Evaluating the green supply chain of small and medium-sized manufacturing companies using a combination of association rule mining and fuzzy inference system from the perspective of environmental sociology

Environmental legal regulations, stakeholder pressures, and globalization have led firms and organizations to develop environmental practices and practices; Accordingly, the purpose of this paper is to evaluate the green supply chain of small and medium-sized manufacturing companies using a combination of dependency rules and fuzzy inference system. This research has been applied from the point of view of purpose and based on the method of conducting descriptive modeling research. The statistical population of this study included all small and medium production companies in East Azarbaijan province. Stati.stical sample of 297 companies has been determined. A researcher-made questionnaire was used to collect the data. To investigate the validity of the questionnaire, the validity of the structure was used based on confirmatory factor analysis. Cronbach's alpha coefficient was also used to evaluate the reliability. The research questionnaires were distributed among the members of the statistical sample after confirmation of validity and reliability. In order to evaluate the green supply chain of companies, fuzzy inference system has been used based on triangular membership functions, Mamdani inference and dependency rules. The results show that a system designed with 43 dependency rules is able to assess the greenness of a company's supply chain based on numerical values and linguistic terms