Events at CERGE-EI

Jana Gieselmann

Düsseldorf Institute for Competition Economics (DICE), Germany

 Abstract: As platforms collect more user data, they can tailor algorithms to better match users. At the same time, on matching platforms, users pay to be matched by the platform, while the platform makes money as long as it does not match them. This paper analyzes the matching rule of a profit-maximizing monopoly platform when the incentives between users and the platform are misaligned. Contrary to the intuition that more data about users might improve matching efficiency and speed, I show that more data allows the platform to design a matching rule that increases search time and distorts matching and sorting outcomes in the market. I demonstrate that frequently studied matching rules, such as random matching and positive assortative matching, can be suboptimal for the platform. Instead, the platform strategically lowers match quality to increase search time and thus profits, leading to unnecessary delays and potentially inefficient matches. Finally, I provide two explanations for why platforms adopt business models with misaligned incentives: targeted advertising and the presence of overconfident users.

Ful Text: (Mis-)Matchmaker