Advancing Logistics and Supply Chain Efficiency Through Artificial Intelligence and Machine Learning

Dr. Niraj Chaudhari, Mr. Vikram Kalekar, Mr. Nikhil Rane and Mr. Prathamesh More
Additional contact information
Dr. Niraj Chaudhari: Dr. Moonje Institute of Management and Computer studies, Nashik, MS, India
Mr. Vikram Kalekar: Dr. Moonje Institute of Management and Computer studies, Nashik, MS, India
Mr. Nikhil Rane: Dr. Moonje Institute of Management and Computer studies, Nashik, MS, India
Mr. Prathamesh More: Dr. Moonje Institute of Management and Computer studies, Nashik, MS, India

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 7, 607-610

Abstract: The logistics and supply chain ecosystem encompasses a network of interconnected entities that must work collaboratively to enhance operational efficiency and reduce overall costs. This study explores the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in modern supply chain and logistics management. It examines the integration of advanced ML techniques across various supply chain functions such as demand and supply forecasting, pricing strategy formulation, and text analytics. By leveraging these technologies, organizations can streamline processes, mitigate risks, reduce operational costs, and enhance profitability. The research further emphasizes the practical implications of adopting AI and ML, presenting real-world applications that demonstrate their potential in driving data-driven decision-making and achieving competitive advantage in the logistics domain.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.14Issue7/607-610.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-14-issue-7/607-610.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:14:y:2025:i:7:p:607-610

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().