• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.403-408
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• 2007

The purpose of this paper is to show a way for measuring the rankings of efficient seaports in Korea by using DEA(data envelopment analysis) and model suggested by Jahanshahloo et al(2006). Two inputs(birthing capacity, and cargo handling capacity) and three outputs(export cargo handling amount, import cargo handling amount, and number of ship calls), and one cross sectional data(2004) for 26 Korean seaports are considered for measuring the efficiencies. An empirical main result indicates that ranking order of efficient seaports are Okpo, Samcheok Ulsan, Daesan, Busan, Gohyun Ports. Samcheok Port is classified as the most strong efficient port among 16 general ports except 10 container ports. The Korean seaport authority can adopt the new measurement way introduced in this paper for measuring the exact ranking order of efficient seaports when it decides the development and investment to each efficient seaport.

• Journal of Korea Port Economic Association
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• v.35 no.1
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• pp.117-138
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• 2019

This paper examines Korea's top 30 authors, in the maritime transportation field to compare their world ranking. The analysis covers the affiliation of the authors and their articles published in 65 SSCI and SCI journals on maritime and transportation over a 16-year period (2000-2015). The following three indicators are used for ranking: number of papers; the weighted score that reflects the contribution of the authors; and the impact score, which considers the impact factor. The two most active two schools are Pusan National University and Inha University. Star players are deemed to have contributed greatly to boosting the ranking of their affiliated institution. The institutions that are located in a city that is a seaport show higher research outcomes. Because of the fall in the proportion of Korean papers in the total papers published globally on maritime transportation, the country's future rankings are likely to suffer.

• Journal of Korea Port Economic Association
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• v.26 no.2
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• pp.82-98
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• 2010

The purpose of this paper is to suggest the efficiency measurement way of Korean seaport by using Average Index Transformation model of fuzzy DEA(Data Envelopment Analysis). Two inputs[cargo handling capacity, and berthing capacity], and outputs[cargo handling amount, and the number of ship calls] are used in 1995 and 2004 for 26 Korean seaports. Empirical main results are as follows: First, Tongyung, Gohyun, Okpo, and Sogcho Ports are efficient, and Yeasu Port shows the high efficiency level over 95% under input oriented CCR model. Gohyun and Sogcho Ports showed the most efficient score under average index transformation model. Okpo and Yeasu Ports increased their efficiency scores as the lamda(λ) values are up. The empirical results of fuzzy DEA average index transformation model for Wando, Yeasu, and Seoguipo ports showed that if the lamda values are higher, the efficiency scores are also higher. The main policy implication based on the findings of this study is that the management manager of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the fuzzy DEA average index transformation model for deciding the size of inputs including the port investment amount and evaluating the port efficiency.

• Journal of Korea Port Economic Association
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• v.20 no.2
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• pp.35-52
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• 2004

The purpose of this paper is to measure the competition power of administration service in Korean Seaports by using the scores of customer satisfaction for administration service investigated yearly from 2000 to 2003 by Ministry of Maritime Affairs & Fisheries. And also, this paper shows the competition power of Korean seaports in terms of efficiency by using DEA(data envelopment analysis) method after measuring the change of productive efficiency scores subject to including and excluding the scores of customer satisfaction for administration service as output variable. The empirical main results of this paper are as follows: First, the efficiency scores of the Ports of Donghae, Gunsan, Jeju, Yeosu, Masan, and Pohang have worsened if the customer satisfaction score is excluded as output variable. Therefore these ports have been influenced by the score of customer satisfaction more positively. Second, the changes of the ranking order by measuring the average efficiency scores of each ports subject to including and excluding the scores of customer satisfaction for administration service as output variable are as follows: Busan(9-->7), Incheon(6-->6), Yeosu(1-->4), Gwangyang(4-->3), Masan (10-->9), Ulsan(5-->5), Donghae(8-->11), Gusan(12-->12), Mogpo(3-->2), Pohang(11-->10), Jeju(7-->8), Daesan(2-->1).

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.73-87
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• 2016

The purpose of this study is to investigate the empirical results of Analytic Hierarchy Process/Data Envelopment Analysis-Assurance Region(AHP/DEA-AR) by using multiple regression analysis during the period of 2009-2012 with 5 inputs (number of gantry cranes, number of berth, berth length, terminal yard, and mean depth) and 2 outputs (container TEU, and number of direct calling shipping companies). Assurance Region(AR) is the most important tool to measure the efficiency of seaports, because individual seaports are characterized in terms of inputs and outputs. Traditional AHP and multiple regression analysis techniques have been used for measuring the AR. However, few previous studies exist in the field of seaport efficiency measurement. The main empirical results of this study are as follows. First, the efficiency ranking comparison between the two models (AHP/DEA-AR and multiple regression) using the Wilcoxon signed-rank test and Mann-Whitney signed-rank sum test were matched with the average level of 84.5 % and 96.3% respectively. When data for four years are used, the ratios of the significant probability are decreased to 61.4% and 92.5%. The policy implication of this study is that the policy planners of Korean port should introduce AHP/DEA-AR and multiple regression analysis when they measure the seaport efficiency and consider the port investment for enhancing the efficiency of inputs and outputs. The next study will deal with the subjects introducing the Fuzzy method, non-radial DEA, and the mixed analysis between AHP/DEA-AR and multiple regression analysis.

• 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.

• Journal of Korea Port Economic Association
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• v.25 no.3
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• pp.139-164
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• 2009

The purpose of this paper is to investigate the value chain efficiency of Korean port investment by using the newly developed multi-year and multi-stage value chain efficiency 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 14 years(1994-2007) for 20 Korean seaports by using two kinds of DEA models. Empirical main results are as follows: First, Model 1 shows that the ranking order of multi-stage value chain efficiency is Stage 2, Stage 3-1, Stage 1, and Stage 3-2. And according to the value chain average efficiency scores, ranking order is stages 2, 1, 3-1, and 3-2. In Model 2, 3(Incheon, Mogpo, and Jeju) out of 9 ports show the ranking order of Stages 2, 3-2, 3-1, and 1. And value chain average efficiency scores rank in order of Stages 2, 3-2, 3-1, and 1. Second, the difference among the value chain efficiency scores of each stage comes from the efficiency deterioration of all ports except Stages 2 and 1 in Model 1. In Model 2, value chain efficiency scores among the Stages 3-1, 3-2 compared to Stage 1 were deteriorated. The main policy implication based on the findings of this study is that the manager of port investment and management of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the multi-year, multi-stage value chain efficiency method for deciding the port investment amount and evaluating the effect of port investment after considering the empirical results of this paper carefully.

• Journal of Korea Port Economic Association
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• v.27 no.1
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• pp.185-212
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• 2011

The purpose of this paper is to show the empirical analysis way for measuring the seaport efficiency by using the previous radial model and the newly modified non-radial models( panel additive model, panel RAM model, and panel SBM model)with Spearman rank order correlation coefficient(SROCC) for 20 Korean ports during 11 years(1997-2007) for 1 inputs(port investment amount) and 4 outputs(Number of Ship Calls, Port Revenue, Customer Satisfaction Score for Port Service and Container Cargo Throughput). The main empirical results of this paper are as follows. First, consistency ratio of SROCC in terms of efficiency scores between radial and panel Additive model was over about 76% and overall consistency ratio was about 71.6%. Second, an efficiency of panel RAM model was higher than that of radial model with similarity. However, panel SBM model shows the very similar efficiency scores with panel radial model. Third, the slack size of radial model is smaller compared to non-radial model. Models' ranking orders in terms of efficiency scores, number of efficient ports are panel RAM model, panel SBM model, and radial model. The order from the minimum efficiency scores was the same order like just before. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like non-radial models(panel additive model, panel RAM model, and panel SBM model) for measuring the port performance.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.757-772
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• 2019

The purpose of this paper is to measure the clustering change and analyze empirical results, and choose the clustering ports for Busan, Incheon, and Gwangyang ports by using Artificial Neural Network, Social Network, and Tabu Search models on 38 Asian container ports over the period 2007-2016. The models consider number of cranes, depth, birth length, and total area as inputs and container throughput as output. Followings are the main empirical results. First, the variables ranking order which affects the clustering according to artificial neural network are TEU, birth length, depth, total area, and number of cranes. Second, social network analysis shows the same clustering in the benevolent and aggressive models. Third, the efficiency of domestic ports are worsened after clustering using social network analysis and tabu search models. Forth, social network and tabu search models can increase the efficiency by 37% compared to that of the general CCR model. Fifth, according to the social network analysis and tabu search models, 3 Korean ports could be clustered with Asian ports like Busan Port(Kobe, Osaka, Port Klang, Tanjung Pelepas, and Manila), Incheon Port(Shahid Rajaee, and Gwangyang), and Gwangyang Port(Aqaba, Port Sulatan Qaboos, Dammam, Khor Fakkan, and Incheon). Korean seaport authority should introduce port improvement plans by using the methods used in this paper.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.31-70
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• 2021

The purpose of this paper is to measure the clustering change and analyze empirical results, and choose the clustering ports for Busan, Incheon, and Gwangyang ports by using Hierarchical clustering(single, complete, average, and centroid), Silhouette, and 2SCE[the Second Stage(Type II) cross-efficiency] matrix clustering models on Asian container ports over the period 2009-2018. The models have chosen number of cranes, depth, birth length, and total area as inputs and container TEU as output. The main empirical results are as follows. First, ranking order according to the efficiency increasing ratio during the 10 years analysis shows Silhouette(0.4052 up), Hierarchical clustering(0.3097 up), and 2SCE(0.1057 up). Second, according to empirical verification of the Silhouette and 2SCE models, 3 Korean ports should be clustered with ports like Busan Port[ Dubai, Hong Kong, and Tanjung Priok], and Incheon Port and Gwangyang Port are required to cluster with most ports. Third, in terms of the ASEAN, it would be good to cluster like Busan (Singapore), Incheon Port (Tanjung Priok, Tanjung Perak, Manila, Tanjung Pelpas, Leam Chanbang, and Bangkok), and Gwangyang Port(Tanjung Priok, Tanjung Perak, Port Kang, Tanjung Pelpas, Leam Chanbang, and Bangkok). Third, Wilcoxon's signed-ranks test of models shows that all P values are significant at an average level of 0.852. It means that the average efficiency figures and ranking orders of the models are matched each other. The policy implication is that port policy makers and port operation managers should select benchmarking ports by introducing the models used in this study into the clustering of ports, compare and analyze the port development and operation plans of their ports, and introduce and implement the parts which required benchmarking quickly.