The rapid diffusion of industry 4.0 technologies has substantially transformed the maritime transportation sectors by enabling data-driven operations, enhanced connectivity, and more intelligent decision-making processes. Digital technologies such as the Internet of Things (IoT), simulation systems, and advanced data analytics are increasingly reshaping operational structures in maritime logistics, positioning technological transformation as a strategic priority for firms. However, the weighting and prioritization of components emerging with industry 4.0 technologies remain an underexplored area in the literature. The primary motivation of this study is to determine the weights of these industry 4.0 components using the Bayesian Best Worst Method (BWM) and to reveal their corresponding credal ranking levels. In this context, the present study aims to evaluate and prioritize the critical industry 4.0 components influencing technological transformation processes using the Bayesian BWM. Bayesian BWM is preferred over alternative Multi Criteria Decision Making (MCDM) approaches due to its ability to explicitly model uncertainty within a probabilistic framework, generate more consistent weighting results, and flexibly incorporate decision-makers' judgments. The findings reveal that safety and security (0.2945) constitute the most influential main component, underscoring the necessity of robust digital infrastructures and reliable systems within highly digitalized operational environments. Among the sub-components, data privacy (0.1301) demonstrates the highest global weight, highlighting the growing importance of safeguarding sensitive information in data-intensive digital systems. The results further indicate that autonomous operation and coordination play significant roles in facilitating efficient digital operations, particularly through real-time equipment monitoring and IoT-based operational visibility. Moreover, sustainability (0.1968) emerges as the second most important component, suggesting that organizations increasingly assess technological investments not only in terms of operational efficiency but also with respect to long-term resilience. Within this dimension, continuous training (0.0614) is identified as the most influential component, indicating that the success of digital transformation depends not only on technological infrastructure but also on the development of human capabilities. With the increasing digitalization of the maritime industry, protection against cyber threats has become essential for ensuring operational continuity and safeguarding data integrity. In this regard, adopting proactive cybersecurity strategies and continuously monitoring and updating systems are of critical importance. In the digital transformation of maritime transportation, integrating sustainability considerations is essential to ensure long-term operational efficiency and environmental responsibility. These practical implications are particularly relevant for policymakers, port authorities, and shipping companies seeking to enhance both digital capabilities and sustainable performance.

The study evaluated the effect of leisure internet use on individual work performance and the possible moderating role of attitudes toward artificial intelligence in this relationship. Responses from 206 freight forwarders were analyzed using the PROCESS macro (v.5.0) to implement the Johnson-Neyman (JN) approach for probing regions of significance. Findings indicated that, while was an initial direct negative effect of leisure internet usage on individual work performance, the moderation analysis showed a statistically significant positive interaction between leisure internet usage and attitudes toward artificial intelligence. The negative effect of leisure internet usage on individual work performance diminished as attitudes toward artificial intelligence increased. The JN analysis revealed a critical point in artificial intelligence attitudes (6.02 on a 10-point scale), beyond which leisure internet usage no longer had a statistically significant negative effect on individual work performance. To protect productivity, organizations should develop strategies that foster a more positive technological orientation toward AI among employees, shifting the focus away from merely restrictive internet policies. The boundary condition of these specific findings is defined by the sample of freight forwarders, requiring caution when generalizing to the broader industrial context.

This study aims to reveal the current container trade and future forecasting estimations for Türkiye. To address this aim, study develops a deep learning based long term forecasting framework for containerized trade by integrating time series decomposition with and attention mechanism. This study proposes a decomposition based deep learning architecture for long term forecasting of containerized maritime trade, with a primary methodological contribution centered on improving predictive stability across short- medium- and long-term horizons. The approach begins with a time-series decomposition procedure that separates container throughput data into trend, seasonal, and residual components, thereby reducing noise and isolating distinct temporal dynamics. Each decomposed component is modeled using a hybrid neural network structure, integrating Long-Short Term Memory (LSTM) layers to capture sequential dependencies and an attention mechanism to dynamically assign weights to historically relevant observations. Empirical findings demonstrate that the decomposition attention model consistently outperforms baseline approaches, particularly in medium- and long-term forecasts where traditional time-series models exhibit declining accuracy. The results confirm that integrating structural signal decomposition with attention-enhanced deep learning significantly improves robustness, reduces forecast error propagation, and enhances temporal feature extraction in container trade prediction.

This study examines the Warehouse Management System (WMS) evaluation in digitalized logistics operations as a multidimensional decision-making problem. By integrating the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT), the study develops a framework that links technology acceptance considerations with operational and strategic software evaluation criteria. The fuzzy Best–Worst Method (BWM) was applied to prioritize the criteria under uncertainty, using evaluations obtained from logistics professionals, software experts, warehouse managers, and academics. The findings show that Software Architecture and Flexibility is the most important main criterion, followed by Security and Performance and System Integration Capability. At the sub-criteria level, Compliance with Standard Protocols, Modularity, Scalability, ERP/TMS/CRM Integration, and Mobile Compatibility emerged as the five most critical determinants. The results indicate that logistics firms prioritize standard compliance, architectural flexibility, scalability, system integration, and mobile compatibility over user-centered criteria. The study contributes to the WMS evaluation literature by combining TAM and IDT with a fuzzy multi-criteria decision-making approach and provides managers with a structured framework for aligning WMS evaluation with operational fit and digital transformation goals.

The increasing exposure of global supply chains to environmental, social, and operational disruptions has intensified scholarly interest in sustainability and resilience. While these concepts are widely discussed, existing research often addresses them separately, preventing understanding of their combined role in supply chain management. In response, the concept of susilient supply chains has emerged to capture the joint consideration of sustainability and resilience. This study presents a systematic literature review conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol. Based on an analysis of 73 peer-reviewed articles retrieved from the SCOPUS database, the study examines the general characteristics of the susilient supply chain literature in terms of research focus, methodological approaches, and theoretical orientations. The review identifies dominant analytical patterns and recurring research themes, while also outlining the overall structure of the field. The findings suggest that current research is largely shaped by established modeling approaches, such as structural equation modeling (SEM), and dynamic capabilities and resource based theoretical perspectives. The review highlights the need for broader and more integrative research designs to support the continued development of susilient supply chain studies. By offering a structured overview of an emerging and dispersed literature, this study contributes to a clearer positioning of susilient supply chains within the broader sustainability and resilience discourse.

ABSTRACT This study aims to examine digitalization processes in port operations, identify current research trends and technologies, and provide recommendations for future studies aligned with these developments. To achieve these objectives, a comprehensive literature review was conducted. Initially, a detailed analysis of existing studies was performed, including the creation of keyword and country heat maps. Subsequently, the literature was examined using VOSviewer software. Bibliographic coupling analysis showed that the studies fell into four main clusters. The findings indicate that port digitalization is playing a significant role in transforming the sector. Despite a substantial body of research, several areas remain underexplored and open to further development. Key topics identified for future investigation include cost-benefit analyses of digitalization and the adaptation of operational processes to digital technologies.

. Background: The Best-worst Method (BWM) has been successfully applied in various fields since it was first proposed in 2015, with numerous extensions developed over time. Its advantages over other pairwise comparisonbased multi-criteria decision-making (MCDM) methods-such as requiring fewer pairwise comparisons and providing more consistent evaluations-make it preferable. The primary motivation for this article stems from the fact that no comprehensive review of the method has been published since 2019. The reason for focusing specifically on the "Transportation and Logistics" field is the significant increase in BWM applications within this sector and the large number of BWM studies conducted since the last review article in 2019. Methods: This article provides a bibliometric analysis using VOSviewer visualizations, complemented by a robust interpretation and inference analysis that explores in-depth connections between studies. Specifically, the analysis covers key statistical aspects, including the specific issues to which BWM is applied in the transportation and logistics field, publication trends, methods with which it is integrated, and the concepts (such as fuzzy set, rough set, neutrosophy, stratification etc.) with which it is commonly used. Additionally, the study examines the journals in which these studies are published and the distribution of studies across different countries. Results: The study revealed that several key areas within the transportation and logistics industry, such as occupational health, personnel selection, and the effects of pandemics, remain underexplored. Conclusion: The article highlights emerging research opportunities within the transportation and logistics sector and explores various ideas for the applications of BWM extensions. It also discusses activities, software, books and events related to BWM. The study provides an overview of the current state of BWM applications in transport and logistics and serves as a guide for potential future research.

Many different types of barriers have been developed because of ever-increasing environmental awareness and need to protect the marine environment from pollution. Most barriers comprise floating booms to block floating debris with a skirt or subsurface portion to trap oil. An alternative is air bubble barriers, which have several advantages over traditional booms for protecting permanent structures like harbor entrances and water intakes. This study investigates the use of air bubble barriers as an oil spill containment technique. Eleven marine professionals with an average of 15 years experience participated in a SWOT-Interval Type-2 Fuzzy Analytical Hierarchy Process (IT2-FAHP). In-depth interviews and literature review of studies of air bubble barriers were conducted to establish the SWOT critera and sub-criteria. The main critera identified was strengths, with a score of 0.459, while the top-prioritized sub-critera was “Unlike traditional oil containment booms, the fastest response to the spread of oil spills”, with a score of 0.187.

This study investigates energy efficiency indicators including the Energy Efficiency Design Index (EEDI), Energy Efficiency Operational Index (EEOI), Ship Energy Efficiency Management Plan (SEEMP), Energy Efficiency Existing Ship Index (EEXI), and Carbon Intensity Indicator (CII) by providing a comprehensive scientometric analysis. The specified indices are scrutinized using papers from WoS and Scopus databases by applying the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) method to select the most appropriate papers in the related literature. Keyword and citation analysis of papers were performed using the VOSviewer software program to reveal the current research trends. The analysis addresses several critical aspects. Firstly, it focuses on identifying which indicators are employed more frequently in the literature, and secondly, it classifies the research according to whether a calculation was made, and the yearly distribution was determined. The results pinpoint that the EEDI and EEOI were examined in 42.55% and 22.49% of the reviewed studies, respectively. Furthermore, it is evident that the EEXI and CII percentages have increased drastically over the past three years, with the figures standing at 20.01% and 18.59%, respectively. Consequently, in alignment with the findings, the theoretical and managerial implications are highlighted for the private sector, academia, and maritime stakeholders.

It is predicted that the seafarer shortage in the global seafarer market will continue in the next years. In particular, the expected shortage of officer-licensed seafarers in the coming years should be considered as an opportunity for the seafarer supplier countries. For this purpose, this study aims to make implications about how to improve the skills of seafarers by analysing seafarer selection criteria in Turkish maritime companies. In this context, the criteria related to the selection of seafarers were defined, these criteria were evaluated by the selected experts, and managerial implications in the context of talent management were made. The results showed that ‘Knowledge of the English Language’ was seen as the most significant criterion, and it was followed by respectively ‘Having Sufficient Knowledge of the Safety Management System’ and ‘Validity Period of Seafarer Documents (passport, certificates, qualification, etc.)’. According to the results obtained from the study, suggestions have been made that are thought to enable Turkish seafarers to get a larger share of the international seafarer market.

United Nations (UN) introduced Sustainable Development Goals (SDGs) to create comprehensive agenda for achieving economic, social, and environmental sustainability in the world. In 2015, the UN released 17 SDGs specifying 169 targets to achieve this important aim. It is vital to adapt these goals to provide a livable environment for the next generations. One of the most important stakeholders in contributing to global sustainability is the maritime industry. This article aimed to connect each of the reviewed papers to the SDGs while also presenting a comprehensive view of SDGs in maritime transportation. Therefore, this paper has novelty to reveal the gaps related to the goals achievement of sustainable development. This study, it was conducted a comprehensive literature review of 67 peer-reviewed studies in the Scopus database regarding the achievement of SDGs in maritime transportation. With this direction, four separate clusters were created by utilizing the VOSviewer software program with a bibliographic coupling method. From this point of view, it was identified scholars’ most recent intentions, applications, and suggestions in the existing literature. Finally, gaps in the current literature revealed, potential theoretical and practical implications suggested, and recommendations to researchers for further studies were given to make contributions for achieving SDGs.

IMO has introduced regulations to improve fuel quality in the sector to reduce emissions from ships carrying the vast majority of world trade. As a result of these regulations, which were planned gradually, carbon-neutral shipping was targeted. In line with this goal, it was seen that ship operating companies tend to various alternatives to increase fuel quality. This study evaluated various fuel alternatives for ship investment decisions by employing the Technique for Order Preference By Similarity to Ideal Solution (TOPSIS) method under the Single Valued Neutrosophic Sets (SVNS) in terms of sustainability aspects. First, criteria that are specific to the ship investment decision under the aspects of sustainability and their weights were determined. Then, these weights were placed in the model to determine the most sustainable ship fuel produced within the scope of the study. Finally, alternatives determined in terms of fuel type, which is one of the items to be decided on ship investment, were listed according to their degree of sustainability. According to the findings, dual fuel and bio-fuel were selected as more sustainable bunker fuels for today. Technically, findings were evaluated, and the pros and cons of the related bunker fuels were revealed. In the light of the findings, evaluations were made on alternatives.

Route optimization in maritime transportation provides enormous cost saving and efficient resource allocation for companies. Shipping companies need to create an optimized route for shipping fleets. That is why route optimization has gained considerable and increasing attention in maritime transportation literature over the past few years. This research aims to identify the theoretical cornerstones, current research trends, and possible research avenues for future studies by reviewing 256 peer-reviewed route optimization articles in maritime transportation literature. For this purpose, first, theoretical cornerstones of route optimization in maritime transportation literature were examined by co-citation analysis and three clusters were identified: fleet routing and deployment; liner shipping rotation; and optimization of fuel consumption and vessel speeds. Second, current research trends of route optimization in maritime transportation literature were uncovered via bibliographic coupling analysis. The analysis results revealed that current research trends could be considered in four clusters: route planning; routing under different weather conditions; liner shipping network and service design; and environmental speed optimization. Finally, author-keyword analysis was performed to specify knowledge gaps and recommend future research areas.

PurposeConsidering the human factor, the quality of the personnel is vital to ensure especially the value creation in the ports. Therefore, employee quality stands out for withstanding the pressures that stem from global trade on its operational speed felt by ports in recent years. Accordingly, the selection of the qualified personnel at the ports is very critical and a tool based on dynamic capabilities is needed to manage this process well. The aim of this study is to develop a model based on dynamic capabilities for recruitment process of ports.Design/methodology/approachPort personnel should have dynamic capabilities detected from the literature. These capabilities were approached as criteria. In this study, Buckley's proposed fuzzy analytical hierarchy process (AHP) method was employed for weighting the whole criteria. After that, weights of the criteria were used to prioritize alternatives with the fuzzy TOPSIS method.FindingsThis model reflects port managers' priorities and port customers' evaluations. Thus, the model can also reflect the level of integration of ports' related department managers into the recruitment process. The analyses allow the evaluation of the attitudes of the human resources department in the related port while fulfilling the personnel recruitment function. As a result of analyses, differences between perceptions of port managers and customers served as a feedback to the human resource management department of the ports.Originality/valueOne of the originalities of this study was derived from its customer-oriented perspective. This is a unique study that gathers common personnel capabilities related to the operation, planning and customer relationship departments and evaluates the success of these capabilities from the customer perspective.

Port service quality stands in a vital position in port competitiveness. In this study, we aimed to prioritize the Sustainable Port Service Quality (SPSQ) factors. Firstly, we investigated the SPSQ factors with the help of the related literature. We determined 3 main, and 15 sub-criteria evaluate the SPSQ. Survey questionnaire forms were sent to the experts who perform in several different areas in the port sector. Afterward, we employed the interval type-2 fuzzy analytic hierarchy process (IT2-FAHP) to weighting the identified criteria. According to the results, the economic main criteria were selected as the most prioritized criteria for experts’ evaluations. Furthermore, C1.2. “Efficiency of Loading and Discharging Operations” and C1.5 “Port Infrastructure” and C3.1. “Environmentally Responsible Operations (Waste Management etc.)” were evaluated as the most three prioritized sub-criteria with the highest scores respectively. This study contributed to the literature in two different unique ways; (1) revealing the SPSQ criteria and (2) employing the IT2-FAHP method to prioritize the port service quality criteria. Identified service quality model can be used for port practitioners and findings may be applied as recommendations for port practitioners to have a greater influence on their customers.

The Covid-19 pandemic affected almost all sectors of the economy. The maritime industry was also affected by the pandemic in various ways. During the pandemic period, the maritime industry experienced such challenges as empty container shortages, port congestion, labor shortages, etc. Different sectors of the maritime industry developed resilient strategies against these challenges. Liner shipping companies also developed horizontal integration strategies along supply chains to control and manage the whole process of door-to-door transportation. In this study, factors that accelerated the supply chain integration strategies of liner shipping companies during the Covid-19 pandemic period were investigated. In this context, the relevant literature was investigated in the SCOPUS database, and 24 articles were examined in a detailed manner. As a result of the literature review, the factors that accelerated the supply chain integration of liner shipping companies were coded through the MAXQDA 20 qualitative data analysis program, and the relationship between these factors was determined.

Industry 4.0 technology has affected almost every sector in the world. Maritime sector is one of them that were affected by this technology. In this study, components of the maritime sector were prioritized to find out which of them should comply with this transformation primarily. Many different criteria were taken into consideration for the solution of such problems. Therefore, multi-criteria decision-making (MCDM) methods required to solve this problem. Fuzzy AHP (Analytic Hierarchy Process) and VIKOR (VlseKriterijumska Optimizacijia I Kompromisno Resenje) hybrid method was employed for revealing the prioritization ranking for maritime sector components. A group of experts assessed and compared 22 criteria and scored them for each alternative. Proposed methodology was employed through the experts’ assessments. Results were displayed and suggestions were given for the further studies

During the Covid-19 pandemic, all sectors experienced chaotic dynamics worldwide. For example, maritime transport, particularly ports as one of its main elements, had to continue operating in this chaotic environment. Ports developed their own strategies to provide resilience against these challenges. However, any study in the related literature has not been reached that reveals resilience strategies of ports by combining literature review and interviews with port practitioners. As a novelty of the study, it was tried to evaluate resilience strategies of ports by grounding chaos theory. Therefore, this study had two aims: (1) identifying the Covid-19 strategies of Turkish container ports; (2) prioritizing these strategies in terms of impact level. First, interviews were conducted with Turkish container port representatives to find out their resilience strategies. These strategies were then validated with a literature review and new ones were detected. Second, separate relation analyses of the strategies were conducted for the interviews and literature. Finally, ports' resilience strategies against Covid-19 disruptions were prioritized using Fuzzy Analytic Hierarchy Process (AHP) based on the port managers' evaluations. Fuzzy AHP is widely used and accepted in the maritime business literature. This method also diminishes inconsistencies and subjective evaluations by employing fuzzy logic. The results showed that 'Control Mechanism', 'Hygienic Measures', and 'Information Exchange' were the most effective resilience strategies. By using chaos theory, this study helped to theoretically clarify the role of port management approaches to the challenges of the Covid-19 pandemic. These findings can therefore guide container port practitioners in overcoming pandemic conditions.

The negative impact of air pollution on human health had become a vital issue as a result of the increasing use of fossil fuels in recent years. In this context, maritime transportation is one of the most contaminant sectors by using much more fossil fuels. Ships which have a major role in maritime transport, directly affect human health via its emissions, especially in marine areas close to the land such as around the ports, canals, and straits. In this study, strategies were gathered by evaluating International Maritime Organization (IMO) regulations, European Union (EU) recommendations and the applications of the ship owner companies to reduce air pollution stem from ships, and considering the priority perception of these strategies, the effect level of the strategies at the marine areas where ships are approaching the land was analysed by the Fuzzy Analytic Hierarchy Process-Visekriterijumska Optimizacija I Kompromisno Resenje (AHP- VIKOR) hybrid method. As a result of the study, the most effective strategies appeared as “Forbiddance of Heavy Fuel Oil (HFO) usage on Ships” and “Detection of Low Sulphur Fuel Usage by the help of Remote Detector Systems”, and it was seen that these strategies would be most effective in canal or strait passing of the ships. It was also revealed that the relevant expert opinions and IMO regulations meshed together, and it was pointed out the applications for increasing fuel quality.

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