Maritime Transportation Network Research Articles

Reconstructing and assessing global maritime transport network: based on the Port Cargo Composite Transport index

ABSTRACT Solution to the problem of limited explanatory power of transport economics due to the homogenisation of existing the Global Maritime Transport Network (GMTN) construction indicators. By integrating the Port Cargo Composite Transport (PCCT) index and considering the volume-value mismatch relationship and the type and flow of cargo transported in ports, the GMTN can be reconstructed through a bottom-up logic. Combining the complex network, natural breaks, and point mutual information method with the Leiden and PageRank algorithm, the characteristics of the GMTN were derived from three aspects, i.e. network topology, node characteristics, and inter-node dependency. The GMTN presents the characteristics as follows. Community division presents typical geographical aggregation and industrial complementarity. Node characteristics show the classic phenomenon of rich people’s clubs, with obvious heavy-tailed distribution. Maritime transport linkage preferences present a phenomenon of geographical proximity, and their expansion can clarify the direction of the main links. Enhancing their maritime links will be more targeted to support the transport of trade cargoes. These findings help us to understand the characteristics of the international maritime trade pattern, and provide decision references for industry stakeholders to provide a strategic layout of maritime transport.

A comprehensive assessment of the importance of the “Maritime Silk Road” route based on multi-dimensional data-driven approaches

Worldwide straits are crucial pathways for global trade and energy transportation, occupying key strategic positions. Therefore, this study utilizes automatic identification system (AIS) data and the structure of the maritime transportation network formed by ship navigation, combined with geospatial big data analysis, to fully consider factors including the natural navigational conditions of routes, the support capabilities of surrounding ports, the geographic advantages of neighboring countries, and the distribution of the shipping network importance in the CCAS evaluation model. To assess the navigability of maritime routes, a data-driven model was constructed using three layers of this model. Empirical analyses were conducted on 22 major routes along China's coast and the “Maritime Silk Road”. This method has significantly enhanced the accuracy and reliability of route assessments, and the improved assessment model demonstrated better navigational conditions in the South China Sea routes, identifying internal factors hindering the development of these critical maritime routes. The findings of this study provide a comprehensive assessment and analysis framework for global maritime transportation, offering crucial reference information for key stakeholders, including policy makers, port and berth infrastructure investors, maritime economists, and large shipping companies. Additionally, the study's results can be practically applied in the actual shipping trade, emphasizing the role of our framework in facilitating effective decision-making and strategic planning within the maritime industry.

Creating New Antifoulants Using the Tools and Tactics of Medicinal Chemistry.

The unwanted accumulation of marine micro- and macroorganisms such as algae and barnacles on submerged man-made structures and vessel hulls is a major challenge for any marine operation. Known as biofouling, this problem leads to reduced hydrodynamic efficiency, significantly increased fuel usage, microbially induced corrosion, and, if not managed appropriately, eventual loss of both performance and structural integrity. Ship hull biofouling in the international maritime transport network conservatively accounts for 0.6% of global carbon emissions, highlighting the global scale and the importance of this problem. Improved antifouling strategies to limit surface colonization are paramount for essential activities such as shipping, aquaculture, desalination, and the marine renewable energy sector, representing both a multibillion dollar cost and a substantial practical challenge. From an ecological perspective, biofouling is a primary contributor to the global spread of invasive marine species, which has extensive implications for the marine environment.Historically, heavy metal-based toxic biocides have been used to control biofouling. However, their unwanted collateral ecological damage on nontarget species and bioaccumulation has led to recent global bans. With expanding human activities within aquaculture and offshore energy, it is both urgent and apparent that environmentally friendly surface protection remains key for maintaining the function of both moving and stationary marine structures. Biofouling communities are typically a highly complex network of both micro- and macroorganisms, representing a broad section of life from bacteria to macrophytes and animals. Given this diversity, it is unrealistic to expect that a single antifouling "silver bullet" will prevent colonization with the exception of generally toxic biocides. For that reason, modern and future antifouling solutions are anticipated to rely on novel coating technologies and "combination therapies" where mixtures of narrow-spectrum bioactive components are used to provide coverage across fouling species. In contrast to the existing cohort of outdated, toxic antifouling strategies, such as copper- and tributyltin-releasing paints, modern drug discovery techniques are increasingly being employed for the rational design of effective yet safe alternatives. The challenge for a medicinal chemistry approach is to effectively account for the large taxonomic diversity among fouling organisms combined with a lack of well-defined conserved molecular targets within most taxa.The current Account summarizes our work employing the tools of modern medicinal chemistry to discover, modify, and develop optimized and scalable antifouling solutions based on naturally occurring antifouling and repelling compounds from both marine and terrestrial sources. Inspiration for rational design comes from targeted studies on allelopathic natural products, natural repelling peptides, and secondary metabolites from sessile marine organisms with clean exteriors, which has yielded several efficient and promising antifouling leads.

New canal construction and marine emissions strategy: a case of Pinglu

As an important component of new western land-sea corridor, the construction of Pinglu Canal will effectively alleviated waiting time and congestion costs and enhance the reliability and resilience of the regional maritime transport network in the post-pandemic era in particular. From the perspective of competition and cooperation game, this paper investigates typical transportation routes from the port of Jakarta in Indonesia to the port of Nanning in China from the key factors of the changes in freight volume and the evolution of profits and subsidies, considering local government subsidies, environmental costs, marine emissions and other critical factors. The results demonstrated that in the centralized strategies adopted by two transport route operators, as the volume of goods transported through Pinglu Canal increased, so the corresponding profits increased. The increase in subsidies also contributed to generating the volume of freight through Pinglu Canal, but the social welfare under the decentralized strategy adopted by both transport route operators was more effective than that of the centralized strategy.

China's One Belt One Road (OBOR) Initiative and Its Ambitions for Global Hegemony

This research paper analyses China's One Belt, One Road initiative and explores its ambitions for influencing the world economy through these economic corridors. However, each economic corridor has been separately explained in order to understand how these economic corridors would contribute to the rise and expansion of China in the world. In addition, to know whether the One Belt and One Road Initiative offers these six corridors' member states an opportunity to create a win-win relationship with China. It will ensure access and increase trade volume to the major world markets, or is it still a pipe dream for these countries to obtain such goals and objectives? Apart from this, to find out how it would improve and enhance regional connectivity, people-to-people contact, economic development, transit trade, road and maritime transport networks and tourism. This study used the qualitative method with an interpretive and descriptive approach. The purposive sampling technique was used to select the participants for the interview, and the snowball sampling technique was used to approach the participants. Five participants were interviewed through an interview schedule. The interview schedule was emailed to participants, and they typed their responses on MS Word and sent them back to the researcher. The researcher developed themes, and data were analyzed according to those themes. The findings of the study suggested that China has initiated these projects to promote its political power and economic interests in the region.

Maritime Transport Network in Korea: Spatial-Temporal Density and Path Planning

The increase in maritime traffic and vessel size has strengthened the need for economical and safe maritime transportation networks. Currently, ship path planning is based on past experience and shortest route usage. However, the increasing complexity of the marine environment and the development of autonomous ships require automatic shortest path generation based on maritime traffic networks. This paper proposes an efficient shortest path planning method using Dijkstra’s algorithm based on a maritime traffic network dataset created by extracting maritime traffic routes through a spatial-temporal density analysis of large-scale AIS data and Delaunay triangulation. Additionally, the depth information of all digital charts in Korea was set as a safety contour to support safe path planning. The proposed network-based shortest path planning method was compared with the path planning and sailing distance of a training ship, and compliance with maritime laws was verified. The results demonstrate the practicality and safety of the proposed method, which can enable the establishment of a safe and efficient maritime transportation network along with the development of autonomous ships.

Assessing the resilience of sustainable autonomous shipping: New methodology, challenges, opportunities

This paper introduces a resilience assessment methodology for sustainable autonomous maritime transport networks developed by the European project entitled “Advanced, Efficient, and Green Intermodal Systems” (AEGIS). This problem being addressed in this paper concerns the investigation of threats, incidents, and risks in an autonomous- and sustainable shipping context, and the research question is the development of both preventive measures and reactive actions to maintain an acceptable level of operational constraints. The paper’s methodology aids in designing sustainable logistics systems for highly automated waterborne transport, identifying threats and barriers to mitigate event consequences, thereby facilitating a seamless green transition. To examine the usability, this methodology is applied in a case study for cargo transportation, where we in this paper consider the maritime corridor between Trondheim and Rotterdam. The findings encompass the spectrum of possible actions to prevent and mitigate unwanted events and enhance resilience and flexibility. This can be used as a tool to respond to unwanted threats, enhance safety, and introduce new strategies. These results are deemed important as resilience is one of the prerequisites for the development of a sustainable transport system. This is true both for the companies that are engaged in the operation of such systems and for policymakers.

An evolution of the Global Container Shipping Network: port connectivity and trading community structure (2011–2017)

Port connectivity and trading community structure are two fundamental network characteristics that complement one another in explaining the evolution of maritime transport networks. Although port connectivity has been widely studied in the literature, the investigations on trading community structures are rather limited. To better fill this gap, this paper aims to provide a more complete picture of the Global Container Shipping Network (GCSN)’s evolution, based on our earlier works in MEL. In doing so, the GCSN, representing a snapshot of trade at the end of each quarter, from Q3/2011 to Q3/2017, is first constructed. The connectivity of ports and their respective trading communities are then extracted by the Container Port Connectivity Index and the Louvain algorithm, respectively. With our proposed framework, related players would be able to understand the growth of GCSN, as well as the impacts of maritime occurrences on the network of container shipping. Our computational results indicate that port connectivity and trading community structure gradually evolve according to the economic conditions that change over time and the evolution of GCSN could be well explained by these two explanatory variables. In this regard, ports in East Asia consistently dominate others in terms of both inbound and outbound connectivity, led by Shanghai and other major ports of mainland China. Furthermore, the formation of trading communities largely depends on trading patterns—rather than geographical locations—which is evident from the insolvency and mergers of communities in the North American region right after the expansion of the Panama Canal in 2016.

Assessing the Connectivity Reliability of a Maritime Transport Network: A Case of Imported Crude Oil in China

Crude oil transportation is a vital component of the global energy supply, and the global Crude Oil Maritime Transportation Network (COMTN) plays a crucial role as a carrier for crude oil transportation. Once the network faces attacks that result in the failure of certain routes, a severe threat is posed to the crude oil supply security of importing countries. Therefore, it is crucial to evaluate the reliability of the COMTN. This study proposes a model for evaluating the reliability of the imported COMTN by analyzing the impact of node failures. Firstly, the network is constructed using complex networks (CNs) theory, with ports, canals, and straits as nodes, and shipping routes as directed edges. Secondly, based on the Weighted Leader Rank algorithm, a comprehensive evaluation metric for CNs is established, and a node importance assessment model is developed to rank the nodes accordingly. Thirdly, a case study is conducted using China’s imported COMTN as an example, evaluating the connectivity reliability (CR) under random and deliberate attack scenarios. Finally, measures and recommendations are provided to enhance the CR of China’s imported COMTN. The findings indicate that deliberate attacks pose a greater threat, and reliability varies across maritime routes, with the Americas route exhibiting higher reliability compared to the Middle East and Southeast Asia routes. The results of this study can provide relevant recommendations for policy makers. The model proposed in this study can also be applied to other countries and regions to assess the connectivity reliability of their local COMTNs and develop appropriate measures for the results.

Systemic risks from climate-related disruptions at ports

Disruptions to ports from climate extremes can have systemic impacts on global shipping, trade and supply chains. By combining estimated climatic-related port downtime at 1,320 ports with a global model of transport flows, we pinpoint systemic risks to global maritime transport, trade and supply-chain networks. We estimate a total of US$81 billion of global trade and at least US$122 billion of economic activity being at-risk on average annually.

A multi-layer modelling approach for mining versatile ports of a global maritime transportation network

ABSTRACT International ports play critical roles in maintaining transportation flows and sustaining the effectiveness of global maritime logistics. Although the concept of versatile ports has been introduced to represent the specific patterns that these ports play at the regional and global levels, there is still a need for the design and development of computational approaches that support these notions. This paper introduces a flexible multi-layer network approach for an international maritime network whose interest is that it offers a flexible model that favours the identification of the different transportation flows and versatile ports. The model is complemented by a series of structural indices complemented by a new overlap measure that evaluates the specific role of a given port across various transportation trades. The whole approach is implemented and experimented with using massive AIS maritime data that supports the automatic generation of the multi-layer network, and derivation of the structural measures while maintaining a flexible view of the maritime network. The experiments applied to the global maritime transportation network identify key versatile ports and highlight significant differences at the regional and trade flow levels.

A Study on Grid-Cell-Type Maritime Traffic Distribution Analysis Based on AIS Data for Establishing a Coastal Maritime Transportation Network

Recently, marine development plans such as offshore wind farms and marina port facilities have been established to use Korean coastal waters, and research on the development of operational ships such as autonomous ships and water-surface flying ships is being rapidly promoted. Since the marine traffic in Korean coastal waters is expected to increase, the government intends to construct a coastal maritime transportation network that connects Korean coastal waters to guarantee safe ship navigation. Therefore, this study used automatic-identification-system data analysis to obtain quantitative evaluation results on maritime traffic distribution characteristics and utilization levels for the entire Korean coastal waters in grid cell for greater consistency and compatibility. The characteristics of marine traffic distribution at a certain site in coastal Korean waters can be quantitatively examined using the findings of this study, and they may be used as grid-cell-type data-based information. Moreover, the vessel traffic index allows for extensive research while quickly understanding the present level of use of the passing ships by the sea area. In this regard, the findings of this study are expected to be useful for the future development of maritime transportation networks in Korean coastal waters.

Prediction of the Estimated Time of Arrival of container ships on short-sea shipping: A pragmatical analysis

Fighting against climate change and global warming is one of the biggest challenges faced by the Maritime Industry nowadays to make the supply chain greener and environmentally sustainable. Cutting greenhouse gases (GHG) emissions and decarbonizing the international shipping has been a paramount activity for the International Maritime Organization (IMO) since the first set of international mandatory measures to improve ships' energy efficiency and reduce CO2 emissions per transport work, as part of the International Convention for the Prevention of Pollution from Ships (MARPOL) released in 2011. Besides that, changes in consumption habits around the globe (i.e., digitalization and growth of e-commerce) plus disruptive events like the COVID-19 or the blocking of the Suez Canal, to name only a few, have also highlighted the need for building more resilient maritime transport networks. In this work, a pragmatical analysis of the principal machine learning algorithms has been carried out to provide a qualitative prediction of the Estimate Time of Arrival (ETA) of container vessels applied to short-sea shipping where the distance between ports is reduced. By exploiting both, the Automatic Identification System (AIS) and meteorological data gathered over a desired area of interest, the developed approach delivers a model capable of predicting the ETA of ships where the reaction time of the stakeholders involved in the management of the Port Call is very reduced (i.e., less than two hours of sailing between ports) and therefore, tolerance for error is low. Very positive results were obtained for the training dataset collected under real conditions for more than a year. The best results were obtained by the RF model with a Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 11.31 and 19.56 minutes respectively.

A Practical Accessibility Evaluation Method for Port-Centric Coal Transportation Chains: Considering the Environment and Operational Adaptability

Improving the accessibility of coal transportation is a crucial issue for energy security, national defense, and livelihoods. In this study, a method to evaluate the performance of the port-centric coal transportation chain (PCTC), which is a crucial part of the international coal production and delivery process, is proposed. After analyzing the features of the port-centric coal transportation chain, a practical accessibility evaluation model is established based on the gravity model. Both the foreland and hinterland features are considered in the model. Based on the features of coal transportation, the concept of port operational adaptability is introduced to indicate the port’s ability to manage a fluctuating irregular workload. Moreover, environmental factors, including transportation emissions and dust pollution, are included in the evaluation system. Based on real data collected from China’s north-south coal transportation corridor, a case study presents the implementation of this comprehensive evaluation system in practice. This evaluation system enables us to determine the vulnerable areas in the coal maritime transportation network and provides a decision-making basis for both shippers and port owners.

The dynamics of value propositions through social media engagement in maritime transport networks: Maersk vs Mediterranean Shipping Company

PurposeThis study explores the levels of Facebook engagement of the two largest Europe-based shipping lines, Maersk and Mediterranean Shipping Company (MSC), to discover the marketing orientation of the topics advertised and to ascertain whether they tend to be about brand recognition, new transport services, or value propositions for stakeholders.Design/methodology/approachThe Facebook posts of Maersk and MSC were analysed using social media text mining and social network analysis (SNA); in- and out-degree centrality analysis was performed to determine the key terms in their posts. NetMiner software was used to collect the respective data on Maersk and MSC. The inquiry period was set between May 2020 and February 2021.FindingsThe results indicated a divergence in their post contents, with higher engagement and a wider, more active follower base for MSC than for Maersk. Maersk primarily posts about logistics services and supply chain solutions. MSC communicates about new and large container vessels. Both companies seek greater brand recognition and information sharing through social media.Originality/valueThese results can be used by the stakeholders to evaluate whether Maersk and MSC truly deliver on their respective value propositions communicated online through their social media engagement. It can also help Maersk and MSC gauge the level of effectiveness of their communication with stakeholders and modify their digital engagement strategy accordingly.

Ports’ criticality in international trade and global supply-chains

We quantify the criticality of the world’s 1300 most important ports for global supply chains by predicting the allocation of trade flows on the global maritime transport network, which we link to a global supply-chain database to evaluate the importance of ports for the economy. We find that 50% of global trade in value terms is maritime, with low-income countries and small islands being 1.5 and 2.0 times more reliant on their ports compared to the global average. The five largest ports globally handle goods that embody >1.4% of global output, while 40 ports add >10% of domestic output of the economies they serve, predominantly small islands. We identify critical cross-border infrastructure dependencies for some landlocked and island countries that rely on specific ports outside their jurisdiction. Our results pave the way for developing new strategies to enhance the resilience and sustainability of port infrastructure and maritime trade.

Exploring the vulnerability of transportation networks by entropy: A case study of Asia–Europe maritime transportation network

With the rise of global trade, maritime transportation networks have become an indispensable element of logistics networks. Approximately 80% of the global trade volume is transported by sea with the maritime logistics network fueling global economic integration. Due to the uncertainty of the transportation process and the impact of accidents, the reliability analysis of the logistics network is a topic of immense interest. In this paper, we propose an original and novel model to quantitatively analyze the vulnerability of the maritime logistics network by considering the importance of each port in the network. Three centrality measures that consider different topology information of the network are used in this paper to identify the importance of ports. Different information about the network is considered through the joint entropy and the multiscale factor q to evaluate the vulnerability of the logistics network. The Asia–Europe maritime transportation network serves as a real-world example to demonstrate the effectiveness and applicability of our proposed model. The experimental results suggest that the performance of the maritime network is closely related to the heterogeneity of the connectivity pattern and the process of decentralization can reduce the vulnerability of the maritime network.

Machine Learning Models for Efficient Port Terminal Operations: Case of Vessels’ Arrival Times Prediction

Port terminals are critical nodes in the maritime transport network and play a significant role in the global supply chain. However, they still suffer from many disruptions entailed by their complex environment leading to many challenges. With the maritime digital transformation, ports and ships produce significant amounts of data offering an opportunity to use Machine Learning techniques to address some issues and support port terminal operations management. This paper addresses the problem of vessel arrival times prediction to destination ports using Machine Learning models and vessels’ historical trajectories data. This paper also provides a structured overview of research work concerning the contribution of Machine Learning techniques in handling port terminal concerns. The existing literature shows that related work has tackled different problems, but further development is needed.

Long Short-Term Memory and Graph Convolution Network for Forecasting the Crude Oil Traffic Flow

Understanding maritime network structure and traffic flow changes is a challenging task that must incorporate economic, energy, geopolitics, maritime transportation, and network sciences. Crude oil is the most imported energy in the world. Investigating the crude oil maritime network status and predicting the crude oil traffic flow changes has great significance for the global trade, especially for key crude oil importing/exporting regions and countries. To address this, a system-based approach using long short-term memory and graph convolution network for the crude oil traffic flow forecasting named LGCOTFF is introduced. The LGCOTFF approach constructs a maritime transportation network firstly, and then calculates and predicts the node traffic flow based on trajectory data and crude oil berth geographical position. Firstly, we construct a maritime crude oil transportation network based on supply-demand relationship, ship trajectory and route information. Then, we design an approach to calculate how many crude oil ships finished up-load/offtake tasks in a single week for each port, and gather this data to countries and regions. Finally, we design a deep learning neural network named long short-term memory and graph convolution network (L-GCN) to extract the temporal and spatial characteristics of crude oil transportation, and predict the node traffic flow. We evaluate the proposed model on China, Russia, Middle East and America respectively and observe consistent improvement of more than 10% over state-of-the-art baselines.

Global shipping network dynamics during the COVID-19 pandemic's initial phases

Catastrophic incidents can significantly disrupt supply chains, but most of these disruptions remain localized. It was not until the onset of COVID-19 that a disruption in our lifetimes achieved a global magnitude. In order to contain the pandemic, governments around the world resorted to closing borders, shutting down manufacturing plants, and imposing lockdowns, which resulted in disrupted production capabilities and weakened consumer spending. The effects of these measures have been clearly visible in global transport networks, where disruptions ripple through the system and serve as a precursor to the disruptions in the broader economy. In this study, we use liner shipping schedule cancellations, a form of serious transport network disruption, as distress signals of the pandemic's impact on global supply chains. Our study applies a three-stage approach and provides insights into operator behaviors when under distress. We show that the pandemic challenged service network integrity and that network disruptions first clustered in Asia before rippling along main trade routes. Agile liner shipping operations, aided by planned service suspensions, prevented the collapse of the global maritime transport networks and indicated the maritime industry's ability to withstand even major catastrophic incidents.