{"type":"ScholarlyArticle","title":"Approximately Maximizing the Broker's Profit in a Two-sided Market","authors":[{"name":"Jing Chen","slug":"jing-chen","given":"Jing","family":"Chen","affiliation":"Department of Computer Science , Stony Brook University , USA"},{"name":"Bo Li","slug":"bo-li","given":"Bo","family":"Li","affiliation":"Department of Computer Science , Stony Brook University , USA"},{"name":"Yingkai Li","slug":"yingkai-li","given":"Yingkai","family":"Li","affiliation":"Department of Computer Science , Northwestern University , USA"}],"abstract":"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/valuations are independently drawn from prior distributions, and aim at designing dominant-strategy incentive-compatible (DSIC) mechanisms that are approximately optimal.\r\n\r\nProduction-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.","doi":"10.24963/ijcai.2019/22","url":"https://ijcai.org/proceedings/2019/22","pdf":"https://ijcai.org/proceedings/2019/0022.pdf","markdown":"https://ijcai.org/proceedings/2019/22.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/22","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Agent-based and Multi-agent Systems","track":"Main track","number":22,"pages":{"first":151,"last":157},"keywords":["Agent-based and Multi-agent Systems: Algorithmic Game Theory","Agent-based and Multi-agent Systems: Economic Paradigms, Auctions and Market-Based Systems"],"videos":[],"references":[{"position":1,"raw":"[Balseiro et al., 2019] Santiago R Balseiro, Vahab Mirrokni, Renato Paes Leme, and Song Zuo. 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