Computational Intelligence · 2002 · 148 citations · 21 references
Electronic AuctionFuture EconomyGame TheoryMarket DesignE-businessAlgorithmic Mechanism DesignEconomic AnalysisSystems EngineeringBargaining TheoryAuction TheoryMechanism DesignMarket Mechanism DesignEconomicsMarket MechanismMulti-agent Mechanism DesignGamesTwo-sided MarketMarketingBusinessEconomics Of Information
E‑markets are envisioned as essential exchange hubs for commodities and services, and their design hinges on market mechanisms that define organization, information flow, trading procedures, and the rules governing multi‑agent interactions. The goal is to design a robust, flexible, and efficient e‑market mechanism that is strategy‑proof, weakly budget‑balanced, and individually rational. The mechanism is implemented in the RETSINA multi‑agent toolkit, allowing numerical validation of the analytically derived strategy‑proof, weakly budget‑balanced, and individually rational bounds. The mechanism discourages sellers from underreporting supply, and by bounding efficiency loss it guarantees convergence to high efficiency when the number of trading agents is large.
We envision a future economy where e–markets will play an essential role as exchange hubs for commodities and services. Future e–markets should be designed to be robust to manipulation, flexible, and sufficiently efficient in facilitating exchanges. One of the most important aspects of designing an e–market is market mechanism design. A market mechanism defines the organization, information exchange process, trading procedure, and clearance rules of a market. If we view an e–market as a multi–agent system, the market mechanism also defines the structure and rules of the environment in which agents (buyers and sellers) play the market game. We design an e–market mechanism that is strategy–proof with respect to reservation price, weakly budget–balanced , and individually rational . Our mechanism also makes sellers unlikely to underreport the supply volume to drive up the market price. In addition, by bounding our market’s efficiency loss, we provide fairly unrestrictive sufficient conditions for the efficiency of our mechanism to converge in a strong sense when (1) the number of agents who successfully trade is large, or (2) the number of agents, trading and not , is large. We implement our design using the RETSINA infrastructure, a multi–agent system development toolkit. This enables us to validate our analytically derived bounds by numerically testing our e–market.
21
Theodore Groves · Econometrica · 1973 · 3.3K citations
Resource Allocation Model, Organizational Structure, Incentive Mechanism +14
Multipart pricing of public goods
Edward H. Clarke · Public Choice · 1971 · 3.3K citations
Efficient mechanisms for bilateral trading
Roger B. Myerson, Mark A. Satterthwaite · Journal of Economic Theory · 1983 · 2.5K citations