• Title/Summary/Keyword: DEA-AR

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A Performance Evaluation of Governmental Funding Projects for IT Small and Medium-Sized Enterprises and Venture Business Using DEA/AR-I (DEA/AR-I을 활용한 IT 중소.벤처기업 정부자금지원정책 성과평가)

  • Park, Sung-Min;Kim, Heon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.12B
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    • pp.815-825
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    • 2007
  • It is necessary to establish a systematic framework where the performance of governmental funding projects can be evaluated just-in-time as well as objectively regarding IT small and medium-sized enterprises and venture business. In this study, a framework is proposed for the performance evaluation using Data Envelopment Analysis (DEA) and a case study is illustrated with an empirical dataset. Especially, in order to enhance the reliability of optimal solutions, a DEA/AR-I revised model is developed by adding Acceptance Region (AR) Type I constraints into the DEA basic model. Based on the procedure and the models, it is considered that an 'efficiency score' can be calculated as a guideline for conducting successive performance evaluation processes fast. As for major governmental funding projects with respect to 'IT SMERP 2010 Plan', performance evaluations are discussed concerning between projects as well as between corporate entities within each project.

A Brief Empirical Verification Using Multiple Regression Analysis on the Measurement Results of Seaport Efficiency of AHP/DEA-AR (다중회귀분석을 이용한 AHP/DEA-AR 항만효율성 측정결과의 실증적 검증소고)

  • Park, Ro-kyung
    • Journal of Korea Port Economic Association
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    • v.32 no.4
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    • pp.73-87
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    • 2016
  • The purpose of this study is to investigate the empirical results of Analytic Hierarchy Process/Data Envelopment Analysis-Assurance Region(AHP/DEA-AR) by using multiple regression analysis during the period of 2009-2012 with 5 inputs (number of gantry cranes, number of berth, berth length, terminal yard, and mean depth) and 2 outputs (container TEU, and number of direct calling shipping companies). Assurance Region(AR) is the most important tool to measure the efficiency of seaports, because individual seaports are characterized in terms of inputs and outputs. Traditional AHP and multiple regression analysis techniques have been used for measuring the AR. However, few previous studies exist in the field of seaport efficiency measurement. The main empirical results of this study are as follows. First, the efficiency ranking comparison between the two models (AHP/DEA-AR and multiple regression) using the Wilcoxon signed-rank test and Mann-Whitney signed-rank sum test were matched with the average level of 84.5 % and 96.3% respectively. When data for four years are used, the ratios of the significant probability are decreased to 61.4% and 92.5%. The policy implication of this study is that the policy planners of Korean port should introduce AHP/DEA-AR and multiple regression analysis when they measure the seaport efficiency and consider the port investment for enhancing the efficiency of inputs and outputs. The next study will deal with the subjects introducing the Fuzzy method, non-radial DEA, and the mixed analysis between AHP/DEA-AR and multiple regression analysis.

Measuring Management Efficiency of Architectural Firms in Korea using DEA/AR Models (DEA-AR 모형을 활용한 건축사사무소의 효율성 비교분석)

  • Kim, Sung-Sik;Park, Jung-Lo;Kim, Ju-Hyung;Kim, Jae-Jun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2012.11a
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    • pp.125-126
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    • 2012
  • Domestic architect office from a period of high growth from the 1970s to the '80s has been established as some of the large corporations or publicly traded corporation. 1997 IMF has pointed out there is a lot of need for improvement activities in accordance with the construction recession since the 2008 global financial crisis. In order to address these causes, the company's continuous efficient operation for accurate efficiency and competitiveness analysis was required. Leverage financial ratio indicators Study Using Data Envelopment Analysis Data Envelopment Analysis (DEA) model, how to find a benchmark for the improvement of the efficiency of inefficient enterprises in various sectors being. In this study, a comparison of the conventional DEA model and the DEA-AR model is used to analyze the efficiency and domestic architect office is to improve the management efficiency.

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DEA-AR/AHP Model Design for Efficiency Evaluation of Metropolitan Rapid Transit (지하철 효율성 평가를 위한 DEA-AR/AHP 모형 설계)

  • Sim, Gwang-Sic;Kim, Jae-Yun
    • Journal of the Korean Operations Research and Management Science Society
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    • v.34 no.3
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    • pp.105-124
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    • 2009
  • Data Envelopment Analysis (DEA) is a methodology of computing the relative efficiency of each decision making unit (DMU) by comparing it with other DMUs having similar input and output structure. In this paper, we compare the efficiency of Korean rail transit corporations using DEA. To do this, we design a DEA-AR/AHP model, and evaluate efficiency by comparing the subway operating agencies of six big cities. The analysis reveals that Seoul Metro and Seoul city railroad construction turn out to be the most efficient groups. The result of this research can provide helpful information for effective management in a domestic subway operating agency.

An Analysis of the Efficiency of Korean railroad container freight station with Data Envelopment Analysis-Assurance Region (DEA-AR) (DEA-AR을 활용한 철도 컨테이너 화물역 효율성 분석)

  • An, Chi-Won;Ha, Heon-Gu
    • Journal of Korean Society of Transportation
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    • v.27 no.3
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    • pp.7-16
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    • 2009
  • Because the transport policy of Korea has overemphasized road, the physical distribution function of railroad has dwindled a great deal relatively. Recently, the railway has started to be embossed due to the rise of oil prices and environment problems, in addition the government is investing greatly in railroad. The railway corporation took a big step in its history in changing to a public corporation in 2005, and it has been making every possible endeavor to improve management. This research analyzed the trend and stability of the efficiency of railway container handling goods station in korea from 2002 to 2007 based on time of after being changed to a public corporation in 2005 in order to look into the trend of efficiency. The DEA- AR(Data Envelopment Analysis-Assurance Region) and the DEA-Window, widely used as the estimation techniques of the efficiency, were used. According to the results, the efficiency was a little enhanced in 2003 in comparison with 2002, after which it continuously decreased up to 2006 and again rose in 2007. The efficiency of the railway corporation was 0.6777, but after changing to a public corporation, it showed a trend of better efficiency after some transition period had passed.

Measuring the efficiency of technology innovation of the Global Green Car Companies by ANP/DEA Model (특허지표를 고려한 글로벌 자동차 기업의 그린 카 기술혁신 효율성 평가를 위한 ANP/DEA 통합모형)

  • Kim, HyunWoo;Kim, Jaehee;Kim, Sheung-Kown
    • Journal of Technology Innovation
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    • v.20 no.3
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    • pp.255-285
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    • 2012
  • As the environmental performance is getting important in global automotive industry sector, there is a need to build the intellectual capacity. Hence it is important to measure the performance of the green car patent development of global automotive companies. To do this, we propose to use Data Envelopment Analysis(DEA) Model with Analytic Network Process(ANP), which generates weight coefficients of inputs and outputs for DEA-AR(Assurance Region) model. We considered three inputs: corporate asset, R&D expenditures, number of employees, and three outputs: patent counts, patent citations and patent claims. The results showed that our model could measure the potential of green car technology, and we could see the trend of the green car industry sector.

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A DEA/AHP Hybrid Model for Evaluation & Selection of R&D Projects (연구개발사업의 평가 및 선정을 위한 DEA/AHP 통합모형에 관한 연구)

  • 임호순;유석천;김연성
    • Journal of the Korean Operations Research and Management Science Society
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    • v.24 no.4
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    • pp.1-12
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    • 1999
  • This paper presents a DEA-AHP hybrid model to evaluate and select R&D projects. AHP collects and processes information on the weights of evaluation criteria. The processed information is used as an input for DEA/AR model. Only desirable number of projects are selected by the hybrid model. The model is examined by an example generated from a real data set.

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Empirical Analysis of DEA models Validity for R&D Project Performance Evaluation : Focusing on Rank Correlation with Normalization Index (R&D 프로젝트 성과평가를 위한 DEA모형의 타당성 실증분석 : 정규화지표와의 순위상관을 중심으로)

  • Park, Sung-Min
    • IE interfaces
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    • v.24 no.4
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    • pp.314-322
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    • 2011
  • This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.