A framework for understanding reliability in container shipping networks

Data-driven research on the impact of COVID-19 on the global container shipping network

Shanghai’s container throughput has ranked first worldwide for 13 consecutive years beginning in 2010, indicating that Shanghai has built an international shipping centre capable of allocating resources for global shipping factors. This study considers global container shipping and shipping service networks as research objects to examine the node status and connection directions of Shanghai in these two networks. It also identifies the comparative advantages and weaknesses of Shanghai and proposes countermeasures and suggestions. The results show that Shanghai ranks high in the global container shipping network and is a sub-centre of the Busan system. Shanghai performs well in the mid-to-low-end shipping service industry in the shipping service network; however, a clear gap exists in the high-end service industry between Shanghai and European port cities. Thus, Shanghai should vigorously implement an international development strategy, actively promote a coordinated development strategy between ports, and integrate the construction of the shipping centre with that of financial and technological innovation centres.

With the development of global economic integration, the container shipping has become the main transportation of world shipping industry. Shipping companies usually employ hub-and-spoke shipping network in order to chase for optimal economic benefits. The CO 2 emissions system of global maritime has a direct effect on shipping company’s design for hub-and-spoke container shipping network. With the constraints of container flow equilibrium and hub port capacity limit, a hub-and-spoke container shipping network optimization model by considering CO 2 emissions is established. Under the measurement of container transportation costs, harbor dues and CO 2 emissions costs, the shipping company reconsider the optimal shipping routes and make decision of hub ports to be calling. The decision made by the company should aim to reduce the total shipping costs. Lagrangian relaxation algorithm is applied to solve the model. Numerical experiments show that the model and algorithm are effective. After analyzing the impact of hub ports to hub-and spoke network design, we get to the conclusion that, CO 2 emissions costs are negatively correlated with utilization ratio of hub port. And hub port capacity limit also affects the port selection decision making of shipping companies. The hub-and-spoke container shipping network optimization model by considering CO 2 has a great impact for the decision making and route optimization of the shipping companies in the future.

Transshipment hubs are important components of the global container shipping network. Nowadays, hybrid ports are emerging, handling both gateway and transshipment container traffic depending on their significant maritime connectivity. Effectively identifying transshipment hubs, including traditional transshipment hubs with high transshipment incidences and hybrid ports with sufficient transshipment capabilities, is crucial to gain a good understanding of container shipping networks. The method of reinforced structural holes (RSHs) has been introduced from the sociology to detect transshipment hubs at the global level, as it can fully consider the existence of separated cohesive port communities. The results show that the RSH-based approach is feasible to identify those hubs playing the role of bridges across different port communities worldwide, which is demonstrated from the perspective of maritime connectivity. The higher ranked hubs with higher RSH values generally have better maritime connections with ports from various port communities. Several policy implications have been further elaborated for relevant decision makers, such as liner companies and port operators.

Container (Liner) Shipping

With the increase of international trade activities, the dependence on container shipping is also increasing. The efficiency of container shipping activities will directly affect the trade exchanges between countries. However, traditional network analysis methods face many challenges, such as large-scale, highly dynamic and multi-dimensional issues. To this end, in this article, after reviewing existing network-based analysis methods and their limitations, we introduce the advanced network representation learning technology for container shipping network analysis. To demonstrate the effectiveness of the network representation learning based method, we perform a case study on container shipping network clustering, and the positive results demonstrate the potential of allying network representation learning for container shipping network analysis.

Ports play an important role in maintaining the effectiveness of maritime logistics. When ports encounter congestion, strikes, or natural disasters, the maritime container transportation network might be significantly affected. The Beibu Gulf sea area is a key channel to supporting China’s participation in international economic cooperation in the western region. It is highly susceptible to the influence of the political and economic instability. This study introduces a dual-component framework to analyze the inherent structure and potential vulnerabilities of the container transportation network in the Beibu Gulf Sea areas. The findings show that the core layer of the network exhibited circular solidification characteristics. The entire network heavily relies on some core ports, such as Haiphong Port, Ho Chi Minh Port, and Qinzhou Port, and it highlights the potential increases in vulnerability. The finding shows that deliberate attacks have a greater impact than random attacks on the normal operations of maritime networks. If ports with high intermediary centrality are attacked, the connectivity and transportation efficiency of the Beibu Gulf maritime network will be significantly affected. However, under such circumstances, redistributing cargo transportation through route adjustments can deal with the transmission of cascading failures and maintain the network’s resilience. Based on the existing knowledge and the data collected in a case study, this research stands out as the first to provide a critical examination of the spatial structure and vulnerability of container shipping networks in the Beibu Gulf sea.

Regional trade co-operation, economic growth and greater political stability have enabled increased container throughput and container port capacity development. Earlier academic work has indicated that the functional position of this port region in the global maritime network might be shifting from a remote region in the periphery of the network to a more intermediate position. This paper aims to analyze the changing level of peripherality and remoteness of the Southern African container port system as part of the global container shipping network. The central hypothesis is that Southern Africa has moved from a remote shipping region to a more central shipping region in the global network. The methodology consists of the calculation of network measures for Southern African ports. The changing geographical distribution of flows among the main container ports in South Africa, Namibia, Mozambique, Mauritius and Madagascar will also be explored in terms of their respective shipping services, port calling patterns, market structure (in terms of the number of active carriers) and the up-scaling of vessel and port capacity. The overall result is a mapped port hierarchical structure with a clear indication of the shifted maritime centrality of Southern African ports from 1996 to the present decade.

Containership delay propagation risk analysis based on effective multivariate transfer entropy

This chapter gives a comprehensive overview of existing research works on global container transport network design. In view of competitive pressures and complexity of container shipping networks, global liner shipping companies are seeking optimization-based decision support tools for designing efficient container transport networks. Nevertheless, the status quo research is far lagging, especially in terms of solving practical-size problems while capturing essential operating characteristics, developing efficient solution algorithms, and application by liner shipping companies.

The container shipping network has evolved with the development of trade, but the mechanism of its evolution is still not well studied. Link prediction model is one of the main methods used to study the network evolution. The classic indicators of the link prediction model only consider the structural characteristics of the network, but there are also real factors that can influence the evolution of the network. Therefore, this paper considers the structural characteristics of the network as an endogenous index, which includes common neighbors, Adamic–Adar, resource allocation, and so forth. Considering the factors that may affect the link between the ports, such as sailing distance, operation, economy, and political factors, this paper first develops different attractiveness models and determines an optimal attractiveness model in case analysis. After that, this paper proposes a composite index that combines endogenous and attractiveness indices. Taking the Maritime Silk Road (MSR) shipping network as an example, an optimal attractiveness index and then an optimal composite index are determined. It was found that the prediction accuracy under the composite index is improved compared with single indices, which confirms the effectiveness and superiority of the proposed index. Finally, from the perspective of the overall network, this paper discusses the possible future routes of the shipping network with the aim of providing a reference for the improvement of connectivity of the shipping network and planning new routes for shipping companies.

Maritime shipping lines and global terminal operators have benefited from economies of scale to expand geographically and functionally their infrastructure, leading to a corporatized network. Terminal operators are key asset managers seeking value creation by expanding the global maritime container terminal infrastructure network. While corporatization has systematically ensured that terminal capacity was created to accommodate the rise in global trade volumes, the network hit its boundaries when confronted with COVID-19 induced global supply chain disruptions. This paper provides a better understanding of the importance of infrastructure and observed corporatization as a framework for explaining economic processes, notably when transport infrastructures are extensive and capital-intensive. The structure of the global container shipping network is analyzed to unveil the realities of liner service networks operated by shipping lines, and the market structure and consolidation in container shipping and terminal operations. The discussion on the corporatization of the global maritime infrastructure network for container handling is embedded in international business literature. This study also extracts the main implications of the current structure and governance of the global maritime infrastructure network for international business policy, with a particular focus on the current market structure and network resilience.

Integrated strategic and operational planning of dry port container networks in a stochastic environment

Container shipping networks are vulnerable to cascading failures due to seaport disruptions, underscoring the need for resilient multimodal transport systems. This study proposes a cascading failure model for the seaport–dry-port network in container transport, incorporating a multi-stage load redistribution strategy (CM-SDNCT-MLRS) to enhance network resilience. Extending the Motter–Lai framework, the model introduces multiple port state transitions and accounts for uncertainties in load redistribution, tailoring it to the cascading failure dynamics of SDNCT. Using empirical data from China’s coastal port system, the proposed MLRS dynamically reallocates loads through dry-port buffering, neighboring seaport sharing, and port skipping. This strategy effectively contains cascading failures, mitigates network efficiency losses, and protects major seaports while reducing mutual disruptions. Resilience analysis demonstrates that the network exhibits scale-free properties, with its resilience being highly sensitive to random port failures and critical port vulnerabilities. The experimental results highlight the pivotal role of dry ports, where operational numbers influence resilience more significantly than capacity. In addition, the study identifies the optimal port-skipping probability that mitigates cascading disruptions. These findings provide valuable insights for port management and logistics planning, contributing to the development of more resilient container transport networks.

CO2 emissions in a global container shipping network and policy implications