Competing with Big Data

Jens Prüfer, C. Schottmuller

Research output: Working paperDiscussion paperOther research output

1307 Downloads (Pure)


This paper studies competition in data-driven markets, that is, markets where the cost of quality production is decreasing in the amount of machine-generated data about user preferences or characteristics, which is an inseparable byproduct of using services offered in such markets. This gives rise to data-driven indirect network effects. We construct a dynamic model of R&D competition, where duopolists repeatedly determine their innovation investments, and show that such markets tip under very mild conditions, moving towards monopoly. In a tipped market, innovation incentives both for the dominant firm and for competitors are small. We also show under which conditions a dominant firm in one market can leverage its position to a connected market, thereby initiating a domino effect. We show that market tipping can be avoided if competitors share their user information.
Original languageEnglish
Place of PublicationTilburg
PublisherCentER, Center for Economic Research
Number of pages50
Publication statusPublished - 15 Feb 2017

Publication series

NameCentER Discussion Paper


  • big data
  • datafication
  • data-driven indirect network effects
  • dynamic competition
  • regulation


Dive into the research topics of 'Competing with Big Data'. Together they form a unique fingerprint.

Cite this