University of Commerce Luigi Bocconi

The course uses experiential learning to develop the skills most critical to success in today's business landscape: designing and planning innovative business models. The course offers an industry focus on fashion, luxury, and retail, and integrates key topics such as sustainability and digitalization. This course explores how to design innovative business models with the support of a proprietary simulation software that allows to develop a practical approach integrating creative ideas with competitive and financial dimensions. Students can see the immediate consequences of their decisions and learn what it’s truly like to juggle competing priorities amidst a constant influx of information provided by the professors. The learning process is enhanced by the collaboration of external guest speakers and a start-up accelerator.

This course analyzes advanced management practices in complex business environments and offers a comprehensive introduction to Lean Management, a model derived from the diffusion of the principles and tools originally developed at the Toyota Motor Company. The course emphasizes the organizational, managerial, and human aspects of Lean Thinking and illustrates its adoption in a variety of industries and business functions. It analyzes how firms should design and implement lean systems and offers a framework to undertake and sustain lean transformations. It illustrates how the adoption of Lean Thinking principles and tools affect managerial decision making and problem solving, eliminating waste and variability. It also elaborates on recent trends such as the application of lean thinking to innovation (Lean Product and Process Development), to entrepreneurship (Lean Startup Method), to sustainability (Lean & Green), as well as its connection to the Agile movement.

This course provides an advanced understanding of the python programming language and its main features through various applications in many fields. Students use procedural and object-oriented programming language concepts in real programs; combine programming techniques to solve problems of varying degrees of difficulty in applied fields; find and understand programming language documentation to learn new information needed to solve programming problems; and implement problem solving strategies. Course topics include input/output in Python, classes, databases management with Python, computer simulations, and agent-based modeling. Prerequisites: an introductory course on python programming or similar language (e.g. Java, C, etc.).

Public institutions and non-profit organizations play a fundamental role in today's economic systems as policy designers, public service-providers, grant-makers, and advocates of unmet ever-changing human needs. As their goals are different from those pursued by business companies, managers working in these organizations perform different tasks, follow different logic and must develop different skills. At the end of this course students understand these differences, are able to assess how successful public/nonprofit managers behave, are aware about which mistakes to avoid, and apply this learning to perform basic tasks connected to the overall creation of public value that public/non-profit organizations produce for their communities. The course is divided into 2 parts. Part 1: Public policy and public management (governments and their structure; role of bureaucracies; types of bureaucrats and how to motivate them; decision-making and performance evaluation in public agencies). Part 2: Non-profit management (role of the third sector in the economy; types of non-profit organizations: an overview; governance and management of non-profit organizations; how to secure contributed income: key successful factors in fundraising).

This course provides: (i) a working knowledge of the most important aspects of the linear regression model; and (ii) basic tools needed to understand and critically interpret empirical research conducted by others as well as to plan and conduct empirical analyses using economic data. The key concepts of the underlying statistical theory are covered, but major emphasis is placed on application of the theory from a practical standpoint. The course also provides an introduction on how to conduct empirical analysis of economic data using Stata, a statistical software package. Prerequisites: Sound knowledge of mathematics and statistics.

This course aims at providing the basic theoretical and applied tools for a rigorous statistical analysis. Specifically, the course focuses on techniques to summarize and visualize data of different types and their possible relations, as well as on basic sampling and inferential procedures, and on the assessment of the risk associated to extrapolation and inference. In particular, students learn how to extract information from data and how to assess the reliability of such information. The course covers the following topics: collection, management, and summary of data using frequency distributions, graphical representations, and summaries; study of the relationship between two variables; statistical inference and sampling variability; theory of point estimation and confidence intervals; hypothesis testing; and simple and multiple regression models. All the descriptive and inferential tools introduced during the course are applied to data using the statistical software R - and in particular the integrated development environment (IDE) RStudio. Prerequisites: understanding of the concepts of probability theory and random variables.

This course is an introduction to labor economics. The course objective is to understand how labor markets operate and how they are affected by institutions and labor market policies. Both empirical evidence and standard theory are covered. The course highlights the effects on efficiency and the redistributive properties of institutions operating in imperfect labor markets, subject to market failures. This provides three reasons for the existence of institutions: i) remedying market failures, ii) achieving some redistribution, and iii) remedying potential negative side effects of other institutions. The course consists of 14 key lectures. The first lecture set up the stage by introducing workers’ labor supply, firms' labor demand, the labor market equilibrium and the institutional wedges. Lecture 2 through 14 deal with specific institutions and have the same setup: a description of the institution, some cross-country comparisons, theory in perfect and imperfect labor markets, empirical evidence on the effects of this institution, interactions with other institutions, and policy issues. The four lecture topics are: overview; minimum wages; unions and collective bargaining; antidiscrimination legislation; regulation of working hours; early retirement plans; family policies; education and training; migration policies; employment protection legislation; regulations on self-employment; unemployment benefits and active labor market policies; health related labor policies; and payroll taxes.

The course develops students’ skills in understanding, analyzing, and interpreting financial statements. Conceptually, the course emphasizes that producers and users of financial statements have different objectives and informational needs. At the same time, the course is applied in that it teaches students how to analyze actual financial statements data to make informed business decisions and assessments. The course is designed to broaden and deepen students’ conceptual and technical understanding of accounting as it is used for management purposes. The emphasis in the course is on financial controls, which provides the dominant form of control in the vast majority of decentralized organizations. This module provides support in business decisions, evaluation of organizational performance, or in evaluation of others (and/or be evaluated) through the use of financial and non-financial information. Course topics include understanding financial statements; fundamental analysis; growth strategy and financial tensions: the logic behind target setting; market based measures, ESG, and integrated reporting; management and control; financial responsibility; incentive systems; remedy to the myopia problem; and uncontrollable factors.

The aim of the course is twofold. First, the course provides a toolkit to identify, model, and reason through strategic interactions (such as business strategies, negotiations, etc.) and discusses how to apply this toolkit when designing strategic environments (such as auctions, competitions, teamwork, etc.). Second, and in the interdisciplinary spirit of the program, the course illustrates the ability of mathematics in modeling, analyzing, and understanding real-world social as well as business interactions. Course topics include: what is Game Theory, static and multistage games of complete and incomplete information, signaling and repeated games, mechanism design, Bayesian and dominant-strategy incentive compatibility, efficient mechanisms, auctions, and applications of the theory. Prerequisites: Ability to complete rigorous mathematical proofs.

This provides students with an understanding of the nature and structure of the disclosures that an acquirer must make when proposing a merger with a target. Particular attention is paid to data that is useful for valuation purposes when trying to appraise a target with a view to developing a target identification methodology. Course topics include the anatomy of a typical merger – mini case study; overview of Mergers Analysis – methods to identify prospective targets using financial statements; brief outline of US and European financial reporting requirements; required filings to raising finance to publicly fund transactions; obtaining a purchase price and creating a Pro Forma Valuation; special topic on fair values, goodwill, and intangibles valuation; applied examples; constructing projections including accretion and dilution; and ex-post analysis of deals. Prerequisites for the course: introductory level accounting.