• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.367-371
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• 2005

선진 각국의 지상파 디지털 방송 기술 개발 동향을 파악하고 미국, 영국, 일본, 독일 호주 등 주요 국가별로 대표방송사를 선정하여 재무제표 자료를 토대로 투자 및 운영효율성에 대한 정량적 분석을 수행하고 DEA(Data Envelope Analysis)모형을 이용하여 각국의 경쟁력을 비교 분석한다. 분석 결과를 우리나라의 방송 3사(KBS, MBC, SBS)의 상황과 비교 분석함으로써 국내 디지털 지상파 방송이 경쟁력을 갖추기 위한 조건을 제시하고자 한다.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.201-207
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• 2008

The bankruptcy possibility of apartment construction firms has been incresed because of the environment of current apartment construction industry. This paper analyzes the efficiency of apartment construction firms using DEA model. We evaluate the CCR, BCC efficiency and RTS of 25 apartment construction firms. We also suggest the apartment construction firms which can be benchmarked based on analyzed information. The result shows that four enterprises whose values of CCR efficiency are 1, and ten enterprises whose values of BCC efficiency are 1. RTS indicates IRS of 21 firms and CRS of 4 firms.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.7-18
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• 2004

There have been various research in analyzing airport productivity such as measuring total factor productivity using the models of translog cost function. DEA(Data Envelopment Analysis) model is very useful in measuring productivity with linear programming when the output is not clearly identified and measured quantitatively in such complex facilities as airport. This study is to measure airport productivity using DEA approach for Northeast Asia. Seven international airports were analyzed including Incheon International Airport in Korea, Cheklapkok Airport in Hongkong, Narita Airport in Japan, and Changi Airport in Singapore. With the productivity measured, we can identify one of the important aspects of comparative advantage in hub competition in Asia.

• 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 the Korean Society of Marine Environment & Safety
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• v.13 no.2 s.29
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• pp.141-146
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• 2007

In this study, we have investigated several input factors and output factors to maintain safety management of domestic shipping companies, and then have analyzed the efficiency of performance about each shipping companies' safety management system from 1998 year to 2004 year using DEA method. The result of analysis shows that the annual mean efficiency index of total companies tended downward every year. Analysis was that the cause was increase of the cost of repairing ship, the cost of ship's stores and idle day of ship while the number of marine accidents and sanctions of PSC, ship's insurances and P&I insurances was decreased.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.4
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• pp.101-111
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• 2013

In this study, DEA (Data Envelopment Analysis) was carried out on the four bridges, which have the same extension (L=1,615m), in order to select the most superior, economical method of construction using the LCC concept of each bridge structure in the case of the Ulsan-Pohang double track railway which is scheduled to be constructed. DEA models were analyzed with the CCR model, which was designed for the evaluation of relative efficiency of each model. The initial construction costs, maintenance costs, indirect costs (user costs + indirect loss of social costs), and life cycle costs were used as input variables, and average duration was applied as the output variable. LCC was applied to calculate the input variables, and to get the costs of LCC, 100 years of period and 4.83% of real discount rate were applied, and the costs are classified into initial construction, maintenance, user, and indirect loss of social cost. The analysis results showed that the Method 2 and 3 were evaluated as the most efficient, and the other alternatives were evaluated as the following order; Method 1, the default, and Method 4.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.45-59
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• 2021

As software(SW) has been considered as a key driver of the fourth industrial revolution, significant R&D investment has been made by Korean government. Despite the attention and support by the government, systematic analysis on the SW R&D efficiency has not been fully addressed. In this study, the efficiency of SW national research and development projects was analyzed using Data Envelopment Analysis(DEA) techniques. Efficiency was measured from both static and dynamic perspectives based on 1,463 projects conducted by the National IT Industry Promotion Agency(NIPA) from 2008 to 2018. The static efficiency analysis identified the causes of inefficiency as scale and technology problems. As a result of dynamic efficiency analysis, we present a sector-specific response model using an efficiency-stability matrix. This study is meaningful in that efficiency analysis was conducted on the entire SW national R&D project, and static/dynamic efficiency analysis results are expected to be used as a guideline for planning SW national R&D project.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.2
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• pp.125-136
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• 2017

This study focuses on a relative efficiency of 109 operating food companies out of 22 regions in Jeollanam-do. The relative efficiency has been analyzed by 5 input factors(capital, number of employees, annual labor costs, raw material purchase, and site area) and 2 output factors(annual exports and annual production of the companies in Jeollanam-do). This study suggests efficient companies which inefficient companies can benchmark to improve their system in short-mid-long term in phases. The main result of empirical analysis are as follows: Firstly, according to the Traditioanl DEA analysis, 7 companies out of 109 DMU indicate the optimal production scale in score 1 of CCR efficiency value, BCC efficiency value, and scale efficiency value. Secondly, a result from the Tier 1 step of inefficient companies by Post-DEA suggests that it would be better to apply each Tier step to the proper stage of the worst 5 inefficient companies such as Tier 3 step(short-term benchmark)${\rightarrow}$Tier 2 step(mid-term benchmark)${\rightarrow}$Tier 1 step(long-term benchmark) in step. This study expects that the result of the study can reduce the trial and error in inefficient part, lead to improvement, and have a big help in food exporting industry in the end.

• Journal of Agricultural Extension & Community Development
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• v.23 no.4
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• pp.441-448
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• 2016

The study aims to explore the problems of analysis unit when examining management performance and efficiency using DEA (Data Envelopment Analysis). Generally the DEA results depend on input, output, and analysis units. We used data from Park (2012) which analyze paddy farmers in Jeonnam province. Results show that data from farm household unit was well fitted to examine management efficiency, not data from per area unit. This study will be helpful for researchers and practitioners to understand proper analysis unit when using the DEA for enhancing farm competitiveness.

• Asia pacific journal of information systems
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• v.10 no.1
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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.