Quality Selection in Two-Sided Markets: A Constrained Price Discrimination Approach
研究双边在线平台如何通过选择卖家质量和向买家披露信息来最大化收入，发现简单信息结构（如排除部分卖家或不区分卖家）在某些条件下是最优策略。
Optimizing Revenue in Two-Sided Online Markets through Strategic Quality Selection and Information Disclosure Ensuring profitable operations in two-sided online marketplaces demands an astute analysis of seller quality and strategic information sharing with buyers. A recent paper, titled “Quality Selection in Two-Sided Markets: A Constrained Price Discrimination Approach” by B. Light, R. Johari, and G. Weintraub delves into the nuances of this operation. The authors explore the challenge that platforms encounter in deciding which sellers to allow and how much quality information to share with buyers in order to enhance platform revenue. Utilizing two distinct two-sided market models, the paper unveils conditions under which adopting straightforward information structures, such as excluding certain sellers or not differentiating among participating sellers, proves to be a revenue-maximizing strategy. This study utilizes a constrained price discrimination problem to reveal specific strategies platforms can use to adjust information structures in diverse market scenarios, providing insights for digital platforms aiming to navigate the marketplace more effectively.