Identifying Perverse Incentives in Buyer Profiling on Online Trading Platforms

• 成果类型: Article
• 署名作者: Kannan, Karthik; Saha, Rajib L.; Khern-am-nuai, Warut
• 署名单位: Purdue University System; Purdue University; Indian School of Business (ISB); McGill University
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2021.1077
• 发表日期: 2022
• 页码: 464-475
• 关键词: sponsored search; MODEL; Intermediaries; auction; DESIGN

摘要

Consumer profiling has become one of the most common practices on online trading platforms. Many platforms strive to obtain and implement technological innovations that allow them to understand and identify consumers' needs, and, thereafter, monetize this capability by charging sellers to present and/or sell their products or services based on consumers' interests. However, an interesting and relevant question arises in this context: Does the platform have an incentive to profile its buyers as accurately as possible? This paper develops and analyzes a parsimonious game-theoretic model to answer this research question. We find that, surprisingly, platforms that charge sellers for discoveries have a perverse incentive to deviate from accurate buyer profiling. However, such a perverse incentive does not exist for platforms that charge sellers for transactions. As a result, with such a perverse incentive, social welfare under discovery-based pricing is lower than that under transaction-based pricing.