Analysis of Successful Trades Information Disclosure Mechanism

Abstract

In most of e-commerce sites evaluation systems are employed to evaluate each user after trades. Normally, seller's evaluation score is shown in e-commerce site and computed based on the score given by buyers. In recent e-commerce sites, the evaluation is based on multiple attributes and buyers give their thinking for each attribute. In this viewpoint, the seller evaluation in e-commerce is collected knowledge from buyers and the synthetic score is computational intelligence because each buyer makes his/her decision whether he/she trades with the seller. In this paper, we discuss the computational intelligence of the evaluation system in e-commerce. Then, to avoid asymmetric and incomplete information in trades, we design a mechanism of the trader evaluation. After that, we present some experiments to show the rate of successful trades in our proposed mechanism. Contributions of this paper are showing the theoretical discussion of e-commerce computational intelligence, design of evaluation mechanism and the effectiveness of the proposed mechanism.