Objectives

Video descirption: https://www.youtube.com/watch?v=53IJEsF7rCw

We live in an increasingly digital economy. Information technology (IT) has transformed a large number of markets and advances in Artificial Intelligence will likely further lead to important changes throughout the value chain of individual firms and across a variety of sectors.

The course Strategy in Digital Markets introduces students to some of the fundamental concepts, and strategic challenges and opportunities of digitization. We will explore how digital technologies shape markets and corporate strategy.

We discuss organizational issues, such as whether firms should rely on inhouse IT or source these capabilities from the market. A central part of the course relates to pricing strategies and business models. Most prominently, we will discuss platform strategy from the perspective of entry, openness, and competition. We then focus on data as a strategic resource and the organization and market strategy of Machine Learning (ML) applications. Lastly, we discuss the role of governments in regulating digital markets and the strategic responses firms can take.

The overarching aim is to prepare students for careers in industry/consulting and/or dissertations in this field.

This is a Project-Based-Learning course. Each week we have a section on theory, and a section on empirical evidence. Learning is aided by three types of interactions:

1. Theoretical input videos

2. Flipped classroom and discussion of theoretical material

3. Discussion of research papers

Contents

See complete Syllabus: Link

References

See complete Syllabus: Link

Pre-requisites

Econometrics, Competitive Strategy (it helps, but not mandatory)

Evaluation

First attempt

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Evaluation for Master students

Class participation

You are expected to contribute to the discussion in class. Your active contribution is essential for the quality of class discussion. In my experience class is more interesting for everyone when everyone participates. To be prepared for class, you need to watch and read the material, i.e. videos and research papers for that day before class. I will sometimes cold call and sometimes not call on those who are volunteering to encourage the right climate. If you are not prepared for a particular class, please let me know at the beginning of class. Things happen, and I don’t need to know the reason, but I prefer not to embarrass you by exposing you as unprepared.

To make sure that everybody has the right incentives to prepare for class, there is a weekly assignment to be prepared individually, and a group assignment with presentations. The course closes with an open book final exam.

Weekly assignments (25%)

Following along all semester will be crucial for learning success. However, I do understand that some weeks are busier than others. Therefore you can choose 10 out of 12 papers to read and answer questions about. This will be in the form of online quizzes that you complete before class. The quizzes will be such that it is not necessary to read and digest the paper in full detail (this is what the group assignment is for), but I expect that you carefully read the introduction, discussion and conclusion sections. If you cannot answer a question based on that alone, you can always go back to the paper and read more details.

Essay (50%)

For two research papers, you will need to write a reaction paper. This means that you will write a detailed discussion of the research paper, relating to the concepts discussed in class and beyond. Detailed instructions and an example reaction paper will be provided. You can choose which two papers you want to react on, but you must have submitted two reports before week 14.

Final exam (25%)

The final exam will be open book. This is an individual effort over 60 minutes and involves a discussion of a case study using the theoretical concepts we have learned in class. The date will be announced.

Evaluation for PhD students

This course is open to PhD students. PhD students are strongly encouraged to actively participate in class, follow along all semester and read the assigned papers and case studies before each class.

There are two types of graded assignments.

Active contributions (25%)

PhD students are expected to actively contribute in the discussion of research papers (Friday sessions). Every week, I expect every student to pose at least one question / provide a discussion point. This needs to be done during class and by posting a question / discussion point on the discussion board on Moodle before class. The questions on the Moodle discussion board can be narrowly related to the week’s research paper (e.g. regarding methodology) or broadly related to the overall topic discussed in the week.

Reaction paper (25%)

For one research paper, you will need to write a reaction paper. This means that you will write a detailed discussion of the research paper, relating to the concepts discussed in class and beyond. Detailed instructions and an example reaction paper will be provided. You can choose which paper you want to react on, but you must have submitted your reports before week 14.

Research proposal (50%)

Your second assignment is a research proposal of 15 pages, double-spaced, due four weeks after the last class. This research proposal should be deeply rooted in the literature that we have discussed in class (i.e. beyond the specific papers that we have discussed). Students need to develop hypotheses, describe (anticipated) methods, potentially provide some preliminary findings, and discuss the contribution to the literature and implications for managers/policy.

Retake

Exam:

Written 1h00 hours

Documentation:

Allowed

Calculator:

Allowed

Evaluation:

Examen intégratif valant 100% de la note