基于单值嗜中性集的多属性群体决策的MABAC新方法:在小额信贷群体贷款绩效评估中的应用

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-09-14 DOI:10.3233/kes-221609
Hui Ran
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引用次数: 0

摘要

在40年的全球小额信贷实践中,贷款技术作为小额信贷最重要的支撑要素之一,发挥了积极的作用。小额信贷机构贷款技术的发展和演变是特定区域经济、社会、文化和地理因素综合考虑的结果。在小额信贷技术走向多元化的背景下,合理选择贷款技术,探索灵活的担保条件,创新多样化的贷款技术组合,将成为小额信贷机构面临的现实问题,也是理论研究的方向。小额信贷群体贷款技术的适时创新,对于推动中国乡村振兴战略实施中金融农产品的创新,弥合小额信贷技术的理论争议,具有现实价值和理论意义。小额信贷集团贷款绩效评价是一个MAGDM问题。本文采用单值中性粒细胞集(SVNSs)的距离测度和偏差最大化法(MDM)获得属性权重值。在经典的多属性边界近似面积比较(multi - attribute Border Approximation area Comparison, MABAC)方法的基础上,构造了svns下MAGDM的单值嗜中性数MABAC (SVNN-MABAC)方法。最后,以小额信贷集团贷款绩效评价为例,通过比较决策分析对SVNN-MABAC模型进行了验证。
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A novel MABAC approach for multi-attribute group decision-making with single-valued neutrosophic sets: An application in assessing microfinance group lending performance
In the 40 years of global microcredit practice, loan technology has played a positive role in microcredit as one of the most important supporting elements. The development and evolution of microcredit institution lending technology is the result of comprehensive consideration of specific regional economic, social, cultural, and geographical factors. In the context of the diversified trend of microcredit technology, choosing loan technology reasonably, exploring flexible guarantee conditions, and innovating diversified loan technology combinations will become practical problems faced by microcredit institutions, and also the direction of theoretical research. The timely innovation of group loan technology in microcredit has practical value and theoretical significance for promoting the innovation of financial agricultural products in the implementation of China’s rural revitalization strategy, as well as bridging the theoretical controversy of microcredit loan technology. The performance evaluation of microfinance groups lending is a MAGDM issues. In this paper, the distances measures of single-valued neutrosophic sets (SVNSs) and maximizing deviation method (MDM) is used to obtain the attribute weight values. Based on the classical Multi-Attributive Border Approximation area Comparison (MABAC) method, the single-valued neutrosophic numbers MABAC (SVNN-MABAC) method is constructed for MAGDM under SVNSs. Finally, an example for performance evaluation of microfinance groups lending and some comparative decision analysis are constructed to verify the SVNN-MABAC model.
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