Prioritizing the barriers to achieve sustainable consumption and production trends in supply chains using fuzzy Analytical Hierarchy Process

Currently, production systems and consumption patterns are based on conventional courses of action and utilize methods and technologies that are generally not sustainable. As a result, Sustainable Consumption and Production (SCP) is becoming an important means by which business organizations prepare for sustainable development. Achieving sustainable consumption and production trends in supply chains is difficult due to the presence of several related barriers. In this contribution, we aim to identify and prioritize the barriers pertaining to the achievement of sustainable consumption and production trends in a supply chain context. In this work, firstly, 30 barriers related to implementing SCP trends in supply chain are recognized. These barriers are derived from a literature survey and from field and industrial experts' inputs. Secondly, an operational model is suggested using the fuzzy Analytical Hierarchy Process to prioritize the identified barriers with the goal of improving overall performance. The fuzzy Analytical Hierarchy Process helps determine the priority of concerns of the identified barriers under fuzzy surroundings. Inputs in this work are based upon an ancillary auto manufacturing firm in India. Research findings indicate that the Organizational barriers dimension obtains the highest priority (i.e., it serves as a key hurdle in achieving SCP trends in supply chains. This work also performs a sensitivity analysis to analyze the priority stability of the given SCP implementation focused barriers. This work presents the most important barrier to efficiently manage SCP initiatives. Accordingly, the proposed model is useful for regulatory bodies, policy makers, and industry managers/practitioners not only to recognize a set of related hurdles they will reasonably encounter, but also to provide a means by which to structure their efforts for the effective accomplishment of SCP trends in a supply chain context. (C) 2017 Elsevier Ltd. All rights reserved.