IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v223y2014i1p95-10810.1007-s10479-014-1604-8.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-014-1604-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-014-1604-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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).
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marcel Clermont & Julia Schaefer, 2019. "Identification of Outliers in Data Envelopment Analysis," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 475-496, October.
    2. 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.
    3. Andreas Dellnitz & Madjid Tavana & Rajiv Banker, 2023. "A novel median-based optimization model for eco-efficiency assessment in data envelopment analysis," Annals of Operations Research, Springer, vol. 322(2), pages 661-690, March.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    2. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    3. Dana PANCUROVA & Stefan LYOCSA, 2013. "Determinants of Commercial Banks’ Efficiency: Evidence from 11 CEE Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(2), pages 152-179, May.
    4. Bernardino Benito & José Solana & María-Rocío Moreno, 2014. "Explaining efficiency in municipal services providers," Journal of Productivity Analysis, Springer, vol. 42(3), pages 225-239, December.
    5. Amir Moradi-Motlagh & Ali Emrouznejad, 2022. "The origins and development of statistical approaches in non-parametric frontier models: a survey of the first two decades of scholarly literature (1998–2020)," Annals of Operations Research, Springer, vol. 318(1), pages 713-741, November.
    6. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    7. Bampatsou, Christina & Halkos, George, 2018. "Dynamics of productivity taking into consideration the impact of energy consumption and environmental degradation," Energy Policy, Elsevier, vol. 120(C), pages 276-283.
    8. Agrell, Per J. & Niknazar, Pooria, 2014. "Structural and behavioral robustness in applied best-practice regulation," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 89-103.
    9. Christian von Hirschhausen & Astrid Cullmann, 2008. "Next Stop: Restructuring?: A Nonparametric Efficiency Analysis of German Public Transport Companies," Discussion Papers of DIW Berlin 831, DIW Berlin, German Institute for Economic Research.
    10. Halkos, George & Bampatsou, Christina, 2017. "Technical efficiency, productivity change and environmental degradation," MPRA Paper 77176, University Library of Munich, Germany.
    11. S Blancard & J-P Boussemart & H Leleu, 2011. "Measuring potential gains from specialization under non-convex technologies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(10), pages 1871-1880, October.
    12. Boutheina Bannour & Asma Sghaier & Mohammad Nurunnabi, 2020. "How to Choose a Nonparametric Frontier Model? Technical Efficiency of Turkish Banks Assessing Global," Global Business Review, International Management Institute, vol. 21(2), pages 348-364, April.
    13. Jamasb, Tooraj & Pollitt, Michael & Triebs, Thomas, 2008. "Productivity and efficiency of US gas transmission companies: A European regulatory perspective," Energy Policy, Elsevier, vol. 36(9), pages 3398-3412, September.
    14. José Solana‐Ibáñez & Manuel Caravaca‐Garratón & Ricardo Teruel‐Sánchez, 2020. "Stakeholder perception on corporate reputation and management efficiency: Evidence from the Spanish Defence sector," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(5), pages 2381-2399, September.
    15. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    16. Marcel Clermont & Julia Schaefer, 2019. "Identification of Outliers in Data Envelopment Analysis," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 475-496, October.
    17. Léopold Simar & Paul Wilson, 2011. "Inference by the m out of n bootstrap in nonparametric frontier models," Journal of Productivity Analysis, Springer, vol. 36(1), pages 33-53, August.
    18. Gilbert, R. Alton & Wheelock, David C. & Wilson, Paul W., 2004. "New evidence on the Fed's productivity in providing payments services," Journal of Banking & Finance, Elsevier, vol. 28(9), pages 2175-2190, September.
    19. Pontus Mattsson & Jonas Månsson & Christian Andersson & Fredrik Bonander, 2018. "A bootstrapped Malmquist index applied to Swedish district courts," European Journal of Law and Economics, Springer, vol. 46(1), pages 109-139, August.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:223:y:2014:i:1:p:95-108:10.1007/s10479-014-1604-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.