Data Brokers Co-Opetition

32 Pages Posted: 28 Feb 2019

See all articles by Yiquan Gu

Yiquan Gu

University of Liverpool - Management School (ULMS)

Leonardo Madio

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

Carlo Reggiani

University of Manchester

Date Written: 2019

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

JEL Classification: D430, L130, L860, M310

Suggested Citation

Gu, Yiquan and Madio, Leonardo and Reggiani, Carlo, Data Brokers Co-Opetition (2019). CESifo Working Paper No. 7523, Available at SSRN: https://ssrn.com/abstract=3343854 or http://dx.doi.org/10.2139/ssrn.3343854

Yiquan Gu (Contact Author)

University of Liverpool - Management School (ULMS) ( email )

Chatham Street
Liverpool, L69 7ZH
United Kingdom

Leonardo Madio

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

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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