Abstract
AbstractThe global collaboration and integration of online and offline channels have brought new challenges to the logistics industry. Thus, smart logistics has become a promising solution for handling the increasing complexity and volume of logistics operations. Technologies, such as the Internet of Things, information communication technology, and artificial intelligence, enable more efficient functions into logistics operations. However, they also change the narrative of logistics management. Scholars in the areas of engineering, logistics, transportation, and management are attracted by this revolution. Operations management research on smart logistics mainly concerns the application of underlying technologies, business logic, operation framework, related management system, and optimization problems under specific scenarios. To explore these studies, the related literature has been systematically reviewed in this work. On the basis of the research gaps and the needs of industrial practices, future research directions in this field are also proposed.
Publisher
Springer Science and Business Media LLC
Reference95 articles.
1. Al-Turjman F, Hasan M Z, Al-Rizzo H (2018). Task scheduling in cloud-based survivability applications using swarm optimization in IoT. Transactions on Emerging Telecommunications Technologies, 30(8): e3539
2. Alam K M, El Saddik A (2017). C2PS: A digital twin architecture reference model for the cloud-based cyber-physical systems. IEEE Access, 1: 2050–2062
3. Anandhi S, Anitha R, Sureshkumar V (2019). IoT enabled RFID authentication and secure object tracking system for smart logistics. Wireless Personal Communications, 104(2): 543–560
4. Anderluh A, Nolz P C, Hemmelmayr V C, Crainic T G (2021). Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and “grey zone” customers arising in urban logistics. European Journal of Operational Research, 289(3): 940–958
5. Andersson J, Jonsson P (2018). Big data in spare parts supply chains: The potential of using product-in-use data in aftermarket demand planning. International Journal of Physical Distribution & Logistics Management, 48(5): 524–544
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