• Title/Summary/Keyword: DEA Window Model

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Static and Dynamic Analysis of Efficiency of Korean Regional Public Hospitals (지방의료원의 효율성에 대한 정태적 및 동태적 분석)

  • Kim, Jong-Ki;Jeon, Jinh-Wan
    • 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.

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Measuring Operational Efficiency of Korean Online Game Companies with DEA Window Analysis (DEA Window 분석을 이용한 국내 온라인 게임 기업의 운영 효율성 평가)

  • Chun, Hoon;Lee, Hakyeon
    • 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.

Measuring the Dynamic Efficiency of Government Research Institutes in R&D and Commercialization by DEA Window Analysis (DEA 윈도우 분석을 이용한 정부출연연구기관의 연구개발 사업화 동태적 효율성 분석)

  • Lee, Seonghee;Kim, Taesoo;Lee, Hakyeon
    • Korean Management Science Review
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    • v.32 no.4
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    • pp.193-207
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    • 2015
  • Government-funded research institutes (GRIs) have played a pivotal role in national R&D in Korea. To achieve desired goals of GRIs with the limited R&D budget, their performance along with time needs to be measured and compared so that appropriate R&D policies can be formulated and implemented. This study measures the dynamic performance of GRIs from the efficiency perspective using the window model of 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, and the DEA window model can capture the dynamic changes in efficiency of DMUs during multiple periods. The relative efficiency of GRIs is measured from the two perspectives: R&D and R&BD. Patents, papers, technology transfers are selected as outputs for R&D while compensated technology transfers and technology royalty are employed as outputs for R&BD. This study measures and compares the two types of performance of 20 Korean GRIs under the control of National Research Council of Science and Technology during the period of six years from 2008 to 2013. The results are expected to provide fruitful implications for national R&D policy making.

Measuring Relative Efficiency of Korean Life Insurance Companies Employing DEA/Window Model (DEA/Window 모형을 이용한 국내 생명보험산업의 상대적 효율성 분석)

  • Lee, Hyung-Suk;Kim, Ki-Seog
    • 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.

Port Export and Efficiency of the Regional Economy in Korea (항만수출과 지역경제의 효율성)

  • Kim, Chang-Beom;Lee, Min-Hui
    • Journal of Korea Port Economic Association
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    • v.26 no.3
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    • pp.165-174
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    • 2010
  • DEA converts multiple inputs and outputs of a decision unit into a single measure of performance, generally mentioned as relative efficiency. DEA has been applied successfully as a performance evaluation tool in many fields including manufacturing, banks, pharmacies, and hospitals to name a few. This paper applies the input-oriented DEA model, DEA/Window analysis, and Malmquist indices to the 9 regions in Korea to measure the efficiency and productivity. The empirical results show the following findings. First, the super efficiency indicate that efficiency of Group 2 is greater than Group 1. Second, Malmquist indices show that productivity of Group 2 is less than Group 1. Third, DEA/Window of Group2 show that Chungnam is most stable, while Jeonnam is most unstable.

Evaluation of the Efficiency of Korea's Domestic Passenger Shipping Routes using DEA Window (DEA Window 모형을 활용한 한국의 내항여객운송항로 효율성 평가)

  • Kim, Tae Il;Park, Sung Hwa
    • Journal of Korea Port Economic Association
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    • v.38 no.1
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    • pp.113-127
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    • 2022
  • The purpose of this study is to analyze the efficiency of 90 domestic passenger shipping routes using the DEA Window model as a Decision Making Unit (DMU). Data from 2015 to 2019 are divided into three windows, and efficiency was analyzed by using the number of passenger ships of sails, gross tonnage and distance traveled as input variables and transportation performance of the general public and islanders as output variables. As a result of the analysis, improvements are derived and presented for routes with low relative efficiency. In particular, the efficiency is evaluated for general routes operated by private operators as profit routes and auxiliary routes supported by the government as non-profit routes. In addition, scale efficiency (SE) is derived by using the technical efficiency (TE) of the CCR model and the pure technical efficiency (PTE) values of the BCC model. It is found that the inefficiency of the route was due to pure technical efficiency (PTE) rather than scale efficiency (SE). It will be necessary to consider the improvements for each route shown in the analysis results of this study when establishing the policy for the domestic passenger shipping route.

A Study on the Efficiency and Determinants of Static and Dynamic in Korean property casualty insurance Company (국내 손해보험회사의 효율성 및 결정요인에 대한 Static and Dynamic 분석)

  • Kim, Tae-Hyuk;Park, Chun-Gwang;Kim, Byeong-Chul
    • The Korean Journal of Financial Management
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    • v.25 no.4
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    • pp.183-212
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    • 2008
  • The purpose of this paper is to analyze the efficiency change and determinants of the korean non-life insurance companies. we use DEA (Data Envelopment Analysis) model to measure company efficiency change and use GLS, Tobit model, FIixed effect model, Random effect model, GMM to measure efficiency determinants. we utilize ten non-life insurance companies in korea and the panel data for five from 2001 to 2005. The empirical results show the following findings. First, technical efficiency shows that approximately 15.5% of inefficiency exists on the non-life insurance companies 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 efficiency determinants show that increase efficiency is depend on the premium income and real estates.

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A Study on Operational Efficiency Analysis on the Value of Chinese Shipping Companies

  • Cui, Lin-Lin;Choi, Jung-Suk
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.3
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    • pp.430-440
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    • 2022
  • Shipping companies are key components of the logistics industry, which is extremely significant in enhancing the country's comprehensive national power and promoting global trade development. In the context of the implementation of the new development pattern strategy in China and the impact of the global novel coronavirus (COVID-19), this paper takes 22 Chinese shipping listed companies as the research object and analyses the operational efficiency of them from 2011 to 2020 based on the Super-SBM DEA Model and Window DEA Model. Factors affecting the efficiency are further analyzed with the Tobit model. The research conclude that the operational efficiency of Chinese shipping companies as a whole shows a steady increase from 2011 to 2020. Although most of them are in a relatively ef ective operation state, fewer are absolutely effective companies. Besides efficiency among companies differs obviously, which indicates the potential of further improvement and promotion. What's more, factors such as current economic development level, enterprise size, human resources quality and enterprise turnover speed have significant positive correlation to the operation efficiency of Chinese shipping listed companies, which is significant to improve the operation efficiency of Chinese shipping companies.

Analysis of the Efficiency of National SW R&D Projects Using DEA (DEA를 활용한 SW 국가연구개발사업 효율성 분석)

  • Ro, Seok-Hyun;Cho, Nam-Wook
    • 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.

An Efficiency Analysis for the Korea Container Terminals by the DEA/Simulation Approach (DEA및 시뮬레이션에 의한 컨테이너 터미널의 효율성 분석)

  • Park, Byun-Gin
    • Korean Management Science Review
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    • v.22 no.2
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    • pp.77-97
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    • 2005
  • The traditional measures of a container port (or terminal) efficiency such as crane productivity, cargo throughput, etc. were generally presenting the partial efficiency since they evaluated only each individual factor and based on cross-sectional data. To overcome this problem, and in an effort to help port authorities develop a winning strategy in the increasingly competitive container transportation market, this Paper develops a meaningful set of benchmarks that will set the standard for best practices. In particular, this paper proposed a combined method to merge the DEA and simulation technique over time. To illustrate the usefulness of the proposed combined DEA/simulation model, this paper used the panel data of the four Gwangyang container terminals and seven Busan container terminals in Korea over the four-year period of 1999 through 2002.