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The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode

The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode

Zhezhou Li, Rui Dai, Xuan Feng, Yueming Xiong
Copyright: © 2022 |Volume: 30 |Issue: 11 |Pages: 21
ISSN: 1062-7375|EISSN: 1533-7995|EISBN13: 9781668464434|DOI: 10.4018/JGIM.305238
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MLA

Li, Zhezhou, et al. "The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode." JGIM vol.30, no.11 2022: pp.1-21. http://doi.org/10.4018/JGIM.305238

APA

Li, Z., Dai, R., Feng, X., & Xiong, Y. (2022). The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode. Journal of Global Information Management (JGIM), 30(11), 1-21. http://doi.org/10.4018/JGIM.305238

Chicago

Li, Zhezhou, et al. "The Analysis of Two-Way E-Commerce Credit Evaluation Model Based on the C2C Mode," Journal of Global Information Management (JGIM) 30, no.11: 1-21. http://doi.org/10.4018/JGIM.305238

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Abstract

As an important mode of e-commerce, C2C has become a trading mechanism favored by consumers. However, for C2C transaction in a virtual environment, there is an issue of congenital transaction asymmetry, leading to increased uncertainties and transaction risks as well as credit speculation, false transactions and other credit problems. These problems not only affect the development of enterprises to a large extent, but also hinder the development of e-commerce ultimately. In order to guarantee the safety of both transaction parties, it is particularly important to establish a sound credit evaluation system for shopping sites. Through the analysis of the shortcomings of the existing C2C e-commerce credit evaluation model, this paper proposes a two-way e-commerce credit evaluation model based on the C2C mode. Firstly, a cross-platform two-way credit rating center with a unified rating standard was constructed; secondly, the credit evaluation indicator was reset and revised; then the credit rating of buyers and sellers was unified by combining fuzzy comprehensive evaluation algorithm and