Hesitant Fuzzy Entropy Analysis of Financial Literacy and Micro-credit Accessibility of Pakistani Farmers: A Bankers’ Perspective

Ali Raza (), Umair Kashif (), Tamar Papiashvili (), Vasilii Erokhin () and Ahmad A. A. Fadol ()
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Ali Raza: Northeast Forestry University
Umair Kashif: Fuzhou University
Tamar Papiashvili: Northeast Forestry University
Vasilii Erokhin: Harbin Engineering University
Ahmad A. A. Fadol: Northeast Forestry University

Journal of the Knowledge Economy, 2025, vol. 16, issue 3, No 61, 12727-12763

Abstract: Abstract This research explores the intricate relationship between financial literacy and micro-credit accessibility for Pakistani farmers, utilizing the specialized analytical approach of hesitant fuzzy entropy (HFE) analysis. This methodological convergence has the potential to transform the lives of farmers, but understanding its dynamics and influential factors poses a complex challenge. The HFE analysis provides a quantitative method for navigating uncertainty in multi-criteria decision-making, offering a systematic framework to evaluate diverse factors while accommodating real-world ambiguity. Hesitant fuzzy entropy values quantify variable importance, directly influencing farmers’ economic well-being. The dataset used in this study includes 39 variables that cover various aspects of financial literacy and microcredit accessibility. The results of the logistic regression analysis show that the education level of farmers is a significant determinant at the 1% level, challenging traditional beliefs. Age has a negative effect on financial literacy at the 10% significance level, providing a new perspective on the relationship between age and financial knowledge. The logistic regression model that assesses factors influencing microcredit accessibility has a strong likelihood ratio of 186.39 and a pseudo-R2 of 56.92%. The significance level (P-value) is 0.000, indicating strong statistical significance. Notably, the probability of accessing microcredit for key variables was quantified: financial education experience has a probability of 35.99%, annual income has a significant impact with a probability of 36.67%, and the requested loan amount influences access with a probability of 16%. This comprehensive analysis contributes to the growing body of literature on financial inclusion, providing valuable insights for policymakers and practitioners.

Keywords: Agriculture; Financial literacy; Food security; Fuzzy entropy; Micro-credit; Multi-attribute decision modeling; Pakistan (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13132-024-02385-y

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