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approaches by strengthening industry linkages and engaging with technology providers to
identify suitable solutions and reduce implementation risks.
Finally, the transition toward technology-driven logistics systems should follow a
phased roadmap aligned with enterprise capabilities. Initial efforts should focus on
improving customer experience, real-time information transparency, and internal
management efficiency, before expanding AI applications to optimize resources and
productivity. In the long term, AI will play a crucial role in developing a smart logistics
ecosystem, enhancing Vietnam’s global competitiveness and integration into global value
chains.

References
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[2]. Ministry of Industry and Trade. (2025). Vietnam Logistics Report 2025. Hanoi:
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[3]. Christopher, M. (2016). Logistics and Supply Chain Management (5th ed.).
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[4]. Boute, R. N., & Udenio, M. (2023). AI in Logistics and Supply Chain Management.
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2020s. Springer.
[5]. Kshetri, N. (2021). Artificial intelligence in supply chain management. IT
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industry: Opportunities and challenges. Journal of Asian Business and Economic Studies,
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[8]. Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th
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[10]. Sternberg, H., Hofmann, E., & Roeck, D. (2021). Artificial intelligence in logistics:
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[11]. World Bank. (2023). Connecting to Compete 2023: Trade Logistics in the Global
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[12]. World Economic Forum. (2022). Artificial Intelligence in Supply Chains. Geneva:
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[13]. Winkelhaus, S., & Grosse, E. (2020). Logistics 4.0: A systematic review towards
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[14]. Do, H. G. (2025). Big data analytics adoption for sustainable manufacturing
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