A decision framework for selecting Industry 4.0 technologies in perishable goods reverse logistics

Purpose This study aims to develop a structured decision-support framework to prioritize Industry 4.0 technologies (I4.0Ts) for reverse logistics operations in perishable-goods supply chains. These supply chains face unique challenges, including product perishability, unpredictable return flows, and the need for real-time monitoring and sustainability. Design/methodology/approach A mixed-method approach was adopted, combining a systematic literature review with expert validation to define relevant evaluation criteria based on the Technology–Organization–Environment (TOE) framework, which was extended to include scalability and social acceptance dimensions. The Fuzzy Analytic Hierarchy Process (FAHP) was used to weight five main and 14 sub-criteria, and the Fuzzy TOPSIS (FTOPSIS) was applied to rank four I4.0Ts: IoT, Blockchain, AGVs, and Big Data. Findings The results reveal that cost-effectiveness, scalability, and technological feasibility are the most influential criteria in technology selection. Among the evaluated alternatives, IoT and Blockchain emerged as the top-ranked technologies due to their strong alignment with the needs for traceability, monitoring, and operational responsiveness in perishable reverse logistics. Originality/value This study proposes a comprehensive, criteria-driven framework specifically for evaluating and prioritizing I4.0Ts in the context of reverse logistics for perishable goods. It contributes to the literature by integrating the TOE framework with fuzzy multi-criteria decision-making methods, providing actionable insights for technology selection in complex, time-sensitive supply chains.