Abdullah Açık

This study examined return connectedness and spillover transmission among ten major VLSFO bunker hubs in the post-IMO 2020 era. Using daily log return data from 12 June 2023 to 12 June 2026 and the Diebold–Yılmaz connectedness framework, the study identified the system-wide, directional, net, and pairwise spillovers across key VLSFO bunkering hubs. The baseline results show a Total Connectedness Index of 72.56%, indicating a highly integrated global VLSFO bunker market, and a substantial share of return variation is explained by inter-market spillovers. Singapore emerges as the dominant net transmitter, while Hong Kong, Fujairah, Rotterdam, and Houston also act as important transmission hubs. Santos appears as the largest net receiver, suggesting stronger exposure to shocks originating from other hubs. Pairwise and network results show that the Singapore–Hong Kong–Fujairah axis forms the core of global VLSFO spillover transmission, while the Houston–New York connection and Rotterdam-linked routes represent important regional spillover channels. A complementary 200-day rolling-window analysis further shows that total connectedness varies over time, ranging from 52.75% to 88.80%, indicating that the VLSFO spillover structure is dynamic rather than fixed. These findings provide useful implications for bunker procurement, fuel cost management, and maritime energy risk monitoring by identifying the main transmission hubs and receiver markets in the global VLSFO network.

This paper explores how wheat import volumes in Intergovernmental Authority on Development (IGAD) countries respond to global price changes, and whether these reactions vary across countries or over time. Wheat is a critical staple in the region, and its import dynamics are increasingly important as the bloc faces recurring shocks like drought, conflict, and global price spikes. Using a two-pronged approach, we first apply country-level autoregressive distributed lag (ARDL) models and find long-run cointegration across all IGAD members. Eritrea and Ethiopia show strong long-run negative price elasticities, pointing to substitution or price-sensitive behavior. South Sudan, Sudan, and Somalia display short-run positive responses, likely linked to urgent procurement or aid-related deliveries. Uganda shows limited responsiveness, while Djibouti—though also reactive in the short term—likely reflects its role as a re-export hub rather than fragility-driven volatility. Kenya shows both long-run sensitivity and short-run spikes, indicating a more complex market and policy mix. At the bloc level, panel Granger causality tests reveal a two-way relationship between global wheat prices and imports. Notably, imports also Granger-cause price shifts—an unexpected result suggesting that even uncoordinated regional import behavior may shape market expectations. This finding strengthens the case for more strategic procurement and regional storage mechanisms.

This study offers new empirical insights into the cost implications of container shipping delays and schedule unreliability on international freight rates, using a quantile regression model to capture market heterogeneity. While literature widely acknowledges the theoretical impact of schedule issues on trade costs, there has been a critical lack of empirical analysis quantifying this relationship under different market conditions. The purpose of this study is to explore the influence of schedule reliability in container transportation on freight rates. By integrating the China Containerized Freight Index (CCFI) with key variables such as average vessel delay, schedule reliability, bunker prices, and the Li Keqiang index as a proxy for demand, this research addresses that gap. Unlike conventional linear models, the use of quantile regression reveals how the effects of delays and reliability differ across various freight rate levels, yielding a U-shaped impact pattern—strongest in the worst and booming market conditions. The findings indicate that even a one-day increase in average delay can raise the CCFI by 100-226 index points, while a one-point decrease in schedule reliability can increase the index by 5-13 points. Therefore, service reliability is important for international trade, and countries, individuals, and ship owners adopt different pricing policies in response to market conditions. This study adds significant value to the field by providing policymakers and logistics stakeholders with actionable metrics on the cost of inefficiencies in global maritime transport, especially in post-pandemic and geopolitically volatile contexts.

This chapter explores how geopolitical risks affect international trade, with a specific focus on container throughput. Given the inherently global nature of maritime logistics, geopolitical shocks have intensified disruptions in trade flows. The study investigates whether the causal relationship between geopolitical risk and trade performance differs between advanced and emerging economies. Using non-causality tests on panel data from 39 countries between 2007 and 2022, the analysis reveals significant differences. In advanced economies, declining container traffic is found to increase geopolitical risk, whereas in emerging economies, rising geopolitical risk leads to a reduction in container traffic. These findings underscore the need for differentiated policies: advanced economies should closely monitor trade indicators to anticipate tensions, while emerging economies should prioritize political stability and trade infrastructure. The chapter provides empirical insights for policymakers navigating the complex interplay between geopolitical uncertainty and global maritime trade.

The determination of freight rates in liner shipping is influenced by the market dynamics and the strategic decisions of shipping alliances. This study investigates the effect of non-alliance tonnage on freight rates along the Asia–North America West Coast route, employing a quantile regression method. A dataset covering July 2021 to June 2023 was used, with bunker prices and the Dow Jones Index serving as control variables. The results reveal that the non-alliance share has a significant and negative impact on lower quantiles, suggesting that enhanced competition reduces freight rates when the prices are low. In contrast, this effect disappears at higher freight levels. Bunker prices and the stock market index also exhibit varying effects, depending on the quantile, with demand-side variables being more influential during low-freight conditions. These findings suggest that market concentration affects price-setting power, and quantile-based approaches offer deeper insights into these complex relationships than linear models. These insights contribute to the sustainable development of maritime transport by promoting fair competition, improving pricing transparency, and supporting efficient policy interventions in global liner shipping.

This study explores the asymmetric relationship between the U.S. dollar index (DXY) and dirty tanker freight rates, a largely unexamined area within maritime economics despite the dollar’s profound influence on global oil prices and economic stability. Tanker shipping, the primary mode of transportation for global oil and a capital-intensive sector, plays a crucial role in oil supply chains. Given that oil prices are quoted in U.S. dollars, fluctuations in dollar strength directly impact oil costs, demand for tankers, and the operational costs of tanker shipping. This study employs an asymmetric model, recognizing that dollar value changes affect the tanker market differently depending on whether the dollar is strengthening or weakening. Findings reveal that decreases in the DXY drive up tanker freight rates, while increases do not correspondingly decrease rates, highlighting the unique non-linear dynamics between currency strength and freight costs. This asymmetric approach provides a more accurate framework for understanding these interactions than traditional linear models.

I aimed to econometrically determine the reflection of pressure-increasing events in the global supply chain on the container traffic in Turkish ports, since any disruption or pressure can have negative consequences such as shortages and high prices for consumers, a decline in profitability for companies, reduced job opportunities for workers, a slowdown in economic growth for countries, and a slowdown in trade for the world. I used the Global Supply Chain Pressure Index (GSCPI) to model the impact of events occurring in the global supply chain, and the export and import container traffic at Turkish ports. Instead of examining the relationship between the variables over the whole sample, I used the time-varying causality analysis, which makes it possible to detect the relationship at different periods in time by analyzing it with the rolling window approach. The dataset includes 230 monthly observations and covers the period between January 2004 and February 2023. The pressure in the supply chain differs according to export and import container loads. The Russia–Ukraine war, the Suez Canal closure, economic sanctions between the U.S. and China, economic crisis, geopolitical conflicts, hurricanes, and port congestion in the U.S. all affected the traffic in Turkish ports. Since this research was conducted with a time-varying approach and the GSCPI variable successfully represented many global supply chain events, it was possible to examine which events affected international trade through a single variable. Thus, event-based assessments become possible instead of just saying that supply chain pressure affects international trade.

Container transportation, facilitated by the development of standardized containers, has revolutionized global trade by increasing efficiency, reducing costs, and enhancing the competitive power of countries. The Liner Shipping Connectivity Index (LSCI) plays a crucial role in measuring the supply side of container transportation, influencing strategic decisions regarding infrastructure investments and policy development to boost global trade integration. Our study aimed to determine whether container throughput drives LSCI or vice versa, using panel data analysis to inform strategic decisions in maritime trade, investment priorities, and policy development. We conduct our analysis using a unique data set covers the years between 2008 and 2021 and consists of 85 countries and 1190 observations. The results obtained revealed that there is a two-way interaction between Container Throughput and LSCI variables, the effects of the variables are positive and reflected after 1 period, and the impact of changes in LSCI on Container Throughput is higher than the opposite situation. This shows that there is a positive feedback loop between the variables and that improvement in any one of them returns as improvement to itself after a certain period.

Delays in international trade negatively affect the global world economically, commercially, and politically. We aimed to empirically determine the asymmetrical effect of the delays experienced in the arrival of container shipping vessels to their destinations on the pressure on the global supply chain by using Global Schedule Reliability (GSR) and Global Supply Chain Pressure Index (GSCPI). The dataset covers the period between January 2017 and April 2023 and consists of 76 observations. The results show that the effect of delays on the supply chain is asymmetrical, while the increase in delays increases the pressure, the decrease in delays has no effect. This shows that the effects of delays on the supply chain are sticky and take a long time to clear from the system. In this direction, policies are recommended to minimize the effect of delays on international trade.