AN APPLICATION OF FUZZY ANALYTIC HIERARCHY PROCESS TO OVERCAPACITY ABSORBING METHODS IN CONTAINER SHIPPING

The market in container shipping has been characterised as highly cyclical. In a depressed stage of the cycle, with a sharp decrease in demand, the gap between supply and demand widens significantly leading to a deepening overcapacity in the sector. In order to reduce overcapacity in the container shipping sector specific actions have been undertaken by such shipping operators. This paper describes a study which modelled certain selection criteria applied to overcapacity absorbing methods for containership companies. The relative ranking of each criterion was determined through a fuzzy- AHP method. In order to conduct the method, five main and twenty seven sub-criteria were determined. The results of this approach showed that during the times of a collapsed market the most preferred type of overcapacity absorbing method is to lay-up vessels, followed by adopting slow-steaming and thirdly, scrapping. Newbuilding contract cancellation/postponement and service suspension were found to have the least effect.

Optimal Slow Steaming Speed for Container Ships under the EU Emission Trading System

Slow steaming is an operational measure in ocean-going vessels sailing at slow speeds. It can help climate mitigation efforts by cutting down marine fuel consumption and consequently reducing CO2 and other Greenhouse Gas Emissions (GHG). Due to climate change both the European Union (EU) and the International Maritime Organization (IMO) are analysing the inclusion of international shipping in the EU Emissions Trading System (ETS) in the near future or alternatively implementing a carbon tax. The paper proposes a methodology to decide the optimal speed of a vessel taking into account its characteristics and the factors that determine its economic results. The calculated cash flow can be used in valuation models. The methodology is applied for a case study for any container ship in a range from 2000 to 20,000 Twenty-foot Equivalent Units (TEU) on a leg of a round trip from Shanghai to Rotterdam. We calculate how speed reduction, CO2 emissions and ship owner’s earnings per year may vary between a business-as-usual scenario and a scenario in which shipping is included in the ETS. The analysis reveals that the optimal speed varies with the size of the vessel and depends on several variables such as marine fuel prices, cargo freight rates and other voyage costs. Results show that the highest optimal speed is in the range of 5500–13,000 TEUs whether or not the ETS is applied. As the number of TEUs transported in a vessel increases emissions per TEU decrease. In an established freight rate market, the optimal speed fluctuates by 1.8 knots. Finally, the medium- and long-term expectations for slow steaming are analysed based on future market prices.

Crises and Their Effects on Freight Transport Modes: A Literature Review and Research Framework

Learning from the effects of past crises allows the transport sector to handle future crises effectively and proactively. The goal of this paper is to identify and classify types of crises that have hit Europe in the previous 20 years and to identify the effects of these crises on the freight transport modes. Moreover, further research on each transport mode is derived. To reach this goal, we conducted a systematic literature review by using five well-known databases, which resulted in 296 search results, of which 29 references were relevant. We identified four crises that hit the freight transport modes in the previous 20 years in Europe: the 2008 financial crisis, the 2015 migration crisis, the 2020 COVID-19 crisis, and the ongoing climate crisis. However, the effects of the different crises on the transport modes can be both positive (e.g., the introduction of a new maritime slow-steaming service) or negative (e.g., a reduction in safety). The insights, gaps, and future research directions identified will encourage researchers, as well as practitioners, to learn from previous crises and be prepared for proactive actions during future crises, thus contributing to more reliable and sustainable transportation systems.

Smart Steaming: A New Flexible Paradigm for Synchromodal Logistics

Slow steaming, i.e., the possibility to ship vessels at a significantly slower speed than their nominal one, has been widely studied and implemented to improve the sustainability of long-haul supply chains. However, to create an efficient symbiosis with the paradigm of synchromodality, an evolution of slow steaming called smart steaming is introduced. Smart steaming is about defining a medium speed execution of shipping movements and the real-time adjustment (acceleration and deceleration) of traveling speeds to pursue the entire logistic system’s overall efficiency and sustainability. For instance, congestion in handling facilities (intermodal hubs, ports, and rail stations) is often caused by the common wish to arrive as soon as possible. Therefore, smart steaming would help avoid bottlenecks, allowing better synchronization and decreasing waiting time at ports or handling facilities. This work aims to discuss the strict relationships between smart steaming and synchromodality and show the potential impact of moving from slow steaming to smart steaming in terms of sustainability and efficiency. Moreover, we will propose an analysis considering the pros, cons, opportunities, and risks of managing operations under this new policy.

Real time Energy Efficiency Operational Indicator: Simulation research from the perspective of life cycle assessment

CO2 emissions during ship building, maintenance, and scrapping are not be involved when defining Energy Efficiency Operational Indicator (EEOI). However, these CO2 emissions can only show its value during operation phase of ship life. In order to evaluate the effect of CO2 emissions during ship building, maintenance, and scrapping on energy efficiency, a real time EEOI definition was put forward, a life cycle assessment (LCA) calculation framework was established, and a ship propulsion model with main diesel engine was built. A bulker carrier YUMING was taken as the case ship. CO2 emissions during ship building, maintenance, and scrapping were calculated. Main engine revolution and real time EEOI value with other parameters were obtained by simulating in different ship draft. The results show that life cycle assessment result will explicitly increase the real time EEOI value especially in lower engine speed and lower ship draft. The engine revolution at the lowest EEOI value will increase explicitly by life cycle assessment result. It means that the lower limit of ship speed should increase during slow steaming. Therefore, slow steaming may bring less environmental benefit if the life cycle assessment result is involved.

An Application of Fuzzy Analytic Hierarchy Process to Overcapacity Absorbing Methods in Container Shipping

The market in container shipping has been characterised as highly cyclical. In a depressed stage of the cycle, with a sharp decrease in demand, the gap between supply and demand widens significantly leading to a deepening overcapacity in the sector. In order to reduce overcapacity in the container shipping sector specific actions have been undertaken by such shipping operators. This paper describes a study which modelled certain selection criteria applied to overcapacity absorbing methods for containership companies. The relative ranking of each criterion was determined through a fuzzy- AHP method. In order to conduct the method, five main and twenty seven sub-criteria were determined. The results of this approach showed that during the times of a collapsed market the most preferred type of overcapacity absorbing method is to lay-up vessels, followed by adopting slow-steaming and thirdly, scrapping. Newbuilding contract cancellation/postponement and service suspension were found to have the least effect.