Data‐driven mergers and personalization

Zhijun Chen, Chongwoo Choe, Jiajia Cong and Noriaki Matsushima

RAND Journal of Economics, 2022, vol. 53, issue 1, 3-31

Abstract: This article studies tech mergers that involve a large volume of consumer data. The merger links the markets for data collection and data application through a consumption synergy. The merger‐specific efficiency gains exist in the market for data application due to the consumption synergy and data‐enabled personalization. Prices fall in the market for data collection but generally rise in the market for data application as the efficiency gains are extracted away through personalized pricing. When the consumption synergy is large enough, the merger can result in monopolization of both markets. We discuss policy implications including various merger remedies.

Date: 2022
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https://doi.org/10.1111/1756-2171.12398

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Working Paper: Data-Driven Mergers and Personalization (2020)
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