Data Brokers Co-opetition

30 Pages Posted: 10 Jan 2019 Last revised: 12 Jul 2021

See all articles by Yiquan Gu

Yiquan Gu

Henley Business School

Leonardo Madio

University of Padua - Department of Economics and Management; CESifo (Center for Economic Studies and Ifo Institute)

Carlo Reggiani

The University of Manchester

Date Written: July 12, 2021

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, personal information, privacy, co-opetition, data

JEL Classification: D43, L13, L86, M31

Suggested Citation

Gu, Yiquan and Madio, Leonardo and Reggiani, Carlo, Data Brokers Co-opetition (July 12, 2021). Available at SSRN: https://ssrn.com/abstract=3308384 or http://dx.doi.org/10.2139/ssrn.3308384

Yiquan Gu

Henley Business School ( email )

University of Reading
Whiteknights
Reading, Reading RG6 6UD
United Kingdom

Leonardo Madio (Contact Author)

University of Padua - Department of Economics and Management ( email )

Via del Santo, 33
Padova, 35123
Italy

HOME PAGE: http://www.leonardomadio.eu

CESifo (Center for Economic Studies and Ifo Institute) ( email )

Poschinger Str. 5
Munich, DE-81679
Germany

Carlo Reggiani

The University of Manchester ( email )

Oxford Road
Manchester, N/A M13 9PL
United Kingdom

HOME PAGE: http://https://sites.google.com/view/carloreggianieconomics/home

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