Academic Journal of Business & Management, 2023, 5(19); doi: 10.25236/AJBM.2023.051923.
Ma Xiaokang1, Yuan Yixuan1, Hu Jiarui2
1Beijing Normal University Zhuhai Campus, Zhuhai, China
2Nanchang University, Nanchang, China
In recent years, with the rapid development of Internet in our country and the continuous expansion of the trading volume of e-commerce, supply chain finance came into being. The supply chain financing has not only found a new way out for SME financing difficulties, but also enhanced the stability of the overall operation of the supply chain. Therefore, this article focuses on the management of corporate credit risk under the supply chain finance model. Firstly, we select the economic data of 120 listed SMEs in China as the research sample in 2016, and establish the corresponding credit risk evaluation model by using principal component analysis and Logistic regression. Further, this paper takes Jingdong as an example, uses the model to measure its credit risk, and compares the probability of Jingdong compliance with the supply chain finance financing model and the traditional bank credit model. There is a credit rating system to improve the creditworthiness and financing ability of Chinese enterprises and provide more reference ideas for the healthy development of supply chain finance in our country.
Supply Chain Finance Credit Risk, Principal Component Analysis, Logistic Regression
Ma Xiaokang, Yuan Yixuan, Hu Jiarui. Research on the Enterprise Credit Risk Rating System in Supply Chain Finance Based on Jingdong. Academic Journal of Business & Management (2023) Vol. 5, Issue 19: 164-171. https://doi.org/10.25236/AJBM.2023.051923.
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