• 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.

• 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.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.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.

• Management & Information Systems Review
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• v.37 no.1
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• pp.103-122
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• 2018

This paper expands the results of previous studies indicating that manager's ability positively affects business performance to analyze whether the degree to which the role of manager's ability improves business performance appears differently according to the characteristics of enterprises. As for the characteristics of enterprises, whether enterprises correspond to enterprises with high levels of funding constraints or late movers in the market is considered. Enterprises with high levels of funding constraints greatly require managers' roles not only for efficient use of funds but also for smooth financing. Late movers require more judgments of professional managers to overcome insufficient resources held and low profitability. In the case of enterprises with corporate characteristics with high dependency on the manager, the business performance is expected to greatly vary with the ability of the manager. The empirical analysis was conducted with listed companies from 2010 to 2014, manager's ability was measured by first measuring the efficiency of the entire enterprise through data envelopment analysis (DEA) using the methodology of Demerjian et al.(2012) and removing enterprise characteristics factors thereafter. Business performance was measured by the return on industrial fixed assets. The results of the empirical analysis indicated that the degree to which manager's ability improves business performance was higher in managerial competence enhances managerial performance in enterprises with high levels of funding constraints and late movers. Business performance is considered to have been improved further in cases where manager's ability is high because investments were made more efficiently through smooth funding. In addition, in the case of late movers in relatively poor environments, business performance was improved further because high manager's ability induced efficient decision making. In this paper, we extend the precedent study that the manager's ability improves the management performance, and confirm that the manager's ability to improve the managerial performance can be different according to the situation of the company. In addition, it is meaningful to analyze empirically whether a company's managerial ability is more important. This paper expanded the results of previous studies indicating that manager's ability improves performance to identify that the degree to which manager's ability improves business performance may appear differently according to situations in which enterprises are placed. In addition, this paper is meaningful in that it empirically analyzed what enterprises require manager's ability more importantly.

• 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.36 no.3
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• pp.1-20
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• 2020

Coastal ferry routes are very important because they connect the mainland to islands, offer transportation for islanders, and bring tourism to islands. In particular, the recent increase in national income, prevalence of a culture that emphasizes work-life balance, and introduction of the five-day workweek have stoked interest in travel as a leisure pursuit, and demand for tourism from Korean people in islands has increased. As the number of passengers using coastal passenger terminals increases due to changes in the coastal tourism environment, the importance and need for coastal passenger terminal facilities and services is growing. Under these circumstances, it is necessary for the management organizations of coastal passenger terminals to manage and efficiently operate the terminals in such a way that budgets can be reasonably implemented and the convenience of passengers using the terminals is enhanced. This study primarily analyzed the management efficiency of coastal passenger terminals in terms of profitability and public interest using data envelopment analysis. The eight passenger terminals achieved low management efficiency in terms of profitability. These terminals should improve profitability by increasing income from terminal office rental and ancillary businesses and revenue from terminal fees by boosting island tourism and expanding overseas passenger transportation. The eight terminals with low management efficiency for public interest should increase the number of passengers by promoting island tourism, developing tour packages to Japan and China's coastal areas, developing new routes, and introducing super-high-speed ships.

• Korean Journal of Social Welfare
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• v.52
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• pp.117-141
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• 2003

This study is to identify the efficiency in Busan social welfare agencies between input factors and output factors. For this purpose, gathered are the 2001 services reports of those study agencies. This study used 4 difference model, model 1; comparing input factor(social worker number & labor cost) about output factor(the total number of program used person), model 2; comparing input factor(the total number of social welfare agencies staff & the total working expenses) about output factor(the total number of program used person), model 3; comparing input factor(the total number of volunteer, social welfare agencies staff & a period of operation) about output factor(the total number of program used person), model 4; comparing input factor(the total number of volunteer, social welfare agencies staff, a period of operation & the total working expenses) about output factor(the total number of program used person). Charnes's study(1978) provided an analytical tool for efficiency services output of non-profit organizations, and DEA(Data Envelopment Analysis) was a analytical framework for evaluating the impact of social service outcome. the finding are as follows : (1) In the results of comparing 4 models as same standard, we can find 35-55%(16-25) efficiency agencies among the 45 social welfare agencies. (2) For all DMU becoming the efficiency 1 to standard of output factor, model 1; 33 agencies are increasing the social worker number($\Delta$0.8 number), 10 agencies are raising the labor cost of social worker($\Delta$1,189,000 Won), model 2; 30 agencies are increasing the total number of social welfare agencies staff($\Delta$1.25 number), 14 agencies are raising the total working expenses($\Delta$1,447,000 Won), model 3; 8 agencies are increasing the total number of social welfare agencies staff($\Delta$2.26 number), 14 agencies are increasing the total number of volunteer($\Delta$52 number), and 10 agencies are increasing a period of operation($\Delta$13 month), model 4; 24 agencies are increasing the total number of social welfare agencies staff($\Delta$1.8 number), 12 agencies are raising the total working expenses($\Delta$5,017,000 Won), 12 agencies are increasing the total number of volunteer($\Delta$43.2 number), and 23 agencies are increasing a period of operation($\Delta$16 month).

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.188-206
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• 2010

Data Envelopment Analysis(DEA) is an operations research-based method for measuring the performance efficiency of decision units that are characterized by multiple inputs and outputs. DEA has been applied successfully as a performance evaluation tool in many fields. However, it has not been extensively applied in the shipbuilding industry. This paper applied the input-oriented DEA model, and Malmquist indices to the 7 shipbuilding firms to measure the efficiency and productivity changes during the period of 2004 to 2009. The Malmquist indices will be decomposed into three components such as pure efficiency change, scale efficiency change, and technical change. The empirical results show the following findings. First, the DEA findings indicate that main source of inefficiency is scale rather than pure technical. Second, the Malmquist indices show that an overall decrease in productivity.

• 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.