Driven by the IoT technology and smart sensors development in Industry 5.0, the digital twin as an innovative information technology brings new opportunities and challenges for intelligent maritime logistics management. This paper tries to present a systematic review on digital twin-empowered smart maritime logistics management by employing a bibliometric analysis framework under the Industry 5.0 era. The 3372 related publications from the Web of Science database are collected as research samples from 2003 to 2023. Besides, the VosViewer is adopted to perform the co-word and network analysis by visualizing interactive collaborations of published literature. Specifically, more than 3,000 articles on maritime logistics were reviewed to determine the research trajectories and main themes through same-word study and co-citation analysis. Results show that most publications on maritime logistics management are concentrated in China and the United States, where maritime logistics is developing towards digitization and informatization. In particular, Sustainability, Maritime Policy & Management, and Journal of Marine Science and Engineering are the most important journals focusing on maritime logistics management. Moreover, we hope this review study serves as a future direction on digital twin-empowered smart maritime logistics management practices for both researchers and practitioners.

With the rapid development of digital technology, the smart sensor-based container equipment and intelligent logistics operations contribute to achieving the efficiency improvement and sustainability achievement of container supply chain under the IoT-based logistics 4.0 scenarios. This paper tries to study the state-of-the-art knowledge of the container logistics supply chain management motivated by digital techniques. Through data-driven analysis this review is performed to assist researchers and practitioners to better understand the container logistics management. The integrated research framework is designed by developing a bibliometric analysis study to address the research themes of the container logistics era. The related publications from the Web of Science database from 2003 to 2022 were indexed and 2897 reference samples are collected as the research data. In addition, the VosViewer is adopted to portray the network, co-occurrence, and co-word analysis by visualizing the collaborative relationships of collected samples. The results show that digital technology has been widely applied in container logistics supply chain management practices, contributing to resilience and sustainability improvement by intelligent operations. These research findings are also helpful for researchers by providing a deep penetrating insight into research opportunities and great potentials of container logistics supply chain by innovative digital technology-enabled practices.

Urban safety production is a core component of social safety and is associated with the production, storage and transport of hazardous chemicals, which are potential sources of disaster in an urban area. Chemicals’ locations in a city present a hidden site of danger, which can easily become disaster sites if supervision is inadequate. Aiming to improve the processes and typical scenarios of the production, storage, transportation and use of hazardous chemicals, this paper proposes an intelligent-technology-empowered active emergency command strategy (ITAECS) for urban hazardous chemical disaster management (UHCDM) in smart–safe cities. This paper aims to provide a strategy for active emergency command that takes into account the disaster source; hidden danger site; or disaster site of hazardous chemicals such as natural gas, gasoline and hydrogen energy based on five aspects: intelligent perception technology and equipment, a dynamically perceived IoT system, the accurate deduction of disaster posture, virtual reality emergency rescue rehearsal and an immersive emergency command platform. This research is conducive to the safety, efficiency and greenness of the whole industrial chain, such as the production, storage, transportation, operation and use of hazardous chemicals. There are difficulties and challenges in introducing ITAECS to urban hazardous chemical production safety and emergency management, such as the need for joint promotion of enterprises, industries and governments; uneven technological development; and several scientific–technological issues to be solved, as well as non-uniform standards. Overall, this paper helps improve the emergency management of urban hazardous chemical safety production.

Low-carbon economy advances the sustainable development of the transportation of hazardous chemicals. This paper focuses on the multi-trip heterogeneous vehicle routing problem that includes the prioritization of customers and transportation of incompatible cargoes (MTHVRP-PCIC) in which some customers are prioritized for delivery by heterogeneous vehicles and more than one type of cargo is transported. This is an issue because some cargoes are incompatible with each other and therefore cannot be loaded into the same vehicle. MFHVRP-PCIC aims to find a set of routes resulting in minimal costs including fixed cost, travel cost and carbon emission cost. This problem occurs in real-life applications in the hazardous chemicals road transportation industry. This paper contributes to addressing the MTHVRP-PCIC from a problem definition, model, and methodological point of view. We establish a mathematical formulation for this problem. A two-stage hybrid metaheuristic approach (TSHM) is also devised to solve this problem. First, an improved greedy randomized adaptive search procedure is designed to generate initial feasible solutions. Then, a hybrid genetic algorithm including local search strategies, split-feasibility procedure, and simulated annealing is designed to solve this problem. Finally, the proposed approach is applied to solve a real case of hazardous chemical delivery and a benchmark dataset, and the resulting solutions indicate the advantage of our algorithm compared with those solutions obtained from managerial experience and classical algorithms.

In view of the global information management requirements of intermodal containers, combined with the development status, this paper proposes an IoT model based on LEO satellites, and a big data management and analysis platform based on the model. This paper designs and analyses the scheme of the platform, and proposes a middleware approach to solve the problem of multi-source heterogeneous data access of containers intelligent terminals. Then, this paper designs business processes such as user and device registration, middleware registration, historical data access, and timely data access for the platform. The big data analysis and management platform has been prototyped and verified; the platform has the advantages of compatibility, openness and convenience. This study has certain value.

As cities worldwide pursue sustainable and inclusive mobility, understanding the travel behavior of vulnerable populations in peri-urban resettlement areas is essential for designing equitable built environments. In Shanghai, as in many rapidly urbanizing megacities, government-led redevelopment in central Shanghai displaces residents to the urban periphery, creating accessibility deficits and raising transport inclusivity concerns. Using travel diary data from five peri-urban affordable housing communities collected in 2012 (N = 8390)—a critical baseline before major infrastructure improvements—this study documents limited mobility (residents make significantly fewer trips than the city average) and examines its correlates via logistic regression. A core finding is a type-based threshold effect: awareness of a nearby large shopping mall is associated with higher shopping trip frequency (coefficient −0.332, p = 0.024), whereas awareness of small-to-medium supermarkets shows no significant association. This pattern is consistent with elastic demand theory and challenges the assumption that any retail facility improves accessibility equally. Our models explain very little variance (Nagelkerke R² = 0.078 for overall trip frequency; 0.048 for shopping frequency). This low explanatory power is itself a diagnostic signal—and a core motivation for our hypothesis-generating approach—indicating that unmeasured psychological (attitudes, perceived behavioral control), social (networks, norms), and technological (e-commerce) factors likely dominate travel decisions—directing future research priorities. Methodologically, the 2012 data provide an uncommon early-stage baseline for policy-induced resettlement, enabling future longitudinal comparisons and mechanism identification (e.g., before/after metro or mall openings). For contemporary policy, the findings suggest a testable hypothesis that anchor-type facilities (e.g., mid-sized community hubs with mixed use, rather than merely small supermarkets) may activate suppressed demand, requiring re-evaluation with recent data and causal designs. Readers should not extrapolate numeric trip rates to today’s Shanghai. The primary contributions are theoretical (type-based threshold effects, the anchor-vs.-routine facility distinction, the role of basic spatial awareness) and methodological (historical baseline). The 2012 data predate widespread e-commerce; digital substitution may substantially attenuate these relationships in contemporary contexts.