Bunker Prices Research Articles

How should mode competitiveness and profit be balanced in maritime transport? – Vessel speed optimization approach including Northern Sea Route

ABSTRACT Transport between East Asia and Europe heavily relies on maritime transport via the Suez Canal route (SCR), with the Northern Sea Route (NSR) through the Arctic Sea emerging as a new route due to the continuously melting polar ice. However, the dominance of maritime transport faces a threat from railways and airlines, especially for high-sensitivity commodities. This study mainly maximizes the profit of a shipping company from both NSR and SCR services with vessel speed optimization, focusing on the competition between four alternatives quantified by a logit model. The sensitivity analysis is also conducted with expanding ice-classed vessels and fluctuating bunker prices. Our findings show that maintaining a speed of approximately 20kn can capture an additional 10% of the market share for SCR; however, SCR faces challenges if future advancements enable more frequent and cost-effective railway transport. Moreover, besides expanding ice-classed vessel size, tackling the problem of limited capacity may position NSR as a promising competitor. This study contributes to providing an effective and innovative speed-optimization scheme combining economic viabilities and mode choice. It is aimed to (1) provide feasible political insights regarding mode competitions and (2) promote the commercial economic use of various modes, including NSR.

Capesize time charter equivalent optimization based on speed and environmental regulations

PurposeThis paper aims to identify the interplay of standard Capesize optimal speeds for time charter equivalent (TCE) maximization in the Australia–China iron ore route and the optimal speeds as an operational tool for compliance with the International Maritime Organization (IMO) carbon intensity indicator (CII).Design/methodology/approachThe TCE at different speeds have been calculated for four standard Capesize specifications: (1) standard Capesize with ecoelectronic engine; (2) standard Capesize with non-eco engine (3) standard Capesize vessel with an eco-electronic engine fitted with scrubber and (4) standard Capesize with non-eco engine and no scrubber fitted.FindingsCalculations imply that in a highly inflationary bunker price context, the dollar per ton freight rates equilibrates at levels that may push optimal speeds below the speeds required for minimum CII compliance (C Rating) in the Australia–China trade. The highest deviation of optimal speeds from those required for minimum CII compliance is observed for non-eco standard Capesize vessels without scrubbers. Increased non-eco Capesize deployment would see optimal speeds structurally lower at levels that could offer CII ratings improvements.Originality/valueWhile most of the studies have covered the use of speed as a tool to improve efficiency and emissions in the maritime sector, few have been identified in the literature to have examined the interplay between the commercial and operational performance in the dry bulk sector stemming from the freight market equilibrium. The originality of this paper lies in examining the above relation and the resulting optimal speed selection in the Capesize sector against mandatory environmental targets.

Hedging Strategies in Carbon Emission Price Dynamics: Implications for Shipping Markets

The European Union (EU) has agreed to gradually include shipping in the EU emissions trading scheme (EU ETS), which makes shipping companies vulnerable to carbon price fluctuations. The aim of this paper is to investigate the effectiveness of carbon and petroleum futures contracts in managing carbon and bunker risks. We examine the effectiveness of alternative hedging methods, including both static and dynamic approaches, to estimate optimal hedge ratios under single and composite cross-hedge settings. Our results show that carbon future contracts are important for hedging the carbon emission allowances price risk, and Brent oil futures are the most effective instrument for out-of-sample hedging of bunker prices. In addition, the hedging effectiveness indicates that conventional methods outperform the sophisticated models in terms of variance reduction. Our study offers new insights into how the carbon and bunker markets relate to a combination hedging in reducing the joint price risk, which can be used to promote risk management in the market.

Selection of CO2 Emission Reduction Measures Affecting the Maximum Annual Income of a Container Ship

China’s carbon peaking and carbon neutrality targets have created huge challenges for all the economic sectors in China, including the shipping industry. Various emission reduction measures, such as Waste Heat Recovery Systems (WHRSs), Drag Reduction Coatings (DRCs), and Slow Steaming (SS), are the main options for container ship companies to select in advance. This paper aims to find the optimal combination of measures for container ship companies to reach the carbon reduction targets, which are mainly set according to the carbon reduction requirements of the International Maritime Organization (IMO). A 0–1 integer programming model is proposed under the Maritime Emissions Trading Scheme (METS) to help container ship companies select the optimal combination of measures in the context of carbon peaking and carbon neutrality. Our results show that combination 6 (using a WHRS alone and a 5.0% reduction in the original speed) is the most suitable solution with the selected values of parameters. Sensitivity analyses of the parameters are performed, such as bunker price, the auction and purchase prices of carbon and incentive levels. From the sensitivity analysis, it is found that using a WHRS is the optimal combination of abatement measures within the fluctuation range of the parameters. At the same time, according to the results, container ship companies could choose the most appropriate and profitable strategy in the dual-carbon context. Therefore, container ship companies and policymakers have access to relevant carbon reduction suggestions to encourage the implementation of carbon reduction initiatives.

Performance Analysis: Using the Northern Sea Route as an Alternative to Traditional Routes

The grounding accident of M/V EVER GIVEN in the Suez Canal causes a catastrophic loss on shipping companies. Alternatively, previous studies have presented encouraging findings of the remarkable benefits of time and cost saving in the Northern sea route (NSR) due to extend the ice-free time and shorten the distance. Ships using the NSR could shorten as much as 40% of the sailing distance from China (Shanghai) to Europe (Rotterdam) compared with the traditional route via the Suez Canal. This paper investigates the economic potential of using the NSR as a cost-effective route in comparison with Suez Canal Route (SCR) between China and Europe. To achieve this target, the study evaluates the net profit for the SCR fleet and NSR fleet by involving the factors, e.g., bunker price, ice condition and ship loading rate, etc. The case-study results show that the NSR fleet is not profitable compared to the SCR, due to the limited cargo transport capability and ice restriction. Only if the loading rate for SCR fleet is lower than some threshold value or the bunker price is high enough, the NSR turns to be profitable.

Forecasting Liquefied Natural Gas Bunker Prices Using Artificial Neural Network for Procurement Management

The LNG price is basically determined based on the oil price, but other than that, it is also determined by the influence of the method of LNG transportation; storage; processes; and political, economic, and geographical instability. Liquefied natural gas (LNG) may not reflect its market value if the destination of the purchase is restricted or the purchase contract includes a take-or-pay clause. Furthermore, it is difficult for the buyer to flexibly manage procurement, resulting in the decoupling of oil and natural gas prices. Therefore, as the LNG bunker price is expected to be more volatile than the marine bunker price in the future, shipping companies need to prepare countermeasures based on scientific forecasting techniques. This study aims to be the first to analyze the forecasting of short-term LNG bunker prices using recurrent neural network (RNN) models suitable for highly volatile data such as time series. Predictive analysis was performed using simple RNN, long short-term memory (LSTM), and gated recurrent unit (GRU) models, which effectively forecast time-series data, and the prediction performance of LSTM among the three models was excellent. LSTM had relatively excellent prediction performance of outliers and beyond. In addition, it was possible to effectively manage ship operating costs with improved forecasting in practice. Furthermore, this study contributes to establishing a systematic strategy for supervisors in global shipping companies, port authorities, and LNG bunkering companies.

선박의 운영형태가 해운기업의 현금흐름 변동성에 미치는 영향 분석

Purpose - There are two different vessel employment types in shipping: providing cargo transport services and letting vessels out to other shipping companies. The former is typically in the form of voyage charters or contract of affreightments, and the latter, time charters or trip time charters. This paper analyzes the effect of vessel employment types on the cash flow volatility (CFV) of shipping companies.
 Design/Methodology/Approach - A historical simulation was performed to measure the relationship between transport voyage ratio (TVR, as a proxy of vessel employment type) and realized CFV. The CFV without (Case 1) and with (Case 2) the variation of freight and bunker prices was captured by simulation, and then the relationship was identified by regression analysis. Time series data from Clarkson Research was used to simulate revenues and costs.
 Findings - The results show that the TVR of shipping companies is closely related to the CFV. The TVR reveals a strong positive relation with the CFV both in Case 1 and Case 2, where other determinants, i.e. hire and bunker prices, are included.
 Research Implications - The relationship between vessel employment types and CFV has been neglected in shipping research. This is a novel attempt to analyze the effect of TVR on the CFV of shipping companies. The forecast of CFV is crucial because it is closely related to the financial stability of shipping companies. This research has a practical meaning in enhancing the visibility of corporate CFV in addition to academic contribution in uncovering an additional determinant of CFV.

Did COVID-19 Affect the Financial Performance and Risk of International Shipping Companies?

This study focuses on the shipping sector and examines how it has been affected by the COVID-19 pandemic. More specifically, the paper examines the extent to which stock price returns, corporate systematic risk, and key financial performance variables were affected, as well as how all these variables correlated with the spread of COVID-19. Moreover, the paper examines the correlation of these variables with key shipping indexes, such as the Baltic Dry Index and Baltic International Tanker Route, and bunker prices, and how this correlation changed. Our sample consists of shipping companies listed on US stock exchanges, and the study period is 2015–2021. The findings reveal that the shipping companies’ level of systematic risk increased after the pandemic. In addition, the beta coefficient of shipping companies is more affected by changes in bunker prices since the pandemic, and the average daily returns and bunker prices have a lower correlation after the pandemic.

How Does Oil Future Price Imply Bunker Price—Cointegration and Prediction Analysis

This paper investigates how oil’s future price implies the bunker price through cointegration analysis first. A cointegration test confirms the long-run equilibrium condition of bunker and oil future prices. Based on the cointegration relationship, we construct VECM model to forecast bunker prices. In addition, we also consider ARMA, ARMAX, and VAR models for certifying whether considering the long-run equilibrium between bunker and oil future prices is helpful in prediction. One-step-ahead and four-step-ahead forecasting are considered and two out-of-sample datasets are used. The empirical results show that the increase in the value of the error correction term in the VECM model has the effect of pulling down the bunker return. VECM performs better than other models in prediction. The Crude Oil Future Contract 1 has better forecasting performance for bunker prices with VECM in the 1-step-ahead forecast, while Crude Oil Future Contract 3 performs slightly better than Crude Oil Future Contract 1 in the 4-step-ahead forecast.

Assessing the impact of sulfur cap on bunkering spot selection in the ARA region

The introduction of IMO2020, the outbreak of COVID-19, and the oil price drop in 2020 had a significant impact on operators’ operating profits. Therefore, a competitive analysis of bunkering spots that suggests the optimal location for bunkering is of interest. This paper uses a combination of primary and secondary research, both from operators’ and suppliers’ side, to identify the key performance factors (KPFs) affecting the decision-making process of a bunkering port selection process. Answers were then combined by using a fuzzy TOPSIS analytical approach to quantify the competitive position of each port in the Amsterdam-Rotterdam-Antwerp (ARA) region. Results suggest that availability of low sulfur bunkers, bunker quality, bunker price, reliability, punctuality, and safety of bunkering services, as well as usage and availability of barges are the key KPFs in order of importance. Sulfur cap has not changed the competitive environment in the region as the geographic advantage of the port of Rotterdam plays a crucial role in the comparison with the other ports, in contrast to expressed concerns in the industry.

"The Effect of Bunker Prices on the Volatility Structure of Time Charter Market in Maritime Transport" International Conference on Finance, Bank & Economics (ICFBE-22), Madrid

"The Effect of Bunker Prices on the Volatility Structure of Time Charter Market in Maritime Transport" International Conference on Finance, Bank & Economics (ICFBE-22), Madrid

Modeling and Analyzing the Average Fleet Speed of Major Commercial Ship Types

In this study, the average speeds of container, dry bulk and crude oil fleets, which are the main market types in maritime transportation, are estimated and analyzed by using external factors such as freight rate, bunker price, fleet size and interest rate. Freight and interest rates affect the average speeds positively, while bunker price and fleet size negatively affect in accordance with the theoretical justifications. The freight rate mostly affects the average speed of the container fleet, while bunker price, fleet size and interest rate mostly affect the average speed of the crude oil fleet; the average speed of the dry bulk fleet is least affected by the fuel price and fleet size; and the average speed of the container fleet is least affected by the interest rate. In general, when the coefficient sizes between the factors are considered, the most effective factor in average speeds of the three market is their fleet size. Thus, new dimensions have been added to the empirical literature stuck in the framework of freight rate and bunker price.

Data analytics for fuel consumption management in maritime transportation: Status and perspectives

The shipping industry is associated with approximately three quarters of all world trade. In recent years, the sustainability of shipping has become a public concern, and various emissions control regulations to reduce pollutants and greenhouse gas (GHG) emissions from ships have been proposed and implemented globally. These regulations aim to drive the shipping industry in a low-carbon and low-pollutant direction by motivating it to switch to more efficient fuel types and reduce energy consumption. At the same time, the cyclical downturn of the world economy and high bunker prices make it necessary and urgent for the shipping industry to operate in a more cost-effective way while still satisfying global trade demand. As bunker fuel bunker (e.g., heavy fuel oil [HFO], liquified natural gas [LNG]) consumption is the main source of emissions and bunker fuel costs account for a large proportion of operating costs, shipping companies are making unprecedented efforts to optimize ship energy efficiency. It is widely accepted that the key to improving the energy efficiency of ships is the development of accurate models to predict ship fuel consumption rates under different scenarios. In this study, ship fuel consumption prediction models presented in the literature (including the academic literature and technical reports as a typical type of “grey literature”) are reviewed and compared, and models that optimize ship operations based on fuel consumption prediction results are also presented and discussed. Current research challenges and promising research questions on ship performance monitoring and operational optimization are identified.

Carbon pricing of international transport fuels: Impacts on carbon emissions and trade activity

We study the impacts of carbon taxation of international transport fuels on CO2 emissions and trade activity, focusing on maritime transport, which constitutes the most important international trade transport activity. Our estimated bunker price elasticities range from −0.03 to −0.42. For the current level of international trade, a global tax of US$ 40 per ton of CO2 will reduce CO2 emissions by 7.65% for the heaviest traded products (at the 6-digit HS level of aggregation) transported by sea. The greatest CO2 emission reductions are for products with relatively low value-to-weight ratios such as fossil fuels and ores. Using our estimates, we present a plan with a gradual increase in the carbon tax, including some transition to zero emissions vessels, for reaching the emissions target of the International Maritime Organization by 2050. We compare the reduction in CO2 emissions with a carbon tax policy with CO2 reductions with a feebate policy.

The optimal icebreaking tariffs and the economic performance of tramp shipping on the Northern Sea Route

In comparing the costs between the Northern Sea Route (NSR) and the Suez Canal Route (SCR), the NSR icebreaking tariffs are critical. A balance question of pricing rises: to cut the tariffs to attract more ship operators to use the NSR, or to increase the tariffs to cover the cost of the icebreaker fleet? However, currently active NSR icebreaking tariffs are in ceiling level, and the practical icebreaking fee is often negotiated and lacks transparency. This study explores the optimal NSR icebreaking tariff level from the price maker side for the transit tramp shipping on the NSR. The interlock of the exchange rate of Russian ruble per US dollar and the bunker price is also considered. By establishing a framework with four components and applying real data to implement the empirical study, we find that the optimal NSR icebreaking tariff level is 15% higher than the current ceiling level. At the optimal tariff level, the NSR can save 4.5–12.4% of the annual shipping cost from the SCR, whereas in a single voyage can save as high as 49.4%.

Exploring the factors influencing the cost-effective design of hub-and-spoke and point-to-point networks in maritime transport using a bi-level optimization model

Hub-and-spoke (HS) networks are cost-effective because they allow the realization of economies of density. However, the cost of point-to-point (PP) networks may be lower than that of HS networks when certain conditions, such as cargo demand, bunker price, vessel size, and the shippers’ value of time change. This study explores the factors that influence the cost-effectiveness of HS and PP networks. We developed a mixed-integer programming model that allows for bi-level optimization between shipping lines and shippers. As a case study, we applied it to Chinese and Japanese ports, with both HS and PP networks. We found that high cargo demand increases the use of PP networks while enlarging vessel size increases the use of HS networks. These findings enable us to predict the occurrence of hubbing—shifting from a PP to an HS network—and de-hubbing—shifting from an HS to a PP network.

Simultaneous Optimization of the Liner Shipping Route and Ship Schedule Designs with Time Windows

This paper proposes to address the problem of the simultaneous optimization of the liner shipping route and ship schedule designs by incorporating port time windows. A mathematical programming model was developed to minimize the carrier’s total operating cost by simultaneously optimizing the port call sequence, ship arrival time per port of call, and sailing speed per shipping leg under port time window constraints. In view of its structure, the nonlinear nonconvex optimization model is further transformed into a mixed-integer linear programming model that can be efficiently solved by extant solvers to provide a global optimal solution. The results of the numerical experiments performed using a real-world case study indicated that the proposed model performs significantly better than the models that handle the design problems separately. The results also showed that different time windows will affect the optimal port call sequence. Moreover, port time windows, bunker price, and port efficiency all affect the total operating cost of the designed shipping route.

Joint Optimization of Ship Sailing Speed and Container Handling Rate for a Near-sea Liner Service Route

This paper jointly designs the optimal ship sailing speeds on shipping legs and the optimal handling rates at ports of a near-sea liner service route operated by a container liner shipping company. A mixed integer linear programming model is developed, which can be solved directly by the commercial solvers to give a global optimal solution. The model is further applied to a real-life case. Results demonstrate that both bunker price and unit inventory cost affect the optimal ship sailing speed and the optimal container handling rate.

Cold chain shipping mode choice with environmental and financial perspectives

Mode choice between reefer bulk and container in seaborne cold chains for time sensitive products is a practical problem, in which limited studies are available to guide decision makers. This study thoroughly investigates the cold chain mode choice problem by selecting shipping mode (containerized transport and bulk transport) for each shipment and determining shipment quantities and ship deployment in a multi-period planning environment with independent perishable product demands. Value-Based Management as a novel method in shipping is adopted to consider both economic and environmental objectives from operational and financial aspects. The value-based mode selection models also determine the sailing speed of the heterogeneous chartered reefer bulk fleet under different chartering terms. Furthermore, the paper evaluates greenhouse gas emissions from the cold chain shipping. Findings from a numerical example show that optimal ship speed decreases with a reducing rate when the bunker price increases and with a higher decline rate when goods are less perishable.

Sailing Speed and Fleet Deployment Optimization for Intercontinental Container Liner Shipping Considering Cargo Time Value

Abstract This article collectively addresses the issues of optimizing the sailing speed of containerships and fleet deployment in intercontinental container liner shipping, taking cargo time values into consideration. A mixed-integer nonlinear programming model is developed to maximize the gross profits of a container shipping line. The sailing speed is divided into 0.1 knot intervals and a reciprocal-discretization method is proposed to transform the model into an integer-based linear programming model, which can be solved using optimization solvers such as CPLEX. A case study is conducted based on the Far East-West America liner route of a global container shipping line to assess the effectiveness of the proposed model and the reciprocal-discretization method. The results show that when the cargo time value is taken into consideration, the increased sailing speed of containerships on long legs and the decreased number of deployed containerships will generate greater operating profits for the container shipping line. The rise in bunker price will lead to a stepwise decline in sailing speed of containerships and a stepwise growth in the number of deployed containerships. Moreover, the downward trend of sailing speed due to the increase of bunker price will be somewhat delayed as the unit container cargo value increases. Several useful insights are drawn from analysis of the results.