A Computational Approach to Compare Information Revelation Policies

Revelation policies in an e-marketplace differ in terms of the level of competitive information disseminated to participating sellers. Since sellers who repeatedly compete against one another, learn based on the information revealed and alter their future bidding behavior, revelation policies affect the welfare parameters - consumer surplus, producer surplus and social welfare - of the market. Although, different revelation policies are adopted in several traditional and web-based marketplaces, prior work has not studied the implications of these policies on the performance of a market. In this paper, we study and compare a set of revelation policies using a computational marketplace. Specifically, we study this in the context of a reverse-market where each seller’s decision problem of choosing an optimal bid is modeled as an MDP (Markov Decision Process). Results and analysis presented in this paper are based on market sessions executed using the computational marketplace. The com...

• Type: Conference
• Year: 2003
• Where: ICIS
• Authors: Amy R. Greenwald, Karthik Kannan, Ramayya Krishnan
• Keywords: Computational Marketplace, Game-theoretic Models, ICIS 2003, Information Technology, Revelation Policies