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This paper presents a generic framework on port logistics development and its interaction with hinterland regions. Although earlier work on the topic (e.g. by Ferrari et al., 2006; Kuipers and Eenhuizen, 2004) offers valuable insights in the subject, it contains limitations in geographical applicability. Ports indeed face dissimilarities in, for instance, locational characteristics (a.o. distance from the sea and nautical accessibility) and hinterland connections. Only when a model for determining seaport-located logistics activities takes into account these issues of dissimilarity among ports, the framework could be applied to a variety of seaport ranges worldwide. In this paper we aim to provide a first version of such a framework. More particularly, by means of a survey conducted in the Port of Busan the shortcomings of traditional approaches are illustrated. We then propose a more encompassing model, which seems to explain fairly well the attractiveness of Busan in terms of logistics activities. This framework explicitly adds port and hinterland characteristics to the list of factors decisive in the choice of the location of logistics activities. Finally, we would like to remark that our research on this topic is still ongoing and results for surveys planned in New York and Antwerp will be reported in a later stage.

A number of literature contributions have underlined the importance of developing value-added logistics activities or VALS in order to help improve customers’ satisfaction. However, there is usually very little attention given regarding where to perform these VALS. This study aims to: (1) identify a comprehensive set of factors which may influence the location of VALS, (2) to analyze to what extent those factors influence location decisions, and (3) to distinguish the determinants behind the location choices for distribution centers and for the kind of VALS that will be developed in these distribution centers.

In this paper, we will present a conceptual framework on the locations of VALS in view of the identifying determinants for assigning VALS to logistical centers. We argue that the optimal location of VALS is determined by complex interactions between the determinants at the level of the choice of a distribution system, distribution center location factors, and different logistical characteristics regarding products.

This study proposes practical digitalization strategies and well-grounded evaluation criteria for maritime container supply chains.

The authors identified the status of supply chain digitalization of the Port of Busan in South Korea and developed three digitalization strategies based on industry requirements and consultations with port experts. The authors proposed 11 evaluation criteria for examining the main digitalization strategies in the supply chain operations reference model, based on a survey among 46 experts and used multi-criteria decision-making approaches to prioritize the strategies and evaluation criteria.

The results delineate the status of the digitalization of a real-world port-focal supply chain. The model can be successfully customized to include well-grounded evaluation criteria for digitalization strategies, and presents a practical way to advance the supply chain digitalization strategies. Based on the survey and evaluation, the authors find that increasing data accessibility and improving quality are preferred to adopting a data and information sharing platform.

As the study is limited to the Port of Busan, future case studies could be undertaken to container supply chains driven by different regional ports.

Stakeholders, such as truckers, terminal operators, and shipping liners, might consider the proposed strategies and evaluation criteria when digitalizing their supply chains.

By identifying the needs and specifications of maritime container supply chain digitalization strategies, developing evaluation criteria, and conducting a case study for proof of concept, the study proposes an operational management process with practical, real-world benefits for port-focal supply chains.

The literature on Maritime Transportation (MT) is experiencing a transition phase where the focus of the research is repositioning. It registered steep growth in recent years with its beginning articles on the concepts of cost minimization to the current focus on achieving sustainable operational effectiveness using Information and Communication Technologies (ICTs). Thus, this becomes a right time to investigate the trajectory of research on MT.

The proposed study aims to explore the potential of data analytics techniques such as data mining and network analytics to reflect the trajectory of research in the maritime supply chain over time. This study identifies the eight main dimensions of the research published under maritime paradigm through network analytics. The in-depth review of these dimensions rendered us to segregate them further into sub-dimensions for the ease of understanding and interpretability. Further, the text mining is employed to extract thematic evolution of the research.

The evolved themes are completely exclusive from the conventional MT research with artificial intelligence, digital storage, waste management and biofuels emerging as contemporary themes. It is found that although there are a sufficient amount of literature on sustainable port practices but their policy implications are still underexplored. The inter-dimension research is needed to achieve the motive of economic efficiency and environmental sustainability simultaneously.

The study has contributed on the methodology side of conducting literature reviews. The dimensions, sub-dimensions and themes are obtained using data analytics tools and techniques. This omits the possibility of personal bias and thus making the results verifiable.

Empty container trucks may cause a deficit in transport capacity and contribute to congestion and emissions in the port territory. Reengineering of the container truck hauling process to introduce truck-sharing arrangements using the truck appointment system has the potential of reducing the number of empty-truck trips. The paper aims to discuss these issues.

This research evaluates the results from an investigation of the truck appointment system using a case study approach. The data collection phase involved primary and secondary sources along with using publicly available data on port operations.

The study explores a dynamic truck-sharing facility for a computer-based matching system to assign probable export containers to available empty slots of a container truck. The proposed model reengineers the truck appointment system with a potential to reduce the number of empty-truck trips to increase container transport capacity around seaport gates.

Due to continuous increases in container-freight traffic, leading seaports of the world are experiencing a capacity shortage resulting in traffic congestion. The research findings are useful in practice as the proposed truck-sharing model can be introduced to enhance capacity in the container transport chain of the port territory.

The empty-trucks problem has not been addressed much in studies from a decentralized perspective where all truck operators have an equal chance to contribute to optimize the supply chain in contrast with the typical one-company-based optimization. The solution addressed here uses the shared-transportation concept to cover the research gap.

Despite the recognition that supply chain (SC) learning is important for competitive advantage, little is known how to enable such learning. The purpose of this paper is to examine the effects of information technology (IT) application on different types of SC learning (i.e. internal, customer and supplier learning) and service performance.

This study applies structural equation modeling to test the conceptual model based on data collected from 213 manufacturing firms in China.

Although strategic application has a direct and negative relationship with all three dimensions of SC learning, it indirectly and positively improves SC learning through tactical and operational application. The authors observe that tactical application is positively related to all three dimensions of SC learning, while operational application improves internal and customer learning only. The authors also notice that internal and customer learning are positively related to service performance.

This study classifies IT application into strategic, tactical and operational dimensions, which may not adequately cover the entire set of IT application portfolio.

The findings suggest managers to use corresponding IT application to improve SC learning and service performance.

This study provides a new framework to understand the relationships between IT application, SC learning and service performance.

Distribution of long-haul goods could be managed via multimodal transportation networks where decision-maker has to consider these factors including the uncertainty of transportation time and cost, the timetable limitation of selected modes and the storage cost incurred in advance or delay arriving of the goods. Considering the above factors comprehensively, this paper establishes a multimodal multi-objective route optimization model which aims to minimize total transportation duration and cost. This study could be used as a reference for decision-maker to transportation plans.

Monte Carlo (MC) simulation is introduced to deal with transportation uncertainty and the NSGA-II algorithm with an external archival elite retention strategy is designed. An efficient transformation method based on data-drive to overcome the high time-consuming problem brought by MC simulation. Other contribution of this study is developed a scheme risk assessment method for the non-absolutely optimal Pareto frontier solution set obtained by the NSGA-II algorithm.

Numerical examples verify the effectiveness of the proposed algorithm as it is able to find a high-quality solution and the risk assessment method proposed in this paper can provide support for the route decision.

The impact of timetable on transportation duration is analyzed and making a detailed description in the mathematical model. The uncertain transportation duration and cost are represented by random number that obeys a certain distribution and designed NSGA-II with MC simulation to solve the proposed problem. The data-driven strategy is adopted to reduce the computational time caused by the combination of evolutionary algorithm and MC simulation. The elite retention strategy with external archiving is created to improve the quality of solutions. A risk assessment approach is proposed for the solution scheme and in the numerical simulation experiment.

Creating green ports, while observing international and international standards and maritime conventions and regulations and moving toward smart ports, can increase the speed of goods transfer, enable the tracking of ships and goods, increase the transparency of statistics, increase the quality and capacity of ports and reduce costs. Hence, the purpose of this study the development and evaluation of ports play a key role in their commercial success. Development policies can be formulated for these ports by properly evaluating their performance indicators. On the other hand, traditional methods of performance evaluation cannot provide a good multidimensional evaluation of the status of ports.

More than 90% of the world’s heavy transit today is carried out by the sea. With this volume of freight, transit accidents are inevitable for ships passing through oceans, seas, waterways, rivers, ports and mooring at docks. Besides, gases from ships’ fuels at sea, especially in ports, oil spills due to maritime incidents, the negligence of the ship’s crew, the use of port equipment, dirty fuel of diesel power substations, etc., have increased greenhouse gases, polluted the environment and endangered human lives.

A new approach has been introduced in the field of port performance evaluation based on the components of greenness and intelligence. This approach performs evaluations in two stages and a network. In this study, the performance of 11 Iranian ports was evaluated based on the network data envelopment analysis approach in 2 stages of greenness and intelligence during 4 years. The results indicated that only 5% of the ports meet the standards of intelligence and greenness.

On the other hand, as shown in the above studies, the issue of green ports is directly related to the development of animal and plant ecosystems in the seas and the environment around ports. The presence of pollution in the ports has caused the animal and plant habitats around the ports to face a complete pollution crisis or to be completely destroyed. Therefore, the development of green port concepts in third world countries will help prevent environmental pollution of the seas. Therefore, it is necessary for ports to review their strategic maritime transport model and use the development of green port indicators in their implementation processes. Therefore, the strategic development of green ports is created to create and benefit from the components of intelligence, and as mentioned in previous research, intelligence and greenness are in line and the lack of development of one of the concepts causes defects in others. According to reports provided in Iran’s maritime transport systems, most accidents have led to environmental disasters during the absence of intelligent equipment. The use of smart technologies prevents all environmental damage and the development of port services. On the other hand, in evaluating the published articles in the field of development of green and smart ports, so far, the components of intelligence and greenness have not been evaluated and analyzed in a practical and operational way in ports and only the influencing the development of agents on each other has been done (Chen, 2019). Therefore, evaluating the efficiency of ports based on green components and intelligence causes ports to fundamentally review their executive infrastructure and take an active part in the global green development plan.

This paper focuses on dry port as a key notion in port-hinterland development. We first discuss the concept of dry port by reviewing existing literature. Then, we explore the reasons behind the emergence and development of inland node systems in different geographical, economic and institutional contexts. Next, the paper presents a classification of dry ports based on a multitude of factors and dimensions and the respective benefits to different parties. The study then focuses on the specific characteristics of dry ports and associated transport networks in developing countries.

In the last part, we present a case study on the dry port system in Vietnam by reviewing the seaport and inland transport system and analyzing the current status of inland terminals in Vietnam. To conclude, a SWOT analysis is presented with regard to the development of the dry port network in Vietnam, followed by recommendations for policy makers.

This study aims to identify the characteristics of the maritime shipping network in Northeast Asia as well as compare the level of port connectivity among these container ports in the region. In addition, this study analyses the change in role and position of 20 ports in the region by clustering these ports based on connectivity index and container throughput and route index.

This study employs Social Network Analysis (SNA) to delineate the international connectivity of major container ports in Northeast Asia. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to identify each port's connectivity index and container throughput index, and the resulting indexes are employed as the basis to cluster 20 major ports by fuzzy C-mean (FCM).

The results revealed that Northeast Asia is a highly connected maritime shipping network with the domination of Shanghai, Shenzhen, Hong Kong and Busan. Furthermore, both container throughput and connectivity in almost all container ports in the region have decreased significantly due to the coronavirus disease 2019 (COVID-19) pandemic. The rapid growth of Shenzhen and Ningbo has allowed them to join Cluster 1 with Shanghai while maintaining high connectivity, yet decreasing container throughput has pushed Busan down to Cluster 2.

The originality of this study is to combine indexes of SNA into connectivity index reflecting characteristics of the maritime shipping network in Northeast Asia and categorize 20 major ports by FCM.