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Prüfer, Jens 
ORCID: https://orcid.org/0000-0001-7203-9711 and Schottmüller, Christoph
(2021)
Competing with Big Data.
Journal of Industrial Economics, 69 (4).
pp. 967-1008.
ISSN 0022-1821
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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.
| Item Type: | Article |
|---|---|
| Additional Information: | First published online: 02 February 2022 |
| Uncontrolled Keywords: | accounting,business, management and accounting(all),economics and econometrics ,/dk/atira/pure/subjectarea/asjc/1400/1402 |
| Faculty \ School: | Faculty of Social Sciences > School of Economics |
| UEA Research Groups: | Faculty of Social Sciences > Research Centres > Centre for Competition Policy Faculty of Social Sciences > Research Groups > Economic Theory Faculty of Social Sciences > Research Groups > Industrial Economics |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 12 Sep 2022 10:31 |
| Last Modified: | 21 Oct 2023 00:42 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/88106 |
| DOI: | 10.1111/joie.12259 |
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