题　目：Optimal Match Recommendations in Two-sided Marketplaces with Endogenous Prices

嘉　宾：施鹏 助理教授 南加州大学

主持人：曹宇峰 助理教授 上海交通大学安泰经济与管理学院

时　间：2022年10月5日（周三）10:30-12:00am（Zoom会议）

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内容简介:

Many two-sided marketplaces rely on match recommendations to help customers find suitable service providers at suitable prices. This paper develops a tractable methodology that a platform can use to optimize its match recommendation policy so as to maximize the total value generated by the platform while accounting for the endogeneity of transaction prices, which are set by the providers based on supply and demand and can depend on the platform's match recommendation policy. Despite the complications of price endogeneity, an optimal match recommendation policy has a simple structure and can be computed efficiently. In particular, an optimal policy always recommends the providers who deliver the highest conversion rates. Moreover, an optimal policy can be encoded simply in terms of the frequency of recommending each provider to each customer segment, without the need to encode which subsets of providers are to be recommended together. On the other hand, if the platform were to optimize its match recommendations without accounting for price endogeneity, then the resultant policy would be more complex, and the market is likely to get stuck at a strictly suboptimal outcome, even if the platform were to continually re-optimize its match recommendations after prices re-equilibrate.

Link to paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4034950

演讲人简介：

Peng Shi is an Assistant Professor of Data Sciences and Operations in the USC Marshall School of Business. His current research focuses on optimization in matching markets, with applications in school choice, public housing, organ allocation, and online marketplaces. His research has won multiple awards, including the MSOM Responsible Research in OM Award, the MSOM Service Management SIG Best Paper Award, the ACM SIGecom Doctoral Dissertation Award, the INFORMS Public Sector Operations Best Paper Competition, and the INFORMS Doing Good with Good OR Student Paper Competition. Prior to joining USC, he completed a PhD in operations research at MIT, and was a post-doctoral researcher at Microsoft Research.

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