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This study examines the effectiveness of digital recruitment platforms in addressing labor shortages within Norway's shipbuilding and ship-repair industry. Through a data analysis of 446 job applications over a 12-month period, this study evaluates key recruitment metrics, including application response times (ARTs), candidate acceptance rates (CARs), and the impact of machine learning on hiring outcomes. The findings reveal that specialized digital platforms can significantly improve recruitment efficiency, with 70% of applications being received within 24 h, highlighting the platforms's great potential for time-sensitive sectors. Additionally, pre-vetting candidates enhances hiring precision, achieving a CAR of 90% and reducing mismatches. The application of machine learning algorithms provides predictive insights that support real-time adjustments to job postings, optimizing recruitment strategies. This study contributes uniquely to the literature on cross-border digital recruitment, aligning with the European Union goals of sustainable labor mobility and economic resilience. [ABSTRACT FROM AUTHOR]

The maritime industry is under increasing pressure to reduce CO2 emissions, with the International Maritime Organization (IMO) setting a target to reduce greenhouse gas emissions, including emissions from the port sector, by 40% by 2030. However, accurate and reliable methods for estimating CO2 emissions at container ports, which are significant contributors to maritime emissions, are still lacking. This study aims to address this by evaluating a novel method for estimating CO2 emissions at container ports. The proposed method utilizes the cargo handling equipment movement theory, quantifying both vertical and horizontal movements based on the amount of container handling equipment at the port. The emissions for each piece of equipment are estimated by multiplying the movement quantity by the respective emission factor. To validate the model, a robustness test compares the estimated CO2 emissions with actual energy consumption data from the port. A case study was conducted at a container port with an annual capacity of over 500,000 TEUs and a parallel layout type. The estimated CO2 emissions were approximately 8183 tons per year, with container cranes contributing 56%, rubber-tire gantry cranes contributing 27%, terminal trucks contributing 14%, and reach stackers contributing 3%. The method demonstrated accuracy, with a deviation of less than 1%. This method offers a fast and reliable approach for estimating baseline CO2 emissions at container ports, providing valuable insights for port authorities and policymakers to develop more effective emission-reduction strategies. [ABSTRACT FROM AUTHOR]

The application of artificial intelligence models for the fault diagnosis of marine machinery increased expeditiously within the shipping industry. This relates to the effectiveness of artificial intelligence in capturing fault patterns in marine systems that are becoming more complex and where the application of traditional methods is becoming unfeasible. However, despite these advances, the lack of fault labelling data is still a major concern due to confidentiality issues, and lack of appropriate data, for instance. In this study, a method based on histogram similarity and hierarchical clustering is proposed as an attempt to label the distinct anomalies and faults that occur in the dataset so that supervised learning can then be implemented. To validate the proposed methodology, a case study on a main engine of a tanker vessel is considered. The results indicate that the method can be a preliminary option to classify and label distinct types of faults and anomalies that may appear in the dataset, as the model achieved an accuracy of approximately 95% for the case study presented. [ABSTRACT FROM AUTHOR]

This article proposes a comprehensive framework for enhancing information exchange in ship maintenance through the integration of Digital Twins (DTs) and the Internet of Things (IoT). The maritime industry faces significant challenges in maintaining ships due to issues like data silos, delayed information flow, and insufficient real-time updates. By leveraging advanced technologies such as DTs and IoT, this framework aims to optimize maintenance processes, improve decision-making, and increase the operational efficiency of maritime vessels. Digital Twins create virtual replicas of physical assets, allowing for continuous monitoring, simulation, and prediction of ship conditions. Meanwhile, IoT devices enable real-time data collection and transmission from various ship components, facilitating a seamless flow of information. This integrated approach enhances predictive maintenance capabilities, reduces downtime, and improves resource allocation. The article will delve into the architecture of the proposed framework, implementation steps, and potential challenges, supported by case studies that demonstrate its practical application and benefits. By addressing these aspects, the framework aims to provide a robust solution for modernizing ship maintenance operations and ensuring the longevity and reliability of maritime assets. [ABSTRACT FROM AUTHOR]

Deep learning is crucial in marine logistics and container crane error detection, diagnosis, and prediction. A novel deep learning technique using Long Short-Term Memory (LSTM) detected and anticipated errors in a system with imbalanced data. The LSTM model was trained on real operational error data from container cranes. The custom algorithm employs the Synthetic Minority Oversampling TEchnique (SMOTE) to balance the imbalanced data for operational data errors (i.e., too few minority class samples). Python was used to program. Pearson, Spearman, and Kendall correlation matrices and covariance matrices are presented. The model's training and validation loss is shown, and the remaining data are predicted. The test set (30% of actual data) and forecasted data had RMSEs of 0.065. A heatmap of a confusion matrix was created using Matplotlib and Seaborn. Additionally, the error outputs for the time series for the next n seconds were projected, with the n seconds input by the user. Accuracy was 0.996, precision was 1.00, recall was 0.500, and f1 score was 0.667, according to the evaluation criteria that were produced. Experiments demonstrated that the technique is capable of identifying critical elements. Thus, future attempts will improve the model's structure to forecast industrial big data errors. However, the advantage is that it can handle imbalanced data, which is usually what most industries have. With additional data, the model can be further improved. [ABSTRACT FROM AUTHOR]

Maritime transportation is crucial for global trade and responsible for the majority of goods movement worldwide. The optimization of maritime operations is challenged by the complexity and heterogeneity of maritime nodes. This paper presents the emerging deployment of federated learning (FL) in maritime environments to address these challenges. FL enables decentralized machine learning model training, ensuring data privacy and security while overcoming issues associated with non-i.i.d. data. This paper explores various maritime use cases, including fuel consumption reduction, predictive maintenance, and just-in-time arrival. Experimental results using real datasets demonstrate the superiority of FL in predicting the fuel consumption of large cargo ships in terms of accuracy and spatiotemporal complexity over traditional collaborative machine learning approaches. The findings indicate that FL can significantly improve the performance of fuel consumption models in a collaborative way, while ensuring data privacy preservation and no data transmission during the learning process. Finally, this paper discusses open issues and future research directions necessary for the widespread adoption of FL in maritime transportation and settings. [ABSTRACT FROM AUTHOR]

As technology advances and digitalization becomes more prevalent in the industry, the cyber threats to maritime systems and operations have significantly increased. The maritime sector relies heavily on interconnected networks, communication systems, and sophisticated technologies for its operations, making it an attractive target for cybercriminals, nation-states, and other threat actors. Safeguarding the maritime sector against cyber threats is crucial to ensuring the safety, integrity, and efficiency of maritime operations as well as for protecting sensitive information and global trade. The International Maritime Organization (IMO) has played a significant role in addressing cybersecurity issues, leading to the implementation of regulations aimed at risk reduction. This paper delves into the realm of cybersecurity within the maritime industry, offering an in-depth analysis of its various aspects through an extensive literature review based on the latest Version 2.0 of the National Institute of Standards and Technology's (NIST) Cybersecurity Framework (CSF) functional areas. The primary objective is to establish a connection between research and NIST's functions and categories, thereby presenting a nascent perspective and identifying existing security research gaps. Through the adoption of this strategic approach, the present paper aims to cultivate a forward-looking and proactive state of maturity in anticipation of future developments within the maritime industry. The outcomes of this research can provide valuable reference points in academic discourse, potentially leading to new hypotheses, and fuel innovation in developing advanced cybersecurity measures within the maritime industry. [ABSTRACT FROM AUTHOR]

The concept of maritime circularity has gained increasing attention to address challenges arising from the net-zero targets of the maritime industry. The circular economy provides potential solutions to address these challenges through reuse, remanufacturing, and recycling practices. However, the industry faces complex challenges, including inefficient reverse supply chains, a lack of awareness about circular economy principles, standardisation issues, and the need for digital infrastructure to provide vital information in the sector. These challenges prevent the implementation of circularity practices, as access to crucial data throughout the vessel's life cycle is obstructed. This novel research aims to create a robust first-of-its-kind database solution specifically designed to support the industry's shift towards circularity. The database will facilitate fast and transparent information flow between the stakeholders, providing foundations for asset tracking and a robust reverse supply chain. A case study was conducted to show that a database could help extract higher financial value from end-of-life ships by over 80%. The ageing fleet increases the urgency of utilising such a database, which could be a pivotal strategy for a sustainable and circular industry. This digital solution offers significant benefits to all industry stakeholders and allows holistic resource management, influencing maritime operations' sustainability, resilience, and profitability. [ABSTRACT FROM AUTHOR]

The maritime industry is regarded as the fulcrum of the global economy. It contributes significantly in diverse ways to the movement of goods. To effectively deliver on its mandate, maritime transportation needs to be sustainable. In the absence of a resilient and highly adaptive workforce; however, it is impossible to address the tangible set of economic, environmental and social expectations for the sector. From a human capital perspective, this paper explores the emerging dynamics of producing a sustainable workforce for global maritime transportation. Results from a recent study involving 305 ship officers (web-based survey) are compared with new changes (from academic sources and industry reports) in the maritime transportation sector. The comparison (findings) highlights emerging changes within the global maritime workforce and the implications for skill development. It also emerged that the shortage of highly skilled talent (on both the landside and seaside) is a critical challenge and is being exacerbated by growing industry changes. Ultimately, these developments endanger sustainable maritime transportation. Consequently, the paper proposes a skill resilience framework with which industry stakeholders could identify skill gaps among the workforce and improve training content to produce an adaptive workforce capable of handling emerging challenges. [ABSTRACT FROM AUTHOR]

Recently, decarbonizing the maritime industry, which accounts for 2.8% of world emissions, has become essential. However, as a crucial component of maritime transportation, container shipping also carries substantial significance. In this context, the International Maritime Organization endeavors to endorse several projects and methods to mitigate maritime transport emissions. As a result, this research assesses frameworks, infrastructure, training, and other critical factors to analyze multiple operational and technological possibilities for predicted decarbonization solutions in container shipping using the multi-criteria decision-making (MCDM) approach to assess ship owners' and stakeholders' desires. It employs a comprehensive methodology that begins with a systematic literature review using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) method to prepare questionaries, followed by an MCDM analysis using the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) methods to examine the results. This research contributes to the scholarly discourse on reducing the emissions of maritime transportation. According to the findings, operational alternatives, such as ship speed, trim, and maritime route optimizations, are considerably more appealing than design and technology solutions, such as technically advanced ship hulls or machinery reforms. The pragmatic advantages of the operational alternatives, such as lower costs and shorter implementation schedules, stimulate their adoption. In contrast, design and technological solutions can influence emission reductions in the long term. It is possible to find operational alternatives for short-term decarbonization, while technological and design advancements can aid in long-term emission reductions in container shipping. [ABSTRACT FROM AUTHOR]

Climate change mitigation is one of the most important challenges facing the modern world. It is necessary to monitor the development of new concepts and technologies and take a stab at identifying disruptive innovations, which have the potential of becoming real climate-friendly game changers. The aim of this paper is to examine the patterns of inventive activity aimed at mitigating climate change in the maritime industry with respect to other transport modes. Appropriate research tools in the area of patent analysis were selected and utilised. A new class of patents related to climate change in maritime transport (CPC-Y02T70/00) was used as a data source. The original value of the study consists of offering a complete picture of the efforts made in patenting activity in climate change mitigation in the maritime transport, with a look at leading applicants and countries, knowledge flows, the most robustly developed and underdeveloped technical fields. A map of technical knowledge flows for climate change mitigation in transport was constructed. The research results show that inventions for the maritime industry are less hermetic than those for air and road transport; however, they are not as much linked with previously developed solutions. The most intensively developed technical fields include the design and construction of watercraft hulls (1) and measures to reduce greenhouse gas emissions related to the propulsion system (2). Among the technologies whose further development merits close attention are solutions related to electrical propulsion and wave energy. At the same time, inventive activity in the area of climate change adaptation dedicated to ports is insignificant and definitely needs more support from the community of scientists and inventors. Building knowledge based on patent information can help universities, research institutions, shipyards, manufacturers of marine equipment and other business entities to identify the technologies of the greatest potential for further development. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is significantly transforming the maritime industry, enabling the generation of vast amounts of data that can drive operational efficiency, safety, and sustainability. This review explores the role and potential of data analysis in maritime IoT applications. Through a series of case studies, it demonstrates the real-world impact of data analysis, from predictive maintenance to efficient port operations, improved navigation safety, and environmental compliance. The review also discusses the benefits and limitations of data analysis and highlights emerging trends and future directions in the field, including the growing application of AI and Machine Learning techniques. Despite the promising opportunities, several challenges, including data quality, complexity, security, cost, and interoperability, need to be addressed to fully harness the potential of data analysis in maritime IoT. As the industry continues to embrace IoT and data analysis, it becomes critical to focus on overcoming these challenges and capitalizing on the opportunities to improve maritime operations. [ABSTRACT FROM AUTHOR]

The maritime industry is displaying notable interest in the adoption of cutting-edge technologies within the scope of Industry 4.0, aiming to digitalize both companies and processes. At the core of data science lies machine learning, which serves as the focal point of this article. This study seeks to accomplish two main objectives: firstly, an exploration of various machine learning algorithms, and subsequently, the application of these techniques to analyze predictions within the propulsion system of a 9500 TEU container ship. The outcomes of the study reveal that utilizing distinct machine learning algorithms for predicting braking performance yields a lower mean square error (MSE) when compared to the discrepancy introduced by the J. Mau formula, as evident in the container ship database. The selection of propulsion engines was based on predictions for a 9500 TEU container ship. Similarly, promising outcomes were achieved in predicting propeller diameter in comparison to conventional methods. Thus, these predictions can also effectively guide the appropriate choice of propeller diameter. [ABSTRACT FROM AUTHOR]

Due to an ever-increasing movement of containers across the globe in line with the economic boom, the trade imbalance and issues related to empty containers have become inevitable. Empty containers accumulated at specific ports cannot only generate profit but also increase the environmental footprint. This research proposes a Maritime Empty Container Reposition Modelling Framework by integrating the agent-based modelling (ABM) paradigm to model the global movements of empty containers. An agent-based maritime logistic empty container redistribution model was developed to help minimize the total relevant costs for empty container movement in the planning horizon. In the system, ports, shipping companies, customers, and empty containers were identified as critical agents. Using simulated annealing (SA), shipping line agents were able to optimise empty container repositioning to determine the best sequence for moving containers. The model was applied to the Asia–Middle East region to simulate global empty containers repositioning in the region. The results comparison shows that the proposed optimised empty container repositioning framework can significantly reduce the shipping line's costs and make full use of empty containers. [ABSTRACT FROM AUTHOR]

According to the European Maritime Safety Agency (EMSA), 70% of accidents on board were caused by human error, and almost one-fifth of these accidents have been related to inadequate supervision. Therefore, the aim of this study is to investigate which of the safety factors can influence the quality of safety supervision. For this purpose, a questionnaire with 24 statements was distributed to professional seafarers. Two exploratory factor analyses were conducted to identify the underlying factor structure. The first analysis yielded one factor, quality of safety supervision, and the second analysis yielded four factors, namely: safety communication, safety training, safety compliance, and safety rules and procedures. Hierarchical multiple regression analysis was applied to examine the influence of seafarers' demographic characteristics and the four identified factors on the quality of safety supervision. The results revealed the following two statistically significant predictors of safety supervision quality: safety communication and safety training. The theoretical and practical implications of the results in terms of improving the quality of safety supervision in the maritime industry were discussed and compared with results in other industries. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions in shipping have been receiving growing concerns in the maritime industry. Recently, the International Maritime Organization (IMO) is considering the introduction of a global shipping carbon tax, which has become the most talked-about topic in both industry and academia. To assess the potential impact of the carbon tax on maritime trades, a trade-volume-based model of shipping carbon emissions was developed. Considering that bulk shipping is the second-largest carbon emitter in the maritime industry and the low value-to-weight nature of bulk cargoes, the model was applied to analyze the dry bulk trade in China, one of the leading countries in the global dry bulk trade. The results show that the introduction of the carbon tax could have significant impacts on freight rates and commodity prices. Depending on the trading regions and the carbon charges, shipping freight rates would increase by 10–30%, which is equivalent to 1–4% of the trading prices. Additionally, since shorter shipping distances may have less emission per trading tonnage, the shipping carbon tax may significantly change the dry bulk trade patterns, resulting in China's increasing reliance on nearby countries, e.g., India and Australia, for the import of key commodities. These findings can help shipping companies and sectors make better carbon reduction responses, such as redeploying their fleets, promoting the development of low-carbon shipping technologies, and increasing investments in Australia, as well as South and Southeast Asia. [ABSTRACT FROM AUTHOR]

(1) Background: The resilience concept shows performance improvement in four potential aspects consisting of the ability to respond, provide anticipatory action, control things that occur internally and externally, as well as the learning process of what is going right and what is going wrong. This study aims to analyze the safety resilience implementation in the Indonesian maritime sector. (2) Method: This is a descriptive study using semi-quantitative methods, using interview guides based on the Resilience Assessment Grid (RAG). The sampling technique is purposive sampling. (3) Results: The level of implementation of safety resilience at the public company was 75.1%, while the private company was 70.2%. The score for each safety resilience element in the public and private companies are as follows: the ability to respond (80%), learning ability (74.62%), monitoring ability (70.77%), and the ability to anticipate (66.92%). (4) Conclusion: The safety resilience implementation in Indonesian sea transportation shipping has not been optimal in implementing the safety resilience concept. The focus of implementing safety is still on preventing and controlling accidents. The other orientation of ability improvement in the safety resilience concept has not been implemented. [ABSTRACT FROM AUTHOR]

A growing body of research has pointed out effective leadership as an important influencing factor for safety performance in various high-risk industrial contexts. However, limited systematic knowledge is available about how leaders can effectively persuade rule compliance, and stimulate actions and participation. Recognizing effective means of influence is of value for safety leadership development and evaluation. This study seeks to empirically investigate leaders' influence tactics for safety in a maritime context. Qualitative exploration is performed with data being collected through focus group discussions and individual interviews with 41 experienced shipboard leaders from various shipping sectors. Five core influence tactics--coaching, role modeling, pressure, consultation and exchange tactics--appeared to be the shipboard leaders' effective tactics to influence subordinates' safety compliance and participation behaviors in ship operations. Safety leadership influences flow from exemplification, expert and personal sources of power, and being pursued through soft and rational influence tactics rather than coercion or constructive inducements. The results indicate that the more relationship-oriented the leaders are, the more effective their safety leadership would be in influencing safety behaviors. The implication of the results for maritime safety leadership research, maritime education and training are discussed. [ABSTRACT FROM AUTHOR]

The maritime industry is one of those rare industries that are both highly international integrated to international trade and also highly capital intensive dependent on substantial investment amount. In the literature, ship investments have not been widely examined through the firm-level investment theories to explore the link between investment level and asset price valuation. The general trend in the literature of ship investments is to analyse the relationship among the shipping markets (newbuilding, second-hand, freight rate and scrap) and their impact on asset price valuation, the timing of investments and market entry and exit conditions. In this paper, we extensively reviewed the literature of firm-level investment theories and ship investments. We showed that the application of firm-level investment theories to the ship investments is confined to the basic investment valuation models, such as Net Present Value and Real Option Analysis. Ship investments need to be examined by firm-level investment theories to define firm/industry value maximization level within the approach of the solid investment theories. [ABSTRACT FROM AUTHOR]

The maritime industry is trying to utilize new technology for enhancing its competitiveness to overcome today's severe economic situation, and some interact effects, or potentially emergent effects, will emerge during the introduction of these technologies. In this study, various simulations that relate to marine logistics and shipping were performed. By contrast, a detailed method that can reproduce emergent effects is required to some extent. This study utilized a Monte Carlo simulation for uncertainties, such as market and failure uncertainties. To evaluate and explore the emergent effect correctly and accurately when multiple technologies are introduced, an evaluation methodology was developed, which can evaluate the interact effect from the perspective of profit improvement and CO2 reduction during the transportation period. As a case study, decision making for introducing 28 technology combinations to the maritime industry was conducted, and the utility of the proposed methodology was assessed. [ABSTRACT FROM AUTHOR]

The paper presents a classification of cyber attacks within the context of the state of the art in the maritime industry. A systematic categorization of vessel components has been conducted, complemented by an analysis of key services delivered within ports. The vulnerabilities of the Global Navigation Satellite System (GNSS) have been given particular consideration since it is a critical subcategory of many maritime infrastructures and, consequently, a target for cyber attacks. Recent research confirms that the dramatic proliferation of cyber crimes is fueled by increased levels of integration of new enabling technologies, such as IoT and Big Data. The trend to greater systems integration is, however, compelling, yielding significant business value by facilitating the operation of autonomous vessels, greater exploitation of smart ports, a reduction in the level of manpower and a marked improvement in fuel consumption and efficiency of services. Finally, practical challenges and future research trends have been highlighted. [ABSTRACT FROM AUTHOR]

As pillars of logistics, supply chains, and transport networks, seaports have led to a substantial demand for countless economic advantages. The sustainability and competitive advantage of seaport businesses depend on their ability to adapt to changing business requirements, while Industrial Revolution 4.0 (IR 4.0) is a current phenomenon that connects the global market through smart technologies involving cyber-physical systems to overcome global trade uncertainty. However, focusing only on growing economic benefits might lead to an ineffective sustainable implementation of IR 4.0 within a seaport system. Therefore, this paper compares the current status of IR 4.0 global implementation against the current Malaysian seaport system to ensure that the development of seaports in Malaysia is aligned with technological trends and global requirements. In addition, this paper investigates the critical sustainable factors (CSFs) for the implementation of IR 4.0 in Malaysian seaports. A Focus Group Discussion (FGD) is used to obtain the data from 13 domain experts, from various maritime stakeholders, which is further analysed by using Thematic Analysis. The result has shown that most seaports have started to initiate a fusion by focusing on IR 4.0 adaptation. In contrast, in Malaysia, the seaports in this country are still behind the global trend and are just starting to explore the concept of IR 4.0 instead of expanding to the next level (global benchmark). The current status and CSFs, for the implementation of IR 4.0 in Malaysian seaports, are presented in comparison to global requirements, and the marginal associations between them are shown. As a conclusion, by comparing a global seaport scenario with Malaysian seaports, the main considerations for sustaining the implementation of IR 4.0 in Malaysian seaports can be discovered. [ABSTRACT FROM AUTHOR]

Stakeholders in the maritime industry have agreed to expand commercial operations by developing autonomous vessels, the epitome of innovative technologies. However, they are still concerned about the risks of infringing on the rights and interests of individuals or organizations linked to data transactions. Based on Locke's theory of property ownership, and the assurance of absolute ownership as specified in the Constitution of the Republic of Korea, the business model is still in its early stages. This study examined the concept, transaction structure, and application scope of data activating digital platforms to support data transactions, and aid in advancing the new business sector for commercial operations of maritime autonomous surface ships (MASSs). Consequently, this study contributes to and recognizes the future value of knowledge and intellectual property related to maritime data. This is achieved by defining the intellectual property emerging from newer avenues, such as MASSs, blockchain technology, and smart ports, that are consequential to the rapid development of the maritime industry. [ABSTRACT FROM AUTHOR]

In contrast to the conventional safety management principle, namely, safety-I, which focuses on "what goes wrong", a new-born safety philosophy (safety-II) inspires people to investigate "how and why things go right". In the present study, the cognitive difference and correlation between safety-I and safety-II in the maritime shipping industry are explored and investigated. For this purpose, a questionnaire is administered to survey seafarers and maritime experts, and semi-structured interviews are conducted to collect original data associated with safety-I and safety-II. Then, the data from seafarers and maritime experts are further processed by empirical statistical methods and fuzzy analytic hierarchy process (AHP) methodology. The results show that impacting factors associated with individual aspects are usually accepted as dominant with respect to views of safety-I, while organizational factors are more influential for safety-II, which is essential to developing an organizational resilience capacity. Based on the findings and discussions, potential safety countermeasures that integrate safety-I and safety-II are proposed in this article. The present study discusses the new-born safety-II perspective to elucidate the safety issues associated with maritime shipping operations, which can be seen as the main innovation of this work. [ABSTRACT FROM AUTHOR]

As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals. [ABSTRACT FROM AUTHOR]

The electrification of vessels/ferries for green transformation requires onboard electrical energy storage as well as an energy supply network in the port area. In this context, a lot of efforts have been made in the last decade that have been reviewed in such a way that only a single aspect of the green transformation challenge is highlighted. Consequently, the objective of this research is to develop knowledge by examining the current state of affairs and provide, accordingly, abstract implementation guidelines for green transformation through vessel/ferry electrification. A comprehensive study on the electrification of vessels, in industry as well as in academia, is performed. Based on the data collected through a systematic study, a comparison of various pure electric and hybrid vessels in terms of certain performance attributes, such as battery capacity, passenger and cargo capacities, and size (length) of the vessel, is performed. Moreover, the distribution of vessels according to different countries and manufacturers is provided. Finally, certain technical, operational, and legislative challenges are explored. [ABSTRACT FROM AUTHOR]

3D printing conquers new branches of production due to becoming a more reliable and professional method of manufacturing. The benefits of additive manufacturing such as part optimization, weight reduction, and ease of prototyping were factors accelerating the popularity of 3D printing. Additive manufacturing has found its niches, inter alia, in automotive, aerospace and dentistry. Although further research in those branches is still required, in some specific applications, additive manufacturing (AM) can be beneficial. It has been proven that additively manufactured parts have the potential to out perform the conventionally manufactured parts due to their mechanical properties; however, they must be designed for specific 3D printing technology, taking into account its limitations. The maritime industry has a long-standing tradition and is based on old, reliable techniques; therefore it implements new solutions very carefully. Besides, shipbuilding has to face very high classification requirements that force the use of technologies that guarantee repeatability and high quality. This paper provides information about current R&D works in the field of implementing AM in shipbuilding, possible benefits, opportunities and threats of implementation. [ABSTRACT FROM AUTHOR]

Several heterogeneous, intelligent, and distributed devices can be connected to interact with one another over the Internet in what is termed internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for enhancing the production of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). Emergent configuration (EC) is a technology that can be adopted to enhance the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this paper, a survey of the concept of IoT is presented in addition to a review of IIoT systems. The application of ubiquitous computing-aided software define networking (SDN)-based EC architecture is propounded for enhancing the throughput of oil and gas production in the maritime ecosystems by managing the exploration process especially in emergency situations that involve anthropogenic oil and gas spillages. [ABSTRACT FROM AUTHOR]

This article is devoted to an efficiency measurement of the maritime industry presented through the joint value of industry stakeholders. A list of factors contributing to the efficiency of the state maritime policy and factors in the development of the maritime industry were defined and separated into four groups: group 1 (infrastructural factors): Renewal of port infrastructure; coastal infrastructure of sea stations; ecological and physical safety; and convenience in reaching the port of departure of a cruise ship; group 2 (management factors): The effectiveness of management mechanisms; the level of automatization and effective communications technologies; the coordination of various types of transport; and the efficiency of port services; group 3 (marketing factors): Tariff policies (tariff amounts, number of port fees, flexibility of the price policy); and competition in the ports; group 4 (service factors): Attractiveness of logistics conditions; the development of international tourism; the development of sea leisure; the development of merchant shipping, shipbuilding, ship repair, and instrument making in the port; and the simplification of port entry procedures. The joint value was considered to be a category at both a macroeconomic and microeconomic level, and it was combined with a multivariate regression model performed on the basis of the statistical analysis and data processing system Statistica 8.0. The complex combination of the results of the multifactorial linear model of the joint value created in the maritime industry led to the conclusion that the best alternative to the development of the port industry in Ukraine is the scenario of state modernization and corporatization in the port business model. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop a theoretical framework for blockchain, operations in particular. Furthermore, we aim to identify the main drivers and barriers of digital innovation and explore the general possibilities of blockchain applications within the maritime industry. A case study approach is applied: the Norwegian offshore industry. Primary data is collected through interviews, while secondary data is collected from industrial and company reports, the Internet, and national and international media reports. We have discovered that cost reduction intentions, the high level of regulation in the maritime industry, and the large amount of data that maritime companies should process, along with the intention to work more effectively, are the main drivers of digital innovation. On the other hand, the high cost of implementation, the bad quality of Internet connections offshore, the old age of decision-makers, the technology-oriented culture, the lack of investment initiatives, the low level of blockchain diffusion through the supply chain, and risk aversion are the main barriers. The results of the qualitative study show that some of the barriers and motives of digital innovation and the introduction to blockchain technology were pointed out by earlier studies. However, we have identified several unique drivers and barriers specific to the industry. Finally, the blockchain process framework is developed. [ABSTRACT FROM AUTHOR]