• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.19-30
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• 2021

The 21st Century Maritime Silk Road (MSR) is an important part of Belt and Road Initiative(BRI). As an economic and trade corridor for dozens of countries in Asia, Europe and Africa, and the port as an important link node, the efficiency of port operation directly affects the implementation of BRI's strategy. On the basis of combining BRI and related evaluation methods of port efficiency, this paper uses DEA-BCC model to select port production berth number and production berth length as input index container throughput and cargo throughput as output index to analyze the port efficiency of 14 ports in China. The results show that: (1) The overall efficiency level of the ports along the MSR is relatively low. Most of the ports have not reached the DEA efficiency and there are different degrees of problems in scale investment and technological improvement. However, this situation is accompanied by the implementation of China's maritime cooperation strategy and becoming better year by year. (2) The low operating efficiency of ports along China's MSR is mainly due to the lack of coordination between scale efficiency and technical efficiency, which is caused by insufficient scale investment in the port itself, weak economic linkage between the hinterland and the port, (3) Whether a port has a strong comprehensive strength does not entirely depend on the cargo throughput or scale but also includes the port's operating efficiency.

• 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.

• 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 the Korean Society of Marine Environment & Safety
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• v.14 no.1
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• pp.45-54
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• 2008

"Summer Deadweight Tonnage(SDWT)" is used as the criteria of the berthing capacity when establishing port entry limits under current guideline. The important factors affecting to the maximum ship size of possible berthing are mass, length and breath of the ship rather than deadweight. Therefore this guideline should be modified to ensure safety and efficient operation of berth. This study aimed to propose a rational guideline to adjust the berthing capacity. In order to decide proper berthing capacity, three berths of Port of Ulsan were selected and systematic evaluations for the safety of passage transit, berthing maneuvers, ship motions at berth and stabilities of structures were conducted. Small changes of ship size had little effect on those characteristics and little significant differences were found according to the increase of ship size at the same displacement. The evaluation results of the increasement of 50% of berthing capacity at 20,000 DWT, 25% at 40,000 DWT and 13% at 150,000 DWT were within the design criteria in which the berths were built. Therefore, if the channel width, diameter of turning circle, berth length and mooring arrangements are satisfied with the criteria, the current berth limitations should be adjusted by the displacement. as substitute for the deadweight.

• 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.34 no.3
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• pp.17-52
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• 2018

The purpose of this paper is to measure the clustering change and analyze empirical results. Additionally, by using k-means, hierarchical, and mixed models on Asian container ports over the period 2006-2015, the study aims to form a cluster comprising Busan, Incheon, and Gwangyang ports. The models consider the number of cranes, depth, birth length, and total area as inputs and container twenty-foot equivalent units(TEU) as output. Following are the main empirical results. First, ranking order according to the increasing ratio during the 10 years analysis shows that the value for average linkage(AL), mixed ward, rule of thumb(RT)& elbow, ward, and mixed AL are 42.04% up, 35.01% up, 30.47%up, and 23.65% up, respectively. Second, according to the RT and elbow models, the three Korean ports can be clustered with Asian ports in the following manner: Busan Port(Hong Kong, Guangzhou, Qingdao, and Singapore), Incheon Port(Tokyo, Nagoya, Osaka, Manila, and Bangkok), and Gwangyang Port(Gungzhou, Ningbo, Qingdao, and Kasiung). Third, optimal clustering numbers are as follows: AL(6), Mixed Ward(5), RT&elbow(4), Ward(5), and Mixed AL(6). Fourth, empirical clustering results match with those of questionnaire-Busan Port(80%), Incheon Port(17%), and Gwangyang Port(50%). The policy implication is that related parties of Korean seaports should introduce port improvement plans like the benchmarking of clustered seaports.

• 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.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.

• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.41-58
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• 2020

This study aims to investigate the technical efficiency of major container ports in the Bay of Bengal area and to study how certain factors influence the efficiency of container ports and terminals. The research is conducted on the four main container ports in the Bay of Bengal area, namely, Colombo Port in Sri Lanka, Chennai Port in India, Chittagong Port in Bangladesh, and Yangon Port in Myanmar. There are three input variables (quay length, storage area, and the number of cranes) and two output variables (throughput twenty-foot equivalent units and vessel calls) chosen for the process in this study. This paper evaluates the efficiency score of the defined variables and suggests implications for further improvement of the core competitiveness of the four selected ports. The findings indicate that Colombo Port is the most efficient on a technical scale, followed by Chennai Port, Yangon Port, and Chittagong Port. However, the slack and radial movement calculation results show that the inputs and outputs of the four ports need to be adjusted to be efficient and to reduce the amount of resources that are wasted. The results validate the adaptability of the improved data envelopment analysis algorithm in port efficiency analysis. The research findings provide an overview of the efficiencies of the selected container ports and can potentially affect the port management decisions made by policymakers, terminal operators, and carriers.

• Journal of Navigation and Port Research
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• v.39 no.1
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• pp.55-60
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• 2015

The purpose of this study is to suggest a major strategy to become effective for each port in Northeast Asia by analyzing the relative efficiency of each port to determine the current level of efficiency, efficient harbors plan. Individual port of the major 16 ports in Northeast Asia was analysed targeting efficiency and relative efficiency. In this study, DEA technique was used. Of the DEA model, CCR (constant returns to scale) models and BCC (variable return to scale) model was applied to analyze the efficiency and effectiveness of the port. Then the efficiency measured through CCR model is again compared with the efficiency measured by the BCC model. In this way, the empirical analysis includes the input factors of the operating ports such as the number of berths, wharf, depth, total area of the pier, C / C numbers and output elements includes the container throughput. The results of the study show that most of the ports in China is efficient whereas those in Korea and Japan are relatively inefficient. There are some pairs of ports which has the similar input factors, like Busan port and Shanghai port, Lianyungang port and Incheon port, Dalian port and Gwangyang port, but the container throughput of them has a huge difference.