Using Internet of Things (IoT) in agri-food supply chains: a research framework for social good with network clustering analysis

Yadav, Sanjeev, Choi, Tsan-Ming, Luthra, Sunil, Kumar, Anil and Garg, Dixit (2023) Using Internet of Things (IoT) in agri-food supply chains: a research framework for social good with network clustering analysis. IEEE Transactions on Engineering Management, 70 (3). pp. 1215-1224. ISSN 0018-9391

Abstract

Agri-Food Supply Chains (AFSCs) are critical in our society. Proper management of AFSCs is crucial for improving social welfare. Over the past years, digitisation in AFSCs has emerged as a new paradigm. In this context, the Internet of Things (IoT) is a growing approach, providing a huge amount of information to manage AFSCs. Thus, the purpose of this paper is to examine extensive studies on IoT-based AFSC by notable academics in the form of leading participating institutions, authors, keywords, journals, and citation statistics. Our bibliometric based systematic approach starts with the identification of 346 articles in the relevant field from the Web of Science (WoS) database by applying rigorous filtration. Using the VOS viewer software, a network analysis has been performed for the above fields. With seven identified clusters, this article recognized the role of IoT technologies as Cluster 1: Agri-food safety, traceability and sustainability; Cluster 2: AFSC sustainability; Cluster 3: AFSC performance measurement; Cluster 4: AFSC resilience in disruption; Cluster 5: AFSC integration and traceability; Cluster 6: AFSC transparency and coordination and finally Cluster 7 identified the barriers in IoT adoption. Thus, findings of this study offer robust guidance to link IoT technologies and AFSCs together. Based on these findings, propositions are proposed and a research framework is established. We believe the findings would help engineering managers, researchers and government regulating bodies better plan and manage AFSCs for social good.

Documents
7542:39051
[thumbnail of TEM-Manuscript-agri-R1.doc]
TEM-Manuscript-agri-R1.doc - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (2MB)
Details
Record
View Item View Item