Journal article 181 views
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,
Denis Dennehy
Information Systems Frontiers
Swansea University Authors: Guoqing Zhao , Paul Jones , Denis Dennehy
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DOI (Published version): 10.1007/s10796-024-10539-1
Abstract
The sustainability of agri-food supply chains (AFSCs) is severely threatened by regional and global events (e.g., conficts, 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...
Published in: | Information Systems Frontiers |
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Published: |
Springer
2024
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Online Access: |
https://link.springer.com/article/10.1007/s10796-024-10539-1#citeas |
URI: | https://cronfa.swan.ac.uk/Record/cronfa66992 |
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Abstract: |
The sustainability of agri-food supply chains (AFSCs) is severely threatened by regional and global events (e.g., conficts, 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 efciency. 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 classifcation 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 identifed, 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. |
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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 |
College: |
Faculty of Humanities and Social Sciences |
Funders: |
Swansea University |