Data Brokers Co-Opetition

Yiquan Gu, Leonardo Madio () and Carlo Reggiani

No 202101, Working Papers from University of Liverpool, Department of Economics

Abstract: Data brokers share consumer data with rivals and, at the same time, compete withthem for selling. We propose a “co-opetition” game of data brokers and characterisetheir optimal strategies. When data are “sub-additive” with the merged value netof the merging cost being lower than the sum of the values of individual datasets,data brokers are more likely to share their data and sell them jointly. When data are“super-additive”, with the merged value being greater than the sum of the individualdatasets, competition emerges more often. Finally, data sharing is more likely whendata brokers are more efficient at merging datasets than data buyers.

Keywords: data brokers; consumer information; co-opetition; data sharing (search for similar items in EconPapers)
JEL-codes: D43 L13 L86 M31 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2021-01
New Economics Papers: this item is included in nep-com, nep-gth, nep-ind and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Forthcoming

Downloads: (external link)
https://www.liverpool.ac.uk/media/livacuk/schoolof ... kers,CoOpetition.pdf First version, 2021 (application/pdf)

Related works:
Journal Article: Data brokers co-opetition (2022)
Working Paper: Data Brokers Co-Opetition (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:liv:livedp:202101

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