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Credit rating of sustainable agricultural supply chain finance by integrating heterogeneous evaluation information and misclassification risk

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Abstract

Supply chain finance (SCF) is a financial service that provides convenient loan transactions for small- and medium-sized enterprises (SMEs) upstream and downstream of the supply chain. SCF can help to smooth the capital flow of many SMEs. However, it is difficult for agricultural SMEs to participate in SCF because this kind of SME usually has various risks. Objectively, evaluating the credit rating of agricultural SMEs is difficult for commercial banks. Furthermore, unlike general manufacturing enterprises, agricultural enterprises produce directly based on nature. Sustainable development based on the natural environment is very important for agricultural enterprises. In this paper, considering sustainability, we construct a criteria system to evaluate the credit ratings of agricultural SMEs for SCF. Moreover, we study a method for processing the hybrid heterogeneous evaluation information of SMEs. A co-decision method is proposed to classify the credit ratings of agricultural SMEs with the help of three-way decisions. Agricultural SMEs are evaluated by both criteria evaluation information and misclassification loss. Finally, a credit rating evaluation example is presented to demonstrate the application of our method. The results show that our proposed method can be used to fully evaluate agricultural SMEs with fine classification effects. It can also provide a reference for commercial banks to determine the credit of agricultural SMEs with a low decision risk.

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Acknowledgements

This work is partially supported by the National Natural Science Foundation of China (No. 72071030), the National Key R&D Program of China (No. 2020YFB1711900), the Planning Fund for the Humanities and Social Sciences of Ministry of Education of China (No. 19YJA630042) and the Social Science Planning Project of the Sichuan Province (No. SC20C007).

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Correspondence to Decui Liang.

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Liang, D., Cao, W. & Wang, M. Credit rating of sustainable agricultural supply chain finance by integrating heterogeneous evaluation information and misclassification risk. Ann Oper Res 331, 189–219 (2023). https://doi.org/10.1007/s10479-021-04453-x

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