Consumer privacy concerns, multihoming, and platform competition in two-sided markets

• 成果类型: Article; Early Access
• 署名作者: Zhang, Xin; Xu, Hong; Yue, Wei Thoo; Yu, Yugang
• 署名单位: Chinese Academy of Sciences; University of Science & Technology of China, CAS; Hong Kong University of Science & Technology; City University of Hong Kong
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1177/10591478261483184
• 发表日期: 2026
• 关键词: information; ECONOMICS; PERSONALIZATION; BEHAVIOR; DESIGN

摘要

User data is central to the operations of many online platforms, enabling personalized services for users and targeted advertising for advertisers. However, as users become increasingly aware of privacy issues associated with platform usage, they may alter their usage levels and engagement patterns, such as switching between singlehoming (using one platform exclusively) and multihoming (using multiple platforms). These shifts in user behavior are not only reshaping platform dynamics but also creating ripple effects for advertisers. In this study, we develop a game-theoretic model to explore how privacy concerns influence user strategies, advertiser decisions, and platform performance, and to assess the effectiveness of common privacy practices implemented by platforms. Our analysis generates several interesting insights. First, we demonstrate that as privacy concerns increase, users are motivated to shift from singlehoming to multihoming, especially when their privacy concerns are relatively low. This shift occurs because multihoming allows users to limit their data exposure on any single platform, thereby reducing the potential for platforms to exploit their data in depth. Second, we find that heightened privacy concerns can unexpectedly benefit platforms by increasing user traffic and aggregate usage, which makes platforms more appealing to advertisers and increases advertiser demand. Third, our analysis reveals that increased privacy concerns can reduce the market dominance of the large platform with strong data capabilities, narrowing the gap in market share between competing platforms. Furthermore, we discuss important managerial and policy implications regarding partial data use and privacy protection, offering insights into how platforms can balance user privacy and platform performance. Finally, we extend our model in several directions to demonstrate the robustness of our key findings and obtain additional insights.