Data-driven mergers and personalization

• 成果类型: Article
• 署名作者: Chen, Zhijun; Choe, Chongwoo; Cong, Jiajia; Matsushima, Noriaki
• 署名单位: Monash University; Fudan University; University of Osaka
• 刊物名称: RAND JOURNAL OF ECONOMICS
• ISSN/ISSBN: 0741-6261
• DOI: 10.1111/1756-2171.12398
• 发表日期: 2022
• 页码: 3-31
• 关键词: price; COMPETITION

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.