IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v5y2015i1p2158244015577666.html
   My bibliography  Save this article

Three-Stage Data Envelopment Analysis as a Tool for Nurse Leader Performance Appraisals

Author

Listed:
  • Janko Seljak
  • Andreja Kvas

Abstract

As in other sectors, increasingly higher performance and efficiency are also being required from health care employees. To achieve this goal, every health care organization should have a suitable human resource management system. The selection, education, training, effective performance appraisal, and evaluation of leaders are particularly of key importance for every organization. Data envelopment analysis (DEA) is used in this study to develop a model of practice outputs and inputs to help identify the most efficient nurse leaders. The employees’ performance appraisals are often closely related to their specific organizations. As leaders’ behaviors are also influenced by external, non-discretionary factors, the three-stage DEA was used to include inputs not controlled by individual leaders. This article proposes a performance appraisal based on competency models of leadership for a larger professional group working across several different organizations, yet in similar professional and institutional environments. The empirical data in this article are based on two surveys that were conducted in 15 Slovenian public hospitals.

Suggested Citation

  • Janko Seljak & Andreja Kvas, 2015. "Three-Stage Data Envelopment Analysis as a Tool for Nurse Leader Performance Appraisals," SAGE Open, , vol. 5(1), pages 21582440155, March.
  • Handle: RePEc:sae:sagope:v:5:y:2015:i:1:p:2158244015577666
    DOI: 10.1177/2158244015577666
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2158244015577666
    Download Restriction: no

    File URL: https://libkey.io/10.1177/2158244015577666?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
    ---><---

    References listed on IDEAS

    as
    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. Ruggiero, John, 1998. "Non-discretionary inputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 111(3), pages 461-469, December.
    3. Robert Rosenman & Daniel Friesner, 2004. "Scope and scale inefficiencies in physician practices," Health Economics, John Wiley & Sons, Ltd., vol. 13(11), pages 1091-1116, November.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Joe Sarkis, 2007. "Preparing Your Data for DEA," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 305-320, Springer.
    6. Jon A. Chilingerian & H. David Sherman, 2011. "Health-Care Applications: From Hospitals to Physicians, from Productive Efficiency to Quality Frontiers," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 445-493, Springer.
    7. Josef Jablonsky, 2012. "Multicriteria approaches for ranking of efficient units in DEA models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(3), pages 435-449, September.
    8. Wade D. Cook & Joe Zhu, 2007. "Data Irregularities And Structural Complexities In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 1-11, Springer.
    9. Shiva Prasad H. C. & Damodar Suar & Roman Taraban, 2014. "Antecedents and Moderators of Software Professionals’ Performance," SAGE Open, , vol. 4(1), pages 21582440145, February.
    10. Giulia Garavaglia & Emanuele Lettieri & Tommaso Agasisti & Silvano Lopez, 2011. "Efficiency and quality of care in nursing homes: an Italian case study," Health Care Management Science, Springer, vol. 14(1), pages 22-35, March.
    Full references (including those not matched with items on IDEAS)

    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. Wai‐Peng Wong & Qiang Deng & Ming-Lang Tseng & Loo‐Hay Lee & Chee‐Wooi Hooy, 2014. "A Stochastic Setting To Bank Financial Performance For Refining Efficiency Estimates," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 225-245, October.
    2. Kottas, Angelos T. & Madas, Michael A., 2018. "Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants," Journal of Air Transport Management, Elsevier, vol. 70(C), pages 1-17.
    3. Iparraguirre, José Luis & Ma, Ruosi, 2015. "Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 33-46.
    4. Margareta Gardijan & Zrinka Lukač, 2018. "Measuring the relative efficiency of the food and drink industry in the chosen EU countries using the data envelopment analysis with missing data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 695-713, September.
    5. Mehdiloozad, Mahmood & Zhu, Joe & Sahoo, Biresh K., 2018. "Identification of congestion in data envelopment analysis under the occurrence of multiple projections: A reliable method capable of dealing with negative data," European Journal of Operational Research, Elsevier, vol. 265(2), pages 644-654.
    6. Alessandra Cepparulo & Gilles Mourre, 2020. "How and How Much? The Growth-Friendliness of Public Spending through the Lens," European Economy - Discussion Papers 132, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    7. Necmi Avkiran & Alan McCrystal, 2014. "Intertemporal analysis of organizational productivity in residential aged care networks: scenario analyses for setting policy targets," Health Care Management Science, Springer, vol. 17(2), pages 113-125, June.
    8. George Fragkiadakis & Michael Doumpos & Constantin Zopounidis & Christophe Germain, 2016. "Operational and economic efficiency analysis of public hospitals in Greece," Post-Print hal-01414677, HAL.
    9. Angeliki Flokou & Vassilis Aletras & Dimitris Niakas, 2017. "Decomposition of potential efficiency gains from hospital mergers in Greece," Health Care Management Science, Springer, vol. 20(4), pages 467-484, December.
    10. Widiarto, Indra & Emrouznejad, Ali, 2015. "Social and financial efficiency of Islamic microfinance institutions: A Data Envelopment Analysis application," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 1-17.
    11. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    12. Matthias Staessens & Pieter Jan Kerstens & Johan Bruneel & Laurens Cherchye, 2019. "Data Envelopment Analysis and Social Enterprises: Analysing Performance, Strategic Orientation and Mission Drift," Journal of Business Ethics, Springer, vol. 159(2), pages 325-341, October.
    13. Zhensheng Chen & Xueli Chen & Tomas Baležentis & Xiaoqing Gan & Vivian Valdmanis, 2020. "Productivity change and its driving forces in Chinese healthcare sector," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-16, December.
    14. Simona Cohen-Kadosh & Zilla Sinuany-Stern, 2020. "Hip fracture surgery efficiency in Israeli hospitals via a network data envelopment analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 251-277, March.
    15. Mohamed Dia & Amirmohsen Golmohammadi & Pawoumodom M. Takouda, 2020. "Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA," JRFM, MDPI, vol. 13(4), pages 1-25, April.
    16. Despotis, Dimitris K. & Stamati, Lamprini V. & Smirlis, Yiannis G., 2010. "Data envelopment analysis with nonlinear virtual inputs and outputs," European Journal of Operational Research, Elsevier, vol. 202(2), pages 604-613, April.
    17. George Fragkiadakis & Michael Doumpos & Constantin Zopounidis & Christophe Germain, 2016. "Operational and economic efficiency analysis of public hospitals in Greece," Annals of Operations Research, Springer, vol. 247(2), pages 787-806, December.
    18. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    19. Moran, Valerie & Jacobs, Rowena, 2013. "An international comparison of efficiency of inpatient mental health care systems," Health Policy, Elsevier, vol. 112(1), pages 88-99.
    20. 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.

    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:sae:sagope:v:5:y:2015:i:1:p:2158244015577666. 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: SAGE Publications (email available below). General contact details of provider: .

    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.