The DOI matches its Crossref record; 87 of the 87 references it cites were found in a registry or an index.
Critical success factors influencing artificial intelligence adoption in food supply chains
Open accessAbstract
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.
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Cites
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Artificial Intelligence in Supply Chain Management: A Systematic Literature Review
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Cited by
Dey, P. K., Chowdhury, S., Abadie, A., Vann Yaroson, E., & Sarkar, S. (2024) · International Journal of Production Research · doi:10.1080/00207543.2023.2179859 · Cited by 330
Data-driven optimal dynamic pricing strategy for reducing perishable food waste at retailers
Kayikci, Y., Demir, S., Mangla, S. K., Subramanian, N., & Koc, B. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.131068 · Cited by 125
Self-citationAI Adoption in Jordanian SMEs: The Influence of Technological and Organizational Orientations
Almashawreh, R., Talukder, M., Charath, S. K., & Khan, M. I. (2024) · Global Business Review · doi:10.1177/09721509241250273 · Cited by 39
Harnessing Artificial Intelligence to Safeguard Food Quality and Safety
Singh, D. (2025) · Journal of Food Protection · doi:10.1016/j.jfp.2025.100621 · Cited by 37
Metadata
- Authors
- Dora, M., Kumar, A., Mangla, S. K., Pant, A., & Kamal, M. M.
- Venue
- International Journal of Production Research
- Publisher
- Informa UK Limited
- Published
- 2021-08-10
- Volume
- 60
- Issue
- 14
- Pages
- 4621-4640
- ISSN
- 0020-7543 (ISSN-L)
- 1366-588X
- OpenAlex
- W3184144688
- Cited by
- 294
- References
- 87
- FWCI
- 21.81
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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