Understanding the Drivers of Industry 4.0 Technologies to Enhance Supply Chain Sustainability: Insights from the Agri-Food Industry

Guoqing Zhao (), Xiaoning Chen, Paul Jones, Shaofeng Liu, Carmen Lopez, Leonardo Leoni and Denis Dennehy
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Guoqing Zhao: Swansea University
Xiaoning Chen: University of Plymouth
Paul Jones: Swansea University
Shaofeng Liu: University of Plymouth
Carmen Lopez: University of Southampton
Leonardo Leoni: University of Florence
Denis Dennehy: Swansea University

Information Systems Frontiers, 2025, vol. 27, issue 4, No 15, 1619-1649

Abstract: Abstract The sustainability of agri-food supply chains (AFSCs) is severely threatened by regional and global events (e.g., conflicts, natural and human-made disasters, climate crises). In response, the AFSC industry is seeking digital solutions using Industry 4.0 (I4.0) technologies to enhance resilience and efficiency. However, why I4.0 adoption remains stubbornly low in the agri-food industry remains poorly understood. To address this gap, this study draws on middle-range theory (MRT) and uses thematic analysis, the fuzzy analytic hierarchy process, total interpretive structural modelling, and fuzzy cross-impact matrix multiplication applied to classification to produce insights from nine case studies in China that have invested in I4.0 technologies to improve their AFSC sustainability. New drivers of I4.0 unique to the agri-food industry are identified, showing how I4.0 can contribute to the environmental, economic, and social dimensions of AFSC sustainability. The results have implications for AFSC researchers and practitioners with an interest in supply chain sustainability.

Keywords: Industry 4.0; Agri-food supply chains; Fuzzy analytical hierarchy process; Total interpretive structural modeling; Fuzzy cross-impact matrix multiplication applied to classification analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10796-024-10539-1

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