Suresh Kumar Jakhar
Papers
1
Total Citations
28
H-Index
1
About
Suresh Kumar Jakhar is a prominent researcher in supply chain management, with a specialized focus on the integration of machine learning and artificial intelligence into global logistics and pharmaceutical supply chains. His work addresses critical challenges in omnichannel distribution, particularly in predicting vendor incoterms—the contractual terms governing international trade—using advanced computational techniques. His most-cited paper, "Machine learning-based technique for predicting vendor incoterm (contract) in global omnichannel pharmaceutical supply chain" (2023), has garnered 28 citations, reflecting its timely relevance to both academia and industry. This contribution stands out for its practical application of predictive analytics to enhance transparency, reduce risk, and optimize decision-making in complex, multi-echelon supply networks. Jakhar’s research bridges the gap between theoretical modeling and real-world operational efficiency, making him a key voice in the digital transformation of supply chains. His work is particularly valuable for students and practitioners seeking to understand how data-driven methods can solve traditional logistics problems, and it underscores his commitment to advancing sustainable and resilient supply chain systems.
Research Focus
Key Achievements
Top Papers
- 1