IJCOPE Journal

UGC Logo DOI / ISO Logo

International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
Journal Information
ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 05

Published on: May 2026

A STUDY OF WORKING CAPITAL MANAGEMENT: A STUDY ON INTELLIGENT FLEET OPERATION AND AI-DRIVEN LOGISTICS OPTIMIZATION

Remanciya A

Dr. Daneesh V

School of Management, Dhanalakshmi Srinivasan University, Tiruchirappalli, Tamil Nadu – 621112.

Article Status

Plagiarism Passed Peer Reviewed Open Access

Available Documents

Abstract

Working capital management is a critical financial strategy that directly impacts the operational efficiency and profitability of logistics and fleet-based organizations. With the growing adoption of Artificial Intelligence (AI) and data analytics in transportation, companies are increasingly leveraging intelligent fleet operations to optimize costs, reduce idle time, and improve delivery efficiency. This study examines the relationship between working capital management practices and AI-driven logistics optimization in the context of intelligent fleet operations. It explores how organizations manage short-term assets and liabilities while implementing smart logistics solutions such as route optimization, predictive maintenance, and fuel management systems. The study highlights the financial implications of AI integration in fleet management and offers strategic insights for improving working capital efficiency.

Keywords: Working Capital Management, AI-Driven Logistics, Fleet Optimization, Intelligent Transportation, Route Optimization, Predictive Maintenance, Financial Efficiency, Logistics Automation

How to Cite this Paper

A, R. (2026). A Study of Working Capital Management: A Study on Intelligent Fleet Operation and AI-Driven Logistics Optimization. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.863

A, Remanciya. "A Study of Working Capital Management: A Study on Intelligent Fleet Operation and AI-Driven Logistics Optimization." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.863.

A, Remanciya. "A Study of Working Capital Management: A Study on Intelligent Fleet Operation and AI-Driven Logistics Optimization." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.863.

Search & Index

References


  • Chopra, S., & Meindl, P. (2021). Supply Chain Management: Strategy, Planning, and Operation (7th ed.). Pearson Education.

  • Singh, R., & Kumar, A. (2022). Predictive Maintenance in Fleet Management: A Financial Perspective. Journal of Logistics and Supply Chain Management, 14(2), 45-62.

  • Zhang, L., Liu, Y., & Wang, H. (2022). Route Optimization Using AI: Cost Implications for Logistics Firms. Transportation Research Record, 78(3), 112-128.

  • Mehta, P., & Shah, R. (2022). Working Capital Dynamics in AI-Integrated Logistics Companies. International Journal of Finance and Accounting, 11(1), 33-49.

  • Gupta, N., & Rao, K. (2023). Fleet Data Analytics and Cash Conversion Cycle Optimization. Journal of Business and Financial Management, 5(2), 78-93.

  • Patel, D., & Thomas, J. (2023). Vendor Payment Management in Intelligent Fleet Organizations. Asian Journal of Logistics Research, 9(1), 22-37.

  • Reddy, M., & Nair, S. (2023). Autonomous Scheduling and Fleet Efficiency: A Working Capital Analysis. International Journal of Transportation Management, 6(4), 55-71.

  • Williams, A., & Chen, B. (2023). Liquidity Management in AI-Enabled Logistics: A Comparative Study. Journal of Operations and Financial Research, 13(3), 101-118.

  • Kumar, V., & Fernandez, G. (2023). Proactive Financial Decision-Making with AI Analytics in Fleet Management. Global Business Review, 24(1), 66-82.

  • Sharma, T., & Roy, P. (2024). Sustainable Working Capital Frameworks through AI Fleet Integration. Journal of Sustainable Finance and Logistics, 3(1), 11-28.

Ethical Compliance & Review Process

  • All submissions are screened under plagiarism detection.
  • Review follows editorial policy.
  • Authors retain copyright.
  • Peer Review Type: Double-Blind Peer Review
  • Published on: May 31 2026
CCBYNC

This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

View License
Scroll to Top