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Data Envelopment Analysis as a Tool for Evaluation of Employees’ Performance

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  • Zbranek, Peter

Abstract

Employee performance evaluation systems, which are well designed and properly used, are essential for the effective functioning of the organization. Due to some disadvantages of traditional methods, there is a need to develop new evaluation procedures. The main contribution of this paper is to apply a multidimensional approach, represented by the method of Data Envelopment Analysis (DEA) to measure the performance and efficiency of employees. This approach overcomes several weaknesses of traditional systems of the employees’ performance evaluation and provides a comprehensive indicator of the performance of individual employees, their technical efficiency score. The input variables of the used model were the motivational factors (salary, working conditions and benefits); the output was the indirectly assessed performance through work motivation, job satisfaction and organizational commitment. Furthermore, we applied the nonparametric methods for compliance testing of mean values to validate the stated hypotheses. In a baking company using the DEA method, we identified 12 efficient employees and 48 employees who need to improve their outputs to achieve their maximum efficiency.

Suggested Citation

  • Zbranek, Peter, 2013. "Data Envelopment Analysis as a Tool for Evaluation of Employees’ Performance," Acta Oeconomica et Informatica, Faculty of Economics and Management, Slovak Agricultural University in Nitra (FEM SPU), vol. 16(1), pages 1-10, February.
  • Handle: RePEc:ags:aoeisl:144683
    DOI: 10.22004/ag.econ.144683
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    References listed on IDEAS

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    1. Timothy Anderson & Gunter Sharp, 1997. "A new measure of baseball batters using DEA," Annals of Operations Research, Springer, vol. 73(0), pages 141-155, October.
    2. José L. Ruiz & Diego Pastor & Jesús T. Pastor, 2013. "Assessing Professional Tennis Players Using Data Envelopment Analysis (DEA)," Journal of Sports Economics, , vol. 14(3), pages 276-302, June.
    3. Sueyoshi, Toshiyuki & Ohnishi, Kenji & Kinase, Youichi, 1999. "A benchmark approach for baseball evaluation," European Journal of Operational Research, Elsevier, vol. 115(3), pages 429-448, June.
    4. Cooper, W.W. & Ruiz, José L. & Sirvent, Inmaculada, 2009. "Selecting non-zero weights to evaluate effectiveness of basketball players with DEA," European Journal of Operational Research, Elsevier, vol. 195(2), pages 563-574, June.
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    Cited by:

    1. Han-Shen Chen & Bi-Kun Tsai & Gwo-Bao Liou & Chi-Ming Hsieh, 2018. "Efficiency Assessment of Inbound Tourist Service Using Data Envelopment Analysis," Sustainability, MDPI, vol. 10(6), pages 1-14, June.
    2. Phoebe Gay L. Refamonte & Dr. Ronald S. Decano, 2021. "The Influence of School-Based Management Implementation on Employees’ Performance," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 5(10), pages 692-697, October.
    3. Tadić, Snežana & Krstić, Mladen & Brnjac, Nikolina, 2019. "Selection of efficient types of inland intermodal terminals," Journal of Transport Geography, Elsevier, vol. 78(C), pages 170-180.
    4. Jarmila Horváthová & Martina Mokrišová & Mária Vrábliková, 2021. "Benchmarking—A Way of Finding Risk Factors in Business Performance," JRFM, MDPI, vol. 14(5), pages 1-17, May.
    5. Umi Mahmudah & Muhamad Safiih Lola, 2018. "Robust approach for efficiency measurement of employee performance under profit sharing system," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 10(1), pages 1-7, April.

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