An analytical approach to blockchain technology influence on sustainable supply chain

Blockchain technology holds significant potential to enhance sustainable supply chain management (SSCM) by improving traceability, transparency, and regulatory compliance. However, its adoption remains limited due to managerial unfamiliarity and a lack of structured frameworks for implementation. This study develops a novel decision-support model to identify and prioritize key enablers of blockchain adoption in SSCM, combining Fuzzy Cognitive Mapping (FCM) to analyze causal relationships among adoption factors and the Fuzzy Best-Worst Method (FBWM) to quantify their relative weights. Grounded in network theory, our methodology leverages expert insights and empirical data (collected by UN researchers, 2018–2021 by data from 50 agri-food supply chain to evaluate how blockchain can optimize supplier selection and operational efficiency in fuzzy decision environments. Results reveal [insert key finding, e.g., three critical adoption drivers, with emerging as the highest-priority enabler (weight: 0.82), offering actionable insights for overcoming adoption barriers. The study contributes a systematic, data-driven approach to SSCM decision-making, bridging the gap between blockchain theoretical potential and practical implementation. Limitations and future research directions are discussed, emphasizing scalability testing across industries.