Information Design of Online Platforms

• 成果类型: Article; Early Access
• 署名作者: Ke, T. Tony; Lin, Song; Lu, Michelle Y.
• 署名单位: Chinese University of Hong Kong; Hong Kong University of Science & Technology; China Europe International Business School
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2025.03083
• 发表日期: 2026
• 关键词: consumer search; information design; PERSONALIZATION; platform design; product recommendation; targeted advertising

摘要

We study how an online platform strategically uses information to both guide consumer search and influence sellers' targeted advertising. Our model unifies personalized recommendations and targeted ads under an information design framework. We illustrate a fundamental tradeoff facing the platform between improving match efficiency and extracting seller surplus by inducing their competition for prominence. The optimal information design may be socially inefficient because it balances the tradeoff by limiting consumer search and mixing the matched product with a long tail of unmatched ones for recommendation. This implies that sponsored targeted advertising on retail platforms may introduce match inefficiency.