- Volume 17 Issue 1
This study presented the new evaluation index which can evaluate the discrimination of DEA models. To evaluate the discrimination of DEA models, data were analyzed using importance index as suggested in previous study and the coefficient of variation as suggested in this study for the discrimination evaluation. This study selected the CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, and cross efficiency DEA model for the discrimination evaluation and accomplished empirical analysis. In order to grasp the rank correlation of the models, this study implemented the rank correlation analysis between the efficiency of CCR model and BCC model and entropy, bootstrap, super efficiency, and efficiency of the cross efficiency model. The obtained results of this study are as follows. First, the discrimination rank of models using the importance index and the coefficient of variation was shown to be identical. Therefore, the coefficient of variation can be used the discrimination evaluation index of DEA model. Second, the discrimination of the super efficiency model was found to be the highest rank among 4 models according to the analysis of this present study. Third, the highest rank correlation with CCR model was the super efficiency model. In addition, the super efficiency model was found to be the highest rank correlation with BCC model.
Supported by : 부산가톨릭대학교
- 박만희, 효율성과 생산성 분석, 한국학술정보, 2008.
- 유금록, "공공부문의 효율성과 영향요인 분석: 도시개발공사를 중심으로," 한국행정학보, 제42권, 제3호, pp.79-109, 2008.
- N. Alder, L. Friedman, and Z. Sinuany-Stern, "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Vol.140, pp.249-265, 2002. https://doi.org/10.1016/S0377-2217(02)00068-1
- N. Alder and E. Yazhemsky, "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Vol.202, pp.273-284, 2010. https://doi.org/10.1016/j.ejor.2009.03.050
- M. Bagherikahvarin and Y. Smet, "A ranking method based on DEA and PROMETHEE II (a rank based on DEA & PR.II)," Measurement, Vol.89, pp.333-342, 2016. https://doi.org/10.1016/j.measurement.2016.04.026
- R. D. Banker, A. Charnes, and W. W. Cooper, "Some Models for Estimating Technical and Scale Efficiencies in Data Envelopment Analysis," Management Science, Vol.30, pp.1078-1092, 1984. https://doi.org/10.1287/mnsc.30.9.1078
- A. Boussofinance, R. G. Dyson, and E. Thanassoulis, "Applied Data Envelopment Analysis," European Journal of Operations Research, Vol.52, pp.1-15, 1991. https://doi.org/10.1016/0377-2217(91)90331-O
- A. Charnes, W. W. Cooper, and E. Rhodes, "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, Vol.27, No.6, pp.668-697, 1981. https://doi.org/10.1287/mnsc.27.6.668
- W. Cook, L. Liang, Y. Zha, and J. Zhu, "A modified super-efficiency DEA model for infeasibility," Journal of the Operational Research Society, Vol.60, pp.276-281, 2009. https://doi.org/10.1057/palgrave.jors.2602544
- W. Cook and J. Zhu, Data Envelopment Analysis, A Handbook of Models and Methods, Springer, pp.23-32, 2015.
- J. A. Fitzsimmons and M. J. Fitzsimmons, Service Management for Competitive Advantage, McGrow-Hill Inc, 1994.
- J. Ruiz and I. Sirvent, "Common benchmarking and ranking of units with DEA," Omega, Vol.65, pp.1-9, 2016. https://doi.org/10.1016/j.omega.2015.11.007
- T. Sexton, R. Silkman, and A. Hogan, "Data Envelopment Analysis: Critique and Extensions," New Directions for Program Evaluation, Vol.32, pp.73-105, 1986.
- W. Shen, D. Zhang, W. Liu, and G. Yang, "Increasing discrimination of DEA evaluation by utilizing distances to anti-efficient frontiers," Computers & Operations Research, Vol.75, pp.163-173, 2016. https://doi.org/10.1016/j.cor.2016.05.017
- L. Simar and P. W. Wilson, "Sensitivity analysis of Efficiency Scores: How to bootstrap in nonparametric Frontier Models," Management Science, Vol.44, pp.49-61, 1998. https://doi.org/10.1287/mnsc.44.1.49
- M. Soleimani-damaneh and M. Zarepisheh, "Shannon's entropy for combining the efficiency results of different DEA models: method and application," Expert Systems with Applications, Vol.36, pp.5146-5150, 2009. https://doi.org/10.1016/j.eswa.2008.06.031
- Y. Wang and K. Chin, "Discriminating DEA efficient candidates by considering their least relative total scores," Journal of Computational and Applied Mathematics, Vol.206, pp.209-215, 2007. https://doi.org/10.1016/j.cam.2006.06.012
- Q. Xie, Q. Dai, Y. Li, and A. Jiang, "Increasing the Discriminatory Power of DEA Using Shannon's Entropy," Entropy, Vol.16, No.3, pp.1571-1585, 2014. https://doi.org/10.3390/e16031571