Designing a green supply chain pricing model with a multi-criteria decision-making approach and game theory (case study: home appliance industry)
نویسندگان
1 Assistant Professor, Department of Industrial Engineering and Future Studies, Faculty of Engineering, University of Isfahan, Isfahan, Iran. Email: goli.a@eng.ui.ac.ir
2 PhD Candidate of Industrial Management, Department of Management, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran. Email: Somayeh.sazegari@gmail.com
3 Associate professor. Department of Management ,Dehaghan Branch, Islamic Azad University, Dehaghan. Email: smrdavoodi@ut.ac.ir
doi
10.22091/jemsc.2024.11144.1191چکیده
pressure to continuously reduce the negative effects of pollutant emissions resulting from their supply chains. The aim of this research is to design a green supply chain pricing model using a multi-criteria decision-making approach and game theory (case study: the home appliance industry). In this study, after conducting a literature review and identifying key indicators for predicting green supply chain pricing, screening of the indicators was carried out in three stages using the fuzzy Delphi method. Out of 20 indicators, 13 were selected based on the opinions of 13 experts. According to the preference selection approach, Company D was identified as the leading company in the game theory due to its highest priority. Ultimately, based on game theory, scenarios among four members of the supply chain were evaluated, and the best and worst scenarios were identified. Additionally, to test the structural validity of the proposed model, information related to the green supply chain of nine selected home appliance companies was executed using MATLAB software. Finally, the analysis of this research based on game theory reveals the challenges currently faced by Company A. In recent years, Iran has encountered multiple challenges regarding sustainable growth. The results indicate that Company A can only achieve a better optimal status if its installed capacity is at least 20% larger than its current level. This will help Company A optimize production and reduce negative environmental impacts.