Truthful ownership transfer with expert advice: Blending mechanism design with and without money

TL;DR

This paper designs and analyzes truthful mechanisms for ownership transfer scenarios involving experts and bidders, combining elements of mechanism design with and without money, and provides tight welfare approximation guarantees.

Contribution

It introduces a novel hybrid mechanism design framework that handles both monetary and non-monetary agents, with tight approximation guarantees for social welfare.

Findings

Cardinal information mechanisms achieve better welfare guarantees.

Randomized truthful mechanisms can closely approximate optimal social welfare.

The problem extends classical mechanism design to hybrid settings with mixed agent types.

Abstract

When a company undergoes a merger or transfers its ownership, the existing governing body has an opinion on which buyer should take over as the new owner. Similar situations occur while assigning the host of big sports tournaments, like the World Cup or the Olympics. In all these settings, the values of the external bidders are as important as the opinions of the internal experts. Motivated by such scenarios, we consider a social welfare maximizing approach to design and analyze truthful mechanisms in {\em hybrid social choice} settings, where payments can be imposed to the bidders, but not to the experts. Since this problem is a combination of mechanism design with and without monetary transfers, classical solutions like VCG cannot be applied, making this a novel mechanism design problem. We consider the simple but fundamental scenario with one expert and two bidders, and provide tight approximation guarantees of the optimal social welfare. We distinguish between mechanisms that use ordinal and cardinal information, as well as between mechanisms that base their decisions on one of the two sides (either the bidders or the expert) or both. Our analysis shows that the cardinal setting is quite rich and admits several non-trivial randomized truthful mechanisms, and also allows for closer-to-optimal welfare guarantees.