A Pythagorean fuzzy AHP approach and its application to evaluate the enablers of sustainable supply chain innovation

Sustainable supply chain innovation (SSCI) simultaneously creates value for social, environmental, and economic dimensions. It is a fact that innovation is very significant in achieving long-term sustainability in the supply chain. Literature analysis reveals that an in-depth investigation of SSCI implementation framework in developing nations is still limited. Hence, this research work investigates the sustainable supply chain innovation enablers (SSCIEs) to achieve sustainability in the supply chain using the Pythagorean fuzzy analytic hierarchy process (AHP) framework. The proposed framework is applied to an Indian manufacturing industry for the adoption of SSCIEs in its supply chain. This research identifies a total of thirty-three SSCIEs through extensive literature review and consultation with the decision-making panel. The identified enablers are then ranked based on their relative importance weight. The results reveal that 'collaboration and engagement of a diverse group of stakeholders (suppliers, local people, customers, environmental specialists, NGOs)' is the most critical SSCIE to achieve sustainability in the supply chain, followed by 'develop R&D labs in relationships with marketing, production, universities, and government institutes'. Sensitivity analysis is also performed in this study to check the robustness in the ranking of SSCIEs. This research helps the managers/policy-makers of the Indian manufacturing industry to identify and understand the most significant SSCIEs to achieve sustainability in the supply chain. The ranking of SSCIEs assists the managers to systematically focus on the most significant SSCIE and work towards its successful adoption. This study implies that the successful adoption of SSCIEs enables simultaneous improvement in social, environmental, and economic dimensions for Indian manufacturing industries. (C) 2020 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.