FAEQ - Maritime Business and Strategy

In the global shipping market, uncertainties have risen due to economic fluctuations, changes in trade demand, rising fuel prices, and stricter environmental regulations. In this context, ship lay-up behavior has emerged as a critical strategy for shipowners to manage overcapacity and adapt to market demand volatility. This study explores the key factors influencing lay-up decisions and evaluates their specific impacts on the supply-demand dynamics of the shipping market.
Based on a dataset of 2,348 ships provided by Clarksons during 2015-2024, survival analysis and time-series methods were employed to systematically examine the correlations between macroeconomic indicators (such as the Baltic Dry Index), shipping market characteristics (such as fleet development, demolition rates, earnings, an operating cost), and ship-specific traits (like company size, fleet type) with lay-up behavior. Findings suggest that macroeconomic conditions, shifts in market supply and demand, and profitability levels are likely the main drivers of lay-up decisions. Adverse conditions increase the likelihood of companies opting for lay-up to minimize losses. This study offers valuable insights into market dynamics and provides empirical support for shipping companies to develop flexible operational strategies, aiding adaptation to market changes.

With the dynamic changes in the global shipping market, the idle behavior of vessels has become a significant factor influencing shipping companies' operational efficiency and profitability. To systematically analyze the determinants influencing idle behavior decisions, thisstudy, based on a comprehensive literature review, categorizes these factors into market factors and vessel characteristic factors. Detailed data on idle vessels was obtained from the Clarkson's database and the Automatic Identification System (AIS). According to the idle data's distribution, a zero-truncated Poisson regression model was applied to analyze the impact of various variables on idle behavior. This study findings reveal that market supply, specifically a higher number of fleet, increases the probability of idle status. Conversely, a larger orderbook, indicative of more potential orders, decreases the likelihood of vessels being idle. Similarly, a higher volume of seaborne trade reduces the idle probability. Furthermore, older vessels are more prone to becoming idle and vessels flying open flags are more prone to becoming idle. This study not only contributes to a deeper understanding among shipping companies of the key factors influencing vessel idle behavior but also provides a theoretical basis for formulating effective operational decisions and optimizing resource allocation.

Container shipping lines choose cooperation to maximize their profit, however, the highly cyclical demand for container shipping affects the profit of container shipping lines, and correspondingly, influences their cooperation strategies. Additionally, the profit of shipping lines depends on the fees they pay to the port and terminal operators, which, in turn, are influenced by the competition between them. Therefore, the motivation for shipping lines to ally is affected by the power they gain in the supply chain over the ports and terminal operators. This research studies the combined effect of market demand and port competition on shipping line cooperation. An evolutionary game theory model is developed to study the dynamics of cooperation among shipping lines. Additionally, ports compete to attract shipping lines. Our results show that with increasing demand, shipping lines prefer cooperation over operating independently. However, their evolutionary stable strategies depend on their market share, vessel sharing agreements, freight rate, and charter rate. Additionally, the effect of market share of shipping lines on the dynamics of cooperation of parameters is studied.

This study addresses the vessel schedule recovery problem (VSRP) in liner services, which is crucial for mitigating disruptions in global maritime logistics. The research focuses on optimizing vessel schedules under conditions of delays, port congestion, and port-skipping, using Automatic Identification System (AIS) and port call data from 2019 and 2021. A comprehensive analysis of key trunk routes highlights how disruptions impact vessel behavior, including changes in average speed and waiting times. To address these issues, a cost-minimizing optimization model is developed, incorporating factors such as fuel costs, container time value, and waiting times. The model was initially calibrated and tested on the PS4 service of THE ALLIANCE. Results showed that dynamic adjustments, such as port-skipping and speed changes, can significantly reduce costs during periods of severe port congestion, with sensitivity analysis demonstrating the influence of varying container time values. Building upon these findings, the model is further applied to the ZP9 service of the 2M ALLIANCE to validate its general applicability and performance under different service conditions. This research offers practical insights for shipping operators and port managers in developing strategies to enhance service reliability amidst growing uncertainties in global supply chains.

This study presents the modeling approaches developed for the Passenger Maritime Transport Observatory under the ENIRISST project, focusing on the Aegean Archipelago. A holistic transport model is developed, incorporating aggregate and disaggregate demand analysis, network efficiency assessment, and ferry routing optimization. The methodologies include econometric demand models, supply (network) modelling and routing algorithms to assess the dynamics between supply and demand. Findings indicate inefficiencies in the current ferry network. Optimization scenarios suggest dynamic scheduling and on-demand services could enhance efficiency. The results provide valuable insights for policymakers and industry stakeholders, supporting ferry network redesign, investment planning, and sustainability initiatives. This research contributes to maritime transport modeling and informs policy development for efficient inter-island connectivity.