Computational collective intelligence in electronic commerce: Incentive design in evaluation system

In most of e-commerce site, evaluation systems are employed to evaluate each user after the tradings. Normally, seller´s evaluation score is shown in e-commerce site that is computed based on score given by buyers. In recent e-commerce site, 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 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 evaluation system in e-commerce. Then, to avoid asymmetric and incomplete information in tradings, we design a mechanism of trader evaluation. After that, we give some experiments to show the rate of successful trade in our proposed mechanism. Contributions of this paper are showing theoretical discussion of e-commerce computational intelligence, design on evaluation mechanism and showing the effectiveness of the proposed mechanism.