Evaluation of green supply chain of small and medium manufacturing companies based on green productivity indicators using fuzzy inference system

Environmental pollution has become a green motivation to control the pollution increase in countries which its purpose is to reduce the negative effects of environmental pollution; hence, green chain supply management has an important role in the environmental impact of organizations. Therefore, the purpose of this study is to evaluate the green supply chain of small and medium manufacturing companies based on green productivity indicators. This research is based on practical purposes and quantitative research approaches. The statistical sample was designated by 297 small and medium manufacturing companies in East Azerbaijan province. In order to data collection, a researcher-made questionnaire based on the research literature has been used. The validity of the questionnaire was determined based on the validity of the structure and its reliability using Cronbach's alpha coefficient. To evaluate the green supply chain through green productivity indicators, a fuzzy inference system based on triangular membership functions, Mamdani inference and dependency rules has been used. The results show that the designed inference system based on green productivity indicators to evaluate the green supply chain with 43 dependency rules is able to evaluate the greenness measure of the supply chain of companies based on numerical values and linguistic words