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Socially responsible supplier selection and sustainable supply chain development: A combined approach of total interpretive structural modeling and fuzzy analytic network process
Author(s) -
Chen Yuangao,
Wang Shuo,
Yao Jianrong,
Li Yixiao,
Yang Shuiqing
Publication year - 2018
Publication title -
business strategy and the environment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.123
H-Index - 105
eISSN - 1099-0836
pISSN - 0964-4733
DOI - 10.1002/bse.2236
Subject(s) - vagueness , supply chain , fuzzy logic , supply chain management , selection (genetic algorithm) , process (computing) , computer science , sustainable development , analytic network process , social responsibility , supplier relationship management , fuzzy set , management science , process management , business , operations research , economics , analytic hierarchy process , marketing , artificial intelligence , ecology , engineering , operating system , biology
Socially responsible supplier selection and sustainable supply chain development involve extremely important decision‐making processes in supply chain management encompassing many quantitative and qualitative factors to consider. Given the vagueness of experts' opinions and the complex interrelationships among evaluation criteria, this study proposes and illustrates a hybrid model that combines total interpretive structural modeling (TISM) and fuzzy analytic network process (FANP) to determine the most appropriate supplier from a social responsibility perspective. We use TISM to explain the interrelationships among variables and the FANP to calculate specific scores for each candidate. We illustrate an application of the proposed hybrid model using a case study from the Chinese food industry. The result demonstrates the feasibility and effectiveness of combining TISM and the FANP for socially responsible supplier selection. This research may provide managerial insights for practitioners to evaluate suppliers and develop sustainable supply chain strategies.