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

Muhammad Naseem, Jiequn Guo, Shu Hui, Mario Callefi, Xiang Ziquan and Moacir Godinho Filho ()
Additional contact information
Muhammad Naseem: CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne
Jiequn Guo: NBU - Ningbo University
Shu Hui: JUFE - Jiangxi University of Finance and Economics
Mario Callefi: TU Chemnitz - Chemnitz University of Technology / Technische Universität Chemnitz
Xiang Ziquan: GZU - Guizhou University
Moacir Godinho Filho: Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School

Post-Print from HAL

Abstract: 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.

Keywords: Fuzzy TOPSIS; Fuzzy AHP; Perishable goods; Reverse logistics; Industry 4.0 (search for similar items in EconPapers)
Date: 2026
Note: View the original document on HAL open archive server: https://hal.science/hal-05549682v1
References: Add references at CitEc
Citations:

Published in Journal of Enterprise Information Management, 2026, pp.1-38. ⟨10.1108/jeim-11-2025-1104⟩

Downloads: (external link)
https://hal.science/hal-05549682v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05549682

DOI: 10.1108/jeim-11-2025-1104

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().