Skip to main content

Advertisement

Log in

Enabling artificial intelligence for sustainable food grain supply chains: an agri 5.0 and circular economy perspective

  • Published:
Operations Management Research Aims and scope Submit manuscript

Abstract

The majority of the food grain supply chain (FGSC) is run in a linear fashion, requiring substantial inputs that produce mostly inedible by-products, environmental damage and wastage. Moreover, population increase, declining food resources, shifting weather patterns, and dwindling supplies pose serious problems to the FGSC. Effective usage and consumption of resources to harmonize ecological, economic, and social elements is the need of the hour from the Agri 5.0 and circular economy (CE) perspective. Fortunately, modern technological developments like artificial intelligence (AI) might represent a paradigm change in this context. However, enablers for AI adoption haven't been studied sufficiently despite AI's popularity. Hence, the fundamental objective of this research is to identify and examine key enablers that facilitate rapid AI adoption in FGSC, empowering Agri 5.0 and CE in India. The primary facilitators for AI adoption have been explored via a literature review and expert interviews followed by a questionnaire survey. The fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) approach was then used to create a causal model of the identified enablers. The F-DEMATEL method helps resolve the uncertainty of researching enabler interactions. Research findings suggest that “Legal and regulatory interventions from the government (E7)” and “Green IoT-driven total automation (E5)” have a significant influence in integrating AI in FGSC. The results have major ramifications for policymakers. The results may be used to justify future investments and will also aid decision-makers in India in advancing AI initiatives.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

All the data has been provided in manuscript.

References

Download references

Author information

Authors and Affiliations

Authors

Contributions

Sumanta Das, Ideas, Writing– Original draft preparation, Conceptualization, Formal analysis Dr. Akhilesh Barve, Formal Analysis, Visualization Supervision, Project Administration Dr. Naresh Chandra Sahu, Review editing, Formal Analysis Dr Kamalakanta Muduli, Critical review, Data Curation, Validation, Commentary and Revision.

Corresponding author

Correspondence to Kamalakanta Muduli.

Ethics declarations

Ethics approval

All authors follow the ethics in the research and provide consent to participate in the research.

Consent to participate

All authors provide consent for publication.

Conflicts of interest/Competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Das, S., Barve, A., Sahu, N.C. et al. Enabling artificial intelligence for sustainable food grain supply chains: an agri 5.0 and circular economy perspective. Oper Manag Res 16, 2104–2124 (2023). https://doi.org/10.1007/s12063-023-00390-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12063-023-00390-z

Keywords

Navigation