Competing with Big Data
Jens Prüfer () and
No 2017-007, Discussion Paper from Tilburg University, Center for Economic Research
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.
Keywords: big data; datafication; data-driven indirect network effects; dynamic competition; regulation (search for similar items in EconPapers)
JEL-codes: D43 D92 L13 L43 L86 (search for similar items in EconPapers)
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Working Paper: Competing with Big Data (2017)
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