Research on Credit Evaluation Model and Algorithm for B2B e-Commerce

Credit has been considered as one of the most important problems in e-commerce. There is less research on B2B e-commerce credit evaluation model and algorithm than C2C or B2C. A new enterprise credit evaluation model and algorithm for B2B e-commerce based on intermediate Web site is proposed. It is assumed that an enterprise´s credit in the B2B e-commerce environment is composed of basic credit and transaction credit, and detailed transaction data are available and can be accessed for credit evaluation purpose. According to the BP neural network principles, the models with 3 layers are established to evaluate quantitative-indicators-based credit. Compared with basic credit, an enterprise´s transaction credit is more practical for its potential trading partners on intermediate B2B website. Experimental results demonstrate the effectiveness of the new credit evaluation model and algorithm.