• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.03a
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• pp.189-196
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• 2002

As the quantity of transported goods increases, there is a lot of mechanical trouble with loading facilities. So it tremendously produces not only economic loss but also time loss. To reduce the loss from the trouble of leading facilities, it is necessary to analyse the distribution of the problem's occurrence and use the analyzed data to minimize the outbreak of trouble. So the data can be usefully used when designing or manufacturing and it also can be utilized for proper maintenance of operating equipment, frequency of inspection and repair, know-how of checking on equipment and purchasing of spare parts. And it is possible to minimize the loss if the propel maintenance is adapted

• Journal of Navigation and Port Research
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• v.29 no.10 s.106
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• pp.921-926
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• 2005

The purpose of this paper is to conduct a comparative analysis of container terminal operation in Busan and Kwangyang port. The research method used for this study is DEA(Data Envelopment Analysis} and among DEA methods CCR and BCC model has been used. According to the results of CCR model Gamman in 2004 and Gamcheon in 2004 are found to be the most efficient terminals in the sample and the inefficient terminals include Gwangyang Phase 2 terminal. Based on BCC model Gamcheon and Uam are identified as the most efficient terminals in three consecutive years including Gamman terminal in 2004. The inefficient terminals include New Gamman in 2002 and Hutchison in 2002. The research findings show that inefficient terminals need to fully utilise their terminal facilities and increase container throughput through effective marketing activities.

• Journal of Navigation and Port Research
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• v.30 no.10 s.116
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• pp.819-823
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• 2006

Since the north port in Busan started to operate in general pier (1, 2, central, 3 and 4), the business area had been expanded to Jasungdae, Shinsundae, Gamman zone and so on However, these zones adjoin the Busan city and have caused problems to both logistics and city activities. The operation of Off-Dock Container Yard (ODCY) is a representative example due to the limited sphere of Container Yard in this city. It increases logistics costs and causes serious social problems as a result of increasing traffic in the trunk roads such as Uam and Chungjang roads. This paper aims to analyze the effects of the reduction in traffic of trunk roads in Chungjan, Uam roads and so on, when General Pier and Jasungdae Pier are Re-developed. The effects of the reduction in social cost from traffic congestion are also analyzed. Finally, we predict and evaluate the effects according to the re-development of two piers, north pier and Jasungdae pier.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.275-279
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• 2006

Since the North port in Busan started to operate in general pier (1, 2, central, 3 and 4), the business area had been expanded to Jasungdae, Shinsundae, Gamman zone and so on. However, these zones adjoin the Busan city and have caused problems to both logistics and city activities. The operation of Off-Dock Container Yard (ODCY) is a good representative example due to the limited sphere of Container Yard in this city. It increases logistics costs and causes serious social problems as a result of increasing traffic in the truck roads such as Uam and Chungjang roads. This paper aims to analyze the effects of the reduction in traffic of trunk roads in Chungjan, Uam roads and so on, when General Pier and Jasungdae Pier are Re-developed. The effects of the reduction in social cost from traffic congestion are also analyzed. Finally, we predict and evaluate the effects according to the re-development of two piers, north pier and Jasungdae pier.

• Journal of Korea Port Economic Association
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• v.31 no.3
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• pp.155-166
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• 2015

This study selected container terminals of Gwangyang and Busan Ports to evaluate the influence of efficient container terminals. For the study, after data envelopment analysis (DEA) using the CCR and BCC models, the decision-making unit (DMU) system was used to define nodes; and with the use of a reference group in DEA (BCC model) and a lambda value, this study created a social network and analyzed the influences of efficient DMUs through a centrality analysis of eigenvectors. The results are presented as follows: First, as a result of the DEA, CCR efficiencies in PNC, HJNC, and HPNT container terminals of Busan Port were 1 and BCC efficiencies at Singamman Terminal, Wooam Terminal, PNC, HJNC, HPNT, and BNCT container terminals of Busan Port were 1. Second, as a result of undertaking social network analysis (SNA), according to an eigenvector centrality analysis, HJNC Terminal was referred to the most (influence score of 0.515), which indicates that it is the most influential as a container terminal. The influence of PNC Terminal was 0.512, while that of Wooam Terminal was 0.379. CJ Korea Express in Gwangyang Port was ranked fourth in influence, but its influence score of 0.256 indicates that it was the most influential of the container terminals at Gwangyang Port.

• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.43-60
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• 2010

The purpose of this paper is to show the clustering measurement way for Korean container terminals by using neural network based SOM(Self Organizing Map). Inputs[Number of Employee, Quay Length, Container Terminal Area, Number of Gantry Crane], and output[TEU] are used for 3 years(2002,2003, and 2004) for 8 Korean container terminals by applying both DEA and SOM models. Empirical main results are as follows: First, the result of DEA analysis shows the possibility for clustering among the terminals and reference terminals except Gamcheon and Gwangyang terminals because of the locational closeness. Second, the result of neural network based SOM clustering analysis shows the positive clustering in clustering positions 1, 2, 3, 4, and 5. Third, the results between SOM clustering and DEA clustering show the matching ratio about 67%. The main policy implication based on the findings of this study is that the port policy planner of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the clustering measurement way for the Korean container terminals using neural network based SOM with DEA models for clustering Korean ports and terminals.