• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.29-58
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• 2016

The purpose of this paper is to show the clustering trend and the comparison of empirical results and is to choose the clustering ports for 3 Korean ports(Busan, Incheon and Gwangyang Ports) by using the bootstrapped DEA(Data Envelopment Analysis) and game Cross-efficiency models for 38 Asian ports during the period 2003-2013 with 4 input variables(birth length, depth, total area, and number of cranes) and 1 output variable(container TEU). The main empirical results of this paper are as follows. First, bootstrapped DEA efficiency of SW and LT is 0.7660, 0.7341 respectively. Clustering results of the bootstrapped DEA analysis show that 3 Korean ports [ Busan (6.46%), Incheon (3.92%), and Gwangyang (2.78%)] can increase the efficiency in the SW model, but the LT model shows clustering values of -1.86%, -0.124%, and 2.11% for Busan, Gwangyang, and Incheon respectively. Second, the game cross-efficiency model suggests that Korean ports should be clustered with Hong Kong, Shanghi, Guangzhou, Ningbo, Port Klang, Singapore, Kaosiung, Keelong, and Bangkok ports. This clustering enhances the efficiency of Gwangyang by 0.131%, and decreases that of Busan by-1.08%, and that of Incheon by -0.009%. Third, the efficiency ranking comparison between the two models using the Wilcoxon Signed-rank Test was matched with the average level of SW (72.83 %) and LT (68.91%). The policy implication of this paper is that Korean port policy planners should introduce the bootstrapped DEA, and game cross-efficiency models when clustering is needed among Asian ports for enhancing the efficiency of inputs and outputs. Also, the results of SWOT(Strength, Weakness, Opportunity, and Threat) analysis among the clustering ports should be considered.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.18-41
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• 2010

The purpose of this paper is to show the empirical measurement way for predicting the seaport efficiency by using Super SBM(Slack-based Measure) with Wilcoxson signed-rank test under CRS(constant returns to scale) condition for 20 Korean ports during 11 years(1997-2007) for 3 inputs(port investment amount, birthing capacity, and cargo handling capacity) and 5 outputs(Export and Import Quantity, Number of Ship Calls, Port Revenue, Customer Satisfaction Point for Port Service and Container Cargo Throughput). The main empirical results of this paper are as follows. First, Super SBM model has well reflected the real data according to the Wilcoxon signed rank test, because p values have exceeded the significance level. Second,Super-SBM has shown about 87% of predicting ratio for the ports efficiency and the optimal size of investment in domestic seaport. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like Super-SBM method with Wilcoxon signed rank test for predicting the efficiency of port performance and the optimal size of investment as indicated by Panayides et al.(2009, pp.203-204).

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.371-384
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• 2011

This paper considers logistics decision support system which deals with transportation mode selection considering transportation and carbon emission cost. Transportation and carbon emission costs vary with the choice of transportation modes and to become competitive companies need to find proper transportation modes for their logistics services. However, due to the restricted capacity of transportation modes, it is difficult to balance transportation and carbon emission costs when designing logistics network including transportation mode choice for each service. Therefore this paper aims to analyze the trade-off relationship between transportation and carbon emission cost in mode selection of intermodal transportation and to provide optimal green logistics strategy. In this paper, the logistics decision support system is designed based on mixed integer programming model. To understand the trade-off relationship of transportation and carbon emission cost, the system is tested with various scenarios including transportation of containers between Seoul and Busan. The analysis results show that, even though sea transportation combined with trucking is competitive in carbon emission per unit distance travelled, the total cost of carbon emission and transportation for the sea transportation may not have competitive advantage over other transportation modes including rail and truck transportation modes. The sea-based intermodal logistics service may induce detours which have negative impacts on the overall carbon emission. The proposed logistics decision support system is expected to play key role in green logistics and supply chain management.

• Journal of Korea Port Economic Association
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• v.30 no.1
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• pp.73-96
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• 2014

Competitiveness of container ports has been traditionally evaluated by capability of individual ports to provide services to customers or their service quality. However, since container ports are connected by container shipping networks to varying degrees, the status of the ports in liner shipping service networks also determines competitiveness of the ports. Sometimes same ports may play different roles in different forms of shipping networks. Shipping network connections that formulate in container ports therefore have more significant impact on their performance than service capabilities they have. This study aims to explore how the shipping and port network has been structured and changed in the past and to examine the network characteristics of ports using Social Network Analysis(SNA). In this SNA study, nodes in the network are the ports-of-call of the liner shipping services and links in the network are connections realized by vessel movements, such that the liner shipping networks determine the port networks. This study, therefore, investigates the liner shipping networks and through its results demonstrates the network characteristics of the ports that are represented by the four centrality indices. This provides port authorities and terminal operating companies with managerial implications to enhance competitiveness from customers' perspectives.

• The Journal of shipping and logistics
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• v.27 no.3
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• pp.457-474
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• 2011

The aim of this study is to analyze the efficiency of major ports in Northeast Asia such as Korea, China and Japan. For the empirical analysis, we tried to apply the data envelopment analysis (DEA), which is an efficiency evaluation model based on mathematical programming theory, and we also established a model to Northeast Asian ports. In our opinion, DEA analysis which involves multiple inputs as well as multiple outputs in its efficiency valuation makes analysis more suitable for port efficiency measurement because ports produce a number of different outputs. In this paper, we attempted to analyze the relative efficiency of 27 ports (5 Korean ports, 13 Chinese ports, 9 Japanese ports) through DEA-CCR, DEA-BCC models. According to the result, Chinese ports are relatively efficient than Korean and Japanese ports. The result of the analysis shows that 7 Chinese ports are efficient in DEA-CCR model in 2009, but in DEA-BCC model 8 Chinese ports and 1 Koran port are efficient. Most of inefficient ports have a value closed to 1 in efficiency for scale, it means that the reason of inefficiency is caused from the technical aspect. Furthermore, we also verified that there exists excess of input in Korean and Japanese ports than Chinese ports.

• 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 Korea Port Economic Association
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• v.40 no.1
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• pp.87-118
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• 2024

Coastal ports play an essential role in developing a country and a city. Port efficiency is an important factor affecting port trade, and the importance of port efficiency for port performance has been recognized in previous literature. DEA (Data Envelopment Analysis) and SFA (Stochastic Frontier Analysis) are widely used in this field of research. However, these two methods are limited in selecting input and output variables. In addition, the literature studies on Chinese coastal ports mainly focus on the study of port clusters in local areas, which lacks a holistic approach and generally lacks up-to-date data. Therefore, to fill the gap in this area of research, this paper introduces a model combining principal component analysis and data envelopment analysis to analyze the operational efficiency of the top 17 coastal ports in China in terms of throughput based on the most recent data available in 2021. This paper identifies container throughput as the output variable, and 13 second indicators are selected as input variables from four primary indicators: land, capital, labor, and infrastructure. Four principal components were selected from 13 second indicators using PCA.After that, DEA (BBC) and DEA (CCR) were used to analyze the 17 ports, among which five were Shanghai, Ningbo-Zhoushan, Guangzhou, Xiamen, and Dongguan, respectively, DEA efficient, and the remaining 12 ports were non-DEA efficient. Finally, improvement directions for each port are derived, and brief suggestions are made. This paper provides some reference value for developing and constructing coastal ports in China.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.39-52
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• 2015

The purpose of this paper is to empirically examine whether there are significant relations among rankings of cross-efficiency, web accessibility, and website evaluation. For this purpose, the study uses the KWAH-4 method developed by the Web Accessibility Laboratory in Korea, website evaluation method developed by the Business Development Bank of Canada (BDC), and the cross-efficiency model for 13 Asian container seaports including Korean, Chinese, and Japanese main ports in 3 years (2009, 2010, and 2013) using data for two cases: three inputs (depth, total area, and number of crane) and one output (TEU) in the first case and three inputs and two outputs (TEU and BDC overall score) in the second case. The main empirical results are as follows. First, the ranking orders of cross-efficiency, web accessibility, and website evaluation overall scores are not significantly correlated with each other. Second, if the BDC overall score is included in the output element, the correlation results are improved. However, the correlation coefficient is still low. The container port policy planners should introduce and consider the web accessibility and website evaluation scores when evaluating an efficiency-increasing plan for Korea's main container ports.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.53-82
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• 2012

The purpose of this paper is to show the clustering trend by using the context-dependent and measure-specific models for 38 Asian ports during 10 years(2001-2009) with 4 inputs and 1 output. The main empirical results of this paper are as follows. First, clustering results by using context-dependent and measure-specific models are same. Second, the most efficient clustering was shown among the Hong Kong, Singapore, Ningbo, Guangzhou, and Kaosiung ports. Third, Port Sultan Qaboos, Jeddah, and Aden ports showed the lowest level clustering. Fourth, ranking order of attractiveness is Guangzhou, Dubai, HongKong, Ningbo, and Shanghai, and the results of progressive scores confirmed that low level ports can increase their efficiency by benchmarking the upper level ports. Fifth, benchmark share showed that Dubai(birth length), and HongKong(port depth, total area, and no. of cranes) have affected the efficiency of the inefficient ports.

• 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.