96872 - REGULATION OF DIGITAL MARKETS

Learning outcomes

At the end of the module, students: - have an understanding of types of intellectual property rights, innovation and market failures, private and social value of innovations, and models of R&D investment, and are familiar with the economic policy debate undergirding the reinforcement or weakening of intellectual property; - know how to analyze the drivers of companies’ strategic choices concerning innovation protection.

Course contents

Indicative areas covered include:

1) The first block will introduce the basic concepts, theories and principles of regulation, with particular reference to the regulatory strategies and challenges posed to policy and law makers by innovation and technologies.

2) The second block aims at providing an understanding of the impact of new technologies on markets and their regulation. In particular, it will explore the opportunities and the risks presented by digital technologies in various markets and their ensuing regulation. A pervasive feature of digital technologies is the use of personal data: Therefore, the module will study the latest generation of data protection laws presented by the General Data Protection Regulation, showcasing comparative perspective with models offered in other jurisdictions (e.g. the US).

Indicative content

- Introduction
- The Law and the Digital Single Market
- The Single European Data Space
- Data Law: Data Ownership or Control?
- Privacy and Data Protection
- The GDPR
- EU data protection and the relationship between the EU and third countries
- The Digital Markets Act
- The Digital Services Act
- Intellectual Property and digital markets
- Case studies

Readings/Bibliography

• Federico Ferretti, Allegra Canepa, Francesca Mattassoglio, EU Digital Markets Law, Kluwer Law International (2025)

Teaching methods

Lectures, seminars, group readings, class and/or individual presentations

Assessment methods

For those who attend at least 70% of the classes, the assessment of this course will be:


- 50% by performance in class (intermediary test); and
- 50% by submission of a written research project (coursework) of up to 3.000 words in length (excluding bibliography and/or bibliographical references in the footnotes) on a topic released in the last teaching week. The coursework shall be submitted in WORD format (for the check of the number of words and plagiarism, including the use of chatbots) via email to f.ferretti@unibo.it by the exam date at the stated time. Coursework will not be accepted after that time and date! Equally, coursework will not be accepted for failure to register for the exam; and
- compulsory group presentation (pass/fail). Failure to contribute to the presentation and a poor presentation equal to a fail.


All students are entitled to refuse the partial or overall mark given, or may fail. In these cases they may resubmit for assessment on the basis of 100% submission of a given written research project (coursework) in the following exam session. All submissions shall be of a length between min. 8.000 words and max 10.000 words (excluding bibliography and/or bibliographical references in the footnotes) on a question released on the virtual learning environment 3-4 weeks before the exam date. The coursework shall be submitted in WORD format (for the check of the number of words and plagiarism, including the use of chatbots) via email to f.ferretti@unibo.it by the exam date at the stated time. Coursework will not be accepted after that time and date! Equally, coursework will not be accepted for failure to register for the exam.


For those who do not attend, the assessment on this course will be 100% by submission of a written research project (coursework) of a length between min. 8.000 and max 10.000 words (excluding bibliography and/or bibliographical references in the footnotes) on a question released on the virtual learning environment 3-4 weeks before the exam date. The coursework shall be submitted in WORD format (for the check of the number of words and plagiarism, including chatbots) via email to f.ferretti@unibo.it by the exam date at the stated time. Coursework will not be accepted after that time and date! Equally, coursework will not be accepted for failure to register for the exam.

 

The use of Artificial Intelligence is strictly forbidden.

 

Mark descriptors:

• <18 insufficient - not pass

• 18-23 pass, sufficient

• 24-27 pass, good

• 28-30 pass, very good

• 30 cum laude pass, excellent

Teaching tools

PowerPoint, informative/reading material

Office hours

See the website of Federico Ferretti