• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.109-111
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• 2012

한-EU FTA 발효 등은 교역 확대가 예상되며, 항만의 역할은 더욱더 중요해 질 것이다. 항만의 성과를 측정할 수 있는 방안으로 DEA를 활용한 효율성 측정을 들 수 있으며, 본 연구에서는 DEA 측정 시 모형 선정의 어려움과 동태적 효율성을 변화를 분석하기 위해 DEA와 Shannon's Entropy 결합모형으로 효율성을 분석하고, DEA-Window 모형으로 동태적 효율변화를 분석하였다.

• Journal of Information Management
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• v.40 no.3
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• pp.41-60
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• 2009

This study utilizes DEA/Window analysis in order to investigate the relative efficiency levels of korea national university libraries during the period of transition 2004-2008. The empirical results show the following findings. Firstly, a technical efficiency was not efficient which was a scale efficiency rather than a pure technical efficiency in 2008. Secondly, a technical and pure technical efficiency has increased steadily from 2004 to 2008(but a technical, pure technical efficiency has decreased since in 2008). As a result, a technical efficiency increase can be explained by a pure technical efficiency increase.

• Korea Journal of Hospital Management
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• v.15 no.1
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• pp.27-48
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• 2010

The purpose of this paper is to analyze the efficiency change and its determinants of the regional public hospitals. We utilize 34 regional public hospital's panel data for 6 years from 2003 to 2008. We use DEA(Data Envelopment Analysis)-CCR, BCC model, DEA/Window model, and DEA Profiling. The empirical results show the following findings. First, technical efficiency 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, DEA/Window results show that the stable dissimilarity by standard deviation, LDP of CCR. Third, the results of partial efficiency by DEA Profiling show that increase efficiency depends on the number of beds, doctors, and nurses.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.496-509
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• 2020

This study analyzes 5-year efficiency of the game industry, from 2014 to 2018 which is aimed at 25 online and mobile game companies, that are emerging as a new growth engine of a national economy to come and as a core areas of late entertainment industry. The DEA is used for static efficiency analyze and the DEA-Window is used for dynamic efficiency analyze. This study uses assets, the number of employees and costs as input variables and it also uses operating profits and sales as output variables. The main results show that scale efficiency presents a resonable result over 0.85 on a total average except 2014. However, there has not been a year that is over 0.80 of the whole period in technical efficiency. Also, in terms of business scale, there is a huge efficiency gap between high rank companies and low rank companies and the average trend of efficiency has been increased from 2014 to 2016 but it has been decreased since 2017.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.23-40
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• 2014

This paper measures the operational efficiency of domestic online game companies and analyze its trends and patterns by using data envelopment analysis (DEA). DEA is a non-parametric approach to measuring the relative efficiency of decision-making units (DMUs) with multiple inputs and outputs. 14 online game companies are selected as DMUs and three inputs (number of employees, capital and asset) and three outputs (sales, operating profit and net profit) are selected as DEA variables. First, the output-oriented BCC model and super-efficiency model are employed to measure the static operational efficiency of the online game companies from 2003 to 2012. We also conduct the dynamic analysis with DEA window model to capture the trends of their operational efficiency influenced by internal and external environmental changes. The results are expected to provide fruitful implications for strategic decision making of online game companies and policy making for the online game industry.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.276-284
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• 2009

This paper applies DEA windows analysis in order to determine the efficiency of the Districts of Busan Metropolitan City over time for 5 years (2003 - 2007). This paper used such factors including Number of solutions of civil petitions, Local Tax Collection, and Financial Independent rate as output, Total Labor Costs, Government Employees, Population and Expenditure as inputs. This study concludes that the efficiency of the different District can fluctuate over time to different extents and efficiency of most District decreases from 2003. Indeed, the empirical results reveal that substantial inefficiency exists in some Districts at some point in time. In consequence, this validates the necessity for using DEA windows analysis in preference to an analysis based upon cross-sectional data. This paper shows that Districts' efficiency decreases as Window goes to 1 to 3.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.79-86
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• 2009

The purpose of this paper is to analyze the 24 mail center's efficiency and productivity changes from first quarter to fourth quarter of 2008 using window analysis and Malmquist productivity index. Row views of window analysis results make it possible to determine trends and/or observed behavior with the same data set, and column views to examine the stability of results across different data sets. Malmquist productivity indexes greater than unity translate into improvements in productivity, and less than unity mean deterioration in performance over time. The results of this study suggest that DEA models under dynamic situations such as window analysis and Malmquist productivity index enable us to comprehend the efficiency and productivity changes over time and to show the direction of improvements.

• Information Systems Review
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• v.17 no.3
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• pp.113-133
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• 2015

In this paper, DEA analysis is employed to compare and evaluate the relative efficiency of a business intelligence (BI) system among five industrial groups such as IT and financial services, electricity and electronics, energy and chemistry, automotive and heavy machinery, and food and apparel. Especially, this study has analyzed the improving tendency of relative efficiency of the industrial groups since they adopted the BI System using Time-Window Analysis. The research findings show that the energy and chemical industry group tends to be remarkably more efficient than the other groups and the electrical and electronic industry turns out to gradually improve their efficiency since the adoption of the BI system.

• Journal of Information Technology Applications and Management
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• v.20 no.3_spc
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• pp.169-185
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• 2013

In this research, for find out how operations efficiency for ERP systems, after introducing ERP to manufacturing firms with DEA technique. According to research analyzed relative time dependent efficiency, using Time Window Analysis. And for company group and the other firm within the each same Industry, the relative effectiveness of each company group establishment was compared using DEA.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.192-206
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• 2008

With many changes such as the increase in telemarketing, internet marketing and enforcement of bancassurance, the Korean life insurance companies have undergone a startling transformation. The purpose of this paper is to measure and analyse the static/dynamic efficiency of Korean life insurance companies employing Data Envelopment Analysis(DEA). As the result of the static efficiency analysis, we provide CCR, BCC and scale efficiency, return to scale, and reference set of Korean life insurance companies in 2004. And we also describe about the trend and stability of their efficiency for 7 years(1998-2004) in the dynamic efficiency analysis.