A hybrid framework for prioritizing the solutions to mitigate sustainable supply chain barriers in industry 5.0

摘要

Industry 5.0 is a potential framework that aims to envision the most advanced industrial, transportation, energy-efficient, and sustainable supply chain (SSC) of the future. Industry 5.0 and SSC are essential ideas that are revolutionizing the operational strategies of enterprises in the modern day. Concurrently, these two principles propel the development of a very sustainable and resilient global economy. Contemporary organizations are increasingly adopting sustainable practices in the supply chain by using technology such as blockchain, artificial intelligence (AI), and collaborative robots (co-bots) to trace the source of products, guarantee ethical and sustainable sourcing and procurement, and efficiently and securely collaborate with humans. Focusing on the goal of sustainability, the current study utilized a three-step methodology and a hybrid framework to rank solutions for overcoming SSC barriers in the pharmaceutical industry supply chain. We conduct a comprehensive literature review to identify the barriers and solutions, then finalize them using the Delphi technique. The current study finalized 16 SSC barriers and 14 solutions. The fuzzy analytical hierarchy process (FAHP) is used to prioritize barriers and calculate the weight of each barrier. The main challenge that obstructs the adoption of SSC into practice is higher initial investment and unclear return on investments. The current study used Extended PROMETHEE II (EXPROM2) for prioritization of SSC solutions. The solution ranking indicates that governmental assistance and public–private partnerships are the most effective approaches for overcoming the listed barriers. Additionally, a sensitivity analysis is conducted to assess the appropriateness of the final findings of the current study. The current findings will allow organizations to pinpoint the most troublesome barriers and therefore implement solutions that may mitigate their severity.