A Green Supply Chain Member Selection Method Considering Green Innovation Capability in a Hesitant Fuzzy Environment

• Published in: Axioms Vol. 12; no. 2; p. 188
• Main Authors: Su, Jiafu, Xu, Baojian, Li, Lvcheng, Wang, Dan, Zhang, Fengting
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2023
• Subjects: attribute weight optimization; Carbon; Clean technology; Climate change; Cooperation; Decision making; Efficiency; Environmental impact; Fuzzy algorithms; Fuzzy logic; Fuzzy sets; Fuzzy systems; green innovation capability; green supply chain; hesitant fuzzy multi-attribute decision making; Innovations; Management; Manufacturers; Manufacturing; Methods; Optimization; Product life cycle; R&D; Ranking; Research & development; Society; Suppliers; Supply chain management; Supply chains; three-point estimation method; China; United States > US
• ISSN: 2075-1680; 2075-1680
• DOI: 10.3390/axioms12020188

The purpose of this paper is to propose an improved hesitation fuzzy multi-attribute decision-making method to realize green supply chain member selection under green innovation vision. The method uses hesitation fuzzy sets to express decision information of decision makers, takes green innovation capability as the evaluation perspective, and selects green innovation input, synergy of subjects in green supply chain, green innovation output capability, institutional innovation capability of enterprises in green supply chain, and green innovation sustainability as the indexes to evaluate the green innovation capability of enterprises. The multi-attribute decision method proposed in this paper takes into account the shortcomings of the original hesitant fuzzy multi-attribute decision method considering attribute weight optimization in the determination of attribute weights and scheme ranking, then proposes a three-point estimation method for scheme ranking and optimizes the attribute weights by quantifying the balance coefficients of the original decision method. Finally, an example is used to verify the rationality and effectiveness of the proposed method, and a comparison with the original method is made to highlight the advantages of this paper’s method. This paper provides a certain theoretical basis for the selection of members in green supply chains, which helps the selection of members in green supply chains and provides some insight for similar hesitant fuzzy multi-attribute decision-making problems in other fields. In future research, the method proposed in this paper can be considered to combine with probabilistic hesitant fuzzy sets and some other fuzzy sets for method extensions to solve multi-attribute decision-making problems.