Multi-agent Negotiation System in Electronic Environments

The main purpose of the study is to investigate how costly information could affect the performance of several types of searching agents in electronic commerce environments. Internet searching agents are tools allowing consumers to compare on-line Web-stores' prices for a product. The existing agents base their search on a predefined list of Web-stores and, as such, they can be qualified as fixed-sample size searching agents. However, with the implementation of new Internet pricing schemes, this search rule may evolve toward more flexible search methods allowing for an explicit trade-off between the communication costs and the product price. In this setting, the sequential optimal search rule is a possible alternative. However, its adoption depends on its expected performance. The present paper analyses the relative performances of two types of search agents on a virtual market with costly information. At the theoretical equilibrium of the market, we show that the sequential rule-based searching agents with a reservation price always allow consumers to pay lower total costs. We further test the robustness of this result by simulating a market where both sellers' and buyers' search agents have only partial information about the market structure.