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2021/2022  KAN-CCMVV2423U  Digital Markets & Strategy

English Title
Digital Markets & Strategy

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 80
Study board
Study Board for MSc in Economics and Business Administration
Course coordinator
  • Paul Hünermund - Department of Strategy and Innovation (SI)
Main academic disciplines
  • Innovation
  • Strategy
  • Economics
Teaching methods
  • Face-to-face teaching
Last updated on 20-05-2021

Relevant links

Learning objectives
At the end of the course students should be able to:
  • Understand how digital markets work
  • Pinpoint the differences between digital markets and traditional, mainly offline markets
  • Formulate profitable business strategies in digital markets
  • Discuss the platform business model of companies such as Google, Amazon, Facebook, Apple, AliBaba, Booking, etc.
  • Recognize crucial economic principles governing the platform economy such as network effects and multi-sidedness
  • Understand real-world cases and policy questions that stakeholders (including companies, policy makers, and economic consulting firms like Copenhagen Economics) are dealing with at the moment in the area of digital markets
  • Discuss the role of competition authorities and antitrust in the digital age
  • Put into perspective the current policy discussions around digital markets (e.g., related to market dominance, mergers and acquisitions, and data security) at the European level
Examination
Digital Markets & Strategy:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Case based assignment
Duration 2 weeks to prepare
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

The ongoing digitalization of the economy is affecting business models and changing the nature of competition in fundamental ways. Because of their multi-sidedness, network effects, and heavy dependence on technologies such as machine learning and AI, digital markets often work quite differently from traditional, mostly offline markets. This poses new important challenges for managers who are faced with the problem of digital disruption as well as for policy makers and enforcers across the globe who have to police these new competitive dynamics taming the new monopolistic power of Big Tech firms. This course will provide students with fresh perspectives and analytical frameworks to better understand these ongoing developments in the digital sphere. Topics that will be discussed throughout the course relate to, among others: platform-based business models, innovation eco-systems, envelopment strategies, recommender systems, advertising, data and algorithms as a strategic resource, as well as current policy discussions around data privacy, artificial intelligence, and the potential abuse of market dominance in the tech sector.

 

The course has an applied nature, combining business strategy and economic theory to discuss practical cases and policy developments, which are shaping the way digital markets will work in Europe and globally going forward. It is envisaged for both business and economics students with an interest in digital markets. As a business student you will learn how to develop different value-creating strategies in digital markets, how they may be constrained by competition policy and what the main topics on the current agenda of European policy makers are. As an economics student you will have the opportunity to see economic theory at work in digital markets and to understand the building blocks of current policy discussions at the European level and antitrust cases involving big tech. In this way the course provides students with a solid toolbox and broad knowledge that is used by both strategy teams at tech firms and big corporates, policy makers and advisors.

 

Classes will be offered in collaboration with Copenhagen Economics – one of Europe’s leading economic consulting firms. This cooperation creates the opportunity to offer a more practical perspective on some of the theoretical topics and to draw from real-life cases in the area of digital competition.

Description of the teaching methods
Teaching is based on in-class lectures and case discussions, including external speakers from the industry (depending on availability).
Feedback during the teaching period
Students will receive continuous feedback on case discussions in class. Furthermore, the course will contain a group-based case exercise, which students will receive individualized feedback on.
Student workload
Teaching 36 hours
Preparation 130 hours
Exam 40 hours
Expected literature
  • Agrawal, A. J., Gans, J. S., and Goldfarb, A. (2018). Economic Policy for Artificial Intelligence. NBER Working Paper 24690.

  • OECD (2017). Algorithms and Collusion: Competition Policy in the Digital Age www.oecd.org/​competition/​algorithms-collusion-competition-policy-in-the-digital-age.htm

  • Zhu, F. and Q. Liu (2018). Competing with complementors: An empirical look at amazon.com. Strategic Management Journal 39 (10), 2618-2642.

  • Van Alstyne M, Parker J, Choudary S (2016) Pipelines, platforms, and the new rules of strategy. Harvard Business Rev. (April) 94(4): 54–62.

  • Tucker, C., 2019. Digital data, platforms and the usual [antitrust] suspects: Network effects, switching costs, essential facility. Review of Industrial Organization, 54(4), pp.683-694.

  • Scott Morton F., Bouvier P. Ezrachi A., Jullien B., Katz R., Kimmelman G. Melamed D. & Morgenstern J., Report of the Committee for the Study of Digital Platforms, Market Structure and Antitrust Committee, Chicago Booth Stigler Center.

  • Panico C., and Cennamo C. 2020. User preferences and strategic interactions in platform ecosystems. Strategic Management Journal, https:/​/​doi.org/​10.1002/​smj.3149.

  • Lee, Robin S. 2013. "Vertical Integration and Exclusivity in Platform and Two-Sided Markets." American Economic Review, 103 (7): 2960-3000.

  • Jones C., Tonetti C. 2020. Nonrivalry and the economics of data. American Economic Review, 110 (9): 2819-58. 

  • Hagiu, A. and J. Wright 2015. Multi-sided platforms. International Journal of Industrial Organization 43, 162-174.

  • Hagiu, A. and Wright, J., 2020b. When data creates competitive advantage. Harvard Business Review, 98(1), pp.94-101.

  • Eisenmann T, Parker G, Van Alstyne, M. 2011. Platform envelopment. Strategic Management Journal 32(12): 1270-1285.

  • De Corniere A., Taylor G. 2020. A model of biased intermediation. RAND Journal of Economics, vol. 50: 854-882.  

  • Cennamo C. 2019. Competing in digital markets: A platform-based perspective. Academy of Management Perspectives. https:/​/​doi.org/​10.5465/​amp.2016.0048

  • Cennamo, C., & Santalo, J. (2013). Platform competition: Strategic trade-offs in platform markets. Strategic Management Journal, 34(11). https:/​/​doi.org/​10.1002/​smj.2066

  • Cennamo, C., & Santaló, J. (2015). How to avoid platform traps. MIT Sloan Management Review, 57(1).

Last updated on 20-05-2021