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Article

Identifying and Predicting the Credit Risk of Small and Medium-Sized Enterprises in Sustainable Supply Chain Finance: Evidence from China

School of Management, Shanghai University, Shanghai 200444, China
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Author to whom correspondence should be addressed.
Academic Editors: Lu Zhen, Junliang He and Lufei Huang
Sustainability 2021, 13(10), 5714; https://doi.org/10.3390/su13105714
Received: 7 April 2021 / Revised: 12 May 2021 / Accepted: 14 May 2021 / Published: 19 May 2021
(This article belongs to the Special Issue New Trends in Sustainable Supply Chain and Logistics Management)
COVID-19 has created a strong demand for supply chain finance (SCF) for small and medium-sized enterprises (SMEs). However, the rapid development of SCF leads to more complex credit risks. How to effectively discriminate and manage SMEs to reduce credit risk has become one of the most critical issues in SCF. In addition, sustainable SCF (SSCF) has received increasing attention, and credit risk management is important to achieve SSCF. Therefore, it is significant to identify the key factors influencing the credit risk of SMEs and construct a prediction model to promote SSCF. This study uses the lasso-logistic model to identify factors influencing the credit risk of SMEs and to predict the credit risk of SMEs. The empirical results show that (i) the key factors influencing SMEs’ credit risk include six variables—the matching degree of order data, ratio of contract enforcement, number of contract defaults, degree of business concentration, and number of administrative penalties; and (ii) the lasso-logistic model can identify the key factors influencing credit risk and have a better prediction performance. Moreover, transaction credit and reputation supervision significantly influence the credit risk of SMEs. View Full-Text
Keywords: sustainable supply chain finance (SSCF); credit risk; small and medium-sized enterprises (SMEs); transaction credit; reputation supervision; lasso-logistic model sustainable supply chain finance (SSCF); credit risk; small and medium-sized enterprises (SMEs); transaction credit; reputation supervision; lasso-logistic model
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MDPI and ACS Style

Yang, Y.; Chu, X.; Pang, R.; Liu, F.; Yang, P. Identifying and Predicting the Credit Risk of Small and Medium-Sized Enterprises in Sustainable Supply Chain Finance: Evidence from China. Sustainability 2021, 13, 5714. https://doi.org/10.3390/su13105714

AMA Style

Yang Y, Chu X, Pang R, Liu F, Yang P. Identifying and Predicting the Credit Risk of Small and Medium-Sized Enterprises in Sustainable Supply Chain Finance: Evidence from China. Sustainability. 2021; 13(10):5714. https://doi.org/10.3390/su13105714

Chicago/Turabian Style

Yang, Yubin, Xuejian Chu, Ruiqi Pang, Feng Liu, and Peifang Yang. 2021. "Identifying and Predicting the Credit Risk of Small and Medium-Sized Enterprises in Sustainable Supply Chain Finance: Evidence from China" Sustainability 13, no. 10: 5714. https://doi.org/10.3390/su13105714

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