• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.697-704
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• 2019

The public has grown more anxious towards domestic earthquakes that have been taking place since 2000, and regulations on seismic design has been strengthened. Out of 4,605 Air Force installations that require the application of seismic design, 2,982 remain unapplied. By taking budget issues and the time spent to implement seismic retrofit into account, this paper aims to list up seismic reinforcement priorities for airmen dormitories where they can potentially be most vulnerable to earthquakes. The priorities are extracted based on Data Envelope Analysis(DEA). To apply DEA, two sets of variables are set: seismic reinforcement costs as input variable: age of building, number of residents, and seismic load as output variables. At the end, suggestions are made for developing seismic reinforcement plans that can be applied to all Air Force installations.

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.59-68
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• 2002

Using 1996 annual observations for 69 bus firms in Seoul, this paper measures firm-level efficiency with data envelopment analysis(DEA) and identifies firm characteristics indicative of differential efficiency in these firms with Tobit regression analysis. The paper then conceptualizes that these firms produce two kinds of output(city/seat bus kilometers or city/seat bus Passengers) using four inputs (labor vehicle, fuel and maintenance). The findings show that, on an average, these firms have only a little input saving potential of 0.9 percent, while not a little output increasing potential of 12.9 percent. On the other hand, it is discovered that these firms operate more efficiently with a lower ratio of maintenance employees to total employees. Furthermore, it appears that both the ratio of seat buses to total buses and average speeds positively affect efficiency in this industry.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.598-604
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• 2014

In this paper, we develop stepwise regression data envelopment model to select important variables. We formulate null hypothesis to understand the importance of each variable and use Kruskal-Wallis test for this purpose. If the Kruskal-Wallis test does reject the null hypothesis this will imply there is significant fluctuation in the efficiency score relative to base model. And therefore we have to further check the pair of variables that causes the fluctuation in order to determine its importance using Conover-Inman test. The proposed models helps understand the extent of misclassification decision making units as efficient/inefficient when variables are retained or discarded alongside provides useful managerial prescription to make improvement strategies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.605-616
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• 2014

The purpose of this study is to analyze transport efficiency of each of the 17 urban railway lines being operated by national public agencies using Data Envelopment Analysis (DEA) and to seek strategies for improving efficiency of the urban railway system. The study identified the economies of scale derived from these values of efficiency and examined the effects on cost for free ride loss and profit of transport by the fare system as the external factor. At the time, Transport profits are estimated by two production factors such as the number of vehicles and service frequency derived from multiple regression. Finally, the measures to improve the efficiency were presented in terms of profitability in the national urban railway line by applying the values of efficiency derived from DEA to multidimensional scaling (MDS).

• Information Systems Review
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• v.15 no.2
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• pp.75-90
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• 2013

This research was undertaken to find out how effectively ERP has been employed by the enterprises through comparing and analyzing the management performance of each enterprise after introducing ERP to Retail and Distribution Industry using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative ERP system usage efficiency of 10 Retail and Distribution Industry Companies in terms of such factors as employee, quick assets, inventories, sales revenue, operating income. This paper confirms that the companies having launched management innovation by aggressively adopting ERP saw their management efficiency improving consistently, and in the distribution industry, it took at least 3 years before the effect of ERP introduction on enhancing management efficiency became visible. Furthermore, this paper also reveals that, unlike the manufacturing industry which was the subject of the previous study, efficiency was not necessarily proportional to the size of company in the service industry including distribution and export which was the subject of this paper.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.303-313
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• 2010

The purpose of this study is to evaluate the performance efficiency and productivity change of the regional public hospital in Korea. We use DEA(Data Envelopment Analysis) for CCR, BCC model, and MPI(Malmquist Productivity Index). DEA is a useful nonparametric technique for measurement of efficiency of a DMU(Decision Making Unit) and MPI is a evaluation method to measure DMU's productivity change. We utilize 34 regional public hospital's time-series data over 6 years from 2003 to 2008.The results of this study were as follows. First, technical efficiency(TE) shows that approximately 3.6% of inefficiency exists on the regional public hospitals and it reveals that the cause for technical inefficiency is due to scale inefficiency. Second, MPI's results show that regional public hospital made effort to improve total factor productivity change to raise technical efficiency. In order to raise efficiency, the regional public hospitals should deploy internal innovation and the government should support welfare policies.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.1
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• pp.49-57
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• 2006

In order to strengthen the competitiveness of port against calling for the huge vessel and reducing the shipping service time, the productivity of container terminal must be improved. This productivity variously results according to the kinds of productivity evaluation model, input elements like yard, equipment, employee, facility, etc,. But, it is discussed that the productivity is measured by partial productivity evaluation model or general input elements. Therefore, we measured for the productivity of the container terminal using the Developed the data Envelopment Analysis (DEA), which is developed in order to evaluate the relative efficiency of decision making units - it's difficult to clear cause and effect between input and output. We measured the whole productivity of container terminal in Busan according to decision of the correct input elements. And we investigated the change of the productivity measurement result according to input elements, presents more accurate productivity evaluation model in container terminal.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.4
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• pp.101-111
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• 2013

In this study, DEA (Data Envelopment Analysis) was carried out on the four bridges, which have the same extension (L=1,615m), in order to select the most superior, economical method of construction using the LCC concept of each bridge structure in the case of the Ulsan-Pohang double track railway which is scheduled to be constructed. DEA models were analyzed with the CCR model, which was designed for the evaluation of relative efficiency of each model. The initial construction costs, maintenance costs, indirect costs (user costs + indirect loss of social costs), and life cycle costs were used as input variables, and average duration was applied as the output variable. LCC was applied to calculate the input variables, and to get the costs of LCC, 100 years of period and 4.83% of real discount rate were applied, and the costs are classified into initial construction, maintenance, user, and indirect loss of social cost. The analysis results showed that the Method 2 and 3 were evaluated as the most efficient, and the other alternatives were evaluated as the following order; Method 1, the default, and Method 4.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.63-79
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• 2001

Data Envelopment Analysis(DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications and merits, some features of DEA remain bothersome. DEA offers no guideline about to which direction relatively inefficient DMUs improve since a reference set of an inefficient DMU, several efficient DMUs, hardly provides a stepwise path for improving the efficiency of the inefficient DMU. In this paper, we aim to show that DEA can be used to evaluate the efficiency of life insurance companies while overcoming its limitation with the aids of machine learning methods.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.225-226
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• 2014

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 ${\cdots}$(중략)${\cdots}$.