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Research on Digital Credit Behavior of Farmers’ Cooperatives—A Grounded Theory Analysis Based on the “6C” Family Model

Author

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  • Yangyang Zheng

    (Business School, Wenzhou University, Wenzhou 325035, China)

  • Jianhong Lou

    (Business School, Wenzhou University, Wenzhou 325035, China)

  • Linfeng Mei

    (Business School, Wenzhou University, Wenzhou 325035, China)

  • Yushuang Lin

    (Academy of Humanities and Social Sciences, Wenzhou University, Wenzhou 325035, China)

Abstract

As the main demand side of rural financial services, farmers’ cooperatives are an important part of China’s rural finance. However, due to the lack of effective collateral, farmers’ cooperatives have problems such as difficulty in obtaining loans or expensive loans, which not only hinder the high-quality development of farmers’ cooperatives, but also limit the development of regional rural finance. Digital credit as a new financing model can effectively alleviate the problems of difficult and expensive loans and has received wide attention from the government and academia. Based on this, this paper analyzes the digital credit behavior of farmers’ cooperatives in detail by applying the “6C” family model to the grounded theory, and constructs a theoretical analysis model of farmers’ cooperatives’ digital credit behavior. The findings are as follows: The motivation for the digital credit of farmers’ cooperatives is that the credit procedures are simple, the loan period is short, and the loan interest rate is low; the condition is the farmers’ cooperative reputation advantage and government policy support,; the main form is the participation of cooperatives in short- and long-cycle digital credit; and the consequence is reflected in increasing the income of cooperative members, improving the availability of cooperative loans, promoting cooperative credit building, and achieving sustainable agricultural development. Different participation motivations have different effects on the form of credit. When motivated by simple credit procedures and short loan periods, farmers’ cooperatives choose “Huinong e-loan”; when motivated by simple procedures and low loan interest rates, farmers’ cooperatives choose “Funong Loan”. Different forms of credit will produce different performances. Farmers’ cooperatives choosing “Huinong e-loan” will produce economic performance; farmers’ cooperatives choosing “Funong Loan” will produce economic performance and social performance. In order to deal with the problem of digital credit of farmers’ cooperatives, the government needs to improve the relevant policies and regulations, reduce credit risks, and establish a sound credit system to provide credit guarantees for cooperatives and farmers. Financial institutions need to improve their financial services and innovate financial products and services to meet the multi-level credit needs of cooperatives.

Suggested Citation

  • Yangyang Zheng & Jianhong Lou & Linfeng Mei & Yushuang Lin, 2023. "Research on Digital Credit Behavior of Farmers’ Cooperatives—A Grounded Theory Analysis Based on the “6C” Family Model," Agriculture, MDPI, vol. 13(8), pages 1-19, August.
  • Handle: RePEc:gam:jagris:v:13:y:2023:i:8:p:1597-:d:1216159
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    References listed on IDEAS

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    1. Yang Shen & Xiaoyang Guo & Xiuwu Zhang, 2023. "Digital Financial Inclusion, Land Transfer, and Agricultural Green Total Factor Productivity," Sustainability, MDPI, vol. 15(8), pages 1-25, April.
    2. Anil Kumar & Suneel Sharma & Mehregan Mahdavi, 2021. "Machine Learning (ML) Technologies for Digital Credit Scoring in Rural Finance: A Literature Review," Risks, MDPI, vol. 9(11), pages 1-15, October.
    3. Majid Bazarbash & Ms. Kimberly Beaton, 2020. "Filling the Gap: Digital Credit and Financial Inclusion," IMF Working Papers 2020/150, International Monetary Fund.
    4. Yuanyuan Peng & H. Holly Wang & Yueshu Zhou, 2022. "Can cooperatives help commercial farms to access credit in China? Evidence from Jiangsu Province," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 70(4), pages 325-349, December.
    5. Liyan Yu & Jerker Nilsson, 2018. "Social capital and the financing performance of farmer cooperatives in Fujian Province, China," Agribusiness, John Wiley & Sons, Ltd., vol. 34(4), pages 847-864, October.
    6. Shen, Zhiyang & Wang, Songkai & Boussemart, Jean-Philippe & Hao, Yu, 2022. "Digital transition and green growth in Chinese agriculture," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    7. Yu, Lili & Zhao, Duanyang & Xue, Zihao & Gao, Yang, 2020. "Research on the use of digital finance and the adoption of green control techniques by family farms in China," Technology in Society, Elsevier, vol. 62(C).
    8. Ortmann, Gerald F. & King, Robert P., 2006. "Small-Scale Farmers in South Africa: Can Agricultural Cooperatives Facilitate Access to Input and Product Markets?," Staff Papers 13930, University of Minnesota, Department of Applied Economics.
    9. Mateos-Ronco, Alicia & Guzman-Asuncion, Sandra, 2018. "Determinants of financing decisions and management implications: evidence from Spanish agricultural cooperatives," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(6), July.
    10. Ortmann, Gerald F. & King, Robert P., 2007. "Agricultural Cooperatives I: History, Theory and Problems," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 46(1), pages 1-29, March.
    11. Yue Wang & Feilong Weng & Xuexi Huo, 2023. "Can Digital Finance Promote Professional Farmers’ Income Growth in China?—An Examination Based on the Perspective of Income Structure," Agriculture, MDPI, vol. 13(5), pages 1-22, May.
    12. Constantin Johnen & Oliver Mußhoff, 2023. "Digital credit and the gender gap in financial inclusion: Empirical evidence from Kenya," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(2), pages 272-295, March.
    13. Kremer, Michael & Jack, William & de Laat, Joost & Suri , Tavneet, 2016. "Borrowing Requirements, Credit Access, and Adverse Selection: Evidence from Kenya," CEPR Discussion Papers 11523, C.E.P.R. Discussion Papers.
    14. Xue Wang & Guangwen He, 2020. "Digital Financial Inclusion and Farmers’ Vulnerability to Poverty: Evidence from Rural China," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
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