Purpose Minimizing food loss and waste (FLW) throughout the food supply chain (FSC) is imperative for achieving global sustainability. While Industry 4.0 technologies offer innovative solutions, a practical understanding of their stage-specific suitability in mitigating FLW remains inadequate. This study examines research trends, applicability and impediments in leveraging these technologies and empirically validates their suitability in advancing SDG 12.3. Design/methodology/approach A multi-stage systematic literature review (SLR) of 122 research papers was employed to identify emerging themes. Subsequently, a structured questionnaire was administered to 34 domain experts, who ranked six technologies: Artificial Intelligence (AI), Big Data Analytics (BDA), Blockchain, Cloud Computing (CC), Internet of Things (IoT) and Digital Twin (DT), across five FSC stages. Kendall's Coefficient of Concordance (W) was utilized to assess expert consensus, followed by the determination of suitable technologies across FSC stages. Finally, a decision support framework (DSF) was developed to guide the selection of technologies. Findings A significant consensus was observed across all FSC stages, with the strongest being in the Consumption, Distribution and Post-Harvest stages. Stage-wise rankings identified Blockchain and BDA as most suitable for Production; DT and IoT for Post-Harvest; AI and DT for Processing; IoT and Blockchain for Distribution; and BDA and AI for Consumption. The DSF demonstrates that each technology occupies a distinct resource quadrant. For example, Blockchain falls in the high capital, moderately high technology and low skills quadrant, etc. This precise mapping aids decision-makers in technology adoption under varying organizational constraints. Originality/value Integrating systematic synthesis with empirical validation, the study develops a novel DSF to guide managers and policymakers in adopting stage-appropriate Industry 4.0 technologies for sustainable operations.
Sarna et al. (Thu,) studied this question.