Risk analysis in green supply chain using fuzzy AHP approach: A case study

Due to increase in customer environmental awareness, competitiveness and strict governmental policies, the approach of incorporating green supply chain management (GSCM), to conserve resources and sustainable production, is gradually becoming more imperative for organizations. However, the successful accomplishment of green supply chain (GSC) production and business activities is relatively difficult due to involvement of different risks. These risks and their respective sources have a tendency to disturb the GSC functioning, and thereby, decline in the ecological-economic performance. Therefore, identification of risks and their subsequent analysis in the GSC are very important to know and understand. The present research analyzes the risks relevant to adoption and effective implementation of GSC practices at industrial viewpoint. A two-phase research approach has been proposed and used in this study. In the first phase, six categories of risks and twenty-five specific risks, associated with the GSC, were identified. The basis of identification of the risks was literature and inputs received from experts from industries. Experts' opinion has been collected from the officials and managers of four Indian poly product-manufacturing companies. In the second phase, the fuzzy analytic hierarchy process (fuzzy AHP), a qualitative and quantitative analysis was used to analyze the identified risks for determining of their priority of concern. The used fuzzy AHP approach is also useful in dealing with the human subjectivity and ambiguity involved in the process of risk analysis. In this research, an effort has been made to know the most important risk in GSC context, and the findings would be useful for industries in managing and reducing the consequences of the risks in GSC. The analysis of the results indicates that operational category risks are the most important risks in GSC. Sensitivity analysis is also conducted to examine the priority ranking stability. (C) 2015 Elsevier B.V. All rights reserved.