• 한국경영과학회지
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• 제24권2호
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• pp.53-68
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• 1999

This paper presents a nonparametric method to test if the mean difference of DEA efficiency estimates between two groups statistically exists. A proposed method employs a bootstrapping approach to generation BCC efficiency estimates through Monte Carlo simulation resampling process. For the purpose of demonstration, we empirically apply the proposed method to the korean bank industry and compare its result with the result by the traditional deterministic DEA method. The nonparametric statistical hypothesis testing procedure in this study, which considers not only stochastic variability of the DEA data, but also random radial deviations off the efficient frontier, serves as a useful tool for dbjectively evaluating whether the mean difference of DEA efficiency estimates between groups is statistically significant.

• 산업공학
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• 제17권4호
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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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.405-408
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• 2005

현대 기업 환경에서 리스크 관리의 중요성이 증가함에 따라 기업도산예측을 위한 다양한 통계모형들이 개발되었다. 그러나 이러한 모형들은 기업도산에 영향을 미치는 변수들에 대한 사후적 정보와 함께 도산여부에 대한 사전적 정보를 반드시 필요로 하는 한계가 있다. 이에 따라 DEA가 기업도산예측을 위한 대안으로 연구되고 있다. DEA는 도산여부에 대한 사전적 정보 없이 사후적인 정보만을 가지고 의사결정단위(DMU)의 효율성(재무신뢰도)을 측정할 수 있는 장점이 있다. 그러나 지금까지 기업도산예측에 활용된 DEA 모형은 바람직하지 않은 산출물(negative outputs)은 다루지 못하는 한계가 있었다. 이에 본 논문에서는 Negative DEA 방법을 소개하고, 이를 기존의 DEA 방법과 병행하여 기업도산예측에 적용함으로써 기업도산예측을 위한 대안적 방법을 제시하고자 한다.

• 한국인쇄학회지
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• 제16권3호
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• pp.61-80
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• 1998

To investigate in influence of photosensitizer used with benzophenone(BP) in the curing rate and physical properties of UV curable hard coating on plastic, we prepared UV curable clear and pigmented coatings with DEA, DMA, NPM and TEA as photosensitizer, respectively. The curing rate calculated from the decrease of the absorbance of acrylic double bond measured by FT-IR spectroscopy increased s follows; DEA>DMA>NPM>TEA. this order could be explained by the reactivity of diethylamino group of DEA and the ease of formation of activated complex between BP and photosensitizer during the curing process. In UV curable pigmented coatings, the order of curing rate increased as follows; DEA>DMA>TEA>NPM. It was found that the curing rate of the pigmented coating can be increased by light scattering of TiO$_2$. The hardness of coating film cured by photosensitization of DEA and DMA is higher than other photosensitizers due to the crosslinking reaction of DEA and DMA radical bound to polymer backbone.

• 농촌지도와개발
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• 제23권4호
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• pp.441-448
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• 2016

The study aims to explore the problems of analysis unit when examining management performance and efficiency using DEA (Data Envelopment Analysis). Generally the DEA results depend on input, output, and analysis units. We used data from Park (2012) which analyze paddy farmers in Jeonnam province. Results show that data from farm household unit was well fitted to examine management efficiency, not data from per area unit. This study will be helpful for researchers and practitioners to understand proper analysis unit when using the DEA for enhancing farm competitiveness.

• 한국병원경영학회지
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• 제2권1호
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• pp.22-47
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• 1997

This paper evaluated the relative efficiency of 33 provincial medical centers using Data Envelopment Analysis(DEA) and compared the DEA efficiency results with those of the current method conducted by the management evaluation team. DEA Was selected as an alternative efficiency evaluation method since it could handle multiple inputs and multiple outputs simultaneously and identify the sources of inefficiency. To analyze the sensitivity of productivity values to the variable sets, four different sets of input and output variables were identified. Results showed that most of the medical centers are operating far away from the efficiency frontier supporting the previous results. Some centers showed 100% efficiency regardless of the selected variable sets. DEA results are compared with current management evaluation results. Some inconsistencies were found for some DMUs between the results of two methods showing the existence of methodology bias. DEA results and ratio analyses results mostly agree for 1992 data.

• 한국경영과학회지
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• 제37권1호
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• pp.29-43
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• 2012

We design a DEA-AR model using multiple regression analysis with new methods which limit weights. When there are multiple input and single output variables, our model can be used, and the weights of input variables use the regression coefficient and coefficient of determination. To verify the effectiveness of the new model, we evaluate the efficiency of the Regional Corporations in Korea. Accordance with statistical analysis, it proved that there is no difference between the efficiency value of the DEA-AR using AHP and our DEA-AR model. Our model can be applied to a lot of research by substituting DEA-AR model relying on AHP in the future.

• Asia pacific journal of information systems
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• 제10권1호
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• pp.19-35
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• 2000

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, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

• 한국문헌정보학회지
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• 제36권3호
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• pp.275-286
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• 2002

본 연구는 Charnes, Cooper와 Rhodes에 의하여 고안된 DEA기법을 이용하여 서울지역에 소재하고 있는 29개 대학도서관의 효율성을 평가하였다. DEA의 투입물로는 면적, 직원수, 장서수로 하고, 산출물은 이용책수와 이용자수로 하여 효율성을 계산하였다. 그 결과 평균효율성은 0.5248로 나타나서 비효율성은 47.52%로 나타났다. 이러한 효율치는 투입물과 산출물의 수나 혹은 정의가 다르면 서로 다른 결과를 보여 줄 수 있으므로 절대적인 것은 아니다. 그러나 DEA에서 계산된 정보를 이용하여 적정투입물과 적정산출물을 구할 수 있기 때문에 DEA에 의한 분석정보를 적절하게 사용하면 도서관의 운영효율성을 개선하는 데 도움이 될 것이다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2006년도 춘계 국제학술대회 논문집
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• pp.77-88
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• 2006

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, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.