Papers

2

Total Citations

31

H-Index

2

About

Pankaj Kumar Detwal is a researcher at the forefront of modern supply chain management, specializing in the integration of machine learning and data-driven techniques to solve complex logistical challenges. His work focuses on enhancing the resilience and efficiency of global supply chains, with a particular emphasis on the pharmaceutical sector. Detwal’s most impactful contribution is his pioneering study on using machine learning to predict vendor incoterms in global omnichannel pharmaceutical supply chains, a paper that has garnered 28 citations for its practical approach to reducing contractual ambiguity and operational risk. He has also authored a comprehensive literature review on data-driven techniques in logistics and supply chain management, underscoring the critical role of technology in navigating today’s dynamic business environment. By addressing the sheer complexity of modern supply chains—from vendor selection to omnichannel distribution—Detwal’s research provides actionable insights for both academics and industry practitioners. His work is particularly notable for bridging the gap between theoretical machine learning models and real-world supply chain applications, making him a key voice in the ongoing digital transformation of logistics.

Research Focus

Key Achievements

2
H-Index
2
Papers
31
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Machine learning-based technique for predicting vendor incoterm (contract) in global omnichannel pharmaceutical supply chain
28 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Malaviya National Institute of Technology Jaipur, Indian Institute of Technology Roorkee

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago