Overcoming net-zero emission challenges in healthcare supply chains: a q-rung orthopair fuzzy Einstein-CPT approach

Abstract

This study develops a multi-criteria decision-making (MCDM) framework to prioritize supply chain management practices (SCMPs) aimed at overcoming barriers to achieving net-zero emissions (NZE) in Thailand’s healthcare sector. Grounded in an extensive literature review and guided by three strategic management theories: resource-based view (RBV), resource dependency theory (RDT), and institutional theory (INT), this research identifies twelve key barriers across intra-organizational, inter-organizational, and institutional dimensions, along with nine essential SCMPs. To evaluate the relationships and importance of these barriers, the study employs integrates the fuzzy Einstein-based logarithmic methodology of additive weights (fuzzy Einstein-LMAW) for weight computation. Cumulative prospect theory (CPT) is utilized within a q-rung orthopair fuzzy sets (q-ROFS-CPT) framework to rank the SCMPs. Findings reveal that the most significant barrier is the ‘fragmented supply chain’, followed by ‘limited visibility and data transparency’ and the ‘absence of a nationwide NZE healthcare industry standard’. The highest priority SCMP is ‘integrating NZE with hospital accreditation standards’, succeeded by ‘supplier collaboration’ and ‘sustainable supply chain knowledge management’. These insights aid healthcare managers in refining policies and developing roadmaps for NZE adoption, while also providing a foundation for academia to explore context-specific barriers and formulate tailored SCMP strategies across different healthcare settings.