| Nowadays C2C E-commerce has big market potential. But in the real use, credit risk become more and more crucial, especially the on-line trust, which hinder the progress of the C2C E-commerce. Otherwise, because the E-commerce is virtue, both of the seller and buyer finish their deal in the condition that they do not see each other. This increases the risk of the deal. So how to deal with the problem which bothers C2C E-commerce and how to research strategies which are used for C2C E-commerce become very important and have big research value and economy meaning.Now credit evaluation systems which are commonly used fall short of credit hyping and periodical cheating. This paper gives a new method of credit counting, which uses section distribution of commodity price to rate success trades and uses deducting coefficients to rate failed trades.It designs a risk computing method based on the improved credit counting through analyzing credit risk. The computation method can evaluate the risk of current trade according to history trades. Simulating experiments indicate the improved credit counting is preferable on anti credit hyping and anti periodical cheating, and the risk evaluation method is relatively accurate and effective when it is used to analyze and forecast risk in C2C model e-commerce.This paper gives relevant counter measure to cope with unfair ratings in e-commerce trades. It reduces the probability that conspirators choose specific victim by adopting anonymity scheme which conceals identities of market participants before they start a deal, so it constrains Badmouthing. It increases seller's cost t used for credit hyping through Ballot stuffing by adopting charging every deal, so it constrains Ballot stuffing.It designs a simple system to simulate C2C model E-Commerce. In this system, users can choose right sellers to do businesses according to those trust values and trust ranks. The system gives the risk value of the current deal as a reference before every trade. |
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