Challenges Facing Artificial Intelligence Adoption during COVID-19 Pandemic: An Investigation into the Agriculture and Agri-Food Supply Chain in India

Debesh Mishra, Kamalakanta Muduli (), Rakesh Raut (), Balkrishna Eknath Narkhede, Himanshu Shee and Sujoy Kumar Jana
Additional contact information
Debesh Mishra: Sri Polytechnic, Komand 752090, India
Kamalakanta Muduli: Department of Mechanical Engineering, Papua New Guinea University of Technology, Lae PMB 411, Morobe Province, Papua New Guinea
Rakesh Raut: Department of Operations and Supply Chain Management, National Institute of Industrial Engineering (NITIE), Mumbai 400087, India
Balkrishna Eknath Narkhede: Industrial Engineering & Manufacturing Systems, National Institute of Industrial Engineering (NITIE), Mumbai 400087, India
Himanshu Shee: Supply Chain and Logistics Management, College of Business, Victoria University Business School, Melbourne 3000, Australia
Sujoy Kumar Jana: Department of Surveying and Land Studies, Papua New Guinea University of Technology, Lae PMB 411, Morobe Province, Papua New Guinea

Sustainability, 2023, vol. 15, issue 8, 1-25

Abstract: The coronavirus (COVID-19) pandemic has witnessed a significant loss for farming in India due to restrictions on movement, limited social interactions and labor shortage. In this scenario, Artificial Intelligence (AI) could act as a catalyst for helping the farmers to continue with their farming. This study undertakes an analysis of the applications and benefits of AI in agri-food supply chain, while highlights the challenges facing the adoption of AI. Data were obtained from 543 farmers in Odisha (India) through a survey, and then interpreted using “Interpretive Structural Modelling (ISM)”; MICMAC; and “Step-Wise-Assessment and Ratio-Analysis (SWARA)”. Response time and accuracy level; lack of standardization; availability of support for big data; big data support; implementation costs; flexibility; lack of contextual awareness; job-losses; affordability issues; shortage of infrastructure; unwillingness of farmers; and AI safety-related issues are some challenges facing the AI adoption in agri-food supply chain. Implications were drawn for farmers and policy makers.

Keywords: agriculture; agri-food supply chain; farmers; Artificial Intelligence; challenges; parameters; AI; ISM; SWARA; India (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/8/6377/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/8/6377/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:8:p:6377-:d:1118474

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().