• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2017.11a
• /
• pp.160-162
• /
• 2017

부표정비선(창명3호) 추진장치 및 코레인 형식에 관한 고찰.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 1993.10b
• /
• pp.3-10
• /
• 1993

• Journal of Korean Port Research
• /
• v.3 no.1
• /
• pp.57-75
• /
• 1989

• Journal of Korea Port Economic Association
• /
• v.23 no.3
• /
• pp.53-77
• /
• 2007

This paper is designed to look for a specialized strategies by drawing the special features of Busan New Port from both a comparative analysis of major factors of harbor competitiveness and a SWOT analysis of Busan New Port and Yangshan Port, one of the biggest competitive ports in Northeast Asia, so that Busan New Port may preoccupy a status as the hub port of the area. The researcher would like to suggest the following measures to make Busan New Port serve as the central port of Northeast Asia on the basis of the findings; Korea should push ahead with creating a railroad transportation linking with Eurasia Contient, secure the amount of goods and resources with the help of the early development of the surrounding complex of the port, make a considerable progress in the level of port service, come up with a differentiation strategies for harbor marketing activities and improve its productivity.

• Journal of Korea Port Economic Association
• /
• v.24 no.2
• /
• pp.209-239
• /
• 2008

The purpose of this paper is to investigate the effectiveness of Korean port investment by using the newly developed slack-based multi-year panel congestion model of DEA(Data Envelopment Analysis). Inputs[port investment amount, cargo handling capacity, and berthing capacity], and outputs[cargo handling amount, number of ship calls, revenue, and score of customer service satisfaction] are used during 1994-2004 for 20 Korean seaports. Empirical analysis identified congestion especially in port investment as input at the ports of Gunsan, and Busan in the all 3 models, and the ports of Pyungtag, Mogpo, Yeosu, and leju in over 2 models. Port investment induced the rapid increase of port efficiency from the ports of Masan, Incheon, Donghae, and Samcheok. Therefore other ports except these ports should examine the reason about the inefficiency of port investment by searching out the situation of each ports directly. The main policy implication based on the findings of this study is that The Ministry of Land, Transport and Maritime Affairs in Korea should introduce the new measurement way after reviewing the multi-year slack-based congestion approach when the amount of port investment for each port is decided.

• Journal of Navigation and Port Research
• /
• v.44 no.3
• /
• pp.187-194
• /
• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.

• Journal of Korea Port Economic Association
• /
• v.25 no.2
• /
• pp.149-176
• /
• 2009

In Count case, the owners claimed from the charterers the amount of their loss resulting from the delay to the Count caused by the blockage of the channel due to stranding of the Pongola on the ground that this loss resulted from breach by the charterers of the safe port provisions. The Claim was referred to arbitration and dealt with on written submission. In a reasoned award, the arbitrators upheld the owners' claim. The charterers seek an order reversing the award or remitting it to the arbitrators for further consideration : (1) That the tribunal was wrong to find that the port of Beira was unsafe and that in consequence the charterers were liable to the owners in damages for detention. (2) That the tribunal was wrong to find that the port was unsafe in the abstract by reference to the fact that two other vessels had grounded there. (3) Having held that the Count was delayed for a little over four days by the fact that, after the charterers had nominated the port, the Pongola had grounded in the access channel, the tribunal should have held that the port was not prospectively unsafe. On the that the grounding the Pongola was caused by the characteristics which made the port an unsafe port to nominate for the Count. The court was held that it was not an independent event which broke the chain of causation between the breach of contract and the owner's loss. For those reasons, the court was upheld the arbitrator's award.

• Journal of Digital Convergence
• /
• v.19 no.1
• /
• pp.167-176
• /
• 2021

Incheon Port urgently requires designation of a free trade zone to pursue development linked with the port hinterland while promoting continuous growth of the port. This study aims to evaluate the optimal location and derive policy implications for the designation of a free trade zone and analyzed factors property divided by groups. This study used the Consistent Fuzzy Preference Relation (CFPR) analysis technique to derive a practical construction direction by quantifying and evaluating linguistic measures. As a result, the Incheon New Port hinterland showed the highest location competitiveness among the four candidate areas of Incheon New Port hinterland, Aam Logistics Complex 2, North Port hinterland, and Gyeongin Port hinterland. Among the eight evaluation factors consisting of qualitative and quantitative factors, the Incheon New Port hinterland ranked no. 1 in all the four qualitative factors and one quantitative factor and received the highest total score. Also, Group 1 presented 'possibility to attract tenant companies' as first. Group 2 was 'complex size' and Group 3 was also 'possibility to attract tenant companies'. This study has the implication for suggesting the factors and evaluation structure of Free Trade Zone. Future research requires detailed empirical studies, such as expanding the subject of study or selecting factors that reflect the interests of each group.

• Journal of Navigation and Port Research
• /
• v.46 no.3
• /
• pp.251-258
• /
• 2022

Donghae Port is adjacently located to a residential area wherein 26,933 generations are creating a living environment. The areas comprise Song-jeong village (5,754 generations) and Bukp-yeong village (21,179 generations). Major cargoes handled in Donghae Port are dusty limestone, cement, anthracite, and bituminous coal, etc. In the process of handling such cargoes, air pollutants including oxide dust and fine dust which adversely impact the living conditions and health of residents are generated, causing air pollution in the vicinity of the port. Currently, Donghae Port is making an effort to improve the operation environment of the infrastructure and equipment in stages, for the purpose of reducing air pollutant emissions caused by the port industries in a long-term perspective. In this study, the sphere of influence of fine dust exposure and the degree of air pollution in the surrounding area were analyzed such as the state of fine dust concentration and diffusion in the vicinity of Donghae Port, fine dust diffusion pattern and spatial distribution of high-concentration considering wind direction and speed characteristics during the day and seasonal cycles. A more effective plan to reduce the concentration of fine dust in nearby areas by combining reduction plan, is being developed in terms of improvement regarding port infrastructure and equipment, and reduction measures considering the characteristics of the atmosphere environment according to the daytime, nighttime and season.

• Journal of Navigation and Port Research
• /
• v.47 no.3
• /
• pp.155-166
• /
• 2023

Trend analysis and time series analysis were conducted to predict the demand of manpower under the smartization of shipping and port logistics with transportation survey data of Statistic Korea during the period from 2000 to 2020 and Statistical Yearbook data of Korean Seafarers from 2004 to 2021. A linear regression model was adopted since the validity of the model was evaluated as the highest in forecasting manpower demand in the shipping and port logistics industry. As a result of forecasting the demand of manpower in autonomous ship, remote ship management, smart shipping business, smart port, smart warehouse, and port logistics service from 2021 to 2035, the demand for smart shipping and port logistics personnel was predicted to increase to 8,953 in 2023, 20,688 in 2030, and 26,557 in 2035. This study aimed to increase the predictability of manpower demand through objective estimation analysis, which has been rarely conducted in the smart shipping and port logistics industry. Finally, the result of this research may help establish future strategies for human resource development for professionals in smart shipping and port logistics by utilizing the demand forecasting model described in this paper.