Study On Trust Model Of C2C E-Commerce Based On Feedback

C2C is the most active model in e-commerce. Compared to B2B and B2C, in addition to the virtual and space across, C2C has its own features including:individual participants, low barriers to entry and exit, anonymous registration and so on. It determines an uncertainty, highly dynamic and virtual trading environment which makes the high risk for C2C trading. With the development of mobile e-commerce, Location-based Service and Context-based Service will have a profound impact on the e-commerce, and conduct the innovation of C2C model. Context-sensitive C2C e-commerce will bring more business, and be accepted by user. The context-sensitive feature aggravates the asymmetry of information, and brings more fraud. The related work shows that establish a trust relationship can reduce transaction uncertainty and risk, improve the efficiency of cooperation and restraint of trade fraud. Although trust management for traditional C2C has been made a lot of research, but there are still many problems in handling reputation fraud, and lack of trust study about context-sensitive C2C. So the analysis of different C2C trading scenario is necessary, construct online trust management to avoid trading risks, and create an integrity trading environment has become a key problem in C2C application and future development.The paper analyzes two significance transactions including:(1) traditional C2C scene, it is generally accepted by people, such as Taobao;(2) context-related C2C scene, it is under the development of Location-based Services in mobile e-commerce environment, C2C platform can recommend trading according to the context, or allow users to search trading. And finally users can deal the trading offline after negotiation,, such as carpooling service. In this paper, two main issues need to be considered based on the two C2C scenes.(1) In the trust management of traditional C2C, it is need to analyze features of reputation fraud, as well as the the existing problems of C2C reputation model, and finally to improve anti-fraud ability of trust management.(2) In the trust management of context-related C2C scene, transactions need to be dealt offline. Different context will have different perceptions of risk. The immature business model may prone to sparse feedback, and will lack of the feedback under the same context. It makes the trust assessment need to reduce the occasional trust, and to deal with different context reputation feedback.The main research work can be subdivided into the following four aspects. (1) Describe the traditional C2C trading scenario, and analyze the fraud in existing C2C reputation model. Then introduce the proposed C2CRep model in this work, including guidelines, parameter selection, the basis of various factors, and experimental evaluation.(2) Analyse the effect of buyers’review feedback to potential buyers in the C2C trust management, and proposes ranking method based on feedback reliability to show the reviews. In order to calculate the feedback reliability, the work has improved the weighted RFM customer value model to adapt to the C2C environment; introduced how to compute each index in RFM model; and then determined RFM weight by AHP method; finally used the customer value theory and the reputation to establish feedback reliability calculation model.(3) Describe the context-sensitive C2C trading scenario, and analyse risk assessment in different contexts. Drawing on information systems risk assessment methodology, the paper has proposed a method based on fuzzy set theory, including analysis of the context of risk hierarchy, quantitative risk analysis of all factors, comprehensive evaluation results of the context risk.(4) Because of context-sensitive C2C transactions prone to sparse feedback, and trust mapping in different context, the paper has proposed a way to filter false feedback rely on the feedback offset, calculated the stability by the amount of feedback. By combined with work context risk assessment, the work realized the trust mapping mechanism of different context through risk value, and constructed a risk perception of context in C2C trust management model.The main innovations of this work are as follow.(1) The paper proposed a C2CRep seller’s reputation model. The new model has added collusion factor to balance the number of transactions and concentrated feedback, added unsatisfied index to inhibit feedback blackmail, and improved price index to dynamically adapt to commodity’s personality. Compared with the traditional C2C model and classic SPORAS model, experimental results show that in low-price reputation deception, reputation collusion, and reputation slander, it can improve the ability to resist reputation fraud.(2) The paper proposed a feedback reliability compute model based on RFM. It has combined the theory of customer value, and improved RFM customer value model to fit C2C environment. Compared with the reputation based model, experimental results show that it can increase the cost of transaction time, frequency, money to obtain high ranking score through fraud trading.(3) The paper proposed a context risk related C2C trust model. It has constructed risk assessment of context in C2C model based on fuzzy set, and realized trust mapping through the risk indicator. It also has introduced a stable index in filtering inaccurate feedback by its offset to avoid accidental factor for insufficient amount of feedback. Simulation results show that, compared with the the traditional mean model and PeerTrust model, it improve the accuracy of trust evaluation, and can inhibit reputation fraud by low-risk context.The work has produced some fruit, which will enrich e-commerce trust management mechanism to some extent, and also further promote the C2C business applications development in future.