• 해운
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• no.8 s.30
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• pp.23-33
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• 2006

컨테이너화물 유치를 위한 세계주요항만간의 경쟁이 날로 치열한 양상을 보이고 있는 가운데 컨테이너화물 처리량에서 과거의 최고기록을 갱신하는 항만이 속출하고 있다. 더구나 중국과 유렵항만의 신장세가 두드러지고 있다. 다음은 한국컨테이너부두공단의 자료를 정리한 것이다.(편집자 주)

• Journal of Korea Port Economic Association
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• v.29 no.1
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• pp.143-175
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• 2013

The purpose of this paper is to show the clustering trend by using the variable group benchmarking(VGB) and categorical variable(CV) models for 38 Asian ports during 9 years(2001-2009) with 4 inputs(birth length, depth, total area, and number of crane) and 1 output(container TEU). The main empirical results of this paper are as follows. First, clustering results by using VGB show that Shanghai, Qingdao, and Ningbo ports took the core role for clustering. Second, CV analysis focusing on the container throughputs indicated that Singapore, Keelong, Dubai, and Kaosiung ports except Chinese ports are appeared as the center ports of clustering. Third, Aqaba, Dubai, Hongkong, Shanghai, Guangzhou, and Ningbo ports are recommended as the efficient ports for the target of clustering. Fourth, when the ports are classified by the regional location, Dubai, Khor Fakkan, Shanghai, Hongkong, Keelong, Ningbo, and Singapore ports are the core ports for clustering. On the whole, other ports located in Asia should be clustered to Dubai, Khor Fakkan, Shanghai, Hongkong, Ningbo, and Singapore ports. The policy implication of this paper is that Korean port policy planner should introduce the VGB model, and CV model for clustering among the international ports for enhancing the efficiency of inputs and outputs.

• Journal of Korea Port Economic Association
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• v.30 no.1
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• pp.23-55
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• 2014

The purpose of this paper is to show the clustering trend and to choose the clustering ports for 3 Korean ports(Busan, Incheon and Gwangyang Ports) by using the self organizing maps based on neural network(SOM) and Tier models for 38 Asian ports during 11 years(2001-2011) with 4 input variables(birth length, depth, total area, and number of crane) and 1 output variable(container TEU). The main empirical results of this paper are as follows. First, clustering results by using SOM show that 3 Korean ports[Busan(26.5%), Incheon(13.05%), and Gwangyang(22.95%) each]can increase the efficiency. Second, according to Tier model, Busan(Hongkong, Sanghai, Manila, and Singapore), Incheon(Aden, Ningbo, Dabao, and Bangkog), and Gwangyang(Aden, Ningbo, Bangkog, Hipa, Dubai, and Guangzhou) should be clustered with those ports in parentheses. Third, when both SOM and Tier models are mixed, (1) efficiency improvement of Busan Port is greater than those of Incheon and Gwangyang ports. (2) Incheon port has shown the slow improvement during 2001-2007, but after 2008, improvement speed was high. (3) improvement level of Gwangyang port was high during 2001-2003, but after 2004, improvement level was constantly decreased. The policy implication of this paper is that Korean port policy planner should introduce the SOM, and Tier models with the mixed two models when clustering among the Asian ports for enhancing the efficiency of inputs and outputs.

• Korea Trade Review
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• v.41 no.3
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• pp.27-42
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• 2016

This study is to investigate seaport clustering by using meta-frontier and cross-efficiency models. Data covers the 13 Asian ports during 2009, 2010 and 2013 with 3 inputs(depth, total area, and number of cranes) and 1 output(TEU). Correlations coefficient from cross-efficiency matrix are used for measuring clustering dendrogram. After that, meta-frontier analysis for investigating whether the clustering using cross-efficiency method increases the meta-efficiency. Empirical main results are as follows: First, group efficiencies of Busan, Incheon, and Gwangyang ports are increased. Second, meta and group efficiencies of China ports are greater than those of Korean ports. Third, distortion of technology gap of Gwangyang is lower than that of Busan and Incheon. Fourth, Gwangyang, clustering with Ningbo, Chingtao, Tokyo and Caosung ports in 2009 and with Dubai port in 2013 can increase the efficiency. Fifth, to enhance the efficiency, Busan port should be clustered to group 2 in 2010 and group 1 in 2013, and Incheon port clustered to group 2 in 2010 and 2013. Fifth, it is empirically investigated that Busan, Incheon and Gwangyang ports can increase the efficiency by using Cross-efficiency and Meta-frontier models. Port policy planner should promote the clustering policy for Busan with Hong Kong, Shanghai, and Singapore, Incheon and Gwangyang with Chingtao, Nagoya, Ningbo, Tokyo, and Kaoshung ports.

• Journal of Fashion Business
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• v.8 no.4
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• pp.1-21
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• 2004

This research suggest the correspondent sizes of female ready-made clothes to export to China on the basis of those of Korean women's ready-made clothes. The following is the concrete coverage of this research: $\cdot$ Analyze the physical measurements and body types of the women in their 30s and 40s in the area of Ningbo, Jeolgang Province in China. $\cdot$ Compare the body measurements of Chinese and Korean women. $\cdot$ Hold compensation measurement by an basic torso pattern test to raise precision of the direct and indirect body measurements. $\cdot$ Establish the corresponding and representative sizes of women's ready-made clothes to go to China. $\cdot$ Make basic torso pattern and sample clothes reflecting representative sizes. $\cdot$ Hold adjustment and compensation through the wearing evaluation by Chinese consumers on the spot. $\cdot$ Finally suggest the correspondent sizes of women's ready-made clothes to export to China.

• Journal of Fashion Business
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• v.11 no.1
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• pp.108-124
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• 2007

Body measurement was held for the subjects of Chinese adult males in their 20s through 40s residing in the Ningbo area of Zhejiang Province in order to provide body type information and raise the fit of clothing products for the advancement into the Chinese market. The following sums up the analysis of body types based on body measurement: 1. Seven factors to compose body types were produced from the analysis of males in their 20s, explaining 76.07% of variables and representing 3 types according to cluster analysis. Type 1 was H-b and appeared as much as 32.14%. Type 2, semi X-d, was 40.81%, while Type 3, A-i, had 27.04%. 2. Eight body type composing factors were extracted from the analysis of men in their 30s and 40s. The factors explained 76.77% of all the variables and represented 4 types according to cluster analysis. Type 1, H-d, had the appearance rate of 18.47%; Type 2, H-b, 40.84%; Type 3, Y-i, 27.71%; and Type 4, semi X-s, 11.95%.

• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.131-143
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• 2010

This study aims to analyse efficiencies of international main container ports. For the purpose, it selected twenty main ports based on the volume of cargo of ports recorded in Containerisation International Yearbook and conducted BCC(efficiency analysis) on them. The variables which may influence efficiency of ports were selected based on previous studies. Berth, Depth, Crane and Total area were input variables and Total TEU was an output variables. The results are summarized as follows: First, DEA-CCR efficiency of Shenchen Port(China) was 1.0, which was the most efficient poor analysed. Second, DEA-BCC efficiency of Port of Singapore, Shenchen Port(China), Ningbo Port (China), Port of Tanjung Pelepas (Malaysia) was 1.0, which was the most efficient analysed. Third, efficient scale of Shenchen Port(China) has been 1.0 for four subsequent years from 2004 to 2007, which was the most efficient analysed.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.175-197
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• 2010

The purpose of this paper is to develop a new strategy from a different angle to become a preferred transshipment hub for sustainable growth. This study would derive new competitive factors through the case study on a global carrier 'A' who shows constant growth in transshipment via Busan and the questionnaire survey was conducted. As to analysis results by matrix, Busan Port needs to strengthen its competitiveness against North China ports due to less local import/export cargo volume and less government support while North China ports continue to be developed with incremental direct calling and government's flexible cabotage rule.

• Journal of Korea Port Economic Association
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• v.31 no.2
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• pp.85-101
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• 2015

This study formulates a development strategy for Gwangyang port through the analysis of its competition with other major Northeast Asian ports. A revised BCG matrix is applied to estimate the change in competition between the major ports in Northeast Asia and the Lotka-Volterra model is used for the competitor analysis. The growing competitive power and influence of Chinese ports, continued competitive advantage of Busan port, diminishing competitiveness of Gwangyang and Incheon ports, and disappearing competitive position of Japanese ports in Northeast Asia are all confirmed. In addition, according to the relationship between Gwangyang port and other major Northeast Asian ports from 2007 to 2014, Gwangyang port has changed to a predatory from a win/win relation with Busan port and has maintained its predatory relationship with Hong Kong port in terms of transshipment cargoes. Moreover, Gwangyang port has formed predatory relationships with Shanghai and Ningbo ports, a pure competitive relation with Tianjin port, and a win/win relation with Qingdao and Dalian ports. Overall, predatory relationships between Gwangyang port and other Northeast Asia ports increased from 2007 to 2014. The counterstrategies for Gwangyang port to address this situation include establishing cooperative relations and continuing the win/win relationships with cooperative ports.

• Journal of Korea Port Economic Association
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• v.33 no.2
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• pp.53-82
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• 2017

The purpose of this study is to show the clustering trend and compare empirical results, as well as to choose the clustering ports for 3 Korean ports (Busan, Incheon, and Gwangyang) by using meta-frontier DEA (Data Envelopment Analysis) and integer models on 38 Asian container ports over the period 2005-2014. The models consider 4 input variables (birth length, depth, total area, and number of cranes) and 1 output variable (container TEU). The main empirical results of the study are as follows. First, the meta-frontier DEA for Chinese seaports identifies as most efficient ports (in decreasing order) Shanghai, Hongkong, Ningbo, Qingdao, and Guangzhou, while efficient Korean seaports are Busan, Incheon, and Gwangyang. Second, the clustering results of the integer model show that the Busan port should cluster with Dubai, Hongkong, Shanghai, Guangzhou, Ningbo, Qingdao, Singapore, and Kaosiung, while Incheon and Gwangyang should cluster with Shahid Rajaee, Haifa, Khor Fakkan, Tanjung Perak, Osaka, Keelong, and Bangkok ports. Third, clustering through the integer model sharply increases the group efficiency of Incheon (401.84%) and Gwangyang (354.25%), but not that of the Busan port. Fourth, the efficiency ranking comparison between the two models before and after the clustering using the Wilcoxon signed-rank test is matched with the average level of group efficiency (57.88 %) and the technology gap ratio (80.93%). The policy implication of this study is that Korean port policy planners should employ meta-frontier DEA, as well as integer models when clustering is needed among Asian container ports for enhancing the efficiency. In addition Korean seaport managers and port authorities should introduce port development and management plans accounting for the reference and clustered seaports after careful analysis.