Revenue Maximization Mechanisms for an Uninformed Mediator with Communication Abilities
Zhikang Fan, Weiran Shen

TL;DR
This paper designs revenue-maximizing communication mechanisms for a mediator in a market with private information, providing an optimal, simple, threshold-based solution and revealing counterintuitive properties like potential mediator losses.
Contribution
It introduces a novel framework for revenue maximization in mediated communication settings and derives a closed-form optimal mechanism under regularity conditions.
Findings
Optimal mechanism has a threshold structure.
Mediator can sometimes incur losses in optimal strategies.
Extension of results using ironing technique for general cases.
Abstract
Consider a market where a seller owns an item for sale and a buyer wants to purchase it. Each player has private information, known as their type. It can be costly and difficult for the players to reach an agreement through direct communication. However, with a mediator as a trusted third party, both players can communicate privately with the mediator without worrying about leaking too much or too little information. The mediator can design and commit to a multi-round communication protocol for both players, in which they update their beliefs about the other player's type. The mediator cannot force the players to trade but can influence their behaviors by sending messages to them. We study the problem of designing revenue-maximizing mechanisms for the mediator. We show that the mediator can, without loss of generality, focus on a set of direct and incentive-compatible mechanisms. We…
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