New Out-of-semester Course: Big Data Economics: Competition, Innovation and Growth

Dear Students,

We are pleased to offer you the opportunity to enrol in the following attractive elective course during the current summer semester. This course is designed to enrich your economic knowledge, enhance your language skills, and broaden your perspective beyond the scope of your standard curriculum. Upon successful completion, you will receive 3 ECTS credits.

This course is classified as an oV elective. (Course 5EN383 can be recognized as an equivalent to 5EN381/382.)

Out-of-semester Course – 5EN383: Big Data Economics: Competition, Innovation, and Growth

Instructor:
Orlando Gomes, Full Professor of Economics at the Lisbon Accounting and Business School, Polytechnic University of Lisbon (ISCAL-IPL).

Schedule:

  • June 9, 2025: 9:00–12:00, 14:00–17:00

  • June 10, 2025: 9:00–12:00, 14:00–17:00

  • June 11, 2025: 9:00–12:00, 14:00–17:00

Location: NB 457

Final Exam: June 13, 2025: 10:00–12:00, NB 457

Language of Instruction: English

You can register for the course now in the “Out-of-semester Courses” section. Registration is open until May 23, 2025, and capacity is limited to 20 students.

Course and Instructor Description:

Impressive technological developments, innovative business models, and increasingly sophisticated consumer preferences have shaped a new economic landscape, where success hinges on access to large volumes of data and the tools to process it—as exemplified by major tech companies. This emerging paradigm calls for a fresh perspective on t

he organization and performance of firms, industries, and markets.

This course offers a comprehensive analysis of the economics of data, drawing on the existing literature and a series of small-scale dynamic models aimed at explaining the choices, behavior, and interactions of economic agents in the data-driven economy.

The course begins by defining big data and explaining its significance for firms. It then explores how the data economy fosters market

power and reshapes business operations, labor relations, and consumer behavior. A key component of this transformation is artificial intelligence (AI), which is inextricably linked to data—data serves as the “fuel” for the AI engine.

Subsequent topics include data vulnerability and privacy, which are central to contemporary debates on the digital economy. The course also investigates big data as a driver of economic growth, addressing questions such as: How does data alter the traditional growth paradigm based on labor and capital accumulation? How is data connected to innovation, ideas, and knowledge?

These topics are approached through two main methods:

  1. A critical review of cutting-edge research on data, AI, and related issues, offering students a rigorous and comprehensive understanding of big data economics.

  2. The development of original analytical models using standard tools of dynamic economic analysis, aimed at illustrating agent behavior and interactions in the data economy, and how data contributes to enhanced outcomes—such as increased firm profitability, improved household welfare, and sustainable economic growth.