Young Research Scholars Workshop Session

Seaports are characterized by tightly interconnected structures, non-linear dynamics, complex workflows, and intricate interactions between human, technological, and organizational elements. Effective risk analysis in seaports requires system-based approaches that offer an integrated perspective on these key components. The Functional Resonance Analysis Method (FRAM) has proven effective in modelling complex interactions and capturing performance variability within such systems. However, its reliance on qualitative data and expert judgment poses significant limitations. BN has revealed its advantages of accommodating both subjective and objective data in risk science. To address these challenges, this study aims to develop a novel FRAM-BN hybrid risk assessment framework grounded in Safety-II concept. This hybrid framework is capable of quantifying performance variability across diverse system components, providing a comprehensive method for both retrospective and prospective risk assessment. The methodology is demonstrated through a case study on seaport operations, highlighting its effectiveness in addressing the complexities of risk assessment and improving risk quantification. The results indicate that the proposed methodology provides decision-makers with actionable insights essential for effective risk assessment. By quantifying and visualizing system variability, it enhances the prioritization of interventions and enables targeted measures to mitigate risks.

Technology evolution in maritime autonomous systems is moving rapidly, yet our understanding of how different technologies interact and evolve remains limited. This study aims to analyze the technological landscape through patent analysis identifying and classifying the major technologies enabling autonomous shipping and analysing their interdependencies. We combine network analysis with topic modeling to analyze 5,987 patents from 2010-2024. Latent Dirichlet Allocation (LDA) was used to extract technological topics, while network analysis quantified interdependencies. We identified 20 technological topics which we then grouped into seven clusters. Network analysis showed high technological interdependency, with sensor integration emerging as the most influential domain. This study provides a quantitative evidence of MASS technology interdependencies. The multi-method analytical approach enables precise measurement of technological evolution patterns, advancing beyond previous studies that primarily focused on component identification. Our findings provide empirical evidence for prioritizing research and development efforts in autonomous shipping.

Weather is an ever-present factor influencing shipping operations at every stage, including port operations. This paper examines the determinants of weather-induced delays in port operations, the probability and duration of such delays, the predictive capability of various statistical models, and the potential for improving upon standard industry methods for estimating port margins. A wide range of models are investigated, including Generalized Linear (GLM) models, Cox Propotional Hazard models, and Autoregressive Conditional Duration (ACD) models. 
The findings reveal that a GLM with gamma-distributed dependent variables provides the best fit for data on delay duration, while a linear multiple regression offers the highest predictive accuracy for delay duration. Similarly, probit and logit models are found to perform comparably well for both predicting delay probabilities and data fit. Moreover, the analysis demonstrates that there are significant potential cost savings when using a linear regression model with a probit model to predict delays compared to a common industry rule-of-thumb of half a day delay. These results underscore the potential for improving operational efficiency and accuracy in port margin estimation through statistical modeling techniques.

The maritime container shipping industry is experiencing a significant transformation through the widespread adoption of digital technologies, which are expected to improve operational efficiency, sustaining competitive advantage, and foster long-term growth. In pursuing digitalization, factors influence companies' decisions within the maritime container shipping industry, i.e., cost, customer satisfaction, operational efficiency, environmental applications, and organizational components. This research introduces a methodological framework that utilizes the Bayesian Best-Worst Method (BBWM) to assess these digitalization factors. By combining Bayesian inference with the Best-Worst Method, this framework enhances decision-making by systematically addressing uncertainties and variations in expert evaluations. The results highlight the relative significance of these factors, providing empirically supported insights for industry stakeholders aiming to navigate the challenges of digital transformation. This research not only broadens the methodological use of BBWM but also enriches the strategic conversation surrounding digital innovation in maritime container logistics.

This study explores the multifaceted dimensions of port automation, focusing on the interplay between technological innovations with organizational and environmental contexts in Automated Container Terminal (ACT). Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, we systematically review and analyze literature trends, identifying key themes and sub-themes that address the policies, operations, and the recent state of automation. The structured approach reveals insights into technological advancements in port automation examining the benefits, challenges, and construction trends. Automation's potential to improve efficiency, sustainability, and productivity is contrasted with challenges, including high capital costs, labor resistance, and technical challenges. The findings are organized into thematic structures, offering a comprehensive perspective on the more established topics and emerging trends in port automation. By addressing key challenges and opportunities, the discussion outlines insights for policy formulation and future directions of advancements, particularly in enhancing system interoperability, promoting workforce inclusivity, and aligning practices with sustainability objectives. Concluding observations advocate a need for a balanced approach to automation that aligns technological progress with broader societal goals, ensuring economic and environmental resilience. Key enablers such as innovative layout designs, digitalization, and collaborative systems emphasize the industry's shift toward integrated and smarter operations.

Despite the spare capacity of inland waterways, roadway transport remains the predominant mode of freight movement, and several issues are being faced. Synchromodality uniquely considers real-time information to select the most efficient and cost-effective transport modes. It presents a promising solution for optimizing freight transport systems but faces significant implementation challenges, particularly in collaboration among multiple actors and ensuring coordinated planning and operations. This study examines the main factors hindering mode shift and evaluates the level of collaboration among supply chain actors in implementing a more flexible and collaborative freight transport system, mainly focusing on inland waterways. This paper's methodology involves data collection and data analysis; 68 supply chain stakeholder perspectives are explored, and challenges and opportunities of synchromodal transport too. The findings reveal the importance of cost, service quality, distance, and infrastructure availability, among other factors, in mode choice processes. The perception of supply chain actors on the level of integration among transport modes and collaboration across stakeholders was also targeted. The research underscores the need for targeted policy interventions, such as promoting stakeholder collaboration, enhancing traffic management systems, and clarifying to the stakeholders the benefits of the shift toward more efficient and sustainable freight transport solutions.

This paper investigates the macroeconomic impacts of exogenous maritime transportation shocks through the flow analysis of the Panama Canal, Suez Canal, and Strait of Malacca chokepoints on the European Union. In contrast to previous studies that rely on price-based indexes, this research incorporates vessel flow data to directly assess supply chain fragility and persistence, eliminating endogenous factors related to container spot prices. Employing a Bayesian Vector Autoregression (BVAR) model with sign restrictions, the main findings highlight the prolonged impacts on producer and consumer prices, emphasizing the necessity for robust policy measures to mitigate vulnerabilities in global maritime networks.

Institutions are the rules of the game in society and they constrain human interactions. To improve the chances of reform policy succeeding, it is imperative that policy makers know which institutions are crucial to their reforms; by what mechanism(s) the institutional influence is transmitted; how these institutions should influence reform rollouts; and what specific institutional adjustments can be made to increase the chances of reform success. Using a multi-stage research design, we present an institutions-based analytical framework for formulating reform policy within a political system. Extending influential research by Cox and McCubbins (2000) and Haggard and McCubbins (2001) we affirm that the most crucial institutions for reform policy are the separation of powers and separation of purpose between the executive and legislative branches. To improve the chances of reform success, reformists should make institutional adjustments that increase reform competence and credibility. This should be proactively signaled to reform partners. Reformists should also focus on improving both reform competence and credibility, which are inter-related, rather than focus solely on one factor. The analytical framework is validated using two illustrative case studies, which are Nigeria's maritime port reforms from 1999-2006, and Egypt's commodity subsidy reforms from 1977-2013.