• Journal of Korea Port Economic Association
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• v.32 no.2
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• pp.25-37
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• 2016

The economy of South Korea has experienced two financial crises: the 1997 Asian financial crisis and the 2008 global financial crisis. These crises had a significant impact on the nation's macro-economic indicators. Furthermore, they had a profound influence on container traffic in container ports in Busan, which is the largest port in South Korea in terms of TEUs handled. However, the impact of the Asian financial crisis on container throughput is not clear. In this study, we assume that the two financial crises are independent and different, and then analyze how each of them impacted container throughput in Busan ports. To perform this analysis, we use an intervention model that is a special type of ARIMA model with input series. Intervention models can be used to model and forecast a response series and to analyze the impact of an intervention or event on the series. This study focuses on the latter case, and our results show that the impacts of the financial crises vary considerably.

• The Journal of Bigdata
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• v.8 no.2
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• pp.165-175
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• 2023

LNG is a representative imported cargo at Incheon Port and has a relatively high contribution to the increase/decrease in overall cargo volume at Incheon Port. In addition, in the view point of nationwide, LNG is the one of the most important key resource to supply the gas and generate electricity. Thus, it is very essential to identify the factors that have impact on the demand fluctuation and build the appropriate forecasting model, which present the basic information to make balance between supply and demand of LNG and establish the plan for power generation. In this study, different to previous research based on macroscopic annual data, the weekly demand of LNG is converted from the cargo volume unloaded by LNG carriers. We have identified the periodicity and correlations among internal and external factors of demand variability. We have identified the input factors for predicting the LNG demand such as seasonality of weekly cargo volume, the peak power demand, and the reserved capacity of power supply. In addition, in order to predict LNG demand, considering the characteristics of the data, time series prediction with weekly LNG cargo volume as a dependent variable and prediction through an artificial neural network model were made, the suitability of the predictions was verified, and the optimal model was established through error comparison between performance and estimates.

• Proceedings of the Korea Society for Simulation Conference
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• 1992.09a
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• pp.217-218
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• 1992

S사는 생산량 증대에 따른 물동량 증가에 대비하기 위하여 물류 시스템 개선안을 수립한 수 , 타다성을 검증하기 위해 시뮬레이션 기법을 채택하여 물류관점에서 현행 시스템 및 개선안에 대한 진단을 실시하였다. 컴퓨터 시뮬레이션 기법은 생산공정에 실질적인 물리적 변화를 가하지 않고도 "What-if" 라는 다양한 시나리오를 작성하고 이들에 대한 분석 및 평가를 통하여 그 가능성을 타진하며 최적안을 도출하는데 유용하게 이용되는 도구이다. 본 진단을 통하여 현행 시스템의 문제점을 정량적으로 파악하였다. 그리고, 물류 개선안에 대한 기대효과를 예측하고 발생가능한 문제점을 사전에 도출하여 시행착오를 최소화하는데 기여하고자 하였다.기여하고자 하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.263-269
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• 1998

The forecasting of container cargo volumes should be estimated correctly because it has a key roles on the establishment of port development planning, and the decision of port operating system. Container cargo volumes have a dynamic characteristics which was changed by effect of competitive ports. Accordingly forecasting was needed overall approach about competitive port's development, alternation and information. But, until now, traffic forecasting was not executed according to competitive situation, and that was accomplished at the point of unit port. Generally, considering the competition situation, simulation method was desirable at forecasting because system's scale was increased, and the influence power was intensified. In this paper, considering this situation, the objectives can be outlined as follows. 1) Structural model constructs by System dynamics method. 2) Structural simulation model develops according to modelling of competitive situation by expended SD method which included HEP(Hierarchical Fuzzy Process) And actually, effectiveness was verified according to proposed model to major port in northeast asia.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.521-526
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• 2012

More efficient and effective volume management of trade cargo is recently requested due to FTA with foreign country. Above all, the grain is the main cargo needed in Korean food life and was appointed as the core trade cargo during FTA. This study is aimed to forecast future demands of grain volumes which are handled at Incheon port because most of the grain volumes are traded at Incheon port in Korea. System Dynamics (SD) was used for forecasting as the methodology. Also, population, yearly grain consumption per a man, GDP, GRDP, exchange rate, and BDI were used as the factors that influence grain volumes. Simulation duration was from 2000 to 2020 and real data was used from 2000 to 2007. According to the simulation, 2020's grain volumes at Incheon port were forecasted to be about 2 million tons and grain volumes handled at Incheon port were continuously reduced. In order to measure accuracy of the simulation, this study implemented MAPE analysis. And after the implementation, the simulation was decided as a much more accurate model because MAPE value was calculated to be 6.3%. This study respectively examined factors using the sensitivity analysis. As a result, in terms of the effects on grain volume in Incheon Port, the population factor is most significant and exchange rate factor is the least.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.165-185
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• 2011

Transshipment traffic has significant meanings because it gives positive effects on increasing the container handling volumes in seaports, and revitalizes the regional and national development. Korean container port's transshipment traffic volumes, however, will slowly decrease due to the direct ships' calling into Chinese ports, which recently has a huge development plan. There are a lot of stress on forecasting the transshipment traffic volumes because the Korean container port development plans are designed based on this container traffic which consists of import and export traffic, and transshipment traffic. The transshipment traffic volumes are assumed to occupy 40% of total container traffic volumes. Despite of the importance of forecasting the transshipment traffic, a little studies are suggested using the concepts of the port competitiveness. In this respect, this study aims to estimate the Port Competitiveness Index and Transshipment traffic Volumes using the System Dynamics methodology. As a result, transshipment traffic volumes are predicted as: 20 million TEUs in Korea under the 4% annual increasing rates, 90 million TEUs in China under the 6% annual increasing rates, and 2.5 million TEUs in Japan under the 1% annual increasing rates respectively. The suggested results can be used to enhance the container port competitiveness and produce more transshipment traffic volumes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.187-188
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• 2009

On this study, the artificial neural network, one of the nonlinear forecasting methods, is compared with ARIMA model through performing a forecast of container traffic. The existing studies have been used the rule of thumb in topology design for network which had a great effect on forecasting performance of the artificial neural network. However, this study applied the genetic algorithm, known as the effectively optimal algorithm in the huge and complex sample space, as the alternative.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.153-171
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• 2008

The purpose of this paper is to estimate economic benefits for the investment of port hinterland. This research has conducted the empirical analysis, by calculating the investment of port hinterland. The key factor for the economic benefits for the hinterland is the utilizing throughputs. This demand is influenced by the throughput in the port. However the data is different between the different organizations. The positive opinions are prevailed about constructing of port hinterland by a optimistic view about throughput. However this paper analyzes the economic benefits by a pessimistic point of view. The main results of this paper are as follows: First, the port hinterland of Busan New Port does not have economic benefit for investment and the hinterland will face the overcapacity problem. We recommend that the plan for investment has to be considered the modification. Second, data of forecasted throughputs is an important factor for evaluation of hinterland's investment. The research for reliable forecasting of throughput has to be preceded for the pertinent evaluation of hinterland's investment.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.91-104
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• 2020

Seosan-Daesan Port is the sixth largest port in Korea, and it promotes port infrastructure expansion, regular route development, overseas marketing, and port incentive systems for continuous growth. In addition, the port is planning to open a regular car ferry line to Weihai, China. This study aims to provide useful research data for effective decision making by analyzing the feasibility of opening the Chinese (Weihai) car ferry route of Seosan-Daesan Port. Currently, some car ferry routes that operate between Korea and China are open at Incheon Port, the Port of Pyeongtaek-Dangjin, and the Port of Gunsan. In order to estimate the volume of cargo that will be created when the car ferry route from Seosan-Daesan Port to Weihai opens, this research analyzes the domestic cargo volume from the Chungcheongnam-do region, where Seosan-Daesan Port is located, to each of the regions where the other ports are located. We estimated the volume of cargo that can be transported on the car ferry from Seosan-Daesan Port to Weihai. As a result, by 2020, about 76,000 passengers and about 50,000 tons of cargo could be created. Suggestions were made for policy strategies that would revitalize passenger numbers and secure the cargo volume of the car ferry, along with a discussion of and the port incentive system.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.37-37
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• 1998

현재 정부는 우리나라 물동량 증가에 따른 수도권 항만의 기능 재정립 및 신항만 입지를 선정하기 위한 조사·연구를 진행중이다. 본 연구에서는 현행 인천항의 항만 시스템과 신규항만 시스템에 대한 컴퓨터 시뮬레이션 모형을 개발하여 신항만 개발로 인한 선박대기시간의 감소 및 항만 체류 시간의 감소 등을 예측하였다. 이 결과는 신항만 개발의 경제적 타당성 분석에서 사용자 편익으로 활용될 수 있다. 시뮬레이션 모형은 ARENA를 이용하여 개발하였다. 수도권 항만 즉 인천항에서 처리되는 화물은 양곡을 비롯한 12개 품목이며, 각각의 화물은 5단계의 규모별로 나누어 선박의 도착간격 및 재항시간 분포 등을 1995년 인천항의 실제 자료를 토대로 추정하였다. 선박의 도착간격은 지수 분포로 나타났으며, 서비스시간은 삼각분포(Triangular Distribution)로 근사되었다. 화물량 예측치가 1996, 2001, 2006, 2011, 2020년으로 되어 있고, 이에 따른 신항만 입지 및 규모가 결정됨에 따라 각 연도별로 신항만을 개발할 경우와 개발하지 않은 경우의 각각에 대한 연간 화물별 선박대기 시간 및 재항시간 등을 추정하였다.