Abstract
Amidst stiff competition, Small and Medium scale Enterprises (SMEs) need to continuously improve their supply chain sustainable performance. Due to customer pressure and government interventions, the focus has also shifted to enhancing the social and environmental performance of the SC. However, the challenge faced by SMEs is to identify the necessary socio-ecological key factors (KF)s required for a better sustainable performance and how to constantly assess the KFs for improving the SC performance. Hence, the research objective of the study is development of a decision model for assessing the social and environmental key factors or Indian SMEs and analyzing their interrelationships. To attain the research objective, the KFs for social and environmental performance are first identified through an extensive literature survey. Further, the KFs are evaluated using fuzzy-DEMATEL technique. The fuzzy-DEMATEL method is used to draw a directed graph for visibly capturing the causal relationships between the multiple KFs. The structural graph helps to portray a contextual relationship among 12 identified KFs including green market trends, business risk protection, and green collaborations. The result reveals that product responsibility and stakeholders’ involvement are both significant factors affecting other factors and play key roles in overall sustainable enhancement of SC for SMEs. The research is based on data collected from an electronics firm, analyzed to extract cause factors, which foster sustainability satisfaction from the SME’s perspective. The results of the study provide a benchmark for decision-makers to estimate the uncertain environment for developing a socio-ecological responsive and performance-driven SC.
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Solanki, R., Darbari, J.D., Agarwal, V., Jha, P.C. (2020). A Fuzzy Multi-criteria Decision Model for Analysis of Socio-ecological Performance Key Factors of Supply Chain. In: Das, K., Bansal, J., Deep, K., Nagar, A., Pathipooranam, P., Naidu, R. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1048. Springer, Singapore. https://doi.org/10.1007/978-981-15-0035-0_55
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DOI: https://doi.org/10.1007/978-981-15-0035-0_55
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