• Journal of Korea Port Economic Association
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• v.33 no.3
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• pp.53-68
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• 2017

The purpose of this study is to develop a new Korean container freight index by applying weights based on the global trade volume. To achieve this, it was decided to determine the conditions such as establishment of routes and regions, weighting of trade volumes which based on prior research and expert advice. Based on this, the individual index and regional index and composite index were calculated, and then reliability and statistical significance of the index was verified through correlation analysis and Granger causality analyses. This study suggest the following findings, through the development of the Korean container freight index. Firstly, Korean freight index reflects the overall market situation and can be used as a benchmark for determining the conditions of each market, consisting of criteria of region and routes. Secondly, it is possible to reflect the market conditions in which actual freight differences exist, since it has developed separate indexes for export and import routes. Finally, The composite index is the only index that reflects not only exports and imports but also 27 individual routes based on Busan, which is the most comprehensive indicator of the korean container freight market.

• 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.

• Proceedings of the Korea Port Economic Association Conference
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• 2006.08a
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• pp.159-179
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• 2006

As the current trend to the main index of the port competitiveness evaluation, the competitiveness index of the port service comes to more important than the part of expense, location and facility. To reform the bottleneck of port has an effect on improving port service competitiveness. Therefore, this study shows the importance of analyzing bottlenecks on logistics to improve port competitiveness. It collected recent questionnaire data which are the subject as the Custom Service, the Chamber of Commerce and Industry, the Trade Association about bottlenecks of port logistics for working out bottlenecks of domestic port logistics and it produced the order of priorities of bottlenecks by multiplying each output priorities and weights of each process in user of Incheon inner-outer port which is focused on container freight by analysis of priority and Analytic Hierarchy Process(AHP). Unlike existing studies, this study has important values. It presents the priority evaluation only focused on the container freight was produced by port users who are categorized into shipping company, terminal operation company and forwarder, car-ferry in Incheon inner-outer port and making a application of logistics process. It means internal and external competitiveness improvement plan can be presented more concretely and detailed than past competitiveness attributes such as location, facility, service and expense. If the analysis of port logistics bottlenecks which was focused on container freight is extended to the part of general cargo and sundries such as haul grain, car, scrap iron, those studies will be able to provide Incheon port users with useful information and a model of analyzing overall bottleneck of logistics in Incheon port.

• 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 Korea Port Economic Association
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• v.34 no.3
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• pp.133-158
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• 2018

The role and ratio of national vessels in the global container shipping market have reduced significantly due to the bankruptcy of Hanjin Shipping in early 2017. All import-export companies, as well as container ports in Korea, are facing a crisis. The Trump's tariff and trade battles have had a negative impact on the increase in the North American cargo. However, Chinese and Japanese container shipping companies, which merged with domestic container shipping companies, and mega carriers such as Maersk and CMA CGM have benefited from the decline in shipping supplies due to the collapse of Hanjin Shipping, the world's 10th largest container carrier in Korea. The import/export freight trade in Korea is witnessing the increasing stronghold of foreign carriers. This scenario is expected to weaken Korea's negotiation powers with overseas shipping companies in domestic ports, such as Busan and Kwangyang, thereby making it more challenging to attract shipping carriers. This study compares the global container-shipping network in 2007 and 2017 by combining the network topology of the social network analysis and the economics of the liner shipping connectivity index (LSCI) and the container port connectivity index (CPCI) analysis. The findings of this study are that the role of the ports across the world can be identified, and CPCI has a high correlation with the centrality index and freight volume data. These findings can contribute toward the utilization of the meaning of the necessary centrality index without an additional centrality analysis. This study can be applied not only to the call strategy of container carriers but also to the alliance and development strategy of Korean ports.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.547-553
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• 2022

This study analyzed the changes in the operational productivity of fourteen Korean container lines from 2019 to 2021 using MP I(Malmquist Productivity Index). The results indicated that the operational productivity of the shipping companies has increased by 38.4% annually, representing the TCI (Technical Change Index) increasing by 58.3% and the TECI (Technical Efficiency Change Index) decreasing by 12.6%. The increase in the operational productivity of the container shipping lines was mainly attributed to the high rise in ocean freight rates rather than an increase in fleet size or ship technical efficiency. However, the deep-sea shipping lines (i.e. HMM and SM lines) experienced increases in both the TCI and TECI, which was not the case for other shipping lines(i.e. Intra-Asian short-sea shipping lines). The intra-Asian short-sea shipping lines enhance their productivity due to the TCI but failed to appreciate the cost savings of the increased fleet effects due to the low SECI(Scale Efficiency Change Index) values.

• Journal of the Korean Society for Railway
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• v.15 no.3
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• pp.272-277
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• 2012

KORAIL's logistics business coefficient is improved slightly from 197.4 in 2009 to 190.7 in 2010 but the cost is still high compared to the revenues. In order to derive activities for the efficient logistics and measure their effects quantitatively, the analysis of various indexes that can be extracted from the statistical data is very important. In this study, the various indexes are analyzed to evaluate the efficiency of freight cars based on railway logistics. It can be used to estimate the various activities for the efficient logistics associated with freight cars. We suggest the Indexes as the number of transport, cumulative transport distance and transport income to evaluate the efficiency of freight cars and they should be applied according to the characteristics of each index.

• Journal of the Korean Society for Railway
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• v.16 no.2
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• pp.138-143
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• 2013

Recently, the demand for rail freight has gradually decreased. In particular, the demand in Korea for open freight cars, which classification includes gondola cars, hopper cars and gravel cars has been significantly reduced. The role of gondola cars in the rail transportation market shrank to 14.5% in 2010 from 23.3% in 2001. The transportation demand of gondola cars in the long term is expected to be reduced further. Because some gondola cars have been converted to container cars and various containers are being developed to transport bulk cargo by container cars. However, gondola cars still play an important role in rail freight transport. Therefore, the management planning of gondola cars is needed in order to prepare for the long-term declining demand. In this study, we propose a future direction for the management planning of gondola cars through the effectiveness analysis of gondola cars operation.