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Maritime taught postgraduate education plays a vital role in cultivating expertise within the ever-evolving global logistics industry. Notably, the diverse backgrounds of students are of great importance in this context, given the scarcity of undergraduate maritime programs and the industry's demand for professionals from various disciplines. However, this diversity also poses a challenge to educators in terms of effectively training and evaluating these students. This study focuses on a maritime taught postgraduate professional program and investigates how student background characteristics affect their learning outcomes and academic performance. By utilizing both stated preference data (SP) and revealed preference data (RP) collected from a postgraduate maritime professional program in Hong Kong, the study aims to mitigate hypothetical bias and gain a comprehensive understanding of the factors influencing student perceptions and experiences in maritime industry. The study measures five dimensions of student learning outcomes, including professionalism, strategic thinking, lifelong learning capability, career development, and academic performance. The findings suggest that student background characteristics have minimal impact on maritime learning outcomes, with only gender and undergraduate programs showing some influence. The study highlights the inclusive nature of maritime professional education, emphasizing that training quality, rather than personal background, is the key determinant of success. • We highlight the inclusive nature of maritime professional education. • Both stated preference data and revealed preference data are applied. • Student background have minimal impact on maritime learning outcomes. • Findings emphasize that training quality is the key determinant of success. [ABSTRACT FROM AUTHOR]

This exploratory study delves into the factors influencing digital technology adoption and the dynamics of its institutionalization within the Thai maritime industry, a key sector underpinning Thailand's economic expansion. Data was collected through semi-structured interviews with executive leaders from seven Thai shipowners, utilizing a snowball sampling method. The study reveals that digital technology adoption is driven by a complex interplay of factors including reliable IT infrastructure, perceived technological benefits, organizational culture, top management support, IT skills and support, legal, regulatory, and policy requirements, social pressure influence, and varying degrees of government support. Additionally, the institutionalization of such technologies within the maritime sector is heavily reliant on well-defined organizational rules and the establishment of trust in technological advancements. These findings not only enrich the theoretical landscape regarding digital adoption but also offer practical insights for industry stakeholders, paving the way for more nuanced interventions and policy formulations aimed at enhancing digital integration in this traditionally conservative sector. [ABSTRACT FROM AUTHOR]

Alternative fuels of low or zero carbon content can decarbonise the shipping operations. This study aims at assessing the lifetime environmental-economic sustainability of ammonia and hydrogen, as alternatives to diesel fuel for short sea shipping cargo vessels. A model is employed to calculate key performance indicators representing the lifetime financial sustainability and environmental footprint of the case ship using a realistic operating profile and considering several scenarios with different diesel substitution rates. Scenarios meeting the carbon emissions reduction targets set by the International Maritime Organisation (IMO) for 2030 are identified, whereas policy measures for their implementation including the emissions taxation are discussed. The derived results demonstrate that the future implementation of carbon emissions taxation in the ranges of 136–965 €/t for hydrogen and 356–2647 €/t for ammonia can support these fuels financial sustainability in shipping. This study provides insights for adopting zero-carbon fuels, and as such impacts the de-risking of shipping decarbonisation. [Display omitted] • Economic and environmental sustainability assessment of diesel fuel substitution. • Scenarios for addressing IMO decarbonisation targets with ammonia and hydrogen. • Hydrogen fuel prices below 700 €/t provide economic sustainability. • Carbon tax of 136 €/t for H 2 and 261 €/t for NH 3 is required to reach baseline NPV. • H 2 substitution scenarios over performs ammonia in economic sustainability. [ABSTRACT FROM AUTHOR]

Visual object detection and tracking is a fundamental task in artificial intelligence and plays a crucial role in various maritime applications, leading to enhanced maritime traffic safety and security. Although significant progress has been made in object detection and tracking in recent years, it still remains a challenge due to the image quality decline and object appearance changes caused by complex maritime traffic environments. This article aims to provide a comprehensive review of the current state of research in the field. We have examined the latest advancements in various aspects and proposed some directions for future research. Firstly, we delve into four main challenges in ship detection and tracking, including environmental variations, ship scale, ship occlusion, and lightweight models. Subsequently, we review the methods employed to address these challenges, and key contents about ship detection and tracking, include datasets, evaluation metrics, experimental results from mainstream methods. Finally, we offer a discussion and some future research directions that warrant attention, which will become potential research effort in the future. [ABSTRACT FROM AUTHOR]

Although the maritime industry has introduced technological improvements, shipping activity is still a major contributor to greenhouse gas emissions. Using more intelligent incentive policies, such as subsidies, seems a way to increase green technology adoption. Our proposal is to engineer micro-level incentives to target a reduced set of adopters to optimize subsidies while encouraging adoption by shipowners. We focus on wind-assisted propulsion technology in shipping and test the effectiveness of targeting using agent-based simulations. The agent-based model employs a three-phase process, influenced by awareness of technology, economic factors, and networking. Experiments under different scenarios robustly analyze targeting policies and their impact on adoption rates. Our findings reveal that targeted incentives significantly improve adoption compared to a uniform distribution. The most effective targeting policies are those that select receptors based on their social activity and energy consumption, although the available budget affects the selection of criteria. [ABSTRACT FROM AUTHOR]

The main objective of this study is to address one of the significant challenges maritime SMEs, as well as the whole industry, are facing concerning the general necessity to digitize the global supply chain: the lack of transparent information flows between participants and the non-existing documentation standards. This objective includes a proposal of using blockchain technology for data sharing as a solution to counter this challenge. To understand how a blockchain-based data-sharing platform would succeed and tackle this challenge, TradeLens was selected as a case study. The literature review has addressed the shipping industry as a whole, blockchain technology, and its features and current initiatives that facilitate this technology. The case study analysis and discussion focused on the architecture, data sharing model, and standards for documentation as well as challenges associated with the solution TradeLens is offering for maritime enterprises. From this analysis, implications for SMEs have been elaborated. Concluding these implications have been validated through interviews with industry experts and strategic decision-makers in maritime SMEs. [ABSTRACT FROM AUTHOR]

The concept of transforming maritime industry into a digital platform with real-time communication has rapidly emerged within industry discussions. A big part of the topic was tied around blockchain technology that due to its decentralization feature can simplify the complexity of the supply chain network and interconnect its actors. Nevertheless, only a few studies have investigated the feasibility in detail, yet not covered limitations other than those generally discussed. The purpose of the study is to identify and summarize the challenges of blockchain implementation in the maritime industry and within maritime ports. Based on the literature and previous research findings, 18 challenges to the blockchain implementation were identified and categorized into four dimensions: human factor, operational, organizational, and technological. The findings show that different priorities among ports, low level of digitalization, scalability of blockchain systems, and unwillingness to change business routine are important challenges. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has stifled international trade and the global maritime industry. Its impact on the routing of the regional vessel traffic flow provides supportive data to port authorities, ship owners, shippers, and consignees. This study proposes a spatiotemporal dynamic graph neural network (STDGNN) model that includes the usual primary part of the vessel flow and an auxiliary part of newly confirmed COVID-19 cases near the port. The primary part consists of a time-embedding (TE) block, two dynamic graph neural network (DGNN) blocks, and a gated recurrent unit block, to capture the spatiotemporal dependence in the regional vessel traffic flow. The auxiliary part is made of multiple blocks to exploit the dynamic temporal relationships in hours, days, and weeks. Moreover, the performance of the STDGNN model is verified by utilising real vessel traffic flow data (i.e. inflow, outflow, and volume) and the new cases of COVID-19 near the port of New York, USA, provided by the automatic identification system and the Johns Hopkins University Centre for Systems Science and Engineering. The 2-h prediction result shows a 37.7%, 17.23%, and 11.4% improvement in the mean absolute error (MAE) over the gated recurrent unit (GRU), STGCN, and TGCN models, respectively. The delicate and adaptable prediction of vessel traffic flow could help the port relieve congestion, enhance efficiency, and further assist the recovery of regional maritime industries in the post-COVID era. [ABSTRACT FROM AUTHOR]

• Proposed Cross-Hybrid Process (CHP) to improve Design Review Processes (DRPs). • Addressed key risks in metal additive manufacturing (AM) for the maritime industry. • Analysed impact of AM anisotropy and material variability on structural integrity. • Combined interdisciplinary approaches to mitigate omissions and enhance reliability. • Integrated quantitative and qualitative methods for robust AM evaluation. Additive manufacturing (AM) arises as a promise to increase design freedom and hence to optimize equipment, as this uncages the manufacturing of more complex geometric shapes. Metal AM in the maritime industry is a process in early stages of development so caution- and consciousness are required when designing and reviewing processes (DRPs) are performed, since technological gaps represent a high risk for equipment structural resistance and life. Presented work researched some of most important technological gaps and failures within metals AM, lessons learned from past novel technologies, the environment in which the maritime industry is enclosed and respective common practices, concluding that dichotomy − decisions framed as binary choices of approval or rejection −, fixed mindsets − a belief that abilities and characteristics are static and unchangeable − and dependence of immature standards, guidelines and regulations represents a risk in terms of high potential of omissions. One of the challenges within mentioned ecosystem consists in improving internal processes and mindsets, both presenting necessary requirements to ensure safety of well-established technologies but also headlining gaps when under development ones are assessed. This publication suggests that the use of the new herein developed Cross-Hybrid Evaluations (CHP) in DRPs represents a significant leap towards safety insurance, increasing of reliability and reduction of barriers that hinders the plenty expansion of metal AM within maritime industry. [ABSTRACT FROM AUTHOR]

Corrosion poses a significant threat to the integrity and longevity of ship, offshore, and oil & gas structures, resulting in substantial economic losses, environmental hazards, and safety concerns. In recent years, machine learning (ML) has emerged as a promising tool for corrosion analysis in maritime industry. This paper provides a critical review of prevalent ML approaches, including Convolutional Neural Networks (CNNs), Random Forests (RFs), computer vision, image processing techniques, and hybrid models in corrosion detection and classification from 2018 to 2024. Beyond a typical review, this study meticulously examines these approaches, focusing on model development, efficacy, limitations, and practical implementation challenges in details. Key findings reveal that while ML models hold considerable potential to enhance the efficiency of corrosion detection and classification, significant barriers such as data quality, model interpretability, and integration into existing maintenance workflows impede widespread adoption. Furthermore, the paper identifies best practices and proposes future research directions to bolster the robustness and reliability of ML models in corrosion analysis. The insights gleaned from this review aim to guide industry experts and academicians in developing more effective corrosion management strategies through the integration of machine learning, ultimately mitigating the impact of corrosion on maritime and offshore operations. • Machine Learning approach effectively detects and classifies corrosion. • Challenges include data quality, generalization capability, and environmental conditions. • Future research should enhance data quality, model reliability, and practical application. • Provides comprehensive guidance to industry professionals and researchers. [ABSTRACT FROM AUTHOR]

The global maritime industry is facing the goal to achieve "carbon neutrality", and substituting traditional ship fuel with clean energy is the most important solution. Whether to promote clean-energy ships through state governance or unified international supervision to achieve carbon neutrality has been a long-standing debate. This study employs both a tripartite evolutionary game model and a quadrilateral evolutionary game model to compare the effectiveness of state governance and unified international supervision in promoting clean-energy ships. The tripartite model simulates interactions between local governments, shipping companies, and shippers, revealing that high subsidy costs reduce local governments' incentives to promote clean-energy ships. The quadrilateral model introduces international supervision, demonstrating that a unified international oversight mechanism can accelerate the global maritime industry's progress toward carbon neutrality. Numerical simulations indicate that lowering the purchase costs of clean-energy ships and introducing government subsidies significantly influence the adoption of clean-energy ships, while supervision costs impact the effectiveness of international regulations. These findings provide critical insights for policymakers aiming to balance financial incentives and global supervision strategies to foster low-carbon development in the maritime sector. [ABSTRACT FROM AUTHOR]

The innovation and governance of the global international ship registry system have become key to achieving sustainable development for maritime nations worldwide. For a long time, many maritime nations have chosen to fly flags of convenience for commercial or political reasons, causing major maritime nations to lose effective control over their fleets. To counteract the negative impacts of flags of convenience, major maritime nations have established international ship registry systems. This paper analyzes the development process and basic characteristics of the global international ship registry system, points out the main problems in its implementation, and proposes major directions for innovation and governance of the international ship registry system worldwide. By reviewing the development history of the global international ship registry system, evaluating key issues in its implementation, and constructing future reform and governance directions, this paper aims to provide policy innovation suggestions for the ship registry policy reforms of global maritime nations. [ABSTRACT FROM AUTHOR]

Highly efficient manufacturing processes in which innovative technologies are continuously integrated are essential for a globally competitive European maritime industry. Promising optimization potential lies in the welding of thick sheet metal. The use of new high-power diode lasers with output powers of up to 60 kilowatts can replace conventional welding processes and significantly improve welding quality and efficiency. In addition to the welding process development with extremely high laser powers, ensuring laser safety is a major challenge for adequate employees' protection. This work aims to investigate the spatial distribution of laser radiation backscattered from the laser process zone into the hemisphere above the sheet metal. The results of the scattered radiation measurements performed are used to estimate the amount of thermal energy introduced from the laser process zone into a possible protective shielding against the scattered radiation. The derived maximum temperatures finally allow a suitable dimensioning of the shielding. [ABSTRACT FROM AUTHOR]

DFA2 refers to a set of design rules introduced by S. Eskilander in his doctoral thesis[3] as a method to help design products for automatic assembly. In this method, design rules are used to assign an index to a particular design which can then give an indication of the suitability of that product/module to be assembled automatically. However, this methodology is based on a general perspective and is not fully suitable for the needs of every industry. This article reviews the methodology in the context of the maritime industry in Norway after studying a typical product offering from a maritime company. Based on the review, shortcomings of the DFA2 are realized and new design rules are proposed to be added to the original method. Additionally, this paper tries to prioritize the design rules based on certain criteria. This study suggests that the DFA2 methodology is customizable to meet the needs of any particular industry or organization. To achieve a high level of customization, a more detailed study of different product offerings from any individual company or industry is required. [ABSTRACT FROM AUTHOR]

Solving uncertainty-related tasks such as accident investigation, risk analysis, reliability prediction, and port sustainability analysis has been a key focus in the maritime industry. Over the years, conventional tools such as fault tree analysis, event tree analysis, and statistical-driven methods have been used for accident, risk, and reliability analyses in the maritime industry, which is considered weak. For this reason, the application of the Bayesian network (BN) is attracting growing interest in the maritime industry. A comprehensive review of the past 20 years on the application of BN in the maritime industry is provided. To conduct the review, relevant publications involving 115 journal articles focusing on BN application in the maritime industry were extracted. Based on the extracted studies, a classification framework involving application areas, data sources, operational waters, geographical locations, and model validation was proposed. The proposed framework was used to analyze the literature in detail to reveal the necessary findings and extract possible future research areas. The findings of the research revealed an increasing trend in the application of BN in the maritime industry in diverse areas of risk assessment, human error analysis, reliability estimation, and accident investigation. Furthermore, issues emanating from the systematic review analysis are discussed. • To provide a comprehensive review of BN application in the maritime industry. • To analyze relevant scholarly articles with a focus on BN application in the maritime sector from 2000 to 2022. • To identify various methods used in validating BN models in the maritime industry. • To discuss the critical issues obtained through the systematic review analysis. • To suggest possible areas of interest for future research work. [ABSTRACT FROM AUTHOR]

The maritime industry is facing increasing challenges due to decarbonization requirements, trade disruptions, and geoeconomic fragmentation, such as International Maritime Organization (IMO) sets out clear framework to reach net zero emissions by 2050, Russia-Ukraine war disrupted maritime activities in the Black and Azov seas, and increased trade tensions between the United States and China. To enhance their sustainability, operational efficiency, and competitiveness, maritime organizations are therefore very keen to build big data analytics capability (BDAC). However, various barriers, mean that only a handful are able to do so. We adopt a mixed-method approach to analyze these barriers. Thematic analysis is used to identify five categories of barriers and 16 individual barriers based on empirical data collected from 26 maritime organizations. These are then prioritized using the analytic hierarchy process (AHP), followed by total interpretive structural modelling (TISM) to understand their interrelationships. Finally, cross-impact matrix multiplications applied to classification (MICMAC) is employed to differentiate the role of each barrier based on its driving and dependence power. This paper makes several theoretical contributions. First, China's hierarchical cultural value orientation encourages competition and obedience to rules, resulting in unwillingness to share knowledge, lack of coordination, and lack of error correction mechanisms. These cultural barriers hinder BDAC development. Second, organizational learning category barriers are found to be the most important in impeding BDAC development. This study also raises practitioners' awareness of the need to tackle cultural and organizational learning barriers. • Identifying, ranking, linking, and categorizing BDAC development barriers • 16 barriers to BDAC development of maritime industry were identified. • Cultural and organizational learning related barriers found to be critical to BDAC development. • Allocating barriers into different layers of a framework to understand their interactions • Differentiating the barrier's role based on its driving and dependence power [ABSTRACT FROM AUTHOR]

The advancement of the maritime industry towards technologically integrated and automated systems has significantly increased the complexity of onboard Industrial Control Systems (ICS), raising concerns about cybersecurity risks. In this paper, we examine typical onboard ICS configurations through an adversarial lens. We introduce a threat model that leverages domain-specific peculiarities, e.g., maritime protocols, and targets vulnerability vectors to execute software attacks against the infrastructures of shipboard ICS. This includes a case study on a critical subsystem of ship machinery: the steering gear system. We have developed a novel attack methodology intended for use by targeted malware. A comprehensive experimental assessment confirms the feasibility of attacks devised according to our methodology. [ABSTRACT FROM AUTHOR]

International shipping is crucial for freight transport, but it relies primarily on fossil fuels, contributing 3% of global greenhouse gas emissions. This calls for urgent action to decarbonize the shipping industry. While renewable-based e-fuels are a strong candidate for decarbonization of this sector in the long run, deploying these to the required scale will take significant time, considering technical modifications onboard the vessels, as well as the changes in fuel production and infrastructure for distribution. Carbon capture from ships is another route to emission reduction that can be implemented faster due to the relatively high maturity of the technology. Tankers, dry bulk carriers, and container vessels contribute a majority of global shipping emissions and are therefore prime candidates for carbon capture and storage. Solvent-based post-combustion capture is chosen for this study as it is mature and suitable for marine applications, though technical, economic, environmental, and practical challenges remain. This paper assesses the technical feasibility of the capture system for ships; both retrofit and newbuild vessels. While achieving zero-emissions presents a significant challenge, it is feasible to attain 70%–90% CO 2 reduction through carbon capture in the near term. This reduction is crucial for transforming the industry into a more sustainable and environmentally friendly state. The limitation of space onboard is identified as a key factor in determining the viability, and the 70%–100% increase in energy consumption between existing ships and newbuild will be a substantial operational challenge. However, the high fuel consumption of the capture system could be economically acceptable if the price of alternative fuels remains high. [ABSTRACT FROM AUTHOR]

Robotic welding has garnered significant attention in the maritime industry for its potential to enhance marine structure quality and optimize production processes. This systematic literature review aims to provide a comprehensive overview of the current state of research in robotic welding for marine applications, encompassing marine structures and production processes, following the PRISMA statement and guidelines. The review encompasses various facets, including welding techniques, processed materials, types of robotic welding, technological advancements, potential advantages, and challenges encountered when implementing robotic welding systems in the maritime sector. The results spotlight the pivotal role of gas metal arc welding (GMAW) in propelling robotic welding technology forward, while wire arc additive manufacturing (WAAM) has experienced a notable surge in popularity, signifying its potential to catalyze significant changes in maritime manufacturing processes. Notably, the predominant use of robotic welding centers on carbon steel materials. However, ongoing advancements indicate a growing diversification, with the incorporation of advanced materials like high-strength alloys on the horizon. Additionally, the utilization of 6-axis robot welding in conjunction with fully autonomous systems has emerged as a versatile and potent instrument that has revolutionized welding methodologies across various maritime research domains. Robotic welding provides a number of advantages, such as increased productivity, higher quality, adherence to industry standards, adaptation to confined and dangerous locations, and facilitation of innovative construction techniques. Nevertheless, adoption of this cutting-edge technology is not without challenges. By synthesizing the results from several investigations, this research study offers useful insights into the current knowledge gaps, emerging trends, and future prospects for the growth of robotic welding in maritime applications. • This review explores welding techniques, materials, advancements, and challenges. • Robotic welding improves productivity, quality, safety, and innovative construction. • WAAM emerges as a transformative and popular technique for maritime manufacturing. • Increasing use of advanced materials like high-strength alloys is on the horizon. • Valuable insights on trends and prospects in robotic welding for maritime applications. [ABSTRACT FROM AUTHOR]

The world's maritime market and the global supply chain are grappling with the far-reaching impacts of the COVID-19 pandemic. The surge in shipping costs and the emergence of unreasonable overcharges and price fixing among carriers once became global issues, encompassing pivotal factors that are undermining the stability of the supply chain. In response, countries have initiated a shift toward the use of competition regulatory mechanisms as a means of addressing these pressing issues. Against the backdrop of competition regulation being used as a remedy for disruptions to the maritime supply chain, this research employs a normative legal study approach, coupled with a comprehensive analysis of existing competition enforcement cases to examine China's maritime competition regulation. By dissecting various competition cases, we elucidate the foremost concerns pertaining to China's competition regulation in the maritime domain and critically delve into the shortcomings inherent in the institutional framework and enforcement practices. This research also examines the impact of China's competition regulation on managing sea freight rate, preserving supply chain stability, overseeing port operations, promoting cross-border collaboration, and influencing the corporate behaviors of maritime enterprises in the post-COVID-19 era. • The COVID-19 pandemic has affected the global supply chain, and the variability of freight charges becomes a global issue. • Competition regulation appears to have evolved into a regulatory tool on which countries rely to mitigate the soaring sea freight and port charges. • China has pursued rigorous competition enforcement in the maritime industry in recent years. • China's initiatives in competition regulation are likely to prompt maritime enterprises to adjust business strategies to thrive in the new market environment. [ABSTRACT FROM AUTHOR]

• Time pressure and vigilance demands are associated with seafarers' self-reported sleep difficulties. • Social support onboard is associated with reduced acute fatigue and improved recovery. • Job demands and resources impact seafarers' chronic fatigue through impaired sleep and recovery. • Incomplete recovery is the strongest driver of seafarers' chronic fatigue. • Vigilance demands and autonomy also have a direct effect on seafarers' chronic fatigue. • Having more job resources can reduce fatigue when seafarers are working under high time pressure. The aim of the present study was to examine how different work demands and resources characteristic to the maritime industry are related to chronic fatigue in seafarers. Moreover, we investigated the role of different fatigue related processes, such as acute fatigue, sleep problems and inter-shift recovery in explaining the association between work characteristics and chronic fatigue. 199 seafarers working for the marine operations of a large global mining company participated in a cross-sectional survey design. Findings showed that working under time pressure and vigilance demands have differential relationships with chronic fatigue, with vigilance demands showing a stronger association. Moreover, this association was only partially mediated by fatigue processes, indicating that there might be several mechanisms involved. Social support emerged also as a critical job resource that can protect against fatigue, highlighting potential negative implications of current HR and staffing practices in the industry that discourage stable crews and might impair the development of supportive social climates onboard ships. Job autonomy also showed direct negative associations with chronic fatigue. Overall, our findings support the application of job demands – resources models to emphasize the importance of understanding the differential effects of work demands and resources characteristic to the maritime industry environment for seafarers' chronic fatigue. Shipping companies should therefore consider the impact of these factors when trying to improve safety or wellbeing of the seafarers onboard their ships, given the critical role that chronic fatigue plays for both these outcomes. [ABSTRACT FROM AUTHOR]

Highlights • Anomaly detection with signal reconstruction and residuals analysis. • Reduced computation time, due to use of training data clustering. • Applied on 14 imbalanced datasets, including recent data from a marine diesel engine in operation. • Regional credibility estimation used in the residuals analysis. Abstract We propose novel modifications to an anomaly detection methodology based on multivariate signal reconstruction followed by residuals analysis. The reconstructions are made using Auto Associative Kernel Regression (AAKR), where the query observations are compared to historical observations called memory vectors, representing normal operation. When the data set with historical observations grows large, the naive approach where all observations are used as memory vectors will lead to unacceptable large computational loads, hence a reduced set of memory vectors should be intelligently selected. The residuals between the observed and the reconstructed signals are analysed using standard Sequential Probability Ratio Tests (SPRT), where appropriate alarms are raised based on the sequential behaviour of the residuals. The modifications we introduce include: a novel cluster based method to select memory vectors to be considered by the AAKR, which gives an extensive reduction in computation time; a generalization of the distance measure, which makes it possible to distinguish between explanatory and response variables; and a regional credibility estimation used in the residuals analysis, to let the time used to identify if a sequence of query vectors represents an anomalous state or not, depend on the amount of data situated close to or surrounding the query vector. We demonstrate how the anomaly detection method and the proposed modifications can be successfully applied for anomaly detection on a set of imbalanced benchmark data sets, as well as on recent data from a marine diesel engine in operation. [ABSTRACT FROM AUTHOR]

With the advancement of maritime unmanned aerial vehicles (UAVs) and deep learning technologies, the application of UAV-based object detection has become increasingly significant in the fields of maritime industry and ocean engineering. Endowed with intelligent sensing capabilities, the maritime UAVs enable effective and efficient maritime surveillance. To further promote the development of maritime UAV-based object detection, this paper provides a comprehensive review of challenges, relative methods, and UAV aerial datasets. Specifically, in this work, we first briefly summarize four challenges for object detection on maritime UAVs, i.e., object feature diversity, device limitation, maritime environment variability, and dataset scarcity. We then focus on computational methods to improve maritime UAV-based object detection performance in terms of scale-aware, small object detection, view-aware, rotated object detection, lightweight methods, and others. Next, we review the UAV aerial image/video datasets and propose a maritime UAV aerial dataset named MS2ship for ship detection. Furthermore, we conduct a series of experiments to present the performance evaluation and robustness analysis of object detection methods on maritime datasets. Eventually, we give the discussion and outlook on future works for maritime UAV-based object detection. The MS2ship dataset is available at https://github.com/zcj234/MS2ship. [ABSTRACT FROM AUTHOR]

The bodies governing the global maritime industry have set short- and long-term targets for reducing GHG emissions from shipping. Various emission abatement measures exist, but their applicability in different contexts widely varies. The situation is unclear, especially for the so-called alternative fuels. These fuels hold the biggest emission reduction potential. Conversely, they are expensive, and the feasibility of investments in those technologies has high uncertainty. Despite a growing body of knowledge on the characteristics and potential of alternative fuels, no consensus exists as to which fuels would be best for each segment of the maritime industry – in the near future and the long run. We contribute with a Delphi study to fill this gap. Our results pinpoint the differences between the shipping segments and the short- and long-term choices for alternative fuels. [ABSTRACT FROM AUTHOR]

The maturing literature on innovation has recognized the processes of sectoral and technological systems of innovation as helpful frameworks to analyze environmental innovation – a field whose importance continues to grow amidst contemporary regulatory pressures, for example, on maritime industry and shipping. This paper intertwines these key innovation concepts and applies them to classify and systematize an environmental product innovation: marine scrubber systems. The paper also addresses the linkage between innovation policy and environmental regulation and presents an overall framework to visualize and systematize conceptual connections between sectoral and technological systems of innovation to further develop and manage these complex systems of environmental innovation inducement. The paper applies technological and legal materials depicting the context of maritime scrubber systems as technological responses to more rigid environmental regulation by addressing their implications for market potential and change. The results underline the importance of environmental regulations as the driver of the development of technological innovation systems centered on environmental innovation. [ABSTRACT FROM AUTHOR]

Abstract Monitoring of operational efficiency in ship fleets is a complex maritime problem which requires an analytical approach in order to provide satisfactory solutions. Since the problem involves high-dimensional data, this paper develops tree-based modelling on bagging, random forest and bootstrap approach to analyse the ship performance under operational condition. To demonstrate the proposed model, the publicly accessible dataset for 254 trips derived from a particular designed acquisition system on-board ferry ship is utilised. In operational variable analysis on speed through water and fuel consumption, the bootstrap approach yields more accurate prediction rate than random forest and bagging. The proposed model is superior to the others such as ANN and GP applications in ship performance monitoring. Consequently, the tree based model adopting bagging, random forest, and boosting environment is capable of increasing the predictive performance during monitoring of ship performance in maritime industry. Beside its theoretical insight, the findings of the paper contribute ship management companies to monitor ship operational performance. Highlights • Advance statistical learning model have employed in maritime field. • A practical application in shipping industry. • Utilising the high-frequency ship operational data. • A practical solution for the ship performance monitoring problems. [ABSTRACT FROM AUTHOR]

This viewpoint emphasizes gendered perspectives and reflects on gender roles for sustainability-focused governance. It argues that when considering gender in this context, not only equity, or power-plays between genders are at stake; in addition, for effective ocean governance, an irreducible contribution of female voices is necessary. Some key contributions of women in the field of ocean governance-related research are described as examples. If women, for instance, are not included in fisheries management, we miss the complete picture of social-ecological linkages of marine ecosystems. Overall, women are often regarded as major actors driving sustainable development because of their inclusiveness and collaborative roles. Similarly, women have advocated for the common good in marine conservation, raising important (and often neglected) concerns. In maritime industries, women enlarge the talent pool for innovation and smart growth. Besides the manifold possibilities for promoting the involvement of women in ocean governance and policy-making, this viewpoint highlights how gendered biases still influence our interactions with the ocean. It is necessary to reduce the structural, and systemically-embedded hurdles that continue to lead to gendered decision-taking with regard to the ocean. [ABSTRACT FROM AUTHOR]

Mobbing is a universal problem in every industry, but it is a particularly serious problem for seafarers who are tied to their work 24 h a day, 7 days a week. In this study, it was first aimed to develop a mobbing scale for seafarers from Turkey as one of the countries that provide the most seafarers to the international maritime sector and to examine their mobbing behaviors. A total of 518 people participated in the development of the scale, while 211 participated in a validation study. Factors were determined using exploratory factor analysis and then the validity of the developed scale was verified utilizing confirmatory factor analysis. Secondly, an interval type-2 fuzzy logic system was designed based on the developed scale to deal with the imprecision and vagueness inherent to the answers to the questions. To our knowledge, this is the first study to employ interval type-2 fuzzy sets to measure mobbing behavior. The results of the study demonstrate that there are inverse relationships between the age, professional experience, and position of seafarers and the severity of the mobbing to which they are exposed. The study recommends that the awareness of mobbing be promoted among seafarers. [Display omitted] • For the first time, a mobbing scale is developed for Turkish seafarers. • An interval type-2 fuzzy inference system (IT2FLS) is designed based on the developed scale. • The findings reveal that the most frequent mobbing behavior is pressure to work out of hours. • Mobbing scores decrease as age, professional experience, and position on the ship increase. • Seafarers should be made more aware of the concept of mobbing. [ABSTRACT FROM AUTHOR]

Accurate and reliable ship price forecasts can assist shipping firms, investors, and other participants to withstand risks and make profits in a highly volatile shipping market. Considering the nonlinear behavior and sophisticated interrelationship of the shipping market, in this paper, a novel multiscale and multivariable methodology based on multivariate variational mode decomposition (MVMD) and machine learning (ML) algorithms is proposed for forecasting monthly newbuilding ship price (NSP), secondhand ship price (SSP), and ship scrap value (SSV). The proposed methodology involves three main modules: (1) data decomposition by MVMD; (2) mode forecasting using ML algorithms, including multi-layer perceptron, support vector regression, long short-term memory, and gated recurrent unit; and (3) ensemble forecasts via simple addition. The novelty of this paper lies in the employment of MVMD, which is capable of capturing complicated multiscale relationships among the NSP , SSP , and SSV data by extracting multiple frequency-aligned oscillatory modes. This will largely help in the multivariable forecasting of ship prices at each timescale. With Capesize bulker and VLCC tanker as study samples, the empirical results show that the novel methodology outperforms other considered benchmark models in terms of both level and directional forecasting accuracy. This suggests that the developed multiscale and multivariable methodology is a promising alternative for shipping market analysis and forecasting. [ABSTRACT FROM AUTHOR]

• Investigating digitalization as well as data sharing in the maritime logistics industry; • Understanding the strategies and payoffs of two players-platform enterprises and participants; • Distinguishing key and general participants with high or low privacy costs; • Policy implication on promoting data sharing in the digital platform is given. Digital platforms simplify the complexities of day-to-day transactions in the maritime logistics industry and facilitate participants to seamlessly connect with each other. However, platform enterprises find it difficult to involve participants in their platforms. It is also challenging for these enterprises to share data out of consideration for participants' privacy concerns, rights, and interests. To promote data sharing, this study intends to understand the strategies of both platform enterprises and participants based on a dynamic game model to provide policy implications to platform enterprises and the government. The main findings are as follows. First, when platform enterprises move first, they should subsidize key participants with high privacy costs to compensate for the negative externality of data. Second, in the early stages of building a platform, when supporting platform enterprises move first, they must subsidize both key participants with low privacy costs and general participants. Third, governments must introduce regulations and laws to govern the delimitation of data property rights. [ABSTRACT FROM AUTHOR]

Digitization is rapidly reshaping industries and economic sectors. It enables novel Product-Service Systems (PSS) that transform customer/supplier relationships and introduces new value propositions. However, while opportunities for novel types of PSS arise, it is not clear how digitization and the institutionalisation of digital capabilities, particularly within the customer organisations, may affect implementation of PSS, potentially leading to transformational changes in the customer organisation. This paper examines one such potential transformational change from three complementary viewpoints – the resource based, the dynamic, and the relational viewpoint. It does so through action research study in the context of the maritime industry, which is particularly attractive for PSS offerings. The research methodology comprised a two-step action research process, focusing on both digitization and PSS development and implementation. The main findings are that rather than facilitating procurement to co-development of PSS, institutionalisation of digital capabilities facilitated development of PSS by stakeholders internal to the company, and strategic co-development with external stakeholders. The new digital capabilities circumvented cost barriers associated with the procurement of services from external stakeholders, supported process standardisation - to the expense of process innovation-, and transformed the network that delivered PSS by closing opportunity gaps for externally procured services. Furthermore, the uptake of digital capabilities highlighted the importance of cost estimation in making the customer more responsive to threats and opportunities. [ABSTRACT FROM AUTHOR]

How does environmental regulation impact the performance of economies? Scientific literature on impact assessments on environmental regulation are analysed in this article, focusing on the ex-ante studies on the Sulphur Emission Control Area (SECA) in the Baltic Sea and North Sea. The SECA regulations on shipping exhaust gases are an example that may appear to be straightforward, but on closer inspection, this is a multifaceted issue that has several aspects that are difficult to measure and balance against each other. As such, it offers a good case example to categorize and conceptualize the questions of impact assessment. The SECA regulations are aimed at creating environmental and health benefits, and presumed to incur compliance costs. Other benefits and costs have not received much attention. Macro-economic effects and the issues of international distribution of costs and benefits are often neglected. The relevant impact categories for the SECA regulations are identified and discussed systematically. We propose a comprehensive regulation impact framework for socio-economic effects that can be extended to other environmental regulation to support the needs of consistent and reliable evidence-based maritime policy. [ABSTRACT FROM AUTHOR]

The notion of clusters has increasingly been integrated into regional economic development policies. This paper examines the extent to which maritime cluster policy strategies in Québec's coastal region are associated with employment growth in the region, and more specifically, science-based, skill-intensive employment. Whilst early evaluations conducted about a decade ago suggested that cluster policies implemented from the mid-1990s onwards had little effect, the question addressed in this paper concerns their effect over the long term. Based on descriptive statistics and trend analysis, the results reveal that the sectors targeted by the cluster policies have tended to grow more slowly within the cluster, and that jobs in the cluster are decreasingly science-intensive. At best, cluster policies have had a weak and diffused effect. This is in keeping with other recent work on clusters, and calls into question policy attempts to generate cluster dynamics in regions where these do not emerge spontaneously. [ABSTRACT FROM AUTHOR]

Safety regulation can decrease the frequent accidents in sea transportation, but aspects of the existing regulations are found to contribute negatively to safety. Earlier studies suggest other framework conditions to influence maritime safety more than regulation, without reviewing the relation between the maritime context and regulation. Therefore, this paper explores maritime regulators’ safety-related decisions. The data consist of interviews with regulators and facts about other actors (i.e., politicians, shipping companies, interests groups, and the media) in the maritime transport arena. The findings, which are based on safety, decision-making, and arena theories, are not described by earlier research. Primarily, I find that a paralysis constrains safety regulation. Despite wanting a safe industry, transport competition leads the maritime actors to disagree about the priority of safety or profit, which paralyzes safety regulation development and constrains the regulators and their discretionary space (where they enforce the right safety regulations for the right sectors). Many of the decision criteria with which regulators must comply are forced upon them by others, so that regulators see them as constraints. Safety regulation is further weakened when market forces influence both regulation-making and enforcement. The findings demonstrate that industrial or political actors do not prioritize safety in practice; however, safety priority could lift maritime transport above the choice between safety and survival. [ABSTRACT FROM AUTHOR]

[Display omitted] • Proposed a novel MCDM model to chemical tanker vessel selection in the maritime & logistics industries. • Criteria were determined together with experts. • The model is extended with the help of Type-2 Neutrosophic Numbers. • It can reach to accurate and reasonable results with fewer computations. • A validation test was performed to verify the proposed model. Shipping companies may not present appropriate and reasonable shipping charges to their customers due to the high investment costs of chemical tanker vessels. Hence, the second-hand chemical tanker vessel selection may present many advantages and opportunities to the shipping companies. However, selecting a suitable chemical tanker represents a complicated process requiring overcoming many ambiguities and considering many conflicting criteria. For this purpose, the current paper proposes a new and integrated MCDM approach based on Type-2 Neutrosophic fuzzy sets. The proposed model combines the advantages of TOPSIS and WASPAS techniques, and it uses Type-2 Neutrosophic fuzzy sets to process the uncertainties. The proposed model was applied to solve decision-making problems in selecting appropriate second-hand chemical tankers among 15 alternatives to show effectivity, pertinence, and robustness. In the current paper, 14 different selection criteria were identified to evaluate the chemical tanker vessels. According to the results, C13″ Maintenance cost" is the most significant factor, and A3 is the best and most preferable chemical tanker. Also, a comprehensive sensitivity analysis was carried out to test the validity and applicability of the suggested model, and the sensitivity analysis approves the applicability, robustness, and validity of the model. [ABSTRACT FROM AUTHOR]

Abstract: European shipbuilders are facing a strong, worldwide competition. Consequently they have to reinvent their market approach and expand their business. In the past, European shipbuilders were focused on cost reduction in the production process to offer new build vessels at a competitive price for decades. Changing the focus from the selling price optimisation to the life cycle cost optimisation could lead to competitive advantages and enable new business opportunities. This new approach of through-life asset management is investigated in the EU- funded project ThroughLife. The minimisation of a vessel’ life cycle costs could be realised by applying new and innovative technologies. However, new technologies are characterised by higher investment costs and uncertainty regarding functionality, reliability and reparability. As a result, the situation can be characterised as a dilemma for the new building yard the ship owner and the repair yard. Therefore the ThroughLife project focuses besides the development of new technologies on the identification, elaboration and application of new business model concepts to overcome this dilemma. One business model concept is the offer of a comprehensive service package against a fixed, time based fee, which would lead to an overall cost reduction due to economies of scale, lower administration costs and a risk reduction for the customer, which would support the market penetration of new technologies. Combining this business model approach with the technology of monitoring sensors increases the potential of this approach. The service provider could use the gathered information to schedule maintenance according to the actual condition of the vessel and identify potential mistreatment by the client. The customer would benefit from reduced, calculable costs and a lower risk level when applying new technologies. Further research contains lifecycle cost model calculations as well as real-life tests of the monitoring hardware in order to proof the concept. [Copyright &y& Elsevier]

Abstract: The study empirically analyses the time-varying properties of the spread between voyage and time-charter rates and presents evidence that these properties are directly related to the business cycle (market demand) of the maritime industry, to the expectations for the future market demand and to market volatility. Using a real options methodology, it is demonstrated that the time-varying properties of the spread is the outcome of the strategic decision to time-commit company resources in the industry. During a market upturn (downturn) managers choose to commit company resources for a short period (long period), and thus, maintain flexibility (commitment) in better exploiting the upcoming business opportunities (protecting company resources from lack of business opportunities). Overall, the fluctuations of the time-varying spread between voyage and time-charter rates offer managerial insights in resource allocation that can better shape up chartering, budgeting and financial management decisions on the time commitment of resources in the maritime industry. [Copyright &y& Elsevier]

Abstract: Studies conducted to determine the efficacy of the ISM Code in the past include investigations of the trends of accident numbers and insurance claims and users'' perceptions. None of these, however, could produce a definitive conclusion. This is because both the use of safety outcome as well as the use of perception have inherent problems and are not reliable. This paper takes a different approach. It draws on wider research on management of workplace health and safety to ascertain whether or not employment and social conditions that support effective implementation of self-regulation are present in the maritime context. The findings reveal a considerable disparity between managers'' and seafarers'' understanding of the use of the Code resulting in a wide gap between its intended purpose and practice. The analysis shows that the critical factor is the lack of seafarers'' participation in management of workplace health and safety. The underlying causal factors for such lack of participation were located in seafarers'' poor employment condition and low-trust relationship with their managers. [Copyright &y& Elsevier]

Abstract: There has been recent growth of professional education where academic institutions increasingly offer postgraduate programmes on subjects traditionally emphasizing on apprentice-style/practical learning approach. The motivations behind such growth and the added values of these programmes to students, however, have remained under-researched. Hence, by investigating the maritime industry, this paper attempts to address such deficiency. Through a Likert-style questionnaire survey, it is found that the changing requirements within the maritime industry serve as the core factor in aspiring practitioners to pursue postgraduate maritime degrees, while such programmes are pivotal in human capital management through preparing and re-training maritime professionals to ensure ongoing excellence and provisions of effective services within the ever-changing maritime industry. [Copyright &y& Elsevier]

As the human presence and more specifically the seafarers or the crew has been long ago recognized in the shipping (or maritime) industry as critical for company' success, little -if not at all- effort has been attributed to how to opt for the optimum partners (manning agencies) or employees (seafarers) to achieve or co-create efficiently the best value for them. This study's objective is to bridge the gap in the relevant maritime or transport literature by aiming at i) exploring the criteria that shipping companies use to select manning agencies or agencies that provide crew for their ships as business partners and ii) examining the influence that selection criteria have on value creation for shipping companies. Evidence has been drawn and data were collected through a survey conducted in 246 Greek shipping companies which own or manage vessels and are based in Greece. The results both endorse the positive role of a "good" selection to value co-creation and further identify that creation of value can be attributed to certain criteria such as quality, recommendation and crew management and recruitment. [ABSTRACT FROM AUTHOR]

Abstract: The seas and oceans are increasingly a focus of policy interest in Europe. This is mirrored in wide-ranging activities to manage and protect the marine environment, which raises the question of whether such activities go towards developing sustainable management of the seas. Sustainable management calls for an integrated and cross-sectoral approach in order to protect highly valuable marine biodiversity from sea- and land-based activities of all kinds. While some recent developments are fairly promising, there are still no moves on the policy agenda towards uniting all relevant European policy sectors – and particularly the Common Agricultural Policy and the Common Fisheries Policy – under the shared objective of sustainable management and protection of the marine environment and its resources. [Copyright &y& Elsevier]

Abstract: This paper presents the main results of a project on Canada''s regional clusters in the maritime industry. The objectives of this paper are twofold: firstly, the driving forces and the development processes of the different maritime clusters in Canada are described. Secondly, the role of cluster policy in promoting maritime competitiveness in Canada and the key institutional and geographic barriers that affect their growth and development are discussed. The empirical work consists of analyses and assessment of three clusters in different provinces in Canada: Quebec, Newfoundland and Labrador, and British Columbia. [Copyright &y& Elsevier]

Abstract: The paper presents an innovative approach to integrate Human and Organisational Factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the Maritime Transport System (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The latter have been modelled by means of a set of dependent variables whose combinations express the relevant functions performed by each actor. The BBN model of the MTS has been used in a case study for the quantification of HOF in the risk analysis carried out at the preliminary design stage of High Speed Craft (HSC). The study has focused on a collision in open sea hazard carried out by means of an original method of integration of a Fault Tree Analysis (FTA) of technical elements with a BBN model of the influences of organisational functions and regulations, as suggested by the International Maritime Organisation''s (IMO) Guidelines for Formal Safety Assessment (FSA). The approach has allowed the identification of probabilistic correlations between the basic events of a collision accident and the BBN model of the operational and organisational conditions. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the BBN have been estimated by means of experts’ judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis has been carried out over the model to identify configurations of the MTS leading to a significant reduction of accident probability during the operation of the HSC. [Copyright &y& Elsevier]

Abstract: Environmental changes at home and abroad as well as rapid advancement in ocean technology are calling for a great shift in the perception of the maritime industry and for new policy measures. This situation demands that researchers provide policy-makers with accessible and reliable information regarding the role of the maritime industry. This study employs input–output (I–O) analysis to examine the role of the maritime industry in the national economy for the period 1975–1998, with specific application to Korea. This paper, therefore, has two major goals. The first is the development of a static I–O framework for examining the role of the maritime industry in the short run. The second goal is obtaining at least a preliminary indication of the role of the maritime industry. This study pays particular attention to the maritime industry by taking the industry as exogenous and then investigating its economic impacts. Finally, we present the results, which address inter-industry linkage effects in 32 sectors, production-inducing effects, employment-inducing effects, supply-shortage effects of the maritime sector and pervasive effects of price change in the maritime sector. [Copyright &y& Elsevier]

While land-based sources of marine plastic pollution have gained widespread attention, marine-based sources are less extensively investigated. Here, we provide the first in-depth description of abandoned, lost or otherwise discarded fishing gear (ALDFG) on northern and southern beaches of the English Southwest Peninsula, Great Britain's region of highest ALDFG density. Three distinct categories were recorded: twisted rope (0.28 ± 0.14 m−1, 17%), braided rope (0.56 ± 0.28 m−1, 33%) and filament (0.84 ± 0.41 m−1, 50%), which likely correspond to fishing rope, net and line. Estimating the disintegration of ALDFG from length and filament number suggests that it has the potential to generate 1277 ± 431 microplastic pieces m−1, with fishing rope (44%) and net (49%) as the largest emitters. Importantly, ALDFG was over five times more abundant on the south coast, which is likely attributable to the three times higher fishing intensity in that area. [Display omitted] • Beached fishing litter abundance is linked to fishing effort (total catch). • Fishing ropes, nets and lines are the main contributors to beached fishing litter. • Beached fishing litter may release hundreds of microplastic pieces per metre. • Microplastic release could potentially be traced to specific fishing activities. [ABSTRACT FROM AUTHOR]

• Developed a new Safety Leadership Self-Efficacy Scale (SLSES) in maritime context. • SLSES has revealed adequate measurement properties with good explanatory power. • It can be used as a tool to assess and enhance safety leadership potentials of current and future shipboard officers. • Theoretical, methodological and practical contribution of SLSES were discussed. Extensive studies have highlighted the importance of leadership on safety in the maritime industry. However, current research lacks empirically tested theoretical models with valid and reliable scales for describing and measuring safety leadership in ship operations. This study reports the development and validation process of the first Safety Leadership Self-Efficacy Scale (SLSES) for assessing shipboard officer's efficacy in exercising leadership for safety in merchant shipping. The research has been divided into three stages, including a content validation study (20 subject matter experts), an Exploratory Factor Analysis (EFA) (n = 150) and a Confirmatory Factor Analysis (CFA) (n = 396). The results have supported a higher order factor structure with three subscales – motivation facilitation, safety management and safety initiative – contributing to the measurement of safety leadership self-efficacy. The resulting scale has revealed adequate measurement properties with good explanatory power, construct validity and high internal reliability (Cronbach's α = 0.971). SLSES can provide maritime researchers, practitioners and shipping organizations with a tool to assess and enhance safety leadership potentials of current and future shipboard officers. The theoretical, methodological and practical implications of SLSES were discussed. [ABSTRACT FROM AUTHOR]

Maritime Knowledge Clusters (MKCs) are the advanced stage in the evolution path of maritime clusters. Earlier literature however mostly focused on either the characteristics i.e. critical success factors or competitiveness of maritime clusters in general and not on the components of MKCs, their interrelationships, and impact on the performance of constituent firms. This study proposes and tests a conceptual model of Maritime Knowledge Clusters (MKC) and the relations between their components, making use of survey data from 203 shipping professionals located in Singapore. Three theoretical perspectives, namely, relational view, knowledge-based view and resource-based view, have been employed. The results demonstrate that MKCs are substantiated by three critical components, in which the local knowledge cluster can develop global systemic mechanisms, thus further strengthening global linkages. Policy makers must endeavor to create a conducive local cluster environment with maritime firms being located in geographical proximity, and having local networks, knowledge base, and knowledge flows. They form the fundamental foundation for the growth of MKCs. Besides, maritime firms shall optimize the MKC's local knowledge cluster to facilitate their global expansion, which will in turn boost the internationalization of the MKC. • This study conceptualizes the Maritime Knowledge Clusters (MKCs) and empirically examines the interrelationships between its components. • Structural equation modeling was employed to test the conceptual model. • MKCs are substantiated by three critical components: local knowledge cluster, global systemic mechanisms, and global linkages. • Policymakers should create a conducive local cluster environment with maritime firms being located in geographical proximity, having local networks, knowledge base, and knowledge flows. [ABSTRACT FROM AUTHOR]