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

Content Provider	IEEE Xplore Digital Library
Author	Chunhui Piao Changyou Zhang Xufang Han Jing An
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. & Inf. Eng., Shijiazhuang Railway Inst., Shijiazhuang (Changyou Zhang; Xufang Han) \|\| Sch. of Inf., Renmin Univ. of China, Beijing (Chunhui Piao) \|\| Comput. Eng. Dept., Shijiazhuang Vocational Technol. Inst., Shijiazhuang (Jing An)
Abstract	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.
Starting Page	606
Ending Page	609
File Size	245908
Page Count	4
File Format	PDF
ISBN	9780769533957
DOI	10.1109/ICEBE.2008.87
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Railway engineering BP network Predictive models Enterprise resource planning Electronic commerce Data mining Environmental economics enterprise credit B2B e-commerce credit evaluation algorithm Forward contracts Neural networks Rail transportation Internet credit evaluation model
Content Type	Text
Resource Type	Article

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