TY - GEN
T1 - Analysis of the Drivers of Industry 4.0 Technology Deployment to Achieve Agri-Food Supply Chain Sustainability
T2 - 29th Annual IEEE International Symposium on Technology and Society, ISTAS 2023
AU - Zhao, Guoqing
AU - Jones, Paul
AU - Liu, Shaofeng
AU - Lopez, Carmen
AU - Dennehy, Denis
AU - Chen, Xiaoning
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/9/13
Y1 - 2023/9/13
N2 - Agri-food supply chains (AFSCs) are struggling to achieve sustainability in the face of increasing social, environmental, and economic challenges. Industry 4.0 technologies are widely deployed to monitor, assess, and analyze their operational process, and thereby drive sustainable value. This study adopts a hybrid approach to analyze the drivers of industry 4.0 technology deployment to achieve AFSC sustainability. Thematic analysis of 24 interviews was carried out to identify 13 drivers, and these were used as inputs into the fuzzy analytic hierarchy process (AHP), total interpretive structural modeling (TISM), and fuzzy cross-impact matrix multiplications applied to classification (MICMAC). The results show that enhancing efficiency of water and fertilizer use, reducing carbon emissions, and reducing work intensity contribute significantly to economic, environmental, and social aspects of sustainability. We also identify that government subsidies for agricultural facilities and strengthening of farmers' agri-tech skills are key drivers that should be given priority.
AB - Agri-food supply chains (AFSCs) are struggling to achieve sustainability in the face of increasing social, environmental, and economic challenges. Industry 4.0 technologies are widely deployed to monitor, assess, and analyze their operational process, and thereby drive sustainable value. This study adopts a hybrid approach to analyze the drivers of industry 4.0 technology deployment to achieve AFSC sustainability. Thematic analysis of 24 interviews was carried out to identify 13 drivers, and these were used as inputs into the fuzzy analytic hierarchy process (AHP), total interpretive structural modeling (TISM), and fuzzy cross-impact matrix multiplications applied to classification (MICMAC). The results show that enhancing efficiency of water and fertilizer use, reducing carbon emissions, and reducing work intensity contribute significantly to economic, environmental, and social aspects of sustainability. We also identify that government subsidies for agricultural facilities and strengthening of farmers' agri-tech skills are key drivers that should be given priority.
KW - agri-food supply chain sustainability
KW - fuzzy AHP
KW - fuzzy MICMAC
KW - industry 4.0 technologies
KW - TISM
UR - http://www.scopus.com/inward/record.url?scp=85178514442&partnerID=8YFLogxK
U2 - 10.1109/ISTAS57930.2023.10306146
DO - 10.1109/ISTAS57930.2023.10306146
M3 - Conference proceedings published in a book
AN - SCOPUS:85178514442
T3 - International Symposium on Technology and Society, Proceedings
BT - 2023 IEEE International Symposium on Technology and Society, ISTAS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 13 September 2023 through 15 September 2023
ER -
