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Competing with Big Data

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  • Jens Prüfer
  • Christoph Schottmüller

Abstract

We study competition in data‐driven markets, where the cost of quality production decreases in the amount of machine‐generated data about user preferences or characteristics. This gives rise to data‐driven indirect network effects. We construct a dynamic model of R&D competition, where duopolists repeatedly determine innovation investments. Such markets tip under very mild conditions, moving towards monopoly. After tipping, innovation incentives both for the dominant firm and the competitor are small. We show when a dominant firm can leverage its dominance to a connected market, thereby initiating a domino effect. Market tipping can be avoided if competitors share their user information.

Suggested Citation

  • Jens Prüfer & Christoph Schottmüller, 2021. "Competing with Big Data," Journal of Industrial Economics, Wiley Blackwell, vol. 69(4), pages 967-1008, December.
    • Handle: RePEc:bla:jindec:v:69:y:2021:i:4:p:967-1008
    DOI: 10.1111/joie.12259
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    More about this item

    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L43 - Industrial Organization - - Antitrust Issues and Policies - - - Legal Monopolies and Regulation or Deregulation
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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