• Journal of agriculture & life science
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• v.45 no.6
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• pp.279-289
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• 2011

The purpose of this study is to estimate efficiency of item-based agricultural cooperative by using Data Envelopment Analysis. A proposed method employs a bootstrapping approach to generating efficiency estimates through Monte Carlo simulation resampling process. The technical efficiency, pure technical efficiency, and scale efficiency measure of item-based agricultural cooperative is 0.80, 0.87, 0.93 respectively. However the bias-corrected estimates are less than those of DEA. We know that the DEA estimator is an upward biased estimator. In technical efficiency, average lower and upper confidence bounds of 0.726 and 0.8747. According to these results, the DEA bootstrapping model used here provides bias-corrected and confidence intervals for the point estimates, it is more preferable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.6
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• pp.1304-1316
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• 2009

This study is for the pursuit of the basic application of the efficient conversion factor in the fee contract. This aims to investigate the effects of DEA efficiency index and conversion factors to identify and group the 60 hospitals with intern and residents education. To achieve the aims, AHP was used to select the inuput and output variables for DEA. It was found that the more inefficient in the technical and scale side, the higher the conversion factors were. Conversion factor and DEA efficiency index can be used very effectively to group and discriminant hospitals into a specialized general hospital and a general hospital. Even if the variables used to calculate DEA efficiency are applied to discriminant analysis, The conversion factor and DEA efficiency index have a significant power to make a function modeling. So, if we can make a more conclusive proof based on the large number samples, We can imagine to introduce a efficiency concept in the insurance fee contracts about a conversion factor in Korea Health Insurance System.

• Safety and Health at Work
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• v.1 no.2
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• pp.175-182
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• 2010

Objectives: This study examined how ethanolamines (EAs) with the same functional alcohol group ($HOCH_2CH_2$), such as mono-EA (MEA), di-EA (DEA), and tri-EA (TEA), in water-based metalworking fluids (wbMWFs) are vaporized, condensed, and transformed by heat generated during metalworking. Methods: Two types of experimental apparatus were manufactured to achieve these objectives. Results: Vaporization tests using a water bath showed that the vaporization rate increased markedly from $0.19\;mg/m^2{\cdot}min$ at $23.5^{\circ}C$ to $8.04\;mg/m^2{\cdot}min$ at $60^{\circ}C$. Chamber tests with a heat bulb revealed that "spiked" MEA was fully recovered, while only 13.32% of DEA and no TEA were recovered. Interestingly, non-spiked types of EAs were detected, indicating that heat could convert EAs with more alcohol groups (TEA or DEA) into other EAs with fewer group(s) (DEA or MEA). The EA composition in fresh fluid was 4% DEA, 66% TEA, and 30% MEA, and in used fluids (n = 5) was 12.4% DEA, 68% TEA, and 23% MEA. Conversion from TEA into DEA may therefore contribute to the DEA increment. Airborne TEA was not detected in 13 samples taken from the central coolant system and near a conveyor belt where no machining work was performed. The DEA concentration was $0.45\;mg/m^3$ in the only two samples from those locations. In contrast, airborne MEA was found in all samples (n = 53) regardless of the operation type. Conclusion: MEAs easily evaporated even when MWFs were applied, cleaned, refilled, and when they were in fluid storage tanks without any metalworking being performed. The conversion of TEA to DEA and MEA was found in the machining operations.

• Journal of Korea Port Economic Association
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• v.38 no.2
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• pp.123-138
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• 2022

Korea has been huge investments in its port system, annually upgrading its infrastructure to turn the ports into Asian hub port. However, while Busan port is ranked fifth globally for container throughput, Other Korean ports are ranked much lower. This article applies Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI) to evaluate selected major Korean seaports' operational efficiency and productivity from 2010 to 2018. It further integrates Principal Component Analysis (PCA) into DEA, with the PCA-DEA combined model strengthening the basic DEA results, as the discriminatory power weakens when the variable number exceeds the number of Decision Making Units(DMU). Meanwhile, MPI is applied to measure the seaports' productivity over the years. The analyses generate efficiency and productivity rankings for Korean seaports. The results show that except for Gwangyang and Ulsan port, none of the selected seaports is currently efficient enough in their operations. The study also indicates that technological progress has led to impactful changes in the productivity of Korean seaports.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.57-67
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• 2015

Objectives : This study has analyzed the relationship between DEA efficiency of costs-patient revenues, productivity per value added and management performance in mental hospitals. Methods : The relationship between DEA efficiency of costs-patient revenues, the productivity per value added and management performance were conducted with correlation analysis and logistic regression. Results : The DEA efficiency of costs-patient revenues had a significant causal relationship with the value added ratio to gross revenue indexing productivity per value added. On the other hand, it was revealed that the operating margin indexing management performance had a slightly significant causal relation with DEA efficiency of costs-patient revenues. Conclusions : The material costs should be focused on the management stability of mental hospitals, and known to the desirable management orientation for the higher efficiency of costs-patient revenues.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.517-521
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• 1998

DEA(data envelopment analysis) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities with common crisp inputs and outputs. In fact, in a real evaluation problem input and output data of entities often flucturate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers. Based on a fundamental CCR model, a fuzzy DEA model is proposed to deal with fuzzy input and output data, Furthermore, a model that extends a fuzzy DEA to a more general case is also proposed with considering the relation between DEA and RA (regression analysis) . the crisp efficiency in CCR modelis extended to an L-R fuzzy number in fuzzy DEA problems to reflect some uncertainty in real evaluation problems.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.800-806
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• 2007

IT 벤처기업은 자본 대비 높은 수익성을 가지므로 지식기반 산업환경에서 많은 투자자들의 집중적인 관심을 받고 있다. 이러한 IT 벤처기업의 효율성을 평가하기 위한 방안으로, DEA 와 데이터마이닝 기법을 통합하는 방안을 제시하였다. 국내 코스닥 상장 기업 가운데 IT 에 주력하고 있는 벤처기업들을 대상으로 본 연구에서 제시한 효율성 평가방법을 적용 하였다. 대표적인 비모수적 분석기법인 Data Envelopment Analysis(DEA)를 이용하여 연구대상 기업들을 효율기업 및 비효율기업으로 구분한 후, DEA 의 효율성을 설명하는 모형을 logit 을 이용하여 구축하였다. DEA 는 기업의 상대적인 효율성을 측정하는 데에서 우수하지만, 효율성 정도를 설명하는 모형의 구축에는 한계가 있다. 이를 보완한 DEA 의 결과를 logit 과 통합한 효율성 모형에 대해서 데이터 마이닝 기법인 logit, 판별분석, Support Vector Machine(SVM) 등을 적용하여 IT 벤처기업의 효율성을 사전에 예측하여 평가 및 투자에 활용할 수 있는 방안을 제시하였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.365-373
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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 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.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.449-458
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• 2004

Data envelopment analysis (DEA) estimators have been widely used in productivity analysis. The asymptotic distribution of DEA estimator derived by Kneip et al. (2003) is too complicated and abstract for analysts to use in practice, though it should be appreciated in its own right. This paper provides another way to express the limit distribution of the DEA estimator in a tractable way.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.80-90
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• 2009

Nowadays, there are many companies which employ the SQI measurement to assess service quality. The purpose of this study is to measure the service efficiency for Bank Industry. In this paper, we tried to measure the efficiency of service quality and overall customer satisfaction by using Data Envelopment Analysis(DEA). Rather than using the usual method of converting the Service Quality Index(SQI) into mean value, we applied CCR/BCC models in DEA to service quality efficiency. Also, DEA/PS Model is recommended as appropriate model for evaluating service efficiency by complementing the shortfalls of the weighted value of DEA Model. In this study, six dimensions of service quality were considered as input variables and output variables(overall customer satisfaction, reusing intention, and word of mouth). The result of this study statistically verifies that 5 DMUs are relatively efficient, and intensive activities for service efficiency are needed for 20 sample branches. Managerial implications based on the analysis were suggested.