• Journal of Distribution Science
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• v.15 no.11
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• pp.59-72
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• 2017

Purpose - This paper evaluated the efficiency performance of the three major maritime transport markets and examined the determinants of the performance. The firms' revenue fluctuates with the changes of the economic cycle; hence it is important for them to set up business strategies to improve efficiencies. A lack of efficiency measurements for shipping firms leads to a significant gap in determining their overall performance. Research design, data, and methodology - Each of DEA scores was adopted for the evaluation and panel regression was used to examine the impact of determinants on the performance. The analysis included 50 shipping firms from three maritime transport markets as follows; 15 firms of container liners, 18 firms of bulk carrier and 17 firms of tanker carriers, and its period was from 2010 to 2016. Results - In the CCR model, container liners were the highest, tanker carriers were the second, and bulk carriers were the lowest in operation efficiency and financial efficiency. By region, operation efficiency and financial efficiency was high in the order of America, Asia, and Europe. Conclusions - This study suggests business strategies for maritime transport companies based on the analytical results of determinants of operational and financial efficiency.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.497-508
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• 2019

Purpose: The purpose of this study is to overcome limitations of conventional studies that to predict Baltic Dry Index (BDI). The study proposed applications of Artificial Neural Network (ANN) named Long Short-Term Memory (LSTM) to predict BDI. Methods: The BDI time-series prediction was carried out through eight variables related to the dry bulk market. The prediction was conducted in two steps. First, identifying the goodness of fitness for the BDI time-series of specific ANN models and determining the network structures to be used in the next step. While using ANN's generalization capability, the structures determined in the previous steps were used in the empirical prediction step, and the sliding-window method was applied to make a daily (one-day ahead) prediction. Results: At the empirical prediction step, it was possible to predict variable y(BDI time series) at point of time t by 8 variables (related to the dry bulk market) of x at point of time (t-1). LSTM, known to be good at learning over a long period of time, showed the best performance with higher predictive accuracy compared to Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN). Conclusion: Applying this study to real business would require long-term predictions by applying more detailed forecasting techniques. I hope that the research can provide a point of reference in the dry bulk market, and furthermore in the decision-making and investment in the future of the shipping business as a whole.

• Journal of Navigation and Port Research
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• v.41 no.1
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• pp.25-32
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• 2017

The purpose of this investigation is to analyze the synchronization between the representative global freight index, the Baltic Dry bulk Index (BDI) and the China Container Freight Index (CCFI) with monthly data from 2000 to 2016. Using the non-stationarity of the business cycle that is able to include common trends, we employ the Engle-Granger 2 stage co-integration test and found no synchronization. On the contrary, we additionally estimated the causality between the markets and revealed the causality, which implies that the Chinese economy has a significant effect on the global market. The results of this empirical analysis demonstrate that the CCFI of China is appropriate for analyzing the shipping industry. In practice, this means that it is more appropriate to include CCFI in the global market outlook than use it as a substitute for the global freight rate index, the BDI. This is a case study of the synchronization of the economic fluctuations of the shipping industry. It suggests that the economic fluctuations of China need to be considered in the unstable global market forecast. In particular, this case applies to the fluctuations in the shipping industry synchronism and provides important results in scientific terms.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.441-448
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• 2022

The aim of this study was to examine determinants of secondhand Bulk carrier and Oil tanker prices. This study compiled S& P transaction data taken from the Clarksons Research during J anuary 2018 to April 2022 to see how independent variables influenced secondhand ship prices. In the secondhand ship pricing model of entire segments, size, age, and LIBOR showed significant effects on prices. A vessel built in J apan and Korea was traded at a higher price than a vessel built in other countries. In the bulk segment, size, age, Clarksea index, LIBOR, and inflation were meaningful variables. In the Tanker segment, unlike Bulk carrier, only size and age were useful variables. This study performed regression analyses for various sizes of Bulk carriers and Oil tankers. It verified that impacts of variables other than ship size and age were significantly associated with ship type and size while macroeconomic variables had no influence except for bulk carriers. By applying diverse variables affecting secondhand ship price estimation according to various sizes of Bulk carriers and Oil tankers, this study will expand the scope of practical application for investors. It also reaffirms prior research findings that the secondhand ship market is primarily market-driven.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.33-51
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• 1998

The industrial operation is one of the three basic modes of shipping operation with liner and Tramp operations. Industrial operators usually control vessels of their own or on a time charter to minimize the cost of shipping their cargoes. Such operations abound in shipping of bulk commodities, such as oil, chemicals and ores. This work is concerned with an operational optimization analysis of the fleet owned by a major oil company. a typical industrial operator. The operational optimization problem of the fleet of a major oil company is divided Into two phase problem. The front end corresponds to the optimization problem of the transportation of crude oil. product mix. and the distribution of product oil to comply with the demand of the market. The back end tackles the scheduling optimization problem of the fleet to meet the seaborne transportation demand derived from the front end. A case study reflecting the practices of an international major oil company is demonstrated to make clear the underlying ideas.

• The Journal of shipping and logistics
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• v.34 no.4
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• pp.615-635
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• 2018

Using data from 2008 to 2017, this study analyzed the financial characteristics of offshore freight shipping companies in Korea, categorized by vessel type, and their impact on business performance. The analysis showed an upward trend in the overall debt ratio of offshore freight transport companies and differences in the financial characteristics of each vessel type as well as the major factors affecting business performance. In particular, the significant factors affecting the ROA performance of the business are the size of business and debt ratio in the LPG line; the growth rate in the bulk line; the size of business, debt ratio, and year in the general freight line; and the size of business, growth rate, entertainment expense rate, debt ratio, and year in the full container line. Therefore, each shipping company needs to recognize differences in key financial factors affecting its performance based on vessel type, implement proactive measures, and diversify its vessel portfolio.

• Journal of the Korean Institute of Navigation
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• v.7 no.2
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• pp.65-113
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• 1983

A lot of studies of ship's economy are on the traditional fields such asreducing propulsion resistance, raising cargo handling rates and lessening building consts, but there are few researches on the merchant ship's economy concerning their deadweights and speeds according to shipping companies managerial cercumstances. Contrary to the contemporary trend that "the bigger, the better, if the cargo handling rate could increased sufficiently to hold down port time to that rate of smmaler vessels", this paper demonstrates the existence of certain limits in ship's size and speed according to the coditions of the freight rates, voyage distances, cargo handing rates, prices of fuel oil, interst rates etc. Fom the curves of criteria contour for various ship's deadweights and speeds which are depicted from the gird search method, one can get the costs and the yearly profit rates under the conditiions of large volume with long term contracts for the transportation of bulk cargoes. In estimating ship's transportation economy, the auther takes the position that the profit rate method is properer than the cost method, and introduces the calculation table of the voyage profit rate index. The use of the criteria contours will be of help to ship owners in determining the size and speed of the ship which will be built or purchased and serve in a certain trade route.

• Korea Trade Review
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• v.44 no.2
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• pp.127-141
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• 2019

In this study, the relationship between Baltic Dry Index(BDI) and maritime trade volume in the dry cargo market was verified using the vector autoregressive (VAR) model. Data was analyzed from 1992 to 2018 for iron ore, steam coal, coking coal, grain, and minor bulks of maritime trade volume and BDI. Granger causality analysis showed that the BDI affects the trade volume of coking coal and minor bulks but the trade volume of iron ore, steam coal and grain do not correlate with the BDI freight index. Impulse response analysis showed that the shock of BDI had the greatest impact on coking coal at the two years lag and the impact was negligible at the ten years lag. In addition, the shock of BDI on minor cargoes was strongest at the three years lag, and were negligible at the ten years lag. This study examined the relationship between maritime trade volume and BDI in the dry bulk shipping market in which uncertainty is high. As a result of this study, there is an economic aspect of sustainability that has helped the risk management of shipping companies. In addition, it is significant from an academic point of view that the long-term relationship between the two time series was analyzed through the causality test between variables. However, it is necessary to develop a forecasting model that will help decision makers in maritime markets using more sophisticated methods such as the Bayesian VAR model.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.289-296
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• 2022

The purpose of this study was to investigate the inter-correlation between crude oil prices and Dry Bulk Freight rates. Eco-friendly shipping fuels has being actively developed to reduce carbon emission. However, carbon neutrality will take longer than anticipated in terms of the present development process. Because of OVID-19 and the Russian invasion of Ukraine, crude oil price fluctuation has been exacerbated. So we must examine the impact on Dry Bulk Freight rates the oil prices have had, because oil prices play a major role in shipping fuels. By using the VAR (Vector Autoregressive) model with monthly data of crude oil prices (Brent, Dubai and WTI) and Dry Bulk Freight rates (BDI, BCI and (BP I) 2008.10~2022.02, the empirical analysis documents that the oil prices have an impact on Dry bulk Freight rates. From the analysis of the forecast error variance decomposition, WTI has the largest explanatory relationship with the BDI and Dubai ranks seoond, Brent ranks third. In conclusion, WTI and Dubai have the largest impact on the BDI, while there are some differences according to the ship-type.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.297-311
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• 2011

This paper deals with a strategic investment decision model for improving investment profit in shipping industry. Despite the quantitative expansion of Korean shipping business, many shipping firms have suffered financial difficulties due to financial and operating risks that result from the characteristics of capital-intensive business as well as of volatility of shipping markets. As a result, managers in charge of making an investment decision, particularly in tramper business sector, are required to take both financial and operating risk factors into consideration. Put it differently, managers are strongly recommended to avoid these risks by ship asset play; buy-low and sell-high, which results in considerable capital gain and cost reduction. In addition, managers in shipping industry are also recommended to consider the ship chartering investment alternative when the freight markets show extreme volatility as the case of 2008 triggered by sub-prime mortgage financial crisis in USA. For example, the BDI suffered plunging down from 1000 in 2008 to 100 in 2010. Consequently, the 4th largest shipping company in Korea, DAEHAN Shipping Co., has collapsed primarily due to excessive tonnage expansion during the peak time of bulk market. In sum, the strategic investment decision model, suggested in this paper, is designed to include such factors as capital gain by asset play, timely chartering for alternative shipping service, and optimization of operating profit by tonnage adjustment in accordance with change in the shipping markets concerned.