• Environmental and Resource Economics Review
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• v.15 no.1
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• pp.71-94
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• 2006

Reducing fishing capacity is one of hot issues in the world fisheries. Increased fishing capacity causes not only fish stocks to be depleted, but also additional fishing costs to be incurred, resulting in reductions of fishing profits. In order to achieve a sustainable and profitable development of fisheries, it is inevitable to reduce fishing capacity. For this reason, FAO adopted 'the International Plan of Action for the Management of Fishing Capacity' and recommended member countries to estimate fishing capacity and to implement the policy to reduce fishing capacity. This study is aimed at measuring fishing capacity of Large Purse Seines Fishery using a Data Envelopment Analysis (DEA). The DEA result showed that the practical catch of large purse seine fishery in 2003 was 158,662 tons, but the capacity output for current input was 318,397 tons. The capacity utilization is about 50%, it is obvious the capacity did not utilize enough. The sensitivity analysis on DEA results indicated that the number of ships (including tonnage and horse power) should be scrapped by 50% or days fished should be reduced by 63% if the present catch remained. In addition, if the catch remains at the MSY base level of large purse seines, the analysis suggested that the number of ships (including tonnage and horse power) should be reduced by 30%, otherwise days fished should be reduced by 60%.

• Korea Journal of Hospital Management
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• v.21 no.1
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• pp.43-50
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• 2016

The public medical centers are required to make efficient and profitable operation. The efficiency is usually measured by DEA(data envelopment analysis), and profitability is measured by medical income rate. But DEA is measured by relative, not absolute value. So, profitability rate is used alternatively for DEA. This study want to analyze the interchangeability between DEA ranking and medical income rate ranking among public medical centers. The return on total assets is same ranking with DEA on bed number, employee number and total asset, but 60-70% relationship with DEA on bed number and employee number, as input resources. The operating margin is similar ranking with DEA on bed number and employee number, but 50-60% relationship with DEA on bed number, employee number and total asset, as input resources.

• The Journal of Fisheries Business Administration
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• v.49 no.4
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• pp.1-17
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• 2018

The Korean fisheries industry is a traditional business, the majority of which are small and medium-sized enterprises (SMEs). It has played an important role in the South Korean economies in the past several decades, but it currently faces the limitations of growth potential and profitability due to declining workforce, aging populations, deteriorating fishery environments, climate changes, and rapid changes in the global industrial ecosystem. Many studies have suggested solutions for the fisheries industry in macro perspective, but there are rarely any studies taking the strategic approaches for the problem. If it is possible for governments to support the companies that are likely to increase their value-added selectively, it will break through the current situation more effectively. This paper introduces a study on the selection method utilizing data envelopment analysis (DEA) to find SMEs with potentials to increase profits and growth. We suggest selecting SMEs with high management efficiency and ability to utilize intangible assets as the target companies. We also suggest policy objectives for SMEs in the domestic fisheries industry based on the results of DEA analysis and propose a data-based method for the policy decisions.

• IE interfaces
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• v.17 no.4
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• pp.440-449
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• 2004

The OERA(Offensive Earned-Run Average) is a methodology for the performance evaluation of baseball players, which is based on a well- known Markov chain model. The DEA(Data Envelopment Analysis) is an LP-based evaluation technique for performance analysis of DMUs (Decision Making Units), whose production activities are characterized by multiple inputs and outputs. In this paper, the performances of Korean professional baseball players are analytically evaluated using both OERA and DEA methods. We discuss methodological strengths and drawbacks of two kinds of baseball evaluation techniques, by comparing both results. Finally to overcome the shortcomings of both methods, we develop a new analytical approach for baseball evaluation by combining OERA with DEA.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.99-111
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• 2016

This paper presents a framework to analyze the change in the research and development (R&D) efficiency of government-funded research institutes (GRIs) in Korea. Cumulative data envelopment analysis/Malmquist index method is utilized to analyze the changes in R&D efficiency of GRIs. Data analysis of the R&D activities of 10 GRIs in Korea Research Council of Fundamental Science & Technology showed that the average R&D efficiency of the 10 GRIs improved from 2009 to 2013. However, the efficiency of a few GRIs decreased in terms of the catch-up index. The proposed framework can help management teams diagnose the current state of R&D activities and determine the efficacy of strategic actions by comparing efficiencies in the past.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.299-312
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• 2009

Unlike profit-seeking businesses, hospitals provide medical services to promote the public good in a way, and they need a reform of management to ensure sustainable growth in fast-changing medical environments. The key to the managerial reform is enhancing efficiency, and inefficient managerial practices and factors affecting that should be grasped first of all to boost the efficiency of hospital management. But evaluation methods that are prevalent in the private sector are hardly applicable to hospitals. The purpose of this study was to assess hospital efficiency by using a data envelopment analysis(DEA). The 2006 data on 74 residency training hospitals with 500 beds or more were analyzed. The selected input variables included the number of bed, the number of doctors, the number of nurses, the number of medical technicians, personnel expenses, management cost and materials cost. And the selected output variables were the yearly number of outpatients, the yearly number of inpatients, the number of operation cases and earnings. In addition, the influence of the type of hospital establishment, location, the year of foundation and the type of hospital on hospital efficiency was checked as well.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.165-166
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• 2015

Sea-ports in Northern Vietnam have experienced a rapid growth of container throughput volume in recent years. To accompany with such development, huge investments also have been performed to enhance local ports capacity. It becomes a crucial task for the port authorities or the port stevedoring industry to improve the ports efficiency in order to customize national resources. In this paper, Data Envelopment Analysis (DEA) is employed to evaluate the relative efficiency of container terminals in Northern Vietnam by collecting data from terminals since 2005 up to now. The development progress of the given terminals will be presented before providing a relative comparison among those year by year. The DEA result is then analyzed and suggestions with regard to changes in local economic environment in near future are contributed.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.43-55
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• 2015

Objectives : This study analyzed the managerial efficiency of hospitals and identified the productivity trends for three years. Methods : Data were collected from 44 tertiary hospitals and 32 university hospitals from 2009 to 2011. Efficiency scores and productivity trends were evaluated with the DEA (Data Envelopment Analysis) method. The input variables were the numbers of beds, doctors, nurses, and health personnel, and the medical costs. The output variables were the numbers of outpatients, and inpatients, and the medical revenues. Along with the traditional input-oriented DEA analysis, the Malmquist Productivity Index(MPI) was calculated. Results : First, the mean values of the study variables showed gradual increases in all the variables for all the study years. Second, technical efficiency scores varied depending on the study year. Third, MPI decreased from 2009 to 2010 (MPI=0.986), and then increased from 2010 to 2011(MPI=1.011). The contributions of the Efficiency Change Index and Technical Change Index on the MPI varied depending on the study year. Conclusions : This study provides information to hospital managers about changes in hospital performances. External environments had more influence on hospital performances, and hospital managers will need to manage these influences from factors surrounding the hospitals.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.527-534
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• 2012

In order to achieve sustainable growth and gain competitive advantages business performance should be monitored regularly by a company. In the port industry container terminal operators are facing growing competition. A large scale of new container terminals are constructed and the number of new container terminal operators are increasing. Container shipping lines are gaining bargaining power against terminal operators in terms of negotiating terminal usage. The competitive environments result in reduced cargo handling charges and poor financial performance of container terminal operators. It becomes very important to examine how efficiently container terminal operators are operating their terminals and how to improve their performance. This paper investigates the measurement efficiency for container terminal operators in Korea using Data envelopment analysis(DEA) of DEA-CCR and DEA-BCC Model. This paper finds out which container terminal operators are inefficient and how to improve their management efficiency.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.161-167
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• 2017

This paper measured and evaluated the technical efficiency, pure technical efficiency and scale efficiency of port labor via three inputs and three outputs using Data Envelopment Analysis (DEA). First, the average overall technical efficiency measured about 94.18 %, with 100 % pure technical efficiency being larger than 94.18% scale efficiency. As a result, 7 ports were identified as efficient, and 4 ports were identified as inefficient. Among the 4 ineffiecient ports, Donghae had the highest Increasing Return to Scale (IRS). However, the inefficient ports were all found to be less efficient in terms of resource operation than production scale. On the other hand, the efficient ports established priorities using the super efficiency method. As a result, port efficiency was highest for Incheon, Mokpo, Pyeongtaek-Dangjin, Masan, Yeosu Gwangyang, Jeju, and Gunsan-Daesan Ports, in order. In particular, Busan Port, found to be inefficient, would benefit from using Mokpo Port and Incheon Port as benchmarks to increase trade volume and modernize equipment for full-scale commercialization to improve labor efficiency.