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Data Brokers Co-Opetition

Yiquan Gu, Leonardo Madio () and Carlo Reggiani ()

No 7523, CESifo Working Paper Series from CESifo

Abstract: Data brokers share consumer data with rivals and, at the same time, compete with them for selling. We propose a “co-opetition” game of data brokers and characterise their optimal strategies. When data are “sub-additive” with the merged value net of 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 individual datasets, competition emerges more often. Finally, data sharing is more likely when data 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)
Date: 2019
New Economics Papers: this item is included in nep-com, nep-ind and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed

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Working Paper: Data Brokers Co-Opetition (2021) Downloads
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