Farmers’ Credit Risk Assessment Based on Sustainable Supply Chain Finance for Green Agriculture

Yuehua Xia, Honggen Long (), Zhi Li and Jiasen Wang
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Yuehua Xia: Department of Mathematics, Gansu Normal College for Nationalities, Hezuo 747000, China
Honggen Long: Department of Industrial Engineering and Management, Business School, Sichuan University, Chengdu 610041, China
Zhi Li: Department of Industrial Engineering and Management, Business School, Sichuan University, Chengdu 610041, China
Jiasen Wang: Department of Industrial Engineering and Management, Business School, Sichuan University, Chengdu 610041, China

Sustainability, 2022, vol. 14, issue 19, 1-20

Abstract: With the development of green agriculture, the demand of farmers for operation loans is increasing. Supply chain finance is becoming a new way to solve the problem of difficult credit in agricultural development. As the importance of sustainability issues continues to rise, there are growing numbers of practical examples of combining agricultural supply chain finance (ASCF) with sustainability, and the attendant risks are emerging. The objectives of this study are first to construct a risk indicator system for sustainable ASCF, then to propose a fuzzy decision method that considers the confidence of decision-makers, and finally to perform a risk assessment of a credit case in the coffee bean supply chain. A combination of the neutrosophic enhanced best–worst method (NE-BWM) and combined compromise solution (COCOSO) is used to evaluate risk problems. The practicality and effectiveness of this research method is verified by a numerical simulation and a comparison with the method. The results show that the credit rating of core companies is the most important indicator. In the context of green and sustainable development, this indicator system is more suitable for the current green transformation development of agriculture and can help decision-makers scientifically and reasonably assess the risk level of ASCF. When loans are needed to transform green agriculture, this study provides new ideas for credit models for various actors in the agricultural supply chain and offers a new entry point to the issue of sustainable agricultural development.

Keywords: credit risk evaluation; green agriculture; sustainable supply chain finance; neutrosophic enhanced best–worst method; combined compromise solution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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