• 기술혁신학회지
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• 제3권3호
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• pp.36-52
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• 2000

This study takes an issue of efficiency analysis in the presence of network effect utilizing the DEA (Data Envelopment Analysis) framework. Network effect has important policy implication for the regulation of local monopolies which undertake their business through physical network, such as electricity, natural gas, local telephony, etc. If the difference in spatial condition between companies is not controlled properly, the performance comparison and associated incentive regulation bear significant bias. In this study, we propose a methodology to measure the true managerial or technical efficiency apart from efficiency difference accruing from the difference in spatial condition. A series of modified DEA efficiency models are combined to investigate the extent of exogenous and endogenous efficiency component in the Korean natural gas distribution companies. Empirical results show that the network effect plays significant role in determining superficial performance difference.

• 한국경영과학회지
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• 제37권4호
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• pp.125-138
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• 2012

Health care that is considered to be one of the major factors for the quality of life is nowadays receiving a great deal of attention, and thus there is a growing need in Korea to identify the efficiency of national medical service and enhance the competitiveness. Although there exist studies on the medical service efficiency about general hospitals and local hospitals, they mostly deal with the efficiency problems from a domestic and regional perspective. In response, this paper analyzes the competitive efficiency of national medical service with respect to 16 OECD countries, by exploiting Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). Building on the DEA and MPI analysis results, this paper identifies the competitive position of Korean national medical service and suggests implications for the medical service improvement.

• 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.

• 한국식생활문화학회지
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• 제31권4호
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• pp.339-347
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• 2016

With the interest on operational efficiency due to the rapid growth of food material distribution industry and food service industry, the study adopts DEA (Data Envelopment Analysis) model and examines to measure the technological, pure technical and scale efficiency those companies engaging in the food material distribution and food service business. As a result of analysis, the companies operating integrated business have relatively higher efficiency than those operating only food material distribution or food service companies while the result indicates that three efficiencies don't have significant difference depending on whether affiliated companies or not. In the results from the measuring by DEA.

• 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.

• East Asian Economic Review
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• 제19권2호
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• pp.167-188
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• 2015

The objective of this study is to obtain a better understanding of the current rice production condition in Myanmar through efficiency analysis, especially, to examine the impact of farm mechanization on Myanmar rice production efficiency. For representation of efficiency and the determinants, this paper uses both the data envelopment analysis (DEA) and the stochastic frontier approach (SFA) with variable returns to scale on Myanmar rice production. The efficiency of the rice production was estimated and subsequently the determinants factors were investigated based on the estimated efficiency level of these sample farmers. The empirical evidence finds that farm mechanical tools significantly improve the Myanmar rice production efficiency.

• 한국IT서비스학회지
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• 제6권1호
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• pp.65-81
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• 2007

Recently, the affiliates of the Ministry of Information and Communication have been conducting a performance evaluation study on IT policy projects, based on the performance evaluation model of the U.S. Office of Management and Budgets, with regard to investment in computerization. The performance evaluation model for the policy project could provide the objective information required for the planning, development, and operation of the policy project. However, the performance of the most policy project is likely to be evaluated using the subjective evaluation criteria of evaluators. Therefore, this case study evaluates the relative efficiency using DEA (Data Envelopment Analysis) in order to improve the performance evaluation method of the digital pioneer' project implemented by the Korea IT Industry Promotion Agency. The improvement value of inefficient Decision Making Units (DMUs) was measured by a static efficiency analysis. The measured value will suggest a objective viewpoint of the performance between DMUs to evaluators. In doing so, it will show an appropriate direction for the policy project to be evaluated successfully.

• 한국전자거래학회지
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• 제26권2호
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• pp.45-59
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• 2021

4차 산업혁명의 핵심 동인으로서 Software(이하 SW)의 중요성이 더욱 커짐에 따라, 정부는 국가 경쟁력 강화를 위해 SW R&D 투자를 늘리고 SW 관련 정책을 지속적으로 수립하고 있다. 하지만 SW 연구개발에 대한 정부의 지속적인 투자에 비해, SW 연구개발 투자성과에 대한 체계적 분석은 부족한 실정이다. 본 연구에서는 Data Envelopment Analysis(DEA) 기법을 이용하여 SW 국가연구개발 사업의 분야별 효율성을 분석하였다. 2008년~2018년까지 정보통신산업진흥원(NIPA)에서 수행된 1,463개 과제정보를 토대로 효율성을 정태적/동태적 관점에서 측정하였다. 정태적 관점의 규모효율성 측정을 통해 비효율성 원인을 규모와 기술문제로 분석하였다. DEA/Window 모형을 이용한 동태적 효율성 분석 결과를 제시하고 효율성-안정성 매트릭스를 이용해 분야별 대응 모델을 제시하였다. 본 연구는 SW 국가연구 개발사업 전체를 대상으로 효율성 분석을 수행했다는 점에 의의가 있으며, 정태적/동태적 효율성 분석결과는 향후 SW 국가연구개발사업 기획 시 기초자료로 활용이 가능할 것으로 기대된다.

• 한국산학기술학회논문지
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• 제16권12호
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• pp.8719-8727
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• 2015

본 연구는 장미농가의 생산효율성을 측정하고, 경영의 비효율성에 영향을 미치는 요인을 파악하기 위한 연구이다. SFA(Stochastic Frontier Analysis) 기법과 DEA(Data Envelopment Analysis) 기법을 사용하여 생산효율성을 측정하였으며, 효율성에 영향을 미치는 요인을 분석하기 위하여 Tobit 회귀 분석을 실시하였다. 먼저, SFA 방법을 통한 생산효율성은 88.4%으로 측정되었으며, DEA 방법에서 불변규모수익(CRS) 모형과 변동수익규모(VRS) 모형을 통해서는 생산효율성이 각각 78.5%와 85.2%로 측정되었다. 특히 두 가지 방법의 생산효율성 측정결과는 각 경영체의 효율성 순위를 동일하게 설명하고 있어 상호보완적이다. 다음으로 Tobit 분석 결과, 투입한 6개의 변수가 모두 효율성에 영향을 미치는 것으로 나타났으며, 종묘비와 제재료비는 (+) 부호를 나타냄과 동시에 회귀계수가 가장 크게 나타나 효율성에 미치는 영향력이 가장 큰 경영 항목으로 분석되었다. 이러한 결과는 장미농가는 종묘비와 제재료비의 투입을 증대시켜 더욱 높은 소득을 창출하는 방식으로 경영 효율성을 증대시켜야 함을 시사한다.

• 보건행정학회지
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• 제30권2호
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• pp.199-210
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• 2020

Background: Based on the importance of ceasing smoking programs to control the regional disparity of smoking behavior in Korea, this study aims to reveal the variation of smoke rate and determinants of it for 229 provinces. An evaluation of the relative efficiency of the cease smoking program under the consideration of regional characteristics was followed. Methods: The main sources of data are the Korean Statistical Information Service and a national survey on the expenditure of public health centers. Multivariate regression is performed to figure the determinants of regional variation of smoking rate. Based on the result of the regression model, clustering analysis was conducted to group 229 regions by their characteristics. Three clusters were generated. Using data envelopment analysis (DEA), relative efficiency scores are calculated. Results from the pooled model which put 229 provinces in one model to score relative efficiency were compared with the cluster-separated model of each cluster. Results: First, the maximum variation of the smoking rate was 16.9%p. Second, sex ration, the proportion of the elder, and high risk drinking alcohol behavior have a significant role in the regional variation of smoking. Third, the population and proportion of the elder are the main variables for clustering. Fourth, dissimilarity on the results of relative efficiency was found between the pooled model and cluster-separated model, especially for cluster 2. Conclusion: This study figured regional variation of smoking rate and its determinants on the regional level. Unconformity of the DEA results between different models implies the issues on regional features when the regional evaluation performed especially on the programs of public health centers.