A Study On Net-merchants' Reputation Evaluation Model Based On B2B Hub For Small And Mid-size Enterprises

B2B hubs which are third-party transaction platforms for enterprises are more popular with SMEs ( Small and Mid-size Enterprises) recently. The emergence of B2B hubs not only overcome the weakness of SMEs such as the lack of fund and under-developed technology foundation, but also provide more business chances for them. However, compared with traditional transaction, the risk of trust which is lead by electronic commerce is much higher, and the trust has been the prime problem which hinders electronic commerce for further development. Especially in B2B, the importance of trust is more serious. Many SMEs have the irresolute attitude to have their business on B2B hubs, which show their suspicion for electronic commerce's environment. The transaction trust of electronic commerce includes the static credit and the reputation. The static credit refers to the qualification of enterprises, while the reputation refers to the appearance of the transaction behaviors of enterprises in the past time. Few B2B Hubs have provided the function of the reputation evaluation, so is in academic study. Based on above reasons, reputation evaluation model is the point on which this paper studies.The paper firstly introduces the development of the B2B hub and the trust problem in electronic commerce, and then analyzes the necessary and importance of the reputation evaluation in B2B hubs. According to game theory, single transaction will possibly lead to cheatings, while multiple transactions will avoid it to some extent. From the development of trust perspective, the foundation of trust is the knowledge of historical behaviors for each other. The paper proposes an innovation reputation evaluation model which is based on such a precondition: The reputation is produced by net-merchants' historical behaviors and people always trend to select a good reputation of net-merchant to be the partner. And usually, those honest net-merchants always receive good reputation, while dishonest net-merchants always receive bad ones. The mechanism of the model is that net-merchants evaluate each other after the transaction, and the result will be processed in order to build their reputation. The contributions of the model are: (1) Evaluation ranks and evaluation indexes are more detailed. (2) Evaluation results are more objective after being processing. (3) Avoiding "mutual advantage" phenomenon. In addition, the model is easy to be implemented by computer, and evaluation indexes and other parameters can be adjusted according to the actual situation of each B2B hub.