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As an important mode of E-commerce, C2C e-commerce has become a very popular trade pattern among consumers. Although it is a newly-emerging trade mode, its uncertainty and risk augment as a result of the increasing information asymmetry on both of the trading parties, thus making credit one of the bottlenecks in the development of C2C E-commerce. The builder, the operator of C2C E-commerce web stations as well as the scholars in this field have been seeking one or even many reputation mechanisms to ensure the proper and orderly functioning of E-commerce. https://www.51lunwen.org/australiathesis/

This research has some certain theoretical and realistic sgnificance by selecting this subject. The online reputation feedback system, also named feedback forum by eBay, is regarded as the vital factor that determines the success of C2C E-commerce. Based on the comments of related theories and literature, this research centers on the efficiency of online feedback system, discussing the positive effect of online reputation feedback system on eliminating the adverse choice problems, establishing optimized combination models of online reputation feedback system, and analyzing the positive effect of online reputation feedback system on enhancing the trust in webstations and sellers according to the data of the research.

The main findings are as follows:This dissertation analyzes the formation of adverse choice problem in C2C E-commerce trade and the failure in traditional areas of the ways to solve the adverse choice problem under cyber conditions. Meanwhile, from the perspective of game theory, the online reputation feedback system encourages, to some extent, the users to maintain honesty in trading and to reduce the adverse choice; if the seller could reenter the market with no cost incurred, however, the online reputation feedback system would fail; if there is any noise in trade appraisal, the efficiency of online reputation feedback system will be reduced.The combination model of reputation feedback system is the nucleus of online reputation feedback system, whereas the simply accumulating reputaion feedback model generally adopted by C2C E-commerce webstations now is far from stimulating the sellers to maintain honesty in trading.

This dissertation constructs respectively reputation degree calculation model based on the validity of marker and the one based on the appraisal of time value. In addition, it is pointed out that when the validity of marker serves as the function of reputation degree and negative feedback number meanwhile meeting some certain conditions, the reputation degree calculation model based on the validity of marker can promote the seller to maintain honesty in trading; the bigger the reputation weight of past deals, the less the sellers are motivated to maintain honesty in trading; when there is no time limit for the existance of the seller, and the reputation weight of past deals is small enough, the reputation cumulation model based on the appraisal of time value will stimulate the seller to maintain honesty in trading. This dissertation constructs the multi-factor reputation degree calculation model based on factors like the validity of market, the value of the commodity traded and the time weight, and draws a comparison of trading statistics between two sellers on Taobao website.

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