• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.45-58
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• 2010

This study estimated the technical efficiency of coastal composite fishery in Korea by using the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA) methods, and the results on the respective method were compared. In the DEA method, the constant returns to scale (CRS) and the variable returns to scale (VRS) output-oriented DEA models were separated and technical efficiencies were estimated, respectively. The average estimated value of technical efficiency by the SFA method (0.633) was found to be lower than that by the VRS-DEA method (0.738), while it was higher than that by the CRS-DEA method (0.479). It was found that strong correlation exists between the SFA method and the VRS-DEA method. The method which can utilize both methods in mutually complementing way for the estimation of technical efficiency was also considered.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.2
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• pp.137-160
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• 2004

In order to appreciate the varied activities of university libraries, this study assesses their efficiencies in the process of production and utilization of their services for two consecutive years, 1999 and 2000. Using a Data Envelopment Analysis with exogenously fixed factors, this study analyses separately efficiencies identified. The results show that efficiencies of libraries appear differently according to the year of evaluation, the dimension of evaluation as well as the difference of statute. The specialized libraries as CADIST are definitely higher in terms of use of services. In addition, inefficiency is mainly due to deficits of production of outputs rather than excesses of utilisation of inputs. For example, time devoted to user's training constitutes the most significant potentiality of increase in the production of services.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.2
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• pp.13-18
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• 2015

In this paper the DRC model is presented for solving multi objective problem. The proposed model is a combination of data envelopment analysis, Cuckoo algorithm and the response surface method. Due to reasons like costs, time and irreversible damages, it is not possible to analyze each and every one of the proposed models in practice, so the simulation is used. Since the number of experiments for simulation process is high then the optimization has gone to practice and directs the simulation process. The response surface method is used as one of the approaches of simulation optimization. Furthermore, data envelopment analysis is used to consider several response surfaces as efficiency response surface. Then this efficiency response surface is solved by Cuckoo algorithms. The main advantage of DRC model is to make one efficiency response surface function instate of multi surface function for every output and also using the advantages of Cuckoo algorithms. In order to demonstrate the effectiveness of the proposed approach, the branches of Refah bank in Mashhad is analyzed and the results are presented.

• Health Policy and Management
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• v.6 no.2
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• pp.91-114
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• 1996

In this research, the Data Envelopment Analysis(DEA) was applied to measure production efficiency of Public Corporation Medical Centers(PCMCs) operating in Korea. The focus of this research is triple. First, identifing convenience and usefulness of DEA to measure the relative efficiency among PCMCs. Second, assessing magnitudes of the relative efficiency for each PCMC. Third, adding insights into some factors resulting inefficiency in PCMCs. Then, in this paper technical efficiency and scale efficiency measured by DEA[introduced by Charnes, Cooper, and Rhoides(1978) and Banker, Charnes, and Cooper(1984)] were analyzed and a new separate variable was introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decresing returns to scale(in multiple input and output situations). And a multi-factor Tobit analysis was conducted to see which variables are associated with PCMC's efficiency.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.125-126
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• 2012

Domestic architect office from a period of high growth from the 1970s to the '80s has been established as some of the large corporations or publicly traded corporation. 1997 IMF has pointed out there is a lot of need for improvement activities in accordance with the construction recession since the 2008 global financial crisis. In order to address these causes, the company's continuous efficient operation for accurate efficiency and competitiveness analysis was required. Leverage financial ratio indicators Study Using Data Envelopment Analysis Data Envelopment Analysis (DEA) model, how to find a benchmark for the improvement of the efficiency of inefficient enterprises in various sectors being. In this study, a comparison of the conventional DEA model and the DEA-AR model is used to analyze the efficiency and domestic architect office is to improve the management efficiency.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.141-144
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• 2007

This research aims to propose model for measuring the efficiency of R&D organizations by using Data Envelopment Analysis. In existing research about using Data Envelopment Analysis, the types of R&D organizations have not been clarified and the difference between analysis time from measurement time is usually $4{\sim}5$ years. This research divides R&D organizations into three types and provides proper methods for measuring the efficiency of each R&D organizations.

• Journal of Satellite, Information and Communications
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• v.3 no.2
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• pp.54-59
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• 2008

Traditionally R&D evaluation has been performed by experts who can understand the contents of the study area very well. Recently extensive application of quantitative evaluation methods have been attempted for introducing the administrative management system that poses greater importance on records and results. More objective reviews on the R&D outcomes are called for gaining public supports. In this paper a bibliometrical analysis is to be performed to evaluate satellite communication and broadcasting public R&D outcomes for last 7 years. Data envelopment analysis method is selected for evaluating the efficiencies of multiple outputs (papers, patents, royalties, technology transfers) where multiple inputs (number of researchers and R&D expenses) are given. R&D outcomes from 22 research institutes are being compared and satellite communication and broadcasting R&D efforts turn out to be highly efficient.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.854-855
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• 2007

Analyzing the productivity has been widely applied in economic analysis and of the key concept of utility regulation. In this paper we use benchmarking technique known as Data Envelopment Analysis (DEA) model to analyze the productivity. And we show that from the result it is possible to evaluate the performance of inefficient firms by reducing their input levels.

• Korean Business Review
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• v.3
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• pp.77-98
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• 1990

• Journal of the East Asian Society of Dietary Life
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• v.17 no.5
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• pp.727-737
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• 2007

The aims of this study was to suggest a new efficiency measurement indicator for evaluating the management efficiency of decision making units(DMUs) in the contract foodservice industry. The data envelopment analysis(DEA) model which considers multiple inputs and outputs and looking for benchmarks, was used to compare the productivity of DMUs. We considered sales, profits, and customer satisfaction as output variables and it adopted food cost, labor cost and administrative expense as input variables. The results of applying DEA revealed relatively efficient types of business and service types. The efficiency of school units was highest and the mired service type was the most efficient one. In this study the CCR model efficiency was analysed with profit and the customer satisfaction index by the matrix method. DEA efficiency was correlated with profit but there was no correlation between DEA efficiency and the customer satisfaction index.