• Journal of Digital Convergence
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• v.12 no.8
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• pp.139-146
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• 2014

We investigated the relative efficiency and statistical analysis of Kimchi-related manufactures in Jeollabuk-do for their management efficiency and improvement plans. We used data enveloped analysis (DEA) for the relative efficiency, and principal component analysis (PCA) and t-test for the statistical analysis. We analyzed 34 DMUs among 67 DMUs located in Jeollabuk-do. The results were as follows; the statistical efficiency, pure statistical efficiency, scale efficiency for 34 DMUs were 0.653, 0.761, and 0.863, respectively. The correlated component regression (CCR) showed that DMUs above efficiency 1 were 61.5% among -si (urban area), and 23.8% among -gun (rural area), respectively. However, there were not the significant differences of and BCC, CCR, and scale efficiency between urban area and rural area. This study will be useful for local industry's promotion by providing the information on Kimchi-related manufactures.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.103-114
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• 2014

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple performance factors that are grouped into outputs and inputs. DEA has proven to be superior to simple aggregation of performance measures, and is also useful for evaluating the performance of construction companies for comparison with competitor performance. The purpose of this study was to survey literatures on the application of DEA methodology and to propose a methodological scheme to measure the performance of construction organizations. Articles on previous studies were surveyed and examined as part of a comprehensive review. The survey revealed that the application of DEA in the construction industry was li mited. Further, the survey indicated that there is a need for the development of a methodological framework on the special goals and subjects of performance measurement, methods of data structure and collection, selection of appropriate DEA models, analysis of results, and post-test. Based on the survey, this study identified and discussed the types of major issues and topics for future studies from a methodological perspective, which could be helpful to researchers interested in using DEA to study performance issues in construction organizations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2455-2464
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• 2013

This study is focused on the effect of reformation of public transportation system on the efficiency of bus route system as a result of change of government subsidy scheme. Two types of government subsidy scheme has been considered and before and after analysis by Data Envelopment Analysis technique has been carried out for bus routes in Ulsan Metropolitan City. The analysis output has shown that there is no clear evidence to clarify the relationship between the change of government subsidy scheme and the efficiency of bus route system. There are two types of backgrounds may be suggested for this situation such as more longer period necessary to identify the policy effect and limitation to increase the number of passenger in a provincial city. Tobit regression analysis has also been conducted to discover the most effective variables for maximum efficiency and three variables including route length, frequency per vehicle per day, and headway are found to be influential. It is also seen that strategy to minimising input factors and service upgrade plan such as shortened route length and headway, increasing frequency per vehicle are necessary to develop the efficiency of bus routes operated in Ulsan city.

• Korean Journal of Occupational Health Nursing
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• v.11 no.2
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• pp.108-120
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• 2002

This study analyzed the managerial efficiency of 11 organizations, the branch centers of a occupational health service organization in Korea, using the Data Envelopment Analysis (DEA) method. The DEA is a good method for evaluating health services since it can handle multiple inputs and outputs simultaneously, and also identify the sources and amount of inefficiency. The author approached this study using two efficient models: the monetary value model and the real value model. The DEA method based on the monetary value model included cost factors, while the real value model excluded cost factors. The input variables used were manpower of physicians, medical technicians, nurses, industrial hygienists and administrators; labor, maintenance, and material expenses. The output variables used were the number of medical examinations, workplace evaluations, group health management services and income from each service. The major results were as follows: First, in the monetary value model, 6 out of 11 organizations (54.6%) showed an efficiency score of 1.0, which means that they have been operating in very efficient ways. However, 5 organizations (46.4%) showed themselves to be relatively inefficient. Second, in the real value model, 7 out of 11 organizations (63.4%) showed an efficiency score of 1.0, which means they have been operating efficiently, while 4 organizations (46.4%) showed themselves to be relatively inefficient. Third, the reliability of DEA method were analyzed by comparing the results of the monetary value model and real value model. The results of 8 out of 11 organizations were same in terms of being efficient or not. Thus, the DEA could be a valid application method for occupational health service organizations. Fourth, the organizations that displayed common inefficiency in both the monetary value model and in the real value model 3, 9, and 10, were also considered to be managed inefficiency from expertise opinion. In summary, this study evaluated the efficiency of occupational health service organizations applying the DEA method with different variables, and found that the results of analysis could be valid in terms of both modeling and expert sense. In the future, the DEA method will be used as a useful tool to identify and evaluate the efficiency of occupational health service organizations through more applications and refinements.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.161-174
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• 2013

The purpose of this study was to examine the efficiency of senior welfare centers and the cause of differences among senior welfare centers in that regard, and to investigate influential factors for the differences in efficiency and the size of the influence of the factors. What methods would be effective at assessing the efficiency of senior welfare centers by taking into account their circumstances was reviewed, and post-hoc analyses were made by using data envelopment analysis(DEA) and Tobit analysis, which were useful tools to evaluate relative efficiency. After 24 senior welfare centers located in Seoul were selected, their yearly operating data of 2011 were utilized. In this study, we set limits to the medical welfare of the elderly welfare services business, and divided into model 2 including the elderly population in the region and model 1, input factors for only internal factors, such as full-time workers. We calculated a valid result by proceeding a BCC analysis and analysis of CCR respectively. As this study has some limitations, follow-up research should be implemented. Yet this study is of significance in that it attempted to present general norms for the efficiency analysis of senior welfare centers by using a DEA model and made various post-hoc analyses based on the efficiency data to give significant suggestions on the service of senior welfare centers.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.4
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• pp.137-152
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• 2011

The purpose of this study is to estimate efficiency of agricultural business corporations using Data Envelopment Analysis. A proposed method employs a bootstrapping approach to generate efficiency estimates through Monte Carlo simulation re-sampling process. The technical efficiency, pure technical efficiency, and scale efficiency measure of the corporations is 0.749 0.790, 0.948 respectively. Among the 692 agricultural business corporations, the number of Increasing Returns to Scale (IRS)-type corporations was analyzed to be 539(77.9%). The number of Constant Returns to Scale (CRS)-type corporations was 108(15.6%), and that of Decreasing Returns to Scale (DRS)-type corporations was 45(6.5%). Since an increase in input is lower than an increase in output in IRS, an increase in input factors such as new investments is required. The Tobit model suggests that the type of corporation, capital level, and period of operation affect the efficiency score more than others. The positive coefficient of capital level and period of operation variable indicates that efficiency score increases as capital level and period of operation increases.

• Journal of Technology Innovation
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• v.28 no.2
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• pp.1-36
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• 2020

While the policy intervention of each country for the promotion of renewable energy is strengthened, Korea introduced Feed-in Tariff (FIT) in 2002 to directly support the development of renewable energy. But in 2012, the shift of policy instrument that from FIT to Renewable Portfolio Standard (RPS) is occurred. This is a unique background that is currently found only in Korea, and new answers that focus on the outcomes of the shift of policy instruments are needed in addition to the existing discussion of comparison of FIT and RPS. Therefore, this study analyzed the change of policy efficiency after the shift to RPS using Data Envelopment Analysis(DEA) and Malmquist Index. In the result of analysis, a difference in the improvement of policy efficiency after in shift to RPS is found among each renewable energy source. This result is because renewable energy companies voluntarily entered the market only for energy sources that have secured technology or price competitiveness, and this indicates that the performance of renewable energy after the RPS shift has been concentrated on specific energy sources. As a result of this study, considering that the goal of renewable energy policy is to expand distribution and to drive growth engines, multi-faceted analysis is required in consideration of technology and market in selecting policy instruments.

• The Journal of the Korea Contents Association
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• v.17 no.10
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• pp.216-230
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• 2017

The purpose of this study is to analyze the economic effectiveness of advanced enterprise welfare system utilizing DEA(Data Envelopment Analysis) and contribute to the adoption and implementation of the system conducted by Korea Workers' Compensation & Welfare Service(COMWEL). We classified 48 sample data into 3 categories : A category(basic consulting & intensive consulting, adoption) is 36, B category(basic consulting & intensive consulting, non-adoption) is 5, and C category(only basic consulting, adoption) is 7. A consulting fee is used as input variable, earning per employee and average employee tenure are used as output variables. As a result from DEA, we find out the fact that the economic effectiveness of A category is better than the economic effectiveness of B and C category and it comes to the conclusion that the consulting service provided by COMWEL has a positive effect on the adoption and implementation of advanced enterprise welfare system. Therefore, COMWEL is required to perform consulting service to small & medium business more actively and is needed to look at the reason why some businesses hesitate to accept the relevant system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.517-524
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• 2020

In line with the recent wave of the 4th Industrial Revolution, the environment for defense R&D is transforming into a center of high-tech military technology. In particular, developed countries are strengthening control of technology exports and technology transfer to protect advanced defense science and technology. For this reason, the budget demand for securing the ability to develop independently high-tech weapons and core technologies suitable for the future battlefield environment is increasing, and increasing efficiency in R&D investment has been highlighted for efficient distribution of limited budgets. This study examined the efficiency of the defense basic R&D project using the non-parametric approach, DEA. The R&D budget, R&D researcher, and R&D period were selected as the input variables, and the number of papers and patents were used as output variables. The efficiency of basic R&D projects was analyzed through CCR, BCC models, and SE. Lastly, based on the efficiency measurements, the cause of the inefficiency of R&D projects was suggested, and ways to improve efficiency were suggested. This study is expected to be used as useful information that can be applied to project performance management through efficiency analysis of basic defense R&D projects and be reflected in the project planning stage through feedback.

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.711-735
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• 2016

Drug Development is very important for promoting public health and pharmaceutical industry. There has been many studies on the efficiency of drug development, but there are few studies on the drug development R&D performed by government. Since CCR model assumes unidirectional influence of input and output, it is not appropriate to analyze the efficiency of R&D due to the time-lag and spill-over effect. Also, BBC model which assumes variable returns to scale has difficulty in deriving priorities between decision making units. Recently, Range Adjusted Measure (RAM) model has been suggested in R&D efficiency analysis. RAM model measures the efficincy by eliminating inefficiencies under variable returns to scale assumption, and its strong monotonicity enables to provide clear priorities between decision making units. In this study, we analyzed the efficiency of national R&D programs for drug development using the two-step approach, including RAM model and Tobit regression analysis, and discussed major policy implications.