Data brokers co-opetition

The impact of big data on firm performance: an empirical investigation

Yiquan Gu, Leonardo Madio and Carlo Reggiani

Oxford Economic Papers, 2022, vol. 74, issue 3, 820-839

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 characterize 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.

JEL-codes: D43 L13 L86 M31 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Data Brokers Co-Opetition (2021)
Working Paper: Data Brokers Co-Opetition (2019)
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