The Role of Artificial Intelligence in Optimizing Logistics Management: A Case Study of VS Cargo Limited in Ndola

Joseph Nyirenda and Fr. Mathew Lungu
Additional contact information
Joseph Nyirenda: School of Business and Information Technology, Cavendish University Zambia
Fr. Mathew Lungu: Corner of Great North and Washama Road, Villa Elizabeth, P.O. Box. 34625, Lusaka, Zambia

International Journal of Research and Innovation in Social Science, 2025, vol. 9, issue 7, 3525-3545

Abstract: This study investigates the role of Artificial Intelligence (AI) in optimizing logistics management, using VS Cargo Limited in Ndola, Zambia as a case study. Despite the global rise of artificial intelligence in streamlining operations, many logistics firms in developing economies, including VS Cargo, face difficulties in adoption due to infrastructure challenges, limited expertise, and resistance to change. The research aims to assess current artificial intelligence usage, identify benefits, explore implementation strategies, and examine challenges that affect the adoption. A positivism research philosophy employed, guided by a deductive approach. The quantitative nature of this philosophy allowed for a comprehensive analysis of AI adoption, its benefits, and challenges faced within a dynamic, technology-driven logistics environment. Quantitative data collected through semi-structured questionnaires administered to 35 employees and 6 managers in VS Cargo’s logistics department was analyzed using frequency distribution and Pearson correlation. The findings revealed that real-time tracking and warehouse automation are the primary AI technologies in use at VS Cargo. These tools contribute significantly to route optimization, improved decision-making, enhanced customer satisfaction, and reduced operational costs. However, the company still faces notable challenges, including limited digital infrastructure, lack of skilled personnel, and poor interdepartmental coordination. The correlation analysis indicated strong relationships between AI adoption and logistics performance indicators, with route optimization showing the highest positive correlation (r = 0.877). The study recommends continuous training for staff, leadership sensitization, infrastructure upgrades, and stronger data management practices. It also advocates for employee engagement, structured AI roadmaps, collaboration with experts, and adequate funding. Addressing these areas will support sustainable AI integration and enhance logistics efficiency.

Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijriss/ ... ssue-7/3525-3545.pdf (application/pdf)
https://rsisinternational.org/journals/ijriss/arti ... go-limited-in-ndola/ (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:bcp:journl:v:9:y:2025:issue-7:p:3525-3545

Access Statistics for this article

International Journal of Research and Innovation in Social Science is currently edited by Dr. Nidhi Malhan

More articles in International Journal of Research and Innovation in Social Science from International Journal of Research and Innovation in Social Science (IJRISS)
Bibliographic data for series maintained by Dr. Pawan Verma ().