domain
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
The methodologies studied in the course will be applied within the Project lab to a real case study. The Project lab is part of the innovative didactics program of Politecnico di Milano.

After passing the exam, the student will be able to:
Analyse production problems and devise the requirements for manufacturing/de-remanufacturing systems;
Develop models of manufacturing/de-remanufacturing systems based on a mathematical representation of their characteristics and behaviour and according to the required level of detail;
Identify, select, and manipulate mathematical methodologies to support the design, management and control of manufacturing/de-remanufacturing systems;
Design the configuration and control of manufacturing/de-remanufacturing systems and estimate their performance.
After completing the Project work, the student will be able to:
Write a technical project report;
Analyse production data from complex manufacturing systems to extract relevant performance metrics and use it to validate mathematical models;
Present the results achieved during the analysis, modelling and testing activities.
The course is based on lectures, classworks, project work and optional activities. Guest international speakers will be invited to give special lectures.

Technical design of Manufacturing/de-remanufacturing systems. Relations between technological specifications and production system types. State-based modelling of manufacturing/de-remanufacturing systems. Continuous-time Markov chains to model simple manufacturing/de-remanufacturing systems. Analytical methods (queueing networks) to model complex systems and estimate key performance indicators. Approximate analytical methods to model unreliable manufacturing/de-remanufacturing systems and evaluate their performance. Decomposition techniques to evaluate the performance of long flowlines.
Design of Manufacturing/de-remanufacturing Systems Control. Optimization of token based production policies. Hedging point policies with applications to energy-saving policies and de-remanufacturing control policies.
Analysis of real manufacturing/de-remanufacturing systems.

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
The assessment will be based on a final exam (70% of the assessment) and the evaluation of the Project Work reports (30% of the assessment). Project Work reports are required during the semester and are aimed at assessing the capability of applying the knowledge to a real case. The final exam consists of a written test including practical and theoretical exercises. Practical exercises assess the ability to understand and analyse realistic industrial problems and then create appropriate models based on the learnt methodologies to design manufacturing systems and evaluate the impact of possible reconfigurations. Theoretical exercises request to describe and elaborate on concepts, models, techniques and methodologies presented during the course.
In addition to the mandatory evaluation, students will be given the possibility to improve the final grade through:
an optional oral exam on theoretical and practical questions related to the topics included in the program (max 3 points);
optional seminar work (max 3 points). The work will focus either on the application of a learnt methodology to a real industrial case or the further development of a learnt methodology.
In total, a maximum of 4 points can be added to the grade of the written test.

The goal of the course is to provide future engineers with the required technical and scientific knowledge for assessing the sustainability of production processes and environmental engineering technologies with a life cycle approach, in order to support the achievement of the Sustainable Development Goals (SDGs) number 11 “Sustainable Cities and Communities”, number 12 “Responsible Production and Consumption”, and number 9 "Industry, Innovation and Infrastructure" of the United Nations. All three dimensions of sustainability - environmental, economic, and social - will be addressed.
Students will be provided with the necessary skills to study the environmental, economic and social impacts that industrial activities have on the availability of natural resources and on human health. They will learn to break down complex systems and processes into elementary units, and to analyse and solve problems related to the interaction between technosphere and environment, examining the alternative solutions to choose the most sustainable.

The students will:

• know and understand the fundamentals of the environmental Life Cycle Assessment (LCA) methodology (DdD1);
• know and understand the fundamentals of the Life Cycle Costing (LCC) methodology (DdD1);
• know and understand the fundamentals of the Social LCA (SLCA) methodology (DdD1);
• be able to apply this knowledge in application exercises (DdD2);
• be able to apply the LCA methodology to simplified industrial cases studies (DdD2);
• be able to identify the most sustainable solution (DdD2);
• acquire the ability to communicate their findings (DdD4).

• Industrial ecology definition, introductory concepts, and principles
• The Life Cycle Thinking principle and initiatives at the national, European and worldwide level
• Environmental Life Cycle Assessment (LCA): historical background, standards, methodology, impact assessment, application to products, application to services (e.g. treatment of solid waste), communication of the results, technical software
• Environmental labels
• Link between LCA and circularity assessment
• Life Cycle Costing: methodology and application
• Social LCA: methodology and application
• Sustainability assessment: definition, state of the art
  Theoretical lessons will be integrated by the discussion of case studies, the analysis of scientific works, some practical exercises, and the demonstration of a specialized software, in order to bring out the relationships between theoretical aspects and operational reality.

Prova orale obbligatoria
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, con revisioni periodiche, senza presentazione/discussione finale
The final exam consists of two parts: an oral test and a project that should be delivered at the end of the course. The oral test is more focused on the theoretical concepts whereas the project covers the application of the theory. The project is not mandatory but gives extra points necessary to achieve the maximum score. The evaluation criteria include the ability to explain the theoretical and applicative fundamentals of the methodologies based on the Life Cycle Thinking principle as well as the ability to apply the theoretical knowledge to case studies, complemented by the use of appropriate technical language and clarity of exposition.
The final mark is the sum of the outcome of the oral exam and of the project (if delivered). The oral exam has a maximum score of 29. The score of the project varies between -1 and +3.

Michael Z. Hauschild, Ralph K. Rosenbaum, Stig Irving Olsen, Life Cycle Assessment: Theory and Practice, Editore: Springer, Anno edizione: 2018, ISBN: 978-3-319-56474-6 https://www.dbooks.org/life-cycle-assessment-3319564757/

Il successo di un prodotto industriale è legato al corretto sviluppo della fase di progettazione, che deve considerare tutte le fasi della vita del prodotto, dal concept design fino al fine vita. Per padroneggiare questi aspetti è necessario avere una conoscenza approfondita dei metodi di progettazione da applicare, al fine di indirizzare correttamente la gestione della progettazione. Dopo brevi richiami sugli aspetti generali della progettazione industriale, il corso tratta ed approfondisce i metodi di progettazione che considerano le differenti fasi di vita del prodotto: la progettazione per l'assemblaggio e lo smontaggio, la progettazione per la fabbricazione, , la progettazione per l'ambiente e l'analisi del ciclo di vita, la progettazione per affidabilità.
Vengono anche introdotti i concetti di ottimizzazione multiobiettivo e di progettazione robusta.
Lo sviluppo di un progetto relativo a un caso reale permetterà l'applicazione pratica degli argomenti del corso.

The goal of this course is to provide a framework for advanced modeling and data analysis techniques for dynamical systems, ultimately enabling students to extract (“learn”) useful information from measured data. The course focuses on the following topics: stochastic processes, optimal prediction, parametric and non-parametric system identification, time series and input-output systems. The course has both a theoretical and a practical flavor, with the illustration of some significant applications of the presented techniques in various fields.

Dublin Descriptors
Expected learning outcomes
Knowledge and understanding (DD1)
Through theoretical lectures and numerical exercises sessions, students will achieve a comprehensive knowledge of advanced modeling and data analysis techniques. In particular, they will learn the main tools of system identification. Students will also be able to understand the fundamental problems that can be encountered while extracting information from a finite set of observations taken from an unknown system.
Applying knowledge and understanding (DD2)
Students will be able to apply the mentioned methods to practical estimation, identification, prediction, and fault detection problems, using real data measurements.
Making judgements (DD3)
Students will be able to autonomously analyze temporal data sets and select the most appropriate methodology to extract useful information from the data. They will also be able to critically analyze the validity and reliability of the identified models.
Communication (DD4)
Students will learn to correctly present the results of a model identification process, comparing different models in terms of size, accuracy and reliability, and showing the models’ prediction capabilities.
Learning skills (DD5)
Students will be able to apply the methodologies learned throughout the course to tackle complex modeling and estimation problems in a structured way. They will also have a sufficiently comprehensive background to be able to learn new methodologies. Students will also be able to read current research papers and understand the issues raised by current research in the field.

The program of the course is as follows.
Basic concepts of stochastic processes
ARMA and ARMAX classes of parametric models for time series and for Input/Output systems
Parameter identification of ARMA and ARMAX models
Analysis of identification methods
Model validation and pre-processing
Time series analysis

Prova scritta obbligatoria, senza prove in itinere
Prova orale condizionata (a scelta del docente)
The exam will be a written test in one of the official available dates. The exam will consist of both theoretical questions and simple (i.e., not computer-aided) exercises. The final marks will be awarded based on the correctness of the answers, the appropriateness of the technical terminology employed, and the clarity of exposition. Specifically, the students will be asked to:
show their understanding of the main problems (and the corresponding solution techniques) in the field of data-driven modeling in general (DD1)
select and describe the most appropriate methodological tools for a given problem (DD2, DD3, DD5)
use analytical methods to solve system-identification problems of moderate complexity (DD2, DD3, DD5)
provide a critical analysis of the results and clearly illustrate methodological processes or theoretical properties (DD4, DD5)
An additional oral exam may be required by the professor, at his own discretion.

S. Bittanti, Model Identification and Data Analysis, Editore: John Wiley, Anno edizione: 2018, ISBN: 9781119546368
S. Bittanti and S.M. Savaresi, Lecture notes
P. van Overschee, B.L. de Moor, Subspace Identification for Linear Systems: Theory, Implementation, Applications, Editore: Kluwer Academic Publishers, Anno edizione: 1996 ftp://ftp.esat.kuleuven.be/pub/SISTA/ida/reports/96-26a.pdf
Note: Freely available online.
L. Ljung, System Identification: theory for the user (II ed.), Editore: Prentice-Hall, Anno edizione: 1999
T.S. Soderstrom, P.G. Stoica, System Identification, Editore: Prentice-Hall, Anno edizione: 1989

Nature Based Solutions or NBS refers to nature-inspired environmental management and intervention solutions. It is a relatively recent concept, used by the European Commission to identify strategies, actions, technologies and interventions, which provide environmental services and socio-economic benefits that can increase environmental resilience. Today there is great attention to these solutions and to the development and enhancement of innovative technological solutions based on the example of natural systems. Examples of NBS are the so-called "green infrastructures" used to control stormwater runoff in urban areas, constructed wetlands and the modern "vertical gardens". In the proposed course, the different types of NBS will be illustrated, the main design parameters will be indicated and the basics to quantify their ability to provide ecosystem services will be provided.
The course is held by two teachers:
Arianna Azzellino, main expertise: ecosystems quality, environmental risk, and impact assessment
Grazia Concilio, main expertise: urbanization challenges and policy making for sustainability transition

After taking the course,
D1. knowledge and understanding: a) the student knows the fundamental principles underlying nature-based solutions; b) knows and understands the environmental issues that NBS may help to solve; c) understands the principles of available NBS technologies; d) knows the data and tools needed to build the assessment scenario for designing NBS
D2. Applying knowledge and understanding: the student is able to apply the knowledge acquired to case studies
D3. Making judgements: a) the student is able to evaluate the feasibility and potential benefits of an NBS intervention in a specific context; b) is able to provide an evaluation of NBS, even if not strictly related to those evaluated in the course;
D4. Communication skills: the student is able to explain what he/she has learnt and the reasons for his/her own evaluations in a clear and convincing way
D5. Learning skills: the student has acquired the skills needed to pursue further study independently.

1. Principles of Nature-Based Solutions for enhancing resilience to climate change.
2. The concept of ecosystem services
3. Human activities interrelations with ecological systems and main tools and approaches for applying Nature-Based Solutions to reducing climate risks.
4. Green infrastructures as aviable complement to grey engineered protection structures for reducing impacts of disaster events.
5. Main design parameters of the different types of NBS and their ability to provide ecosystem services
6. Environmental factors of interest for designing NBS
7. Practical guided examples on how to apply Nature-Based Solutions for reducing risks of natural hazards by investing in restoration and protection. (The students will work in teams and will provide a preliminary evaluation of an NBS application scenario. GIS tools will be used)

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The exam consists of two evaluation parts: the first part is an individual test with open / closed questions to be answered on the topics covered during the course and accounts for 90% of the grade; the second part refers to a Lab proejct group that is not mandatory and accounts for 10% of the final grade.
The final examination aims to evaluate not only the students' knowledge of Nature-based Solutions (NbS), but also their ability to apply the concepts discussed during the course to simple real-world situations.
The assessment is based on the following criteria:
Understanding of the fundamental concepts related to Nature-based Solutions and ecosystem services.
Ability to identify and explain the ecosystem services provided by different Nature-based Solutions.
Capacity to interpret simple scenarios and apply the acquired knowledge to support decision-making.
Critical thinking, including the recognition of multifunctionality, synergies and potential trade-offs among alternative Nature-based Solutions.
Quality and clarity of reasoning, particularly when explaining assumptions and justifying answers.
Appropriate use of scientific terminology and effectiveness of communication.

course slides and handouts

The course has the following objectives:
O1. Understand the omnichannel marketing approach, including trends, technologies, key methodologies and stakeholder needs in an omnichannel context.
O2. Develop new ideas and transformative solutions in the marketing field to deliver positive impact on business, industrial and societal scenarios evolving over time.
O3. Interact in a professional, responsible, inclusive, effective and constructive way in a working environment, also motivating group members.

At the end of the course, the student will be able to:
Analyze and interpret an omnichannel marketing context, identifying relevant trends, technologies, methodologies, customer journeys, touchpoints, and stakeholder needs.
Design and critically evaluate an innovative omnichannel marketing solution by applying customer research, customer journey mapping, campaign design, CRM, analytics, performance measurement, and emerging technology frameworks to a business problem.
Develop, present, and justify group-based omnichannel marketing activities, contributing professionally and responsibly to teamwork, incorporating feedback, communicating evidence-based recommendations, and supporting the effective participation of group members.

The course covers the following topics:
Fundamentals of omnichannel marketing and customer-centricity
Customer journey analysis and customer experience design
Digital media, e-commerce, retail media, and emerging marketing technologies for omnichannel marketing
Augmented reality, virtual reality, virtual worlds, and new media applications for omnichannel marketing
Marketing research methods, consumer behavior research, and applied neuroscience
Customer analytics, Customer Relationship Management (CRM) and customer engagement management
Omnichannel campaign design and coordination
Marketing performance measurement, metrics, and key performance indicators
Artificial Intelligence (AI) applications in digital and omnichannel marketing

Prova orale obbligatoria
Altro
The final grade will be determined as follows:
50% Oral examination
50% Applied coursework assessment
For the applied coursework assessment, students can choose one of two alternative assessment pathways:
Continuous assessment pathway: students will complete a series of assessed activities during the course. This pathway requires regular attendance and active participation in classroom.
Final assignment pathway: students will complete a project-based assignment that is independent of participation in classroom activities.
Students wishing to follow the continuous assessment pathway must submit a request within two weeks of the start of the course, following the procedures communicated. The oral examination will cover the topics addressed throughout the course and will require students to critically analyze and discuss short cases. Students who have not successfully completed either the continuous assessment pathway or the final project pathway will not be admitted to the final oral examination.

Palmatier, Sivadas, Stern, El-Ansary, Marketing Channel Strategy: An Omni-Channel Approach, Editore: Routledge, Anno edizione: 2019
Verhoef, P. C., Kannan, P. K., & Inman, J. J., From multi-channel retailing to omni-channel retailing: Introduction to the special issue on multi-channel retailing., Editore: Journal of Retailing. Elsevier, Anno edizione: 2015, Fascicolo: 91(2), 174–181.
Kotler, P., Kartajaya, H., & Setiawan, I., Marketing 4.0: Moving from Traditional to Digital, Editore: Wiley, Anno edizione: 2017
Kotler, P., Kartajaya, H., & Setiawan, I., Marketing 5.0: Technology for Humanity, Editore: Wiley, Anno edizione: 2021
Kotler, P., Kartajaya, H., & Setiawan, I., Marketing 6.0: The Future is Immersive, Editore: John Wiley & Sons, Anno edizione: 2024
Kotler, P., Kartajaya, H., & Setiawan, I., Marketing 7.0: A Guide for Thinking Marketers in the Age of AI, Editore: Wiley, Anno edizione: 2026

The objective of the course is to provide students with principles, methodologies and tools to design, analyze and improve manufacturing and service companies' operations, so to dramatically increase their competitive advantage.
Studenst will learn to deal with the multidimentional aspects of Operations at a strategic, tactical and operational level.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
Develop new ideas and solutions in business and industrial scenarios evolving over time

The student succesfully taking this course is expected to be able to:
DdD1
classify the different Operations Systems
understand the functioning of such systems
match the system characteristics with its target market segment
DdD2 DdD3
generate alternative guidelines to improve the system, considering main goals, constraints and evolutionary trends
design and implement solutions to improve the Operations System through a thorough methodology, sound reasoning and, whenever possible, quantitative ananlysis
Check whether the resuls are in line with the expected ones and the goals achieved

Introduction
1. Operations’ objectives and decision areas.
2. Operations in primary processes, and in supporting processes. Operations in industrial companies and in service companies.
Operations strategy
1. Operations performances, levers, positioning
2. Development of an operations strategy in the broader context of a Business strategy considering the different areas of Operations in an integrated way
3. Structural decisions (resources sizing, system configuration, vertical integration, system international footprint, etc.) and Infrastrctural decisions (resource planning and control, organisational structure, target setting, customer management)
Service Operations Management
1. Distinctive characteristics of service companies. The service concept definition.
2. Designing, managing and improving the Service delivery system. Front office versus back office, demand and capacity management. Demand management in service companies with fixed capacity (Hotels, Airlines, Turist villages,...) Yield management.
3. Queue theory. Single and multiple customer-class systems; single and multiple resource systems.
4. Operations in different service industries
Operations improvement: innovative managerial approaches for OPerational EXcellence-
1. Lean philosophy and principles. Analysis of innovative aspect of Lean approach that allow to achieve such dramatic improvements. Going beyond Just In Time.
2. Lean methodologies and techniques: Value Stream Mapping. Variations reduction. 5S, SMED, Cell design, etc.
3. A new vision of human factor and the impact on operations' structure.
4. Advanced implementation of Lean approach: high variety low volume companies, make to order / engineer to order companies (manufacturing and services). Lean product development, Lean Healthcare, Lean Banking, Lean Insurance.
5. Lean Supply Chain: the impact of applying the Lean philosophy to the whole supply chain.
6. Six Sigma
7. Agile
8. OPEX and Industry 4.0

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Final written exam.
The written exam is made of:
1-3 open questions to assess the knowledge of classifications, relationship between levers and performances, pros and cons of different alternatiove solutions for the positioning of the lever of Operations Strategy, etc. and on the functioning of complex systems
1-2 exercises presenting the quantitative analysis of a present situation in a company, and the student is requeted to take decisions on how to improve present situation and design the detailed future state configuration with a quantitative sizing if different aspects (e.g. amount of inventory; number of operators, etc.) following the 8 steps of the Lean Management approach presented doring the course, making sure that they meet the given target
The voluntary assignment is an assignment, where the student is expected to understand and present a product and market of her choice (respecting the few key characteristics required in the assignment) and design the operation system that is best to be successful with that product on such market segment (therefore showing to know how to align Market and Operations). Including the choiche of the Tecnology to use, the Sizing of the Capacity, definition of the position of the Customer Order Decopling Point, the incentive system, etc.
The proposed charateristics of the Operation system (positioning of the levers) should be justified in the light of their impact on the performance
The assignment is due around half of the semester

N. Slack, A. Brandon-Jones, R. Johnston, A. Betts, Operations and process management., Editore: Pearson ed. 4th ed
J. Bicheno, A. Portioli Staudacher, Metodologie e Tecniche per la Lean, Editore: Pitagora. J. Womack, D. Jones., Lean thinking, Editore: Free press, Anno edizione: 2003. J. Liker, The Toyota Way, Editore: McGraw Hill, Anno edizione: 2005
Terry Hill, Alex Hill, Manufacturing Strategy, Editore: Palgrave Macmillan, Anno edizione: 2009

This course aims at providing the student with fundamental criteria, processes and methods to manage operational and supply chain risks in uncertain business contexts and achieve operational resilience against unexpected disruptions. The student will learn and apply different risk modelling and analysis techniques, either qualitative and quantitative, in relation to specific application contexts. A clear understanding of the peculiarities and relevance of adopting risk-informed or resilience-driven decisions, at both strategic and operational level, is achieved through class discussion of real cases in different industrial sectors and seminars from industry managers.

After successful completion of this course the student:
Will demonstrate the ability of classifying and modelling different risk sources in operations and supply chains, eventually selecting sound mitigation strategies (Knowledge and understanding);
Will be able to select and apply proper qualitative and quantitative risk assessment methods (Applying Knowledge and understanding);
Will be able to identify and critically discuss emerging relevant ORM&R challenges, leveraging on state-of-the art knowledge (Making Judgements and Learning skills), and editing a final report on the subject matters (Communication).

The course covers the following topics:
Introduction to Operations Risk Management. Operations strategy and Operations Risk Management (ORM). Classifications of operational risks. Integration of Operations Risk Management and Enterprise Risk Management. The Risk Management Process (ISO31000). Risk homeostasis.
Quantitative and Qualitative Risk Assessment. Anatomy of risk (the risk concept and fundamental definitions). Reference Risk Identification and Assessment Methods (ISO31010). Application of Monte Carlo Method to operations risk analysis.
Supply Chain Risk Management. Vulnerabilities of global Supply Chains, the case of COVId-19 pandemic. Operational and disruption risks in Supply Chains. Supply and Supplier Risk Management: Business Impact Analysis of supplier disruptions; FMECA-based supplier assessment; risk-based supplier segmentation. Risk mitigation strategies and the role of digital technologies. Exercises and discussion of cases.
Operational & Supply Chain Resilience. Core resilience functions and resilience capabilities. Business Continuity Management. The influence of Operations strategies and Supply Chain complexity on resilience. Business game and discussion of cases.
The learning experience of this course includes, in addition to face-to-face lectures, numerical exercises, case discussions, a group project, real examples and interactions with guest speakers from industry. Groups of students (max 3) will be engaged in a major assignment focusing on either a state-of-the-art review paper or an ex-post analysis of a supply chain disruption event. The final report will be part of the student assessment process (see next paragraph).

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, senza presentazione/discussione finale
Group Assignment: Groups of students (max 3 students per group) will be engaged in actively applying risk management and operational resilience principles, models and methods by means of a major assignment. The assignment may take the form of a state-of-the-art review paper, or an ex-post analysis of a supply chain disruption event, by making use of the methods and tools presented in class. The assignment is intended to evaluate the student’s ability of critically analysing a novel problem and discuss possible alternative solutions, by integrating different perspectives and contributions coming from the team members.
During classes some minor assignments will be suggested, as an extension of in-class exercises, to be completed in groups on a voluntary basis.
Written test: based on a mix of closed- and open-ended questions, it is intended to evaluate the student’s ability of selecting, justifying and applying the relevant knowledge to manage different sources of uncertainty in industrial operations.
Grading: Student evaluation is based on course assignments:
Group assignment: 50%;
Written test: 50%;
The submission of voluntary minor assignments may award the student with max 0.5/30 point each.

Course instructor, Teaching notes, Case texts and suggested readings
Note: Available on Beep course web page
Waters D., Supply Chain Risk Management: vulnerability and resilience in logistics, Editore: KoganPage, Anno edizione: 2011
Sheffi, Y, The Resilient Enterprise, Editore: The MIT Press, Anno edizione: 2005

The course is designed to provide students of engineering with in-depth skills on Intellectual Property (IP) management, with a special focus on patents.
The students' leargning goals are:
Understand challenges, functions, processes in a business and industrial environment and their mutual effects on business, economy, environment and society
Identify trends, technologies, key methodologies and stakeholder needs in a specific domain
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) coupled with participatory approaches to face problems and opportunities in a business, industrial and societal environment

Knowledge, applied knowledge and understanding (DdD1 and DdD2):

• Understand the economic and legal rationale of Intellectual Property rights.
• Understand the range of IP tools and the related procedures available to obtain the desired patent coverage based on the set objectives.
• Understand the functioning of international databases to carry out basic patent searches, for monitoring or determining the freedom of operation.
• Identify the content, duration and coverage of a patent document and the freedom to operate that it entails for future or adjacent inventions.
• Understand the sources of uncertainty regarding IPs and the limits and challenges of IP enforcement.
  Autonomy of judgment (DdD3):
• Design suitable strategies of IP coverage and management, taking into account the specific context of the company and its competitive environment.
• Design IP portfolio strategies that match the strategic objectives of the related organization.

The course includes four parts.
PART ONE (30%) focuses on the explanation of the economic and legal rationale of IP rights and describes the various protection mechanisms available at the Italian, European and extra-European level, highlighting the main international differences.
Topic 1: What are patents. The economic and the legal-procedural point-of-view.
Topic 2: The requirements of patents (novelty, inventive step, industrial applicability, sufficient description).
Topic 3: The full range of IP rights (copyrights, utility models, trademarks, design protection, and other IPs).
PART TWO (30%) focuses on the procedures to obtain IP protection and trains the students on the use of the databases.
This part includes a series of practical exercises, such as those to check the freedom to operate, the monitoring of competitors, and describes the main steps of prior art searches.
Topic 4: The patenting procedure (filing, examination, extension, granting, opposition, maintenance) of the UIBM, EPO, UPC, PCT and the main international differences.
Topic 5: Patent Lab (part I). The patent databases. Search and read basic patent information.
Topic 6: Patent Lab (part II): Freedom to operate, monitoring, preliminary prior art search.
PART THREE (30%) focuses on the management of IPs, providing students with a current and far-reaching view on strategies for managing single IPs and portfolios of patents, discussing the strategies currently used by companies in different types of industries, including those that make an open and semi-open use of patents.
The lecutures will also highlight the global trends in infringement and counterfeiting.
Topic 7: Extracting value from IPs. Closed, semi-closed and open IP strategies and how/when to use them.
Topic 8: Patent portfolio management strategies with practical applications.
Topic 9: IP violations: counterfeiting, plagiarism, piracy and infringment. An equitable balance between IP protection and the human rights to a have affordable healthcare.
PART FOUR (10%) closes the course by presenting the techniques for evaluating and pricing patents in different circumstances and for different purposes.
Topic 10: Methods, circumstances and reliability of IP assessments.

Prova orale obbligatoria
Altro
There are two possible ways to take the exam that stand on an equal level.
REGULAR STUDENTS (NOT ACTIVELY ATTENDING)
Learning outcomes are assessed through a single examination taken after the completion of the course.
The examination normally consists of an individual oral examination with one of the instructors. At the beginning of the examination, the student is given an authentic patent document and asked to discuss the relevant freedom-to-operate issues. A satisfactory and fluent discussion is required to pass this initial part. Students who pass are then asked three brief questions covering different topics from the course syllabus, which contribute to the final grade.
If more than 30 students are registered for a given examination date, making individual oral examinations impracticable, the oral examination will be replaced by a compulsory written test followed by an optional short oral examination. In this event, the two components will take place consecutively on the same day. The written test will be administered in the morning, and the results will normally be published around noon. Students who pass the written test may request an optional oral examination to adjust their final grade (by up to two points, either positively or negatively). The optional oral examination will take place in the afternoon of the same day.
ACTIVELY ATTENDING STUDENTS
Students who actively attend the course and participate in the in-class activities may complete the assessment through two graded group assignments completed during the year and one brief multiple-choice test at the end of the course.
To qualify as actively attending students, participants must:
attend at least 90% of the classes, which are held once a week on Friday mornings;
attend classes in person, as remote participation is not available; and
participate actively in the group activities.
For organizational purposes, students wishing to follow this assessment pathway must register during the first week of the course.
Groups will be formed during the second class meeting. After the groups have been established, students may not join, leave, or change groups.
IMPORTANT
For further information or clarification, please consult the Frequently Asked Questions section on the course WeBeeP page.

Slides and readings https://webeep.polimi.it/my/
Note: Slides, reading, and recording of the lectures provided by the instructors.

To increase the transdisciplinary basic knowledge and understanding of the key facts regarding the pollution phenomena casused by plastic disposal, mostly in aquatic environments, locally and globally.
Main course contents: disposal/fate/recovery of plastic and bioplastic, standard to define bioplastic biodegradabiity, bacterial production of VFA, PHA and EPS, the environmental problems related to the often incorrect use of plastics, including micro and nanoplastic and possible solutions.

Knowledge and understanding
The student will gain an overall knowledge and understanding of of the fate/disposal and recovery route of plastic and bioplastics in the environment; of the environmental problems/impacts and solution approaches.
Application of knowledge and understanding
The student will have to apply the knowledge acquired to perform multidisciplinary projects/case studies and lab activities on actual and emerging problems. These activities will enhance the cultural level and capability of students to confront with the challenges and opportunities coming from plastic and bioplastic in the environment and in different economical sectors.
Autonomy of judgment
The student will carry out autonomous choices and interpretations with respect to case studies and lab activities supplied, being able to debate and explain the pros/cons/uncertainties of the solutions proposed or results obtained

1. Introduction to macroplastic pollution in aquatic environment, evolution, impacts, modelling, solutions
2. Biodegradation of plastics: fundamentals and standards. Fate of biodegradable plastics in the environment and in wastewater/biosolids tretament plant
3. Methods to recover and produce biopolymers from liquid and solid organic waste.
4. Microplastics: origin, fate, impacts, solutions

Prova scritta obbligatoria, senza prove in itinere
The written exam is composed by 2 questions and 2 calculation exercises. The candidate shall answer to 1 question and 1 exercise.
The evaluation/mark depends on:
question: breadth and accuracy of the content reported, level of argumentation and understanding of the question as a whole
exercise: correctness of the solution methods applied and the results obtained

Thinking about platforms we tend to think about the "usual suspects” like Airbnb, Uber, Facebook, and so on, digital companies that are often based on a light-asset structure and that mainly enable connections, exactly like Uber or Airbnb. Still, they are not the only companies that (successfully) managed to use the logic of platforms.
Neverthless, the power of platforms can go much beyond those cases. Think about companies in heterogeneous industries and with very different histories, like John Deere, Telepass, or Poste Italiane, that managed to find new innovative pathways….through platforms. This course aims to let you learn (also) from them!
The course is built on two main steps: using platforms as lenses to read the world around us and to find idle assets, resources, and skills within your organization, and then using Platform Thinking to identify innovative directions through “platform-enabled” opportunities!
The course has a strong “hands-on” approach being built around three workshops to apply the Platform Thinking process to an established company to foster innovation through platforms.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:

• Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance
• Identify trends, technologies, and key methodologies in a specific domain
• Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members

In terms of Platform Thinking, students will learn to:

• Identify socio-economic mega-trends related to digital platforms, innovative business model and data-driven opportunities [Individual essay]
• Identify platforms models and their peculiarities in the reality around us, going beyond the shiny and apparent face of the usual big names in the platform world [Individual essay]
• Run an analysis of an established company to identify idle asset that can represent an innovation opportunity through a platform model [Teamwork/Workshops]
• Apply the Platform Thinking process to identify and exploit innovation opportunities [Teamwork/Workshops]
• Design a platform-based business model and a transformation roadmap for an established organization [Teamwork/Workshops]

Overview of the Course
Over the last two decades, platforms have transformed the way, we search for information (e.g., Google), buy goods (e.g., Amazon), consume news and media (e.g., Facebook and Twitter) and travel and move around (e.g., Airbnb, Booking.com, Uber and TripAdvisor)...more broadly how we live our everyday life.
This phenomenon is known as 'the power of platforms', defined as an innovative business model that relies on digital technologies to assemble people, knowledge and companies in an interactive ecosystem where value can be created, captured and shared. These platforms have a great ability to attract funds and grow rapidly, relying on external resources (e.g. private houses for Airbnb or private cars for Uber), with a significant impact on the market. These companies act as intermediaries, attempting to reduce frictions in the market and helping the supply and demand sides of a product or service to find each other.
As such, existing companies may be inspired by these fast-growing companies to at least partially capture the opportunities underpinning the model. Most of them are digital companies mainly focusing on the service field; nevertheless, recent cases show how platforms are having an impact in many different industries with the spread of the sharing economy and implications in the brick and mortar industries.
Still, we don't believe that platforms are only for the digital world, for start-ups or for ventures created in the Silicon Valley. We do believe that platforms are a powerful tool to foster innovation for every kind of organization - a new one, but also for established organizations - wherever they come from, anywhere in the world and focusing on digital or also physical assets.
The course is based on two main pillars:

• Reading: the chance to develop the ability to asses the reality around us, understanding the differences that platforms have in comparison to traditional linear value chain organizations, and more importantly to assess the various meanings (and typologies of businesses) that stay behind the wide label "platforms"
• Writing: the chance to use those concepts and mechanisms to foster innovation, by designing platforms and highlighting the necessary steps to make the platform real.
  Main Topics
  Therefore, the course covers the following main topics:
• The typologies of platforms (transactional, orthogonal, client-as-a-target, client-as-a-source)
• The characteristics of platform organizations (idle asset hunting attitude, pricing strategies,...)
• The design variables of platforms (double value proposition, the role of trust, the role of personalization, the chicken and egg paradox)
• The data opportunities related to platforms (Business model transparency, data driven epiphanies, data driven innovation)
• The opportunities for an established organization (the idle asset canvas, the evolutionary matrix,...)
• Technological trends for platform businesses ( blockchain, metaverse, web3,...)
• The challenges of platform management (privacy issues, sustainability dimensions, ethical implications...)
  Educational Process
  The course is based on a heterogeneous teaching approach, aimed at create a continuous debate on the world of platforms and helping students in developing a strong critical thinking attitude to consider both the bright side and the challenges of these organizations.
  The learning experience is characterized by various collaborative and different teaching approaches:
• Blended class (through MOOCs)
• Various international guests (live and recorded interviews)
• Hands-on experience through 2 collaborative hackathons
• Critical reading of platform-related news
  During the course, students will apply live 2 hackathons to foster innovation throug platform-based mechanisms, each hackathon will be evaluated in the team based option and will have a different focus, involving key stakeholders and managers:
• (Platform) start-up development
• Established firm applying Platform Thinking

Prova scritta obbligatoria, senza prove in itinere
Prova orale facoltativa (a scelta dello studente)
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
The whole course is designed to propose simulated challenges that students will face in their professional experience, developing a theoretical and practical knowledge that may give you a new asset. Therefore, the entire course is based on the basic mechanisms used in most of the companies: team working. For this reason, the evaluation is going to be based mainly on the outputs presented during the classes.
Moreover, a final individual assignment is going to be required.
Final Grade
The final evaluation will be based on:
50% - The team-based project happening throughout the 3 hackathons
50% - Individual assignment (a brief essay on the critical analysis of a real case to be delivered at the end of the course)
After the end of the course, the forthcoming exam calls are going to be based:
50% - A new individual assignment
50% - An oral exam

Daniel Trabucchi; Tommaso Buganzas, Platform Thinking - Read the past. Write the future. Innovate the present., Editore: Business Experts Press, Anno edizione: 2023
Sébastien Ronteau; Laurent Muzellec; Deepak Saxena; Daniel Trabucchi, Digital Business Models - The New Value Creation and Capture Mechanisms of the 21st Century, Editore: De Gruyter, Anno edizione: 2022, ISBN: 9783110762556

The Policy Design and Evaluation Course prepares students of facing the complexity of our society and the policy making processes, in designing innovative public policies and projects and in the evaluation of their results and impacts.
The course fits into the overall program curriculum pursuing some of the expected learning goals. More speificalli, the course contributes to the development of the following capabilities:
1) to develop new ideas and transformative solutions for the public sector, to deliver positive impact on business, industrial and social scenarios evolving over time;
2) to design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid multidisciplinary background) coupled with co-design and co-production approaches to face problems and opportunities in a business, industrial and social environment;
3) to interact in a professional, inclusive, effective and constructive way in a working and social environment, also motivating group members.

The successful completion of the class will allow the student to:
1.understand and use the analytical concepts and the toolbox to design a policy;
2. understand and define the ex-post evaluation dimensions to analyse the results of a policy, that play a relevant role also in the design phase (using the theory of change, identifying outcomes, outputs, etc.);
3. understand the characteristics and constraints of policy making processes in pluralistic contexts and in addressing complex collective problems with innovative problem definition and solutions;
4. use the analytical tools learned in class in designing solutions and strategies able to overcome the obstacles to introduce innovations in complex organizational and networks settings;
5. developing the capacity to connect the theoretical concepts with concrete and empirical ‘down-to-the-earth’ situations; to accomplish this objective an original educative digital game will be used, developed by Politecnico di Milano (P-Cube game);
6. developing the comprehension of different possible applications, considering the contextual variables, through the interaction in groups in an international class.

The possibility to achieve sustainable development and fight environmental, economic, technological and social problems is linked to the ability to innovate. For many of the most severe problems it is often hard to find appropriate solutions, but, even when the solutions are available, the ways through which they can enter the public agenda, to be adopted and to be implemented, are full of twists and bumps.
The focus of the course is, then, to present concepts, frameworks and tools to address the question of how it is possible to design policies/projects and their decisional processes able to overcome the obstacles likely to arise in the attempts to introduce an innovation in the solution of collective problems.
The participants will be asked, mainly, to put themselves in the shoes of a policy innovator who tries to design and steer a proposal through the complexities of public policy making. In this path, the policy evaluation concepts and methodologies will add some of the necessary theoretical instruments to the design processes.
The course aims to offer a learning experience that does not try to simplify the complexities of public policy making, nor to provide ready-to-use solutions to the design problems. On the contrary it will stimulate the participants to analyze every single case and to derive a first-hand experience of the different elements which compose the conceptual framework developed by the literature and that represents the more realistic description of how public policies and innovative solutions come about.
The core of the course regards the tools and strategies that an innovative designer (public or private) can use in a policy design process able to support the success of a reform/innovation project.
More generally, the course focuses attention on innovations in broad sense, covering fields such as:
a) the Digitalization and AI Policies in the public sector: drovers and constraints
b) Sustainability Policies as for example: Food Policies, Water Management Policies, etc.
The intent is to use analytic concepts and tools to improve managerial capacity for successful changes in dealing with organizational and societal problems.
The analytical framework developed by policy analysts is useful to help both public and private managers in dealing with complex problems, i.e. issues in which there are different, possibly competing, points of view, lack of all the necessary resources, conflicts.
The class will be organized as follows:
Introduction: Syllabus, rules of the course for attending and non-attending students, plan of the Lectures. Theoretical starting point: What is a public policy; the policy design process and its relations with the design thinking approaches. The main example used during the course: a) Digitalization Policies in the Public Sector; b) Sustainability Policies (eg Food Policy, Water Management Policies)
Problem setting and problem solutions: starting the policy design process. Conflicts regarding problem definitions, frames, etc.
The theory of change and the evaluation dimensions; improving evaluation capacities in the design process; identify a theory of change, define the expected outcomes and outputs, selecting the policy instruments, design the implementation activities, considering how to coordinate implementors and to reach the beneficiaries compliance
Policy instruments: models, nudges, etc.
Behavioral assumptions in designing policies and intervention: the causal mechanism approach
The decision-making process: models (rational, bounded rationality, incrementalism, garbage can), elements (the actors and their roles, resources, content of the decision, patterns of interaction, environment), strategies for successful decisions; exercises with the P-CUBE Educative Digital Game
Evaluating policy success and failures: methodological designs of the ex-post evaluation
Project work (starting at the end of April/beginning of May)

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i obbligatorio, di gruppo, con revisioni periodiche, con presentazione/discussione finale
The class is based on lectures, exercises (with the use of the P-CUBE Educational Digital Game) and a project work in group. The students attending the class will participate in at least one Project Work in group and will submint the final collective work.
The mark regarding the Attending Students will be the result of the following assignments evaluation:
the project work in group (45% of the final mark), that will include the analysis of some papers and the discussion in class
an individual written exam based on the lectures’ materials (40% of the final mark)
active participation to the exercises and seminars – this will include the result of the P-Cube Educational Game exercises (15%)
If the project work in group will not possibile to realize, the mark will be the result of:
an individual written exam based on the lectures’ material (70% of the final mark)
active participation to the exercises, P-Cube sessions and seminars, analysis of papers and discussion in class (30%)
Non-Attending students will sustain an individual written exam based on the listed 3 textbooks (100% of the final mark).

Bruno Dente, Understanding Policy Decisions, Editore: Springer, Anno edizione: 2014, ISBN: 978-3-319-02520-9
Note: English Version; see: Italian Version: Bruno Dente, Le decisioni di policy, Editore: Il Mulino, Anno edizione: 2011, ISBN: 978-88-15-23242-7; Spanish Version: Joan Subirats & Bruno Dente, Decisiones Pùblicas, Editore: Ariel, Anno edizione: 2014, ISBN: 978-84-344-0996-5
Di Giulio M. & VecchiG., Policy Making and the Digitalization of the Public Sector. Actors and Strategies in Italy, Editore: Palgrave MacMillan, Anno edizione: 2025, ISBN: 978-3-031-83954-2
Eugene Bardach & Eric M. Patashnik, A Practical Guide for Policy Analysis. The Eightfold Path to More Effective Problem Solving, Editore: Sage CoPress, Anno edizione: 2020, ISBN: 9781506368887
Note: Also previous editions are accepted

The course provides a broad overview of pollution phenomena in the different environmental compartments. The Course starts providing some basic concepts about environment, pollution, development and sustainable development. Then the Course introduce to the acquisition of pollution data through the analysis and characterization of water and wastewater that are necessary to understand pollution of water bodies (river and lakes), The Course describes the pollution phenomena of atmosphere at different scales (global, regional, local) and how to get measures of the emissions affecting air quality. Production and composition of wastes, as well as chemical-physical analyses to define their characteristics will also be considered. Soil and its physical, chemical and biological characteristics will introduce to extent and causes of soil contamination, with some hints on the mechanisms that affect soil-contaminant interaction.
Handouts of the Course will be available on the beep website: https://beep.metid.polimi.it

This course is dedicated to students with a thorough knowledge of energy issues and it aims at explaining the various technologies available for the production of electricity from renewable sources. The course deals with a topic of great interest and relevance, from the technical and engineering point of view: producing electricity from renewable sources is becoming increasingly important in a short-medium term scenario, characterized by the need to drastically reduce greenhouse gases and dependence on fossil fuels. The approach to topics is primarily theoretical, in order to understand the physical principles that are at the basis of operation of the different technologies. It also discusses some technological aspects more closely linked to the industrial manufacturing processes, together with the associated economic, strategic and environmental impact. The course will provide the students with the technical skills to operate in the field of power plants fed by renewable sources: from decision-making skills required in the design phase, to the technical knowledge related to the operation and maintenance of plants.

Knowledge and understanding:
The student is able to understand the physical working principle and main industrial manufacturing processes of a renewable technology.
The student is able to assess the potential energy production and costs of a renewable source.
The student is able to understand the energy and environmental balance of power plant plant based on a renewable source, taking into account its environmental impact and avoided emissions and energy saving in a LCA perspective.
The student is able to understand the part load operation of a renewable plant, and to evaluate the main performance indexes related to an annual operation.
Applying knowledge and understanding:
The student is able to make a preliminary design of a power plant based on a renewable source, assessing both its economic feasibility and environmental benefits, in terms of avoided emmissions and energy saving.
The student is able to correctly operate a renewable plant in terms of optimized schedule and forecasting, dispatching electricity and maintenance operations.
Making judgements:
The student is able to autonomously manage the design choices concerning the construction and operation of renewable source plants.
Communication skills:
The student is able to communicate the results of his / her activity in a clear and effective way.

Introduction and perspectives. The potential of renewable energy. Classification of sources and typical problems related to their exploitation for the production of electricity on an industrial scale. Adopted incentive schemes. Current situation and forecast scenarios.
Wind energy. Betz theory and laws of operation, types of machines, applications. Sizing criteria, plant regulation and characteristic curves. Coupling with the generator, power electronics for rotor speed control. Characterization of the wind resource of a site, analysis and profitability of a wind farm. Environmental impact of wind power installations. Off-shore wind farms. Small and micro-wind.
Geothermal energy. Classification of geothermal sources: liquid and vapor-dominated hydrothermal source, hot dry rocks. Exploration techniques and drilling. Adoptable power plants: direct steam cycle, plant with flash and separation of steam, binary ORC cycles. Cogeneration plants. Design aspects, issues related to geothermal fluids and environmental impact.
Energy from biomass. Classification of biomass and future potential. Conversion systems with grate boilers: water steam cycles and ORC. Flue gas treatment systems. Anaerobic digestion for biogas production. LCA analysis applied to the cycle of biomass.
Solar energy. Solar radiation: characteristic angles and the solar spectrum. Instruments for measuring radiation.
Photovoltaic solar energy: the photoelectric effect, processes for silicon production and photovoltaic cell manufacturing, electrical characteristic of the cell and circuit connection, inverter and power conditioning systems. Design criteria for off-grid and grid-connected plants. Thin-film and multi-junction cells, recent technological developments. Concentrating photovoltaic.
Concentrating solar power: classification of concentrating systems. Parabolic-trough collectors, parabolic dish systems, Fresnel collectors, central receiver systems (i.e solar tower). Thermal performance of a collector, selective coatings. Heat transfer fluids and thermal storage tanks. Sizing of a solar power plant. Operating strategy of a plant and estimation of the yearly production.
Energy from small-hydro plants. Classification of plants and hydraulic machines. Future potential of the resource. Design criteria of a run-of-river hydroelectric plant, regulation. Environmental impact.
Energy from the sea. Exploitation of thermal gradient of oceans (OTEC). Hints on energy from currents, wave, tidal
For the 5-CFU course, "Geothermal energy", "Energy from small-hydro-plants", "Energy from the sea" and "Energy from biomass" modules are excluded from the covered topics.

Prova scritta obbligatoria, senza prove in itinere
The course is organized in lectures and tutorials. Design of plants are also proposed on different technologies. The exercises are functional to the understanding of topics and to the preparation of the exam (the ability to solve the proposed exercises is a necessary but not sufficient condition for passing the exam).
The exam consists of two tests: a written test (duration 90 minutes) that is a practical test based on two numerical problems and a theoretical written test based on open-ended questions and mulitple choice questions (duration 60 minutes). The final mark will result as a weighted average between the practical (60%) and theoretical part (40%). The two tests can be carried out on two separates dates within the same Academic Year. To proceed to the theoretical exam an evaluation equal/above 16/30 for practical test is mandatory.
The two tests aims to ascertain the degree of understanding of the fundamental aspects of the course, from the theoretical working principle of the various renewable technologies, to the operating strategy of a plant in off-design conditions, the forecast of its annual energy output, the evaluation of the environmental balance and the economic assessment of an investment. In particular the written test will aim at evaluating student's ability in the calculation and preliminary design of renewable power plants, assessing the electricity production, economic feasibility and environmental benefits, in terms of avoided emissions and energy saving. The theoretical test will aim at evaluating the understanding of the physical concepts underlying design and operation characteristics specific to different technologies.
For the 5-CFU course, the exam has the same structure and the only difference resides in questions that will be limited to the topics covered.

G. Boyle, Renewable Energy, Editore: Oxford, Anno edizione: 2014
A. Da Rosa, Fundamentals of Renewable Energy Processes, Editore: Elsevier, Anno edizione: 2012, ISBN: 978-0-12-397219-4 http://www.sciencedirect.com/science/book/9780123972194
John F.Walker, Nicholas Jenkins, Wind energy technology, Editore: John Wiley & Sons
A. Luque, S. Hegedus, Handbook of Photovoltaic Science and Engineering, 2nd edition, Editore: Wiley
John A. Duffie, William A. Beckman, Solar Engineering of Thermal Processes, 4th Edition, ISBN: 978-0-470-87366-3
Ronald DiPippo, Geothermal Power Plants: principles, applications and case studies, Editore: Elsevier
Lorenzo Battisti, Gli impianti motori Eolici, Editore: Green place energies
Daniele Cocco, Chiara Palomba, Pierpaolo Puddu, Tecnologie delle energie rinnovabili
Andrea Bartolazzi, Le Energie Rinnovabili, Editore: Biblioteca tecnica Hoepli

Introduzione e prospettive. Il potenziale delle energie rinnovabili. Classificazione delle fonti e problematiche tipiche legate al loro sfruttamento per la produzione di energia elettrica su scala industriale. Sistemi di incentivazione adottati. Situazione attuale e scenari previsionali.
Energia eolica. Teoria di Betz e leggi di funzionamento, tipi di macchine, applicazioni. Criteri di dimensionamento, regolazione dell'impianto e curve caratteristiche. Accoppiamento con il generatore, elettronica di potenza per il controllo della velocità del rotore. Caratterizzazione della risorsa eolica di un sito, analisi e redditività di un parco eolico. Impatto ambientale degli impianti eolici. Parchi eolici offshore.
Energia geotermica. Classificazione delle sorgenti geotermiche: sorgenti idrotermali liquide e a vapore, hot dry rocks. Tecniche di esplorazione e perforazione. Centrali a vapore diretto, impianto con flash e separazione del vapore, cicli ORC binari. Impianti di cogenerazione. Aspetti progettuali, problematiche legate ai fluidi geotermici e all'impatto ambientale.
Energia da biomasse. Classificazione della biomassa e potenziale futuro. Sistemi di conversione con caldaie a griglia: cicli acqua vapore e ORC. Sistemi di trattamento fumi. Digestione anaerobica per la produzione di biogas.
Energia solare. Radiazione solare: angoli caratteristici e spettro solare. Strumenti per la misurazione della radiazione.
Energia solare fotovoltaica: l'effetto fotoelettrico, i processi per la produzione del silicio e la fabbricazione delle celle fotovoltaiche, le caratteristiche elettriche della cella e la connessione dei circuiti, gli inverter e gli impianti di condizionamento dell'energia. Criteri di progettazione per impianti off-grid e grid-connected. Celle a film sottile e multigiunzione, recenti sviluppi tecnologici. Fotovoltaico a concentrazione.

This subject aims to provide students with fundamental knowledge and practical skills for the acquisition, processing, integration, and validation of experimental data related to electric mobility systems, with particular attention to diagnostic applications.
The course is structured into three main chapters. The first chapter introduces the fundamentals of metrology and the three pillars of modern measurement science: measurement uncertainty, calibration, and metrological traceability.
The second chapter covers the fundamentals of sensing systems and transducers for the monitoring and diagnosis of electric vehicles and transportation systems. Particular attention is devoted to electrical, mechanical, and thermal measurements for the assessment of vehicle components and operating conditions.
The third chapter introduces estimation methods for the integration and interpretation of measurement data. It covers multi-sensor data integration, sensor fusion, and model-based estimation techniques aimed at improving the accuracy, reliability, and robustness of diagnostic information. Particular attention is devoted to the integration of experimental measurements with physical and mathematical models through data assimilation methods and Kalman filtering techniques.
Seminars delivered by professionals and experts working in the field will be organised during the course. Visits to industrial and research laboratories will also be arranged, subject to the availability of the hosting organisations.
The course meets the requirements of the Dublin Descriptors (DD), as detailed in the following sections.

At the end of the course, students will have acquired the knowledge and skills required to specify measurement systems for the monitoring and diagnosis of electric mobility systems and to evaluate their performance against the relevant measurement and system requirements (DD1, DD2).
Students will be able to identify and analyse the main requirements of a measurement problem, select appropriate sensors and transducers, and define a suitable measurement system architecture for electrical, mechanical, and thermal quantities (DD1, DD2).
Students will acquire fundamental knowledge of estimation methods for the processing and integration of measurement data. They will be able to describe and apply basic sensor fusion, model-based estimation, data assimilation, and Kalman filtering techniques for the assessment of system states and operating conditions (DD1, DD2).
Students will also be able to integrate experimental measurements with physical and mathematical models and critically evaluate the accuracy, reliability, and limitations of the resulting estimates and diagnostic information (DD2, DD3).
At the end of the course, students who have attended the laboratory activities will also have acquired practical skills in the acquisition and processing of measurement data, the evaluation of measurement uncertainty, and the calibration of simple measurement systems (DD1, DD2).

Fundamentals of metrology. This part of the course introduces the fundamental concepts of measurement science. It covers the definition of measurement models, the identification of the main sources of measurement uncertainty, and the methods used to evaluate and combine uncertainty contributions. Metrological traceability, calibration, and the interpretation of measurement results are also addressed. Particular attention is devoted to the reliability of decisions based on measurement data and to the influence of measurement uncertainty on such decisions.
Sensors and measurements for diagnostics. This part of the course covers the operating principles and main characteristics of sensors and transducers used for the monitoring and diagnosis of electric mobility systems. Particular attention is devoted to electrical, mechanical, and thermal measurements, including the selection of suitable sensors, their static and dynamic characteristics, sensitivity, accuracy, bandwidth, and sources of uncertainty. Measurement system architectures for the acquisition and processing of diagnostic data are also introduced.
Estimation and sensor fusion. This part of the course introduces methods for estimating physical quantities and system states from experimental measurements. It covers the integration of data provided by multiple and heterogeneous sensors, sensor fusion techniques, and the use of virtual sensors. Basic concepts of state-space modelling, model-based estimation, and Kalman filtering are presented.
Physical models and data assimilation. This part of the course addresses the integration of measurement data with physical and mathematical models. Data assimilation techniques are introduced as tools for updating model predictions using experimental observations. Particular attention is devoted to the assessment of estimation accuracy, robustness, and sensitivity to measurement and model uncertainties.

Prova orale obbligatoria
The final test consists of an oral test during which the students will discuss a point of the main topics listed above. The goal of this discussion is to verify whether the student has understood the fundamentals of the above points and can apply them to a simple case (DD1 and DD2).

Note monografiche del corso
Note: disponibili dal sito WeBeep del corso

The course fits into the overall program curriculum and in particular it contributes to the development of the following capabilities:
Understand context, functions, processes in a business and industrial environment under the life cycle thinking perspective, and the impact of those factors on business performance towards the entire product life cycle
Identify trends, technologies and key methodologies in the domain of product life cycle management, within a pletora of different application contexts such as industrial design and engineering, mechanics and automation, fashion and food industry
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in business and industrial environments
The aim of the course is to introduce students to the basic concepts of Product Lifecycle Management (PLM) and Life Cycle Thinking. The acronym PLM enables a holistic life cycle-oriented way of thinking through a set of principles, methods and tools supporting a more effective and efficient management of the life cycle stages of industrial products and systems, from their design/engineering, to production, distribution, usage until disposal/end of life.
In its comprehensive meaning, PLM is a business approach based on collaboration and integration of people, processes and technologies, which aims to support the development of more innovative, reliable and sustainable solutions (products and services) in a shorter time.
From a managerial perspective PLM encompass (i) a strategic management point of view where the product is the enterprise value creator; (ii) the application of a collaborative model for the empowerment of the core competences distributed along the different actors involved in the lifecycle (e.g. designers, engineers, manufacturers, suppliers, etc.); (iii) the adoption of a number of IT solutions for establishing an access-safe product information management environment.
From a technical perspective, PLM is a matter of methods, standards and techniques for structuring the engineering processes, as well as a matter of computer-based tools for enabling virtual prototyping and collaborative workspaces.
In this context, Lean Product and Process Development is a paramount support for the effective understanding and accomplishment of the above mentioned points and will play an important role, not only as topic of discussion taught within the course, but also used to generate within the students critical attitude towards problem understanding, problem setting and problem solving.
The aim of the PLM course is to introduce students to the concepts and elements of PLM, life cycle thinking and lean product and process development, from both managerial and a technical perspective, giving also the basics to run the introduction of PLM (as approach, models, methods, and tools) in the industrial practice, approach problems and process improvement via lean thinking, with the ultimate purpose to grow a life cycle thinking attitude into the students.

Expected results from Product Life Cycle Management Class are:
Understand - provide students with the prevalent knowledge in the field of PLM and Life Cycle Thinking from a theoretical and practical side to show how these aspects reflects on real business. The students are expected to gain general knowledge on PLM, life cycle thinking and all related topics.
Identify - students, will gain general knowledge needed to understand PLM, and will be provided with specific knowledge on trends and approaches existing in effective and advanced PLM impelmentation solutions from industry, such as lean product and process development. Students will be expected to be able to identify how specific approaches enable and impact life cycle thinking within enterprises. In the specific lean product and process development as a overall and growing body of knwoledge will be taught to the class that is expected to acquire deep knowledge on that.
Design - most importantly, students will be provided with the ability to aquire and develop a critical thinking attitude in business process understanding and problem solving. This will be achieved through a continuous link between in class theoretical applications and real world applications, as well as challenges proposed to students to be addressed in class via exercises, serious games, projects and teamwork activities. The ultimate purpose is to make this class not as the arrival learning point for these concepts, but to be the starting platform to build and link what has already been learned and what needs to be learned in the future to address growing buiness needs-by applying either what has been introduced in this course or learnt soemwherelse- enable a relentless life cycle thinking mindest.

Course topics include:
-Life C ycle T hinking, P roduct L ife C ycle M anagement, P roduct L ife C ycle phases
-Innovation, New Product Development Process and Concurrent Engineering
-Lean Product and Process Development
-Set-Based Concurrent Engineering (SBCE)
-The Front-End Process
-Design Methods (Design for X: Design for Manufacturing and Design for Environment)
-Value and Function Analyses (QFD & VA/VE)
-Prototyping, Examples from Virtual Prototyping and CAD tools
-Process Mapping and mapping application case
-Collaborative Platforms (PDM & PLM)
-PLM system and PLM system implementation
-PLM Projects Evaluation. Application case s
-Introduction to S ustainable P roduct D evelopment and C ircular E conomy

Prova scritta obbligatoria, senza prove in itinere
Progetto/i - Elaborato/i facoltativo (a scelta dello studente), di gruppo, senza revisioni periodiche, con presentazione/discussione finale
Class attendance is not mandatory, though encouraged. All material will be provided digitally on line (Beep). Supporting books and references will also be suggested throughout the course. In-class exercises and teamwork will be used to facilitate advanced learning of PLM material and concepts.
The final exam will be a bout 1,5 hour written test, divided in two part: theory and problems/exercises. Questions are mainly multiple-choice questions + some short open questions. The maximum score achievable through the written exam is 30 Laude.
There are not intermediary evaluations.
Complementing the learning activities, a not-mandatory team project can be conducted to go through some of the topics investigated in class with the purpose of enhance the overall topics understanding, determining an indirect improvement of learning and exam performances. Additionally, the project enables students to gain extra score, at a maximum of 3. Time will be dedicated in class for project and practical activities. The project score does not expire through the months/years. It is not possible to run the project individually.