1 research outputs found
Approximately Maximizing the Broker's Profit in a Two-sided Market
We study how to maximize the broker's (expected) profit in a two-sided
market, where she buys items from a set of sellers and resells them to a set of
buyers. Each seller has a single item to sell and holds a private value on her
item, and each buyer has a valuation function over the bundles of the sellers'
items. We consider the Bayesian setting where the agents' values are
independently drawn from prior distributions, and aim at designing
dominant-strategy incentive-compatible (DSIC) mechanisms that are approximately
optimal.
Production-cost markets, where each item has a publicly-known cost to be
produced, provide a platform for us to study two-sided markets. Briefly, we
show how to covert a mechanism for production-cost markets into a mechanism for
the broker, whenever the former satisfies cost-monotonicity. This reduction
holds even when buyers have general combinatorial valuation functions. When the
buyers' valuations are additive, we generalize an existing mechanism to
production-cost markets in an approximation-preserving way. We then show that
the resulting mechanism is cost-monotone and thus can be converted into an
8-approximation mechanism for two-sided markets.Comment: Appeared in IJCAI 1