Reduction of Transportation Cost: Examinig the Moderating Role of Artificial Intelligence (AI) Implementation in Bangladesh
DOI:
https://doi.org/10.54097/z0q2k057Keywords:
Transportation Cost Reduction, Route and Node Optimization, Shipment Consolidation, Demand Forecasting, Artificial Intelligence (AI), Logistics Strategies, Cost Efficiency, AI Implementation, Logistics SectorAbstract
This study investigates the role of logistics strategies Route and Node Optimization, Shipment Consolidation, and Demand Forecasting in reducing transportation costs in the logistics sector of Bangladesh. It also explores the moderating effect of Artificial Intelligence (AI) on the effectiveness of these strategies. With the increasing complexity of logistics operations and the growing need for cost-efficient practices, this research highlights how traditional logistics methods can be augmented with advanced AI technologies to optimize operations and achieve significant cost reductions. Data were collected through structured surveys involving 300 respondents from logistics companies in Bangladesh. Using Principal Component Analysis (PCA) and Multiple Regression Analysis, the relationships between the independent variables (logistics strategies), the moderating variable (AI implementation), and the dependent variable (Transportation Cost Reduction) were evaluated. The results reveal that Shipment Consolidation had the most significant impact on transportation cost reduction, followed by Demand Forecasting and Route and Node Optimization. AI implementation was found to positively moderate these relationships, enhancing the efficiency of each strategy. The findings underscore the transformative potential of AI in logistics operations, particularly in developing economies. The study contributes to both theory and practice by providing actionable recommendations for integrating AI into logistics to achieve cost efficiency. Future research directions are suggested, including exploring longitudinal impacts and expanding the study scope to other regions.
Downloads
References
[1] Guan, X., Zhang, X., & Sun, Y. (2020). Artificial intelligence in logistics and supply chain management: A comprehensive review. International Journal of Production Research, 58(24), 7425-7444.
[2] Hosseini, S., & Vahdani, B. (2020). A data-driven approach to the optimization of transportation costs using artificial intelligence. Transportation Research Part E: Logistics and Transportation Review, 141, 102020.
[3] Zhang, L., & Li, Z. (2021). Optimization of transportation routing with AI-based predictive analytics. Transportation Research Part C: Emerging Technologies, 126, 103084.
[4] Li, Y., & Zeng, Q. (2021). AI applications in supply chain management: Benefits, challenges, and future directions. Journal of Business Logistics, 42(1), 56-78.
[5] Choi, T. M., & Guo, Y. (2020). AI-enabled supply chain optimization and transportation cost reduction. International Journal of Logistics Management, 31(3), 674-692.
[6] Xie, J., & Wang, J. (2020). Using machine learning techniques for optimizing transportation routes in urban logistics. Transportation Research Part B: Methodological, 132, 156-172.
[7] Kusuma, S. D., & Muneer, S. (2020). Artificial intelligence in logistics: A review of AI-based approaches for transportation optimization. International Journal of Logistics Research and Applications, 23(4), 348-368.
[8] Yang, X., & Xie, X. (2021). Optimization of multi-modal transport networks using artificial intelligence. Journal of Intelligent Transportation Systems, 25(2), 136-150.
[9] Liu, H., & Wang, Z. (2020). AI-based demand forecasting for reducing logistics costs in supply chains. Computers & Industrial Engineering, 150, 106101.
[10] Vahdani, B., & Fattahi, M. (2021). A hybrid AI-based model for optimizing transportation and distribution logistics. International Journal of Production Economics, 238, 108162.
[11] Rezaei, J., & Wei, Y. (2021). AI and machine learning techniques in the logistics sector: A systematic review. Computers, Materials & Continua, 67(2), 2121-2137.
[12] Wang, L., & Wang, X. (2020). Artificial intelligence and transportation cost reduction: A review. Journal of Transportation Engineering, Part A: Systems, 146(4), 04020024.
[13] Zhu, M., & Li, W. (2020). The impact of artificial intelligence on logistics cost reduction: A case study in China. Transportation Research Part E: Logistics and Transportation Review, 139, 101951.
[14] Hossain, M. M., & Nandi, S. (2020). AI-driven transportation management in Bangladesh: A case study on reducing logistics costs. Asian Journal of Supply Chain and Operations Management, 5(2), 120-134.
[15] Tan, K. C., & Yang, C. C. (2020). Enhancing transportation efficiency and reducing costs in the logistics sector using artificial intelligence. European Journal of Operational Research, 284(3), 865-878.
[16] Chandra, S., & Mukherjee, A. (2021). Machine learning techniques for route optimization in logistics. Journal of Operations Management, 60(3), 398-415.
[17] Bai, X., & Li, Y. (2021). The role of AI in shipment consolidation for transportation cost reduction. Journal of Business Research, 124, 465-472.
[18] Shang, J., & Tseng, Y. (2020). AI-powered supply chain strategies for cost reduction in developing countries. International Journal of Production Research, 58(24), 7410-7424.
[19] Bai, C., & Duan, Y. (2020). Artificial intelligence in logistics: A review of recent developments. Computers & Industrial Engineering, 146, 106539.
[20] Zhao, X., & Wu, Q. (2021). Leveraging AI for demand forecasting in logistics: A comparative analysis. International Journal of Production Economics, 235, 108104.
[21] Feng, S., & Li, Y. (2021). Role of machine learning in route optimization for logistics cost reduction. Computers & Industrial Engineering, 154, 107091.
[22] Chakravarty, A., & Gupta, S. (2020). AI in logistics: A comparative review of applications and challenges. Journal of Supply Chain Management, 56(1), 45-60.
[23] Zhang, X., & Song, H. (2021). Forecasting transportation demand using machine learning: Implications for cost efficiency. Transportation Research Part A: Policy and Practice, 146, 252-265.
[24] Kaur, P., & Kapoor, V. (2021). AI-powered logistics and transportation cost management in supply chains. Journal of Artificial Intelligence Research, 73(2), 225-244.
[25] Moudgil, P., & Sharma, S. (2020). Artificial intelligence-based optimization of logistics operations: A case study approach. International Journal of Logistics Management, 31(3), 492-511.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
