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This Author published in this journals
All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) Bali Journal of Anesthesiology Civil Engineering Journal International Journal of Supply Chain Management Indonesian Journal of Electrical Engineering and Computer Science Journal of Soft Computing Exploration
Kumar, Sanjeev
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Transportation Other

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Journal : International Journal of Supply Chain Management

 1 
Application of Supply Chain Analytics in Agriculture: A Road to Sustainability Kumar, Sanjeev
International Journal of Supply Chain Management Vol 14, No 4 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i4.6335

Abstract

Every aspect of modern human living has now become significantly dependent on the use of data and analytics to reach optimum utility levels. Agriculture, modernized and mechanized over the ages, now makes judicious use of data analytics, particularly on aspects of agricultural supply chain, to improve efficiency. This article focuses on the merits of using supply chain analytics in agriculture. Global agricultural information can be organized and made universally accessible and useful. This article brings out how and why enormous volumes of data should be harnessed to effectively enhance agri SC in a sustainable manner, and benefit not just the customers but also the environment. This article establishes the rationale behind applying SC Analytics (SCA) in Agriculture and prepares the floor for further research on how volumes of agricultural data can be used effectively by corporate giants to implement Blockchain and Al technologies in agri SC.
Middleware Data Platform in Agricultural Supply Chain Kumar, Sanjeev
International Journal of Supply Chain Management Vol 14, No 5 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i5.6340

Abstract

Demographic and climatic changes, changes in resource distribution and soil condition of compost, depleting water resources, greater demand for customized products, need for traceability to maintain food safety and hygiene; all warrant the use of sophisticated modern technologies all along the food supply chain (SC). The integration of IoT, AI and such other technologies with blockchain can significantly improve operational efficiency of agriculture, allowing traceability and ensuring safety and quality control. Such integration also helps to realize maximum benefits from application of modern technologies to make entire agri SC more resilient. Successful application of various technologies hinges on efficient data analytics and technology integration and can be achieved using middleware for technology integration and seamless data flow within the SC. Though promising, it presents significant challenges that need to be handled to realize its full potential. This article establishes middleware data platform’s potential in integrating AI, IoT and blockchain technologies and enhancing operational efficiency of agri SC through enhanced transparency, efficiency, and security. Using a systematic AI-driven data analytics platform Middleware provides diagnostic intelligence to the farmers. Realizing middleware’s potential and utilizing it can greatly enhance functionality and performance of ASC, making it an essential tool for both developers and users. However, the technology being nascent, there is significant dearth of data, literature and evidence regarding the user experience and success rate of middleware, hence a significant knowledge gap. This article contributes towards bridging the gap, setting the floor for further research.
Co-Authors Bansal, Nidhi Dubey, Kriti Harshit, Harshit Kirti, Ravi Kumar, Amarjeet Kumar, Mohit Kumar, Neeraj Manoj Pandey, Manoj Naval, Sanjeev Prasad, Deepak Sahu, Anil Kumar Sharma, Abhay Sharma, Kaushal Sinha, Chandni Upadhyay, Nishant Velinov, Emil