• Journal of Digital Convergence
• /
• v.15 no.3
• /
• pp.157-163
• /
• 2017

Forecasting container cargo volumes is very important factor for port related organizations in inversting in the recent port management. Especially forcasting of domestic and foreign container volume is necessary because adjacent nations are competing each other to handle more container cargoes. Exact forecasting is essential elements for national port policy, however there is still some difficulty in developing the predictive model. In this respect, the purpose of this study is to develop and suggest the forecasting model of container cargo volumes of China using System Dynamics (SD). The monthly data collected from Clarkson's Shipping Intelligence Network from year 2004 to 2015 during 12 years are used in the model. The accuracy of the model was tested by comparisons between actual container cargo volumes and forecasted corgo volumes suggested by the research model. The MAPE values are calcualted as 6.21% for imported cargo volumes and 7.68% for exported cargo volumes respectively. Less than 10% of MAPE value means that the suggested model is very accurate.

• Journal of Korea Port Economic Association
• /
• v.19 no.2
• /
• pp.55-67
• /
• 2003

The purpose of this study is to estimate and forecast the marine trading volumes based on the structural model. We employ GPH cointegration test since the structural model must be stationary to get the accurate predicted values. The empirical results show that our model is stationary. This paper also applies variance decompositions and impulse-response functions to the structural model composed of exchange rate, domestic industrial activity, and world business. The results indicate that while both loading and unloading volumes respond positively to the shocks in income and then decay very slowly, their responses are different to the shocks in exchange tate.

• Journal of Navigation and Port Research
• /
• v.38 no.6
• /
• pp.701-708
• /
• 2014

This study is aimed to obtain the influence of port hinterlands on container cargo volumes of Incheon port using System Dynamics(SD). Also, macro economic index such as exchange rates(US dollar), balance of current account, capital balance, Japan trade, China trade, export unit value index, import unit value index, total turnover of Incheon port were used as the factors that influence container cargo volumes of Incheon port. Moreover micro index regarding port hinterlands' operating companies such as total sales, rental fee, number of employees were introduced in the simulation model. 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 within 10%. This study respectively examined factors using the sensitivity analysis. As a result, in terms of the effects on cargo volume in Incheon Port, the factor named 'cargo volumes of port hinterlands' operating companies' is most significant. And increasing the rental fee of hinterland was resulted in decreasing the cargo volumes of Incheon port.

• Journal of Korea Multimedia Society
• /
• v.17 no.12
• /
• pp.1503-1510
• /
• 2014

This study will examine the consolidation that is occurring in the shipping industry and its effects on Busan's status as a key transshipment hub in Southeast Asia as well as what measures the port must implement to attract transshipment traffic. With this in mind heading forward, trends in transshipment cargo, problems facing the port, as well as the current status of transshipment volumes at the Port of Busan must be fully understood so that thorough research can be done into appropriate measures to stimulate growth and attract cargo traffic. In this study, We analyze the current problems and status of transshipment cargo at Busan Port and factors affecting the competitiveness of transshipment cargo at Busan New Port, Korea's key import/export gateway, have been examined. We show the Strategies to Attract Transshipment Cargo at the Busan New Port which is to become a an optimal transshipment port, a port's internal environment including the scale and location of its hinterland, facilities and tariffs as well as the external environment including global networks and logistics IT management must be carefully considered as they are all key actors affecting cargo volumes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 1998.10a
• /
• pp.263-269
• /
• 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 the Korean Institute of Navigation
• /
• v.23 no.1
• /
• pp.75-84
• /
• 1999

Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, therefore, a new algorithm called ESD (Extensional System Dynamics) for the evaluation of port competition was presented, and applied to simulate port systems in northeast asia. The detailed objectives of this paper are to develop Unit fort Model by using SD(System Dynamics) method; to develop Competitive Port Model by ESD method; to perform sensitivity analysis by altering parameters, and to propose port development strategies. For these the algorithm for the evaluation of part's competition was developed in two steps. Firstly, SD method was adopted to develop the Unit Port models, and secondly HFP(Hierarchical Fuzzy Process) method was introduced to expand previous SD method. The proposed models were then developed and applied to the five ports - Pusan, Kobe, Yokohama, Kaoshiung, Keelung - with real data on each ports, and several findings were derived. Firstly, the extraction of factors for Unit Port was accomplished by consultation of experts such as research worker, professor, research fellows related to harbor, and expert group, and finally, five factor groups - location, facility, service, cargo volumes, and port charge - were obtained. Secondly, system's structure consisting of feedback loop was found easily by location of representative and detailed factors on keyword network of STGB map. Using these keyword network, feedback loop was found. Thirdly, for the target year of 2003, the simulation for Pusan port revealed that liner's number would be increased from 829 ships to 1,450 ships and container cargo volumes increased from 4.56 million TEU to 7.74 million TEU. It also revealed that because of increased liners and container cargo volumes, length of berth should be expanded from 2,162m to 4,729m. This berth expansion was resulted in the decrease of congested ship's number from 97 to 11. It was also found that port's charge had a fluctuation. Results of simulation for Kobe, Yokohama, Kaoshiung, Keelung in northeast asia were also acquired. Finally, the inter port competition models developed by ESB method were used to simulate container cargo volumes for Pusan port. The results revealed that under competitive situation container cargo volume was smaller than non-competitive situation, which means Pusan port is lack of competitive power to other ports. Developed models in this study were then applied to estimate change of container cargo volumes in competitive relation by altering several parameters. And, the results were found to be very helpful for port mangers who are in charge of planning of port development.

• Journal of Korean Port Research
• /
• v.12 no.1
• /
• pp.1-8
• /
• 1998

If a system has a large boundary and complexity, forecast's accuracy will be very low when consider the system's substance as black box. Thus, it is necessary that analysis by structure model. To examine competition in Northeast Asia Ports, it has assumed that the form of structure model, For which the System Dynamics method is adapted in this paper. Northeast Asia Ports Model includes five ports - Pusan, Kobe, Yokohama, Kaoshiung, Keelung, - which are adjacent to each other by geographically and has a competition relation. The Northeast Asia Ports Model has several sub-systems which consists of each unit port models. And, each unit port model found by quantitive, qualititive factors and their feedback loops. All effects which components of one port have influence to components of the rest ports must be surveyed in order to construct Northeast Asia Ports Model, but it may be impossible currently. In this paper Northeast Asia Ports Model was simplified by HFP-Hierarchical Fuzzy Process Method-adapted to integration of level variables of unit port model. Container cargo volumes in Northeast Ports Model is distributed by results of HFP method. And distributed container cargo volumes effected to unit port model. Developed model can estimate change of container cargo volumes in competitive relation by alternation of simple parameter, and reflects dynamics characteristics which are included in model.

• Journal of Korean Port Research
• /
• v.11 no.2
• /
• pp.145-156
• /
• 1997

The purpose in this study is development of model for the Container Terminals of Pusan Port, First of all, Quantitive and Qualititve factors are characterized which effects on Physical Distribution System in Container Terminals. The System Dynamics method is used to develope the model by using these factor. This model is able to present the timinig of investment in Container Terminals of Pusan Port. Six models are showed by change of parameters in System Dynamics, in this paper. In the model, Five feedback loop were found. Loop 1 : Number of Liners$\rightarrow$Number of Congested ships$\rightarrow$Port's Charges$\rightarrow$Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$The will to investment of government$\rightarrow$Length of berth→Number of Liners. Negative loop was acquired. Loop 2 : Port's Charge$\rightarrow$Economic of Port$\rightarrow$The will to Private management$\rightarrow$Efficiency for Port's Operation$\rightarrow$Port's Charges. Positive loop was acquired. Loop 3 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Information Service$\rightarrow$Support service for port's user$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 4 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Extent of stacking area$\rightarrow$Number of handling equipmint$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 5 : Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$Econmic of Port$\rightarrow$Support service for port's user$\rightarrow$Export & Import Cargo Volumes. Positive loop was acquired. System's level variables were selected as followings ; Number of Liners, Number of Congested ships, Export & Import Carge Volumes, Length of berth, and Port's Charges. As result of simmulation of model, fluctuation of respective year was found in level variables. This fluctuation can be used properly to present timing of investment.

• Journal of Navigation and Port Research
• /
• v.36 no.6
• /
• pp.521-526
• /
• 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
• /
• v.29 no.1
• /
• pp.23-45
• /
• 2013

This paper aims to identify the problems of incentives and find a solution to them by empirically analyzing the port incentives and the development of cargo volume. The current method of paying performance incentives and cargo-increase incentives makes it is possible for shipping companies to get the maximum incentives just by regulating cargo volumes without increasing them. Since the processing volume of transshipment cargo of the Busan port is over the volume eligible for the maximum incentive determined by the tie-up of shipping companies, the transshipment cargo can decrease. The incentive of the Busan port based on the cargo record and increase does not affect the increase of transshipment cargo, only to suffer a loss, and thus a new incentive system is needed that does not allow shipping companies to regulate cargo volumes. Based on the result of this study, We have to apply the even-handed incentive rule which pays the incentive for the cargo volume of the pertinent year with the unit price per 1 TEU to avoid the chicken game among the ports.