TY - JOUR
T1 - Understanding the Drivers of Industry 4.0 Technologies to Enhance Supply Chain Sustainability
T2 - Insights from the Agri-Food Industry
AU - Zhao, Guoqing
AU - Chen, Xiaoning
AU - Jones, Paul
AU - Liu, Shaofeng
AU - Lopez, Carmen
AU - Leoni, Leonardo
AU - Dennehy, Denis
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/9/26
Y1 - 2024/9/26
N2 - 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.
AB - 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.
KW - Agri-food supply chains
KW - Fuzzy analytical hierarchy process
KW - Fuzzy cross-impact matrix multiplication applied to classification analysis
KW - Industry 4.0
KW - Total interpretive structural modeling
UR - http://www.scopus.com/inward/record.url?scp=85205082711&partnerID=8YFLogxK
UR - https://pearl.plymouth.ac.uk/context/pbs-research/article/1301/viewcontent/s10796_024_10539_1.pdf
U2 - 10.1007/s10796-024-10539-1
DO - 10.1007/s10796-024-10539-1
M3 - Article
AN - SCOPUS:85205082711
SN - 1387-3326
JO - Information Systems Frontiers
JF - Information Systems Frontiers
ER -