Toward a sustainable supply chain for social credit: learning by experience using single-valued neutrosophic sets and fuzzy cognitive maps

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Abstract

Social credit’s goal of fighting poverty and social inequality has meant that this concept has attracted increasing interest, particularly after Muhammad Yunus was awarded the 2006 Nobel Peace Prize. However, studies that have analyzed the supply chain and socio-economic impacts of this type of micro-credit are still extremely rare. Social credit is an issue that needs to be taken seriously because its objectives differ from those of other types of credit, that is, its main goals go beyond profit to embrace additional social concerns. Adopting a process-oriented stance that used single-valued neutrosophic sets and fuzzy cognitive maps, this study sought to develop a cognitive structure that facilitates a deeper understanding of social credit’s supply chain. Group meetings were held with a panel of professional credit analysts. The resulting framework shows that the socio-technical approach applied provides value for those analyzing the cause-and-effect relationships between the supply chain components of social credit. The results thus contribute to fulfilling social credit’s goals of promoting sustainability and improving human lives. The advantages, managerial implications, and limitations of this research are also discussed.

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Ferreira, F. A. F., & Meidutė-Kavaliauskienė, I. (2019). Toward a sustainable supply chain for social credit: learning by experience using single-valued neutrosophic sets and fuzzy cognitive maps. Annals of Operations Research. https://doi.org/10.1007/s10479-019-03194-2

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