• Journal of Digital Convergence
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• v.14 no.7
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• pp.145-154
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• 2016

The purpose of this study was to carry out comparative analysis on the world major liner shipping companies' ship investment strategy using Fuzzy-AHP model. In this study, the ship investment factors were firstly selected by literature review and finally adopted them by in-depth interview with experts who had working experiences over 15 years in the field of shipping business. As suggested in the previous research, the liner shipping companies have been classified into four types such as 'ship investment irrelevant to market trend'(Type1), 'ship investment before market rise'(Type2), 'market decline after participation in excessive orders'(Type3), 'avoidance of ship investment during market rise'(Type4) and the comparative analysis were conducted among four ship investment types. According to the results of analysis, ship investment priority in Type1 was freight rates(0.132), price of used ship(0.121) and fleet(0.103). The priority in Type2 was freight rates(0.134), need for ship owner(0.113) and public funding(0.109). Type3 put its priority in freight rates(0.173), fleet(0.169) and the changes in international circumstances(0.121). Type4 considered freight rates(0.239), fleet(0.232) and oil price(0.150) as its priority.

• Journal of Korea Port Economic Association
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• v.35 no.3
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• pp.61-72
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• 2019

In order to enhance the competitiveness of the container shipping industry and promote its development, based on the empirical analyses using multivariate time series models, this study aims to suggest a few strategies related to the dynamics of the container shipping market. It uses the vector autoregressive (VAR) and vector error correction (VEC) models as analytical methodologies. Additionally, it uses the annual trade volumes, fleets, and freight rates as the dataset. According to the empirical results, we can infer that the most exogenous variable, the trade volume, exerted the highest influence on the total dynamics of the container shipping market. Based on these empirical results, this study suggests some implications for ship investment, freight rate forecasting, and the strategies of shipping firms. Concerning ship investment, since the exogenous trade volume variable contributes most to the uncertainty of freight rates, corporate finance can be considered more appropriate for container ship investment than project finance. Concerning the freight rate forecasting, the VAR and VEC models use the past information and the cointegrating regression model assumes future information, and hence the former models are found better than the latter model. Finally, concerning the strategies of shipping firms, this study recommends the use of cycle-linked repayment scheme and services contract.

• The Journal of shipping and logistics
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• v.34 no.4
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• pp.545-563
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• 2018

This study analyzes the major factors affecting the freight rates of Very Large Crude-Oil Carriers (VLCC) using co-integration and vector error correction models (VECM). Particularly, we estimate the long-term equilibrium function that determines the VLCC freight rate by conducting difference conversion. In the VECM regression analysis, the error term converges toward long-term balance irrespective of whether the previous period's freight rate is bigger or smaller than the long-term equilibrium rate. Thus, even if the current rate is different from the long-term rate, it eventually converges to the long-term balance irrespective of a boom or recession. This study follows Ko and Ahn (2018), which analyzed the factors affecting the chemical carrier freight rate and was published in the Journal of Shipping and Logistics (Vol. 34, No. 2). It is expected that an academic comparison of the results of each study will be possible if further research is conducted on other vessel types, such as container ships and dry cargo vessels.

• 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 Navigation and Port Research
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• v.42 no.5
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• pp.365-370
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• 2018

Currently, container transport services play a substantial role in global cargo transportation, by serving as an intermodal between exporter and importer. Container shipping has become increasingly important over the past few decades, due to obvious advantages. However, Vietnam's container market has shown severely ongoing competition among numerous domestic and foreign shipping lines, resulting in serious consequences occurring such as freight rates substantially decreasing within the last 10 years. Vietnam's sea lanes have become more defensive, to cover losses of shipping companies. Selection of criteria for competitive evaluation of container transport companies is necessary, to facilitate addressing the problems within the enterprise, especially relating to its position in the market and from here, business management can implement strategic plans and reasonable policy, to survive and grow.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.166-166
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• 2017

Nowadays, container transport services play a substantial role in global cargo transportation by serving as an intermodal between the exporter and importer. Container shipping has become increasingly important over the past few decades due to its obvious advantages. However, Vietnam's container market has shown severely ongoing competition among numerous domestic and foreign shipping lines resulting in serious consequences occurring such as the freight rates substantially decreasing within the last ten years. In fact, Vietnam's sea lanes have become more defensive to cover the losses of shipping companies. Selection of criteria for competitive evaluation of container transport companies is necessary to help recognize the problems within the enterprise especially relating to its position in the market and from here, business management are able to put strategic plans in place and reasonable policy in order to be able to survive and grow.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.127-132
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• 2021

This paper applies a machine learning model to forecasting freight rates in dry bulk and tanker markets with wavelet decomposition and empirical mode decomposition because they can refect both information scattered in the time and frequency domain. The decomposition with wavelet is outperformed for the dry bulk market, and EMD is the more proper model in the tanker market. This result provides market players with a practical short-term forecasting method. This study contributes to expanding a variety of predictive methodologies for one of the highly volatile markets. Furthermore, the proposed model is expected to improve the quality of decision-making in spot freight trading, which is the most frequent transaction in the shipping industry.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.367-368
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• 2022

The shipping industry is sensitive to the global economy. Therefore, when events such as the global economic crisis occur, shipping market freight rates react immediately, and the long-term stagnation of the industry has been repeated accordingly. In particular, Hanjin Shipping's bankruptcy is an incident in which the nation has become aware of the chronic problems of the Korean shipping industry. The government is making great efforts to rebuild the collapsed shipping industry and become a global leader country. In order for the Korean shipping industry to grow into a global leader, it is important to appropriately respond to the crisis. To this end, it is necessary to establish and operate a crisis response system for the shipping industry at the national level.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• 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.