• The Journal of Fisheries Business Administration
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• v.43 no.2
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• pp.79-94
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• 2012

The purpose of this study is to investigate the production efficiencies of the Korean aquaculture fishery with respect to species and methods using a Data Envelopment Analysis. The study extracted the 8 fishes in each of the sea cage culture, aquarium basin, and enclosed aquaculture for the analytical purposes. First, the study estimated the technical, pure technical, and scale efficiencies of the total of 24 aquaculture fishes based on the traditional DEA under the assumptions of both CRS and VRS. 2 fishes were identified as the efficient DMUs under the CCR-model, and 6 fishes under the BCC-model. Second, we tested to see if there was any difference in production efficiencies regarding those three different methods of aquaculture. we could not find any evidence of the differences in efficiency using a rank sum test based on the traditional DEA. However, we could do find that the pure technical efficiency in the sea cage culture was lower than others at 1% level of significance and the pure technical efficiency in enclosed aquaculture was also lower than others at 5% level of significance using Bilateral-DEA, which could explicitly consider the heterogeneity in the 3 production methods of aquaculture. Finally, the study obtained the 95% confidence intervals of the efficiency scores for the 24 fishes under our study using the smoothed bootstraping method in the process of the re-sampling in cooperation with both a kernel density estimation and a reflection method. At the same time, we could estimate the bias-corrected efficiency scores while the traditionally estimated efficiency scores suffered from the biases in the process of solving a linear programming with the deterministic nature of a production frontier. And hence, we could distinguish the differences in production efficiencies of the 8 fishes with respect to those 3 methods of aquaculture.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.303-313
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• 2010

The purpose of this study is to evaluate the performance efficiency and productivity change of the regional public hospital in Korea. We use DEA(Data Envelopment Analysis) for CCR, BCC model, and MPI(Malmquist Productivity Index). DEA is a useful nonparametric technique for measurement of efficiency of a DMU(Decision Making Unit) and MPI is a evaluation method to measure DMU's productivity change. We utilize 34 regional public hospital's time-series data over 6 years from 2003 to 2008.The results of this study were as follows. First, technical efficiency(TE) shows that approximately 3.6% of inefficiency exists on the regional public hospitals and it reveals that the cause for technical inefficiency is due to scale inefficiency. Second, MPI's results show that regional public hospital made effort to improve total factor productivity change to raise technical efficiency. In order to raise efficiency, the regional public hospitals should deploy internal innovation and the government should support welfare policies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4354-4358
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• 2011

Many Korean construction companies have fallen on hard times because the construction business continues to stagnate. Therefore it is necessary to measure the management efficiency for efficient operation and strengthening competitiveness of them in order to survive a difficult situation. This paper proposes a combined ANP and DEA model to analyze the efficiency of the listed construction firms. In order to determine the input and output variables of DEA, the ANP model is applied to evaluate the importance of input and output variables. The benchmarking companies and efficiency value for the construction firms with inefficiency are also provided to improve the their efficiency. The 57 listed construction companies consisted of 36 listed on KOSPI and 21 listed on KOSDAQ are analyzed in this study. The analysis results show that 11 companies whose values of CCR are 1, and 14 firms whose values of BCC efficiency are 1. In additions, the 19 firms have the scalability efficiency. Finally, we test the correlation between efficiency and the stock price.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.501-507
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• 2018

Owing to the complexity and modernization of weapon systems, the role of the defense industry in producing military supplies has become increasingly important. In previous defense industries, price competitiveness was a key factor in the product choice. On the other hand, as exports of domestic military supplies are expanding rapidly based on superior quality, there is a need to evaluate objectively the efficiency of management in the domestic defense industry. In this study, the efficiency of management was measured using DEA, which is one of the decision methodologies. In addition, the number of employees (QA Employee) and R&D performance were set as input variables to utilize DEA, and the output variables were based on sales and operating profit. Based on the results of the analysis, a future study will measure the efficiency of the management of domestic defense industry to help guide a strategic development plan.

• Journal of Korea Port Economic Association
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• v.30 no.2
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• pp.93-112
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• 2014

To study the business performance, this research reviewed the revenue of 2012 for shipping and logistics companies in Korea, then selected 10 shipping companies and 10 logistics companies according to annual sales amount. These 20 companies are divided into four groups considering their business structure and their financial performance are organized from 2005 to 2012. Then CCR, BCC model has been applied to static efficiency and dynamic changes in productivity for analysis. As an overall result, logistics companies are proven to be better than shipping company in efficiency, change of productivity, growth and profitability. Among the logistics companies, the performance of second party logistics companies are relatively better in those factor above than the third party logistics companies.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.4
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• pp.301-315
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• 2011

DEA(Data Envelopment Analysis) is useful to measure the relative efficiency of organizational units where the presence of multiple inputs and outputs. This study applied DEA-CCR and DEA-BCC to evaluate the technical, pure technical, and scale efficiency of 29 university libraries. The input variables were number of books, print edition expenses, building space, staff, number of seats. As output variables we estimated: reader visits, number of borrowed items, number of visitors. It was found out that number of libraries with 100% relative efficiency among 29 libraries were 13. Also the results shows that main reason of inefficiency was from scale rather than from pure technical. Many inefficient libraries were operations of increasing return to scale.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.129-151
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• 2010

This study is to analyze the efficiency of Korean fishing ports using DEA. First, the study calculated the efficiency scores based on a CCR-BCC framework and hence technical, pure technical, and scale efficiency scores are seperated for the 38 fishing ports under study. The Average of technical, pure technical, and scale efficiency are turned out to be 0.6834, 0.8582, and 0.7774 respectively. The 15 fishing ports are fully efficient under the constant returns to scale while 21 fishing ports under the variable returns to scale. Second, the super efficiency scores are also calculated under the radial model without the consideration of slacks. The highest score is turned out to be 4.4984 for the P16 fishing port with the average score of 0.9652 for the entire fishing ports. Nevertheless, P16 fishing port has showed up only once as a reference set. On the other hand, P34 fishing port has showed up 11 times as a reference set, which scored the second highest score of 2.9815. Finally the super efficiency scores are calculated under the non-radial model with the explicit consideration of slacks. Now the P34 fishing port scored the highest score of 2.3424 with even 15 times referred to a bench-mark. Therefore the importance of P34 fishing port is emphasized once again on the field of bench-marking for the efficiency of fishing ports. When the targets for the input factors to improve the efficiency of each DMU are calculated the area of fishing port needs the most adjustment to be reduced for 40.36% on the average, while the cosignment sales area does the least adjustment for 13.70%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.29-38
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• 2015

In this paper, scale efficiencies and relative efficiencies of R&D projects in Industrial Technology Program, sponsored by Ministry of Trade, Industry and Energy, Korea, are calculated and compared. For the process, various DEA (Data Envelopment Analysis) models are adopted as major techniques. For DEA, two stage input oriented models are utilized for calculating the efficiencies. Next, the calculated efficiencies are grouped according to their subprograms (Industrial Material, IT Fusion, Nano Fusion, Energy Resources, and Resources Technology) and recipient types (Public Enterprise, Large Enterprise, Medium Enterprise, Small Enterprise, Lab., Univ., and etc.) respectively. Then various subprograms and recipient types are compared in terms of scale efficiencies (CCR models) and relative efficiencies (BCC models). In addition, the correlation between the 1st stage relative efficiencies and the 2nd stage relative efficiencies is calculated, from which the causal relationship between them can be inferred. Statistical analysis shows that the amount of input, in general, should increase in order to be scale efficient (CCR models) regardless of the subprograms and recipient types, that the 1st and 2nd stage relative efficiencies are different in terms of the programs and recipient types (BCC models), and that there is no significant correlation between the 1st stage relative efficiencies and the 2nd stage relative efficiencies. However, the results should be used only as reference because the goal each and every subprogram has is different and the situation each and every recipient type faces is different. In addition, the causal link between the 1st stage relative efficiencies and the 2nd relative efficiencies is not considered, which, in turn, is the limitation of this paper.

• Journal of the military operations research society of Korea
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• v.34 no.1
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• pp.61-77
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• 2008

Data Envelopment Analysis(DEA) is a promising methodology to evaluate the relative efficiency of the decision-making units. We have compared the efficiency of six electric power generation companies in Korea using DEA. The analysis results by input-oriented CCR and BCC models are summarized as follows: first, different results were acquired between using input factors as total capacity of generators and as sub-totals of generator capacity based on primary energy sources. It is the result influenced by input factors which are characterized by the proportion of fixed costs(generating facilities) and variable costs(generation costs for primary energy), Second, the efficiency will be increased if the input factors selected, according to primary energy sources discussed in this research, are used during long-term expansion of electric power capacity plans. It is expected that this approach can give a feedback for management of electric power generation companies.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.207-217
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• 2020

The purpose of this study is to analyze the efficiency of Korean child welfare facilities using the DEA analysis method and to present policies. The input variables for the analysis of this data were the number of employees, the number of facilities, and the number of gardens, and the output variables were the current sources. The results of the study are as follows. As a result of CCR analysis, inefficient facilities were found to be temporary protection facilities and comprehensive facilities. As a result of BCC analysis, inefficient facilities were identified as temporary protection facilities. As a result of SE analysis, inefficient facilities were found to be temporary protection facilities. The suggestion is as follows. First, adjustment of the capacity of temporary protection facilities is required. Second, it is necessary to strengthen the professionalism of workers in child welfare facilities. Third, strengthen the expertise of the child welfare facility manager.