Artificial intelligence in logistics and supply chain operations: state-of-the-art and research avenues towards AI-empowered Physical Internet

Shengan Yu, Mengdi Zhang, Zhiheng Zhao, Shenle Pan (), Ming Lim and George Huang
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Shenle Pan: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique, Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres

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Abstract: Artificial Intelligence (AI) is increasingly shaping logistics and supply chain operations through automation, optimisation, and intelligent decision-making. Meanwhile, Physical Internet (PI) is emerging as a revolutionary paradigm for a digitalised, hyper-connected, modular, and sustainable global logistics network. The integration of AI and PI is poised to deliver enhanced efficiency, sustainability, and resilience. This study investigates how AI contributes to logistics operation management under the PI framework, and what new requirements and challenges arise from this integration. We conduct a systematic literature review (SLR) and bibliometric analysis of 117 publications, focusing on three dimensions: AI-driven operational automation, AI-augmented optimisation, and Generative AI in knowledge management and service innovation. Findings indicate that while AI has achieved notable progress in many logistics' applications and cases, its integration within the PI paradigm still lacks research. Accordingly, we propose several research avenues, identify key research gaps, to advance research and applications towards AI-empowered PI scenario.

Date: 2026-06-17
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Published in International Journal of Logistics Research and Applications, inPress, pp.1-29. ⟨10.1080/13675567.2026.2685107⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05659980

DOI: 10.1080/13675567.2026.2685107

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