International Journal of Logistics Research and Applications

Smart Logistics and Supply Chain Management with AI-empowered Physical Internet

Logistics and supply chain management are the key means for promoting economic development (Lim et al., 2024). The Physical Internet (PI) is a paradigm-shifting vision that aims to create a universal interconnection of logistics services and networks that exploits a Digital Internet inspired metaphor (Ballot et al., 2021; Montreuil, 2011). However, today’s logistics and supply chain networks become increasingly complex and stringent subject to uncertainties in international trade tensions, new technologies and new normal in post-pandemic era (Chan & Choi, 2024). The principles of openness, reconfigurability, modularity, and hyperconnectivity inherent in the Physical Internet (PI) establish a robust foundation for achieving sustainable and resilient logistics and supply chain management (Münch et al., 2024; Peng et al., 2024). Digitization with intelligence such as Digital Twin, Internet of Things, blockchain serve as key pathway for realizing PI through enabling seamless interoperability, data synchronization, and real-time monitoring across interconnected logistics networks. (Liu et al., 2024; Zhao et al., 2024).

In Industry 4.0/5.0 era, Artificial Intelligence (AI) has emerged as a transformative enabler to address these pressing challenges (Veile et al., 2024). AI technologies—such as machine learning, Large Language Model (LLM), and computer vision—can optimize logistics operations, enhance decision-making, and enable real-time adaptability within the logistics and supply chain management framework (Choi et al., 2022). AI can revolutionize demand forecasting, inventory management, transportation planning, and risk mitigation, while also fostering eco-friendly logistics through energy optimization and waste reduction.

How the AI can better implement PI and supply chain operations has become a common concern for managers and scholars. Following the stream, this special issue aims focusing on innovative research that explores the transformative role of AI in empowering the PI and improving logistics and supply chain management. The trend of a combination of modelling approach and empirical analysis, focusing on building resilient supply chain across the globe with a holistic view is forthcoming (Shi et al., 2023). We invite contributions that advance theoretical frameworks, propose novel methodologies, or present empirical studies that bridge these gaps, highlighting the disruptive potential of AI in addressing the challenges of modern supply chains.

This special issue invites research on following themes, but not limited to:

• Application of AI in logistics and supply chain management, e.g., Machine Learning, Large language models (LLM), Computer Vision, and autonomous systems;
• Advanced AI analytics for planning, scheduling, execution in PI.
• AI-driven Physical Internet/Cyber Physical Internet standardization, models, routing tables and protocols;
• New PI-based resilience modelling and control methods for logistics and supply chain management;
• IoT, digital twin, blockchain, AR/VR for digital interoperability in PI;
• New AI-based optimization and decision-making models for logistics and supply chain management;
• Sustainability, decarbonization for logistics and supply chain management.

Guest editors’ biographies:
Dr. Zhiheng Zhao - Dr. Zhiheng Zhao is currently a Research Assistant Professor, Director of Industrialized Construction Joint Lab at Department of Industrial and Systems Engineering of The Hong Kong Polytechnic University. His main research areas are the industrial spatial-temporal intelligence, digital twin, smart manufacturing and logistics. He has published over 50 academic papers and has been PI or co-PI for several projects, including NSFC, ITF, RGC RIF, etc., Dr. Zhao’s research outcomes have also been applied in the industrial sector, securing over 15 million HKD in corporate collaboration projects. He is a senior member of IEEE, member of HKIE, IISE and ASME.

Dr. Ming Li - Dr. Ming LI is currently a Research Assistant Professor at Department of Industrial and Systems Engineering (ISE), The Hong Kong Polytechnic University. He has conducted research projects in the field of Industrial Blockchain and Digital Twin for Smart Manufacturing and Logistics with substantial government and industrial grants over 20 million HK dollars. He has published more than 70 papers on leading international journals and top conferences. He has also obtained 50 patents and copyrights. Now he is a senior member of IEEE and CCF, a member of ASME and IISE.

Prof. Shenle Pan - Shenle Pan is Full Professor with Habilitation in sustainable logistics and supply chain management, co-director of the Physical Internet Chair, and associate head of the Center for Management Science at MINES Paris, PSL University in France. Since 2010, he has been PI or co-PI for 20 research projects (H2020, FP7, ANR…), published more than 60 papers in peer reviewed journals and conferences (Transportation Research Part E, Omega, International Journal of Production Economics, International Journal of Production Research, Computers in Industry, etc.), and served as guest editor for 5 special issues published on prestigious academic journals (TRE, IJPR, CII, IMDS).

Prof. George Q Huang - Prof. George Huang is Chair Professor of Smart Manufacturing in Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. He has conducted research projects in areas of Smart Manufacturing, Logistics, and Construction through IoT-enabled Cyber-Physical Internet and Systems Analytics. His research has been supported with substantial government and industrial grants. He has published extensively and his works have been highly cited by research communities. He serves as associate editors and editorial members for several international journals. He is Chartered Engineer (CEng), Fellow of IEEE, IISE, ASME, HKIE, IET and CILT.

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