关键词: 电子中介, 交易匹配, 第三方评价主体, 累积分布函数

Abstract: With advances in information technology and Internet, posting product reviews is getting easier and it has become a habit for most people. These reviews, which can be seen in various websites easily, contain a wealth of information, such as customers' concerns, sentiments and opinions. The existing research results have shown that these reviews, as a third-party evaluation information, have significant impact on consumers' purchase decisions. Especially in multi-attributes trade led by e-Brokerage, the buyers have become increasingly dependent on these reviews (i.e., third-party evaluation information). With the consideration of the dependence on the third-party's evaluations in multi-attributes trade, a method for multiple-attributes trade matching considering evaluations of the third-party in e-Brokerage is proposed, and the probability and statistics theories are employed to deal with evaluation or feedback information provided by the third-party. First, the supply and demand information in multiple forms provided by supplies and buyers is transformed into the uniform one with cumulative distribution function. Second, the evaluation or feedback information of the third-party in multiple forms is also transformed into the uniform one with cumulative distribution function. On the basis of this, overall matching degrees of the supplies and buyers with respect to opposite sides are measured with the consideration of third-party's evaluation or feedback information, and a multi-objective optimization model is formulated to maximize the overall matching degree of the supplies and buyers, as well as to maximize earnings of the e-Brokerage. Furthermore, the weighting sum method based on membership function is employed to transform the multi-objective optimization model into single-objective optimization model. The optimal matching pairs can be determined by solving the single-objective optimization model. To illustrate the performance of the proposed method, a case study is conducted. The data of the case are derived from the related references and websites. The results of the case study show that the third-party evaluations on products can play an important role in multiple-attributes trade. The use of the proposed method will help in obtaining more objective and accepted matching results. It can not only promote buyers to get the desirable products, but also supervise and urge suppliers to pay more attention to their products and words of mouth.

Key words: e-brokerage, trade matching, third-party, cumulative distribution function