Quality Selection in Two-Sided Markets: A Constrained Price Discrimination Approach.

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. Online platforms collect rich information about participants and then share some of this information back with them to improve market outcomes. In this paper, we study the following information disclosure problem in two-sided markets: if a platform wants to maximize revenue, which sellers should the platform allow to participate, and how much of its available information about participating sellers' quality should the platform share with buyers? We study this information disclosure problem in the context of two distinct two-sided market models: one in which the platform chooses prices and the sellers choose quantities (similar to ride sharing), and one in which the sellers choose prices (similar to e-commerce). Our main results provide conditions under which simple information structures commonly observed in practice, such as banning certain sellers from the platform and not distinguishing between participating sellers, maximize the platform's revenue. The platform's information disclosure problem naturally transforms into a constrained price discrimination problem in which the constraints are determined by the equilibrium outcomes of the specific two-sided market model being studied. We analyze this constrained price discrimination problem to obtain our structural results. Funding: This work was supported by the National Science Foundation [Grants 1839229 and 1931696]. [ABSTRACT FROM AUTHOR]