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Influential DMUs and outlier detection in data envelopment analysis with an application to health care

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  • Ali Bahari
  • Ali Emrouznejad

Abstract

This paper explains some drawbacks on previous approaches for detecting influential observations in deterministic nonparametric data envelopment analysis models as developed by Yang et al. (Annals of Operations Research 173:89–103, 2010 ). For example efficiency scores and relative entropies obtained in this model are unimportant to outlier detection and the empirical distribution of all estimated relative entropies is not a Monte-Carlo approximation. In this paper we developed a new method to detect whether a specific DMU is truly influential and a statistical test has been applied to determine the significance level. An application for measuring efficiency of hospitals is used to show the superiority of this method that leads to significant advancements in outlier detection. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Ali Bahari & Ali Emrouznejad, 2014. "Influential DMUs and outlier detection in data envelopment analysis with an application to health care," Annals of Operations Research, Springer, vol. 223(1), pages 95-108, December.
    • Handle: RePEc:spr:annopr:v:223:y:2014:i:1:p:95-108:10.1007/s10479-014-1604-8
    DOI: 10.1007/s10479-014-1604-8
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    1. Zijiang Yang & Xiaogang Wang & Dongming Sun, 2010. "Using the bootstrap method to detect influential DMUs in data envelopment analysis," Annals of Operations Research, Springer, vol. 173(1), pages 89-103, January.
    2. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    3. Puig-Junoy, Jaume, 2000. "Partitioning input cost efficiency into its allocative and technical components: an empirical DEA application to hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 34(3), pages 199-218, September.
    4. HATAMI-MARBINI, Adel & TAVANA, Madjid & EMROUZNEJAD, Ali, 2012. "Productivity growth and efficiency measurements in fuzzy environments with an application to health care," LIDAM Reprints CORE 2407, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. SIMAR , Léopold, 1995. "Aspects of Statistical Analysis in DEA-Type Frontier Models," LIDAM Discussion Papers CORE 1995061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Ouellette, Pierre & Vierstraete, Valerie, 2004. "Technological change and efficiency in the presence of quasi-fixed inputs: A DEA application to the hospital sector," European Journal of Operational Research, Elsevier, vol. 154(3), pages 755-763, May.
    7. Simar, L., 1991. "Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric methods with boot strapping," LIDAM Discussion Papers CORE 1991026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Banker, Rajiv D. & Chang, Hsihui, 2006. "The super-efficiency procedure for outlier identification, not for ranking efficient units," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1311-1320, December.
    9. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    10. Johnson, Andrew L. & McGinnis, Leon F., 2008. "Outlier detection in two-stage semiparametric DEA models," European Journal of Operational Research, Elsevier, vol. 187(2), pages 629-635, June.
    11. Pastor, Jesus T. & Ruiz, Jose L. & Sirvent, Inmaculada, 1999. "A statistical test for detecting influential observations in DEA," European Journal of Operational Research, Elsevier, vol. 115(3), pages 542-554, June.
    12. Wilson, Paul W, 1993. "Detecting Outliers in Deterministic Nonparametric Frontier Models with Multiple Outputs," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 319-323, July.
    13. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    14. Chang, Shyr-Juh & Hsiao, Hsing-Chin & Huang, Li-Hua & Chang, Hsihui, 2011. "Taiwan quality indicator project and hospital productivity growth," Omega, Elsevier, vol. 39(1), pages 14-22, January.
    15. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
    16. Murat Bilsel & Nurhan Davutyan, 2014. "Hospital efficiency with risk adjusted mortality as undesirable output: the Turkish case," Annals of Operations Research, Springer, vol. 221(1), pages 73-88, October.
    17. Seaver, Bill L & Triantis, Konstantinos P, 1989. "The Implications of Using Messy Data to Estimate Production-Frontier-Based Technical Efficiency Measures," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(1), pages 49-59, January.
    18. Joses M. Kirigia & Ali Emrouznejad & Rui Gama Vaz & Henry Bastiene & Jude Padayachy, 2008. "A comparative assessment of performance and productivity of health centres in Seychelles," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 57(1), pages 72-92, January.
    19. Kazley, Abby Swanson & Ozcan, Yasar A., 2009. "Electronic medical record use and efficiency: A DEA and windows analysis of hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 43(3), pages 209-216, September.
    20. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    21. Adel Hatami-Marbini & Madjid Tavana & Ali Emrouznejad, 2012. "Productivity Growth and Efficiency Measurements in Fuzzy Environments with an Application to Health Care," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 2(2), pages 1-35, April.
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    3. Lee, Jiyoung & Kim, Chulyeon & Choi, Gyunghyun, 2019. "Exploring data envelopment analysis for measuring collaborated innovation efficiency of small and medium-sized enterprises in Korea," European Journal of Operational Research, Elsevier, vol. 278(2), pages 533-545.
    4. Mohammed Al-Siyabi & Gholam R. Amin & Shekar Bose & Hussein Al-Masroori, 2019. "Peer-judgment risk minimization using DEA cross-evaluation with an application in fishery," Annals of Operations Research, Springer, vol. 274(1), pages 39-55, March.

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