Please use this identifier to cite or link to this item: http://hdl.handle.net/10739/4988
Title: Critical success factors influencing artificial intelligence adoption in food supply chains
Authors: Dora, Manoj
Kumar, Ashwani
Kumar Mangla, Sachin
Pant, Abhay
Mustafa Kamal, Muhammad
Keywords: Food supply chain
critical success factors
rough theory
TOEH (Technology–Organisation– Environment–Human)
Sustainability
Artificial intelligence;
Issue Date: Aug-2021
Publisher: International Journal of Production Research, Taylor & Francis Group, UK
Citation: Dora, M.; Kumar, A.; Mangla, S.K.; Pant, A. & Kamal, M. M. (2021). Critical success factors influencing artificial intelligence adoption in food supply chains. International Journal of Production Research, (In Press) DOI: https://doi.org/10.1080/00207543.2021.1959665
Abstract: The adoption of Artificial Intelligence (AI) in the food supply chains (FSC) can address unique challenges of food safety, quality and wastage by improving transparency and traceability. However, the technology adoption literature in FSC is still the in infancy stage, meaning little is known about the critical success factors (CSFs) that could affect the adoption of AI in FSC. Therefore, this study makes a pioneering attempt by examining the CSFs influencing the adoption of AI in the Food Supply Chain (FSC). A conceptual framework based on TOEH (Technology–Organisation–Environment–Human) theory is used to determine the CSFs influencing AI adoption in the context of Indian FSC. The rough-SWARA technique was used to rank and prioritise the CSFs for AI adoption using the relative importance weights. The results of the study indicate that technology readiness, security, privacy, customer satisfaction, perceived benefits, demand volatility, regulatory compliance, competitor pressure and information sharing among partners are the most significant CSFs for adopting AI in FSC. The findings of the study would be useful for AI technology providers, supply chain specialists and government agencies in framing appropriate policies to foster the adoption of AI in FSC the sector.
URI: https://doi.org/10.1080/00207543.2021.1959665
http://hdl.handle.net/10739/4988
ISSN: 0020-7543
1366-588X
Appears in Collections:JGU Research Publications

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