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In the digital era, major shipping lines are developing instant quote and online booking platforms. In one of the first attempts to investigate the post-event effects of this trend, we evaluate how a shipping line's online quote platform impacts its shipper portfolio and the ordered container volume. In order to control for unobserved, time-varying effects that could be correlated with the platform's implementation, we apply the regression discontinuity design (RDD) method to the import trade data from 2016 to 2019 of a top shipping line that released its platform in August 2018. We also adopt global polynomial regression and local liner regression so as to control for the effects of different polynomial time trends. We find the container volume assigned to the shipping line declined slightly after the online platform was launched. The container orders of small shippers increase by 3.97 TEU on average after online platform adoption. The volume of assigned containers from other shippersdeclines. These findings hold fruitful implications for shipping lines. A significant increase in the number of small shippers and their container volumes demonstrate administrative cost saving and risk mitigation for a shipping line. However, it also leads to possible loss of large customers. [ABSTRACT FROM AUTHOR]

This article presents an analysis of the competitiveness of Brazilian container port terminals and discusses the implications for the sustainable development of this sector in Brazil in the context of container ship size maximization. A cluster analysis was developed. Thirteen criteria were selected in the analysis taking into consideration both the previous literature and the characteristic of Brazilian ports. The classification shows that the third group of terminals (Santos Brasil, BTP and Paranaguá) has the highest average values in eleven out of the thirteen criteria, standing out mainly in annual capacity, number of plugs, and GDP hinterland. This is the most competitive group with the highest frequency of ship visits. It is also interesting to find that this group of terminals has a limitation regarding the operational draft that limits the port sector when receiving large ships. Considering the expected inclusion of New Panamax-class ships operating on the Brazilian coast, container terminals have restrictions due to the limited operational draft. Conclusions are drawn regarding the potential for implementing strategies and policy interventions. The study represents an application inspired by the current debate in the Brazilian port sector, which presents the country's urgent problem of receiving large capacity ships. [ABSTRACT FROM AUTHOR]

It is a common practice to promote highly discounted fares by cruise companies to enlarge the market share, ignoring economically sustainable development. In some regions, the continuous discounted fares leading to the unsatisfying revenue may be the main cause of decline in ports calls. Cruise companies have learned that dynamic pricing would be much more advantageous at revenue management instead of blindly lowering fares. This paper illustrates such an attempt. We try to dynamically price multiple types of staterooms with various occupancies and evaluate the effect on demand and revenue from different discount and refund policies. We first formulate the cruise pricing problem as Markov Decision Process and Reinforcement Learning (RL), more specifically, state-action-reward-state-action (SARSA) algorithm, is applied to solve it. We then use empirical data to validate the feasibility of RL. Results show that both revenue and demand could be improved under reasonable discount policies. In addition, we demonstrate that reasonable refund policies can also facilitate revenue growth. Finally, a comparison between SARSA algorithm and Q-learning algorithm is discussed. Our finding suggests that SARSA results in higher revenues but takes more time to converge. [ABSTRACT FROM AUTHOR]

This study develops a generalized F distribution model with random parameters to estimate the ship property damage cost in maritime traffic accidents with 10 years’ shipping accident data in the Fujian waters. Model results show that sinking and capsizing can incur the largest property damage cost, followed by collisions, contact, grounding and fire/explosion. There is a smaller ship property damage cost when the ship is moored or docked. The poor visibility has the least impact on the increment of ship property damage cost. Results reveal that the bigger property damage cost is associated with maritime accidents occurring in the Straits/sea areas and under the strong wind/wave condition and nighttime periods. It is also found that the lookout failure exhibits a bigger effect than the operation error. These results are helpful for policy makers to make efficient strategies for reducing property damage cost in maritime accidents. The developed model is useful for insurance companies in determining the appropriate ship insurance rates. [ABSTRACT FROM AUTHOR]

This study proposes high-frequency container port congestion measures based on Automatic Identification System (AIS) data. Vessel movement information of 3,957 container ships from March 2017 to April 2017 is included. The world top 20 container ports' berth and anchorage areas are identified through Density Based Spatial Clustering of Applications with Noise (DBSCAN) and convex hull methods, and their hourly port congestion statuses are depicted in terms of the traffic volume and turnaround time. The constructed congestion measures overcome the disadvantages of the traditionally used port or industry data, which is heterogenous, behind the time and not easy to obtain publicly. The higher frequency (hourly) of the proposed measures can effectively monitor any slight change in port performance. A Long Short-Term Memory (LSTM) neural network model is then proposed for congestion prediction using constructed congestion measures. Point prediction and sequence prediction are both performed. We innovatively introduce congestion propagation effects into the prediction model as input features. Using Shanghai, Singapore and Ningbo ports as case studies, results show that the inclusion of congestion propagation effect can improve the prediction performance especially for sequence prediction. This study provides significant implications and decision support for container shipping market participants. [ABSTRACT FROM AUTHOR]

The focus of this paper is the selection of paths for the maritime transportation of crude oil. In addition to transportation cost, the nodes in a maritime transportation network are always affected by extreme events. Therefore, connectivity reliability must be considered during path selection. In this paper, uncertainty variables are introduced to describe the connectivity reliability of nodes under the influence of extreme events, and an uncertain bi-objective programming model with connectivity reliability maximization and transportation cost minimization as objectives is established for path selection. China’s maritime transportation network for crude oil imports is used as a case study to validate the model, the effects of variations in the model parameters on path selection, transportation cost and connectivity reliability are discussed in the case study. The research results provide a basis on which for government decision makers to better plan crude oil transportation strategies. [ABSTRACT FROM AUTHOR]

The trend towards global warming and the rapid decline in the extent of summer Arctic sea ice over recent years has increased the feasibility of international Arctic shipping. In this study we propose a seasonal NSR (North Sea Route)/SCR (Suez Canal Route)-combined shipping service linking Shanghai and Rotterdam, using the Northern Sea Route during the economical navigable window but using the traditional Suez Canal Route at other times. Different from the previous literatures, this paper dynamically considers the sea ice extent in the model, which is more reasonable for the assessment of Arctic container shipping, because fuel consumption is highly related to ship speed, while ship speed is determined by the relative distances of ice-covered and ice-free route stages. A new approach is developed to predict the time points at which the ship enters and exits the ice-covered stage, given that both the ship position and the extent of sea ice are constantly changing. The results show that the NSR/SCR-combined Arctic container service can be more economical than the SCR, given lower NSR tariffs. [ABSTRACT FROM AUTHOR]

In the past decades, a multilayer transshipment network of bulk shipping has been formed along the Yangtze River so as to support the fast development of Chinese iron and steel industry. Yet with the decrease of iron ore trade in China since 2014, the bulk port system on Yangtze River probably will be subject to change in the future. Under this background, this paper aims to analyze the development potential of Yangtze River bulk ports system with a focus on iron ore transshipment. To realize this objective, we firstly sort out the main transshipment patterns of bulk shipping, and optimize the bulk-shipping network with an optimization model. Several scenarios are then proposed and examined in the model by changing corresponding parameters. Cooperation among ports as one scenario is analyzed by applying core theory in cooperative game. Based on the changes of transshipment plans observed under the various scenarios, we finally ascertain the different development potentials of the system, and provide suggestions to the port operators and local maritime authorities. [ABSTRACT FROM PUBLISHER]

To accommodate the structural changes in logistics, competitions along a maritime supply chain are more intensive than before. This paper adopts a two-stage noncooperative game-theoretical approach to model the horizontal and vertical interactions among liners and ports. In the first stage, Bertrand game is applied to model the interactions between two liners. When the shipping line decides which port to call, a multinomial Logit model is applied. In the second stage, Bertrand game is applied to model the competitions between two ports. Nash equilibrium is derived by solving the Bertrand games. A numerical example is provided as a case study. [ABSTRACT FROM AUTHOR]

The Chinese government has been exploring various paths to find a direction that better suits China’s national conditions during the past 60 years. Meanwhile, a series of political and economic events and policy transformations have had different effects on the port industry. This article attempts to ascertain how these events and port policies have influenced Chinese port traffic through an empirical study on data covering 1952–2009. The findings suggest that foreign trade has been the prime driver of the throughput of Chinese ports. The increase in the ports’ throughput has enabled an increase in domestic demand and the urgent need for further port investment. Chinese port throughput has been subject to multiple shocks. The Great Leap Forward1is found to have had the largest, but only a short-term impact. China’s accession to the World Trade Organization, however, led to a longer and exclusive effect on ports, with little observed effect on the other variables. The reform of port governance is shown to have had a more lasting positive effect on port throughput than physical investment. However, these latter effects are minor, the economic and political factors remain the primary driving factors of port throughput. [ABSTRACT FROM AUTHOR]

As part of a comprehensive regional or global maritime trade modeling framework, it is often necessary to determine the modal share of commodity flow between countries. Typically, this is resolved by either using a constant empirical value (such as the commodity value-weight ratio) or applying statistical models to determine mode choice or share. Whilst the latter method tends to provide a more rational solution, it is constrained by the appropriate choice of trade data classification level during model development. This paper therefore explores the potential impact of trade data aggregation (in terms of trade data classification level) on commodity mode choices derived from discrete choice models. Using international commodity flows between continents, discrete choice models can be developed to compare the modal split between air and sea transport. By considering four different international trade routes and three trade classification levels, the paper shows that detailed commodity trade classification may not necessarily lead to better results. Using the Harmonized Commodity Description and Coding System (or HS System) as an example, it was found that it may be more effective developing models using HS two-digit commodity trade data for the purpose of international freight mode choice studies for the purpose of regional or global maritime trade modeling. [ABSTRACT FROM AUTHOR]

Maritime transportation is important, not only for its contribution to global trade, but also for its potential role in our common effort to curb the global environmental problems and make the world's economic development sustainable. An interesting finding is that shipping firms are more likely to adopt proactive GSCM strategies, which contradicts the findings of most management studies that reactive firms outnumber proactive and leading companies. All sample firms were clustered into "the leaders", "proactive firms", and "reactive firms" according to their level of GSCM strategy adoption. [Extracted from the article]

China has been continuously implementing the open-door policy for past 15 years ever since it joined the World Trade Organization, which escalated international trade and demand for shipping. Compared with the other major importing countries in the world, China’s importing tariff is relatively low. Under the Belt and Road initiatives, more Free Trade Agreements to be concluded and more Free Trade Zones to be established, it is expected that the effective import tariff rate may continue to decrease in the future. This study analyses the impact of further reduction in Chinese import tariff rate on major economic indicators using a computable general equilibrium (CGE) model and based on the Chinese macro-economic data of 2012. The model results show that, with a balanced international payment, such a reduction can increase GDP, resident consumption, both imports and exports, and reduce GDP price, trade surplus, and government revenue. The results ease the concern that further import tariff reduction may harm the domestic production. Rather, it points out that there are still rooms to improve national economy and increase the consumer utility by trade liberation. [ABSTRACT FROM AUTHOR]

To reduce CO2 emissions from shipping activities to, from, and within the European Union (EU) area, a system of monitoring, reporting, and verification (MRV) of CO2 emissions from ships are implemented in 2015 by the EU. Although the MRV records in 2018 and 2019 have been published, there are scarce studies on the MRV system especially from a quantitative perspective, which restrains the potential of the MRV. To bridge this gap, this paper first analyzes and compares MRV records in 2018 and 2019, and then develops machine learning models for annual average fuel consumption prediction for each ship type combining ship features from an external database. The performance of the prediction models is accurate, with the mean absolute percentage error (MAPE) on the test set no more than 12% and the average R-squared of all the models at 0.78. Based on the analysis and prediction results, model meanings, implications, and extensions are thoroughly discussed. This study is a pioneer to analyze the emission reports in the MRV system from a quantitative perspective. It also develops the first fuel consumption prediction models from a macro perspective using the MRV data. It can contribute to the promotion of green shipping strategies. [ABSTRACT FROM AUTHOR]

This study aims to model the complex relationship among the traffic characteristics (i.e. traffic flow, traffic speed, traffic density), environmental conditions (i.e. darkness condition, weather condition and traffic lane width) and frequency of ship collisions in the Yangtze River estuary areas. Taking into account the effects of ship approach angle, ship type, relative speed and darkness condition on the capability of ship collision avoidance, a dynamic ship domain model has been presented to measure ship collision frequency. Considering the big variation associated with the collision frequency, the measured ship collision frequency is further modeled as a loglogistic-distributed function of traffic characteristics and environmental conditions. Results show that the collision frequency is greater for (i) the bigger traffic flow; (ii) the bigger traffic density; (iii) the narrower traffic lane width; and (iv) the adverse weather condition. The darkness condition is the influencing factor that produces the biggest effect on the ship collision frequency. [ABSTRACT FROM AUTHOR]