Data-driven mergers and personalization

被引:19
|
作者
Chen, Zhijun [1 ]
Choe, Chongwoo [1 ]
Cong, Jiajia [2 ]
Matsushima, Noriaki [3 ]
机构
[1] Monash Univ, Dept Econ, Clayton, Vic, Australia
[2] Fudan Univ, Sch Management, Dept Ind Econ, Shanghai, Peoples R China
[3] Osaka Univ, Inst Social & Econ Res, Osaka, Japan
来源
RAND JOURNAL OF ECONOMICS | 2022年 / 53卷 / 01期
基金
中国国家自然科学基金; 日本学术振兴会; 澳大利亚研究理事会;
关键词
PRICE; COMPETITION;
D O I
10.1111/1756-2171.12398
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:3 / 31
页数:29
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