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Competing with Big Data

Author

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  • Prüfer, Jens

    (Tilburg University, School of Economics and Management)

  • Schottmuller, C.

    (Tilburg University, School of Economics and Management)

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.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Prüfer, Jens & Schottmuller, C., 2017. "Competing with Big Data," Other publications TiSEM b09cad5c-e6eb-4fe7-9184-f, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:b09cad5c-e6eb-4fe7-9184-fd52eaabf9e2
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    References listed on IDEAS

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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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