Analysis of Drivers and Barriers in Green Supply Chain Management Using Fuzzy AHP and Fuzzy TOPSIS Approach

Abstract

Environmental concerns around the world necessitate manufacturing firms to embrace new practices that may lessen the negative environmental effect. These days, green supply chain management (GSCM) is gaining more popularity in the manufacturing sector from material acquisition to product delivery to the customers. Adoption of GSCM by Indian manufacturing firms is comparatively slow due to a lack of identification of different barriers and drivers of GSCM. To this end, the present study aims at the identification of barriers and drivers of GSCM, typical to the Indian scenario. Individual groups of six barriers and eight drivers have been identified for this research by industry experts. In addition, the study prioritizes these enabling factors using multi-criteria decision-making (MCDM) processes such as the analytic hierarchy process (AHP) approach and the technique for order of preference by similarity to ideal solution (TOPSIS) approach. In order to handle the ambiguity in decision-making, the data have been extracted from the experts using linguistic terms. A case of an Indian paper manufacturing firm is considered for this study. The fuzzy AHP (F_AHP) model indicates financial implication and lack of awareness/participation in GSCM as first and last ranked barriers, respectively, whereas the fuzzy TOPSIS (F_TOPSIS) model indicates economic consideration and customer, market and societal pressure as first and last ranked drivers, respectively. Finally, to encapsulate the robustness of the final result, sensitivity analysis has been carried out. This research will undoubtedly assist policymakers in developing policies that will facilitate GSCM implementation.