Design of Fuzzy Inference System for Green Supply Chain Evaluation of Export Manufacturing Companies

• Published in: Journal of Industrial Management Perspective Vol. 11; no. 2; pp. 125 - 144
• Main Authors: Narimani Ghourtoular, Easa, Feg-Hi Farahmand, Naser, Pilevari, Nazanin, Rahmani, Kamaleddin, Motadel, Mohammad Reza
• Format: Journal Article
• Language: English; Persian
• Published: Shahid Beheshti University 22.06.2021
• Subjects: export manufacturing companies. input operation; fuzzy inference system; green supply chain; output operations; production operations
• ISSN: 2251-9874; 2645-4165
• DOI: 10.52547/jimp.11.2.125

This paper aims to design a fuzzy inference system to evaluate the green supply chain of export manufacturing companies. This research has been applied from the point of view of purpose. The statistical population of this study included export manufacturing companies in the northwest of the country. The statistical sample is targeted, and 143 companies are determined. A research questionnaire based on the research literature was used to collect the data. In order to examine the validity of the questionnaire, while using formal validity, the validity of the structure has been used based on confirmatory factor analysis. Cronbach's alpha coefficient was also used to evaluate the reliability of the questionnaire. The research questionnaires were distributed among the statistical sample members of the research after confirming the validity and reliability. In order to evaluate the green supply chain of companies, a fuzzy inference system has been used based on triangular membership functions and Mamdani inference. The results show that the designed system is able to show how green the supply chain of companies is based on numerical values ​​and linguistic terms.