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The purpose of this paper is to empirically examine the relationship between intensity of competition and technical efficiency of large European container ports, accounting for regional diversities and spatial aspects of inter-port competition.

The analysis consists of applying a stochastic production frontier approach to a dataset of 77 large European container ports over the period 2002-2012, with inefficiency terms simultaneously modeled as a function of (among other factors) a constructed index of competitive intensity at different spatial levels.

The results indicate that there is no significant negative effect of competitive intensity on efficiency. In fact, for competing European ports within a proximity of 300 km, a higher level of competition is found to be associated with a higher level of technical efficiency.

The originality of the paper stems from its particular focus on European port regions and its novel findings in this context, which have implications for the discussions regarding pro-competitive port policy and regulation in the European Union.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

Container shipping is a crucial component of the global supply chain that is affected by a large range of operational risks with high uncertainty, threatening the stability of service, manufacture, distribution and profitability of involved parties. However, quantitative risk analysis (QRA) of container shipping operational risk (CSOR) is being obstructed by the lack of a well-established theoretical structure to guide deeper research efforts. This paper proposes a methodological framework to strengthen the quality and reliability of CSOR analysis (CSORA).

Focusing on addressing uncertainties, the framework establishes a solid, overarching and updated basis for quantitative CSORA. The framework consists of clearly defined elements and processes, including knowledge establishing, information gathering, aggregating multiple sources of data (social/deliberative and mathematical/statistical), calculating risk and uncertainty level and presenting and interpreting quantified results. The framework is applied in a case study of three container shipping companies in Vietnam.

Various methodological contributions were rendered regarding CSOR characteristics, settings of analysis models, handling of uncertainties and result interpretation. The empirical study also generated valuable managerial implications regarding CSOR management policies.

This paper fills the gap of an updated framework for CSORA considering the recent advancements of container shipping operations and risk management. The framework can be used by both practitioners as a tool for CSORA and scholars as a test bench to facilitate the comparison and development of QRA models.

The accurate valuation of second-hand vessels has become a prominent subject of interest among investors, necessitating regular impairment tests. Previous literature has predominantly concentrated on inferring a vessel's price through parameter estimation but has overlooked the prediction accuracy. With the increasing adoption of machine learning for pricing physical assets, this paper aims to quantify potential factors in a non-parametric manner. Furthermore, it seeks to evaluate whether the devised method can serve as an efficient means of valuation.

This paper proposes a stacking ensemble approach with add-on feedforward neural networks, taking four tree-driven models as base learners. The proposed method is applied to a training dataset collected from public sources. Then, the performance is assessed on the test dataset and compared with a benchmark model, commonly used in previous studies.

The results on the test dataset indicate that the designed method not only outperforms base learners under statistical metrics but also surpasses the benchmark GAM in terms of accuracy. Notably, 73% of the testing points fall within the less-than-10% error range. The designed method can leverage the predictive power of base learners by incrementally adding a small amount of target value through residuals and harnessing feature engineering capability from neural networks.

This paper marks the pioneering use of the stacking ensemble in vessel pricing within the literature. The impressive performance positions it as an efficient desktop valuation tool for market users.

The authors have faced rapid technological developments over the past few years. Still, the authors face challenges of maritime supply chain inefficiency, high costs and the low competitiveness of Indonesian ports. In line with the flow of this research, the purpose of this paper is to conceptualise best practices to improve port connectivity, which impacts improving maritime logistics capabilities in Indonesia that are relevant to the current situation.

The authors utilise surveys and interviews as a data collection method, where several sources were actors in the maritime logistics industry. The authors also use secondary data from the Ministry of Transport of the Republic of Indonesia, online databases as well as trade magazines and newspapers. This paper conducts a multiple case study and principal component analysis (PCA) to meet the research objectives.

The intention to use port digitisation services will increase if the perceived usefulness of the service also increases. Also, if the negative coefficient of user trust rises, it will bring a very sharp decrease in customers' intentions to use. Furthermore, the high estimated value of context indicates that users expect to have a good experience using the application and bring benefit to their business.

Based on the authors’ knowledge, there has been no review about port digitalisation, specifically in Indonesia. The authors initially provided best practices to improve port connectivity, which can impact improving maritime logistics capabilities.

The study examined the effect of optimal port operations on global maritime transportation among selected ports in Nigeria.

It considered research questions such as are the ports in Nigeria functional, are the ports functioning to optimal capacity and are there challenges affecting smooth operations in the Nigerian ports? The study tested the null hypothesis which states that there is no positive and significant relationship between a functional port system and maritime transportation in Nigeria. The nonparametric statistics, chi-square, were used to analyze data. Data were gathered through a questionnaire administered to three major ports in Nigeria, namely Lagos Port Complex (LPC), Port Harcourt Old port and Warri Port.

From the analysis, findings showed that there exists a positive and significant relationship between operations in the ports and maritime transportation in Nigeria. Practical implications: The study showed that the moribund state of some ports and terminals will result in loss of jobs and huge revenue, therefore, compounding the menace of unemployment with its associated vices.

The study concludes that the operations of a functional port affect the economic growth of maritime nations. Thus, it is recommended that government and the private sector should collaborate to raise adequate capital for port development and improve the super structures (infrastructures) for optimal port operations in the country among others.

The introduction of information technology (IT) in port operations has been a tremendous contributor to transformation in world trade. This study was carried out to examine the influence of IT on the efficiency of seaport operations.

The study is quantitative in nature, and it relied on a closed-ended self-administered questionnaire to collect primary data. Structural equation modeling (SEM) was used to test the theoretical model and hypothesis.

The results indicate that IT has a positive direct effect on port operational efficiency (OE) and an indirect effect on port OE through organizational culture (OC). The mediating role of OC is statistically insignificant.

This is among the first few attempts in Sub-Saharan Africa (SSA) that provides researchers with a contemporary view of IT and seaport operations.

Port performance and port choice have been treated as separate streams of research. This hampers the efforts of ports to anticipate on and respond to possible future changes in port choice by shippers, freight forwarders and carriers. The purpose of this paper is to develop and demonstrate a port performance measurement methodology, extended from the perspective of port choice, which includes hinterland performance and a weighting of attributes from a port choice perspective.

A review of literature is used to extend the scope of port performance indicators. Multi-criteria decision analysis is used to operationalize the context of port choice, presenting a weighted approach using the Best-Worst Method (BWM). An empirical model is built based on an extensive port stakeholder survey.

Transport costs and times along the transport chain are the dominant factors for port competitiveness. Satisfaction, reputation and flexibility criteria are the other important decision criteria. The results also show how the availability of different modal alternatives impact on the position of a port. A ranking of routes for hinterland regions is done.

The paper focuses on two extensions of port performance measurement. So far, not all factors that determine port choice have been included in port performance studies. Here, first, factors related to hinterland services are included. Second, a weighting of port performance measures is proposed. The importance of factors is assessed using BWM. The approach is demonstrated empirically for a case of the European contestable hinterland regions, which so far have lacked quantitative analysis.

This study aims to explain the facts about behavioral biases that cannot be explained by rational patterns in ship investments of small-size shipping companies.

A qualitative approach was adopted in this study. The systematic approach of Wolcott (1994) and the action flows proposed by Miles and Huberman (1994) were taken into consideration.

Factors affecting ship investments are classified as ship finance, market timing, ship specifications and profile and business models of ship investors. In addition, behavioral biases that stand out under each theme are explained in the light of behavioral finance literature.

The originality of this study rests on the lack of studies on behavioral aspects of ship investments.