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Benchmarking—A Way of Finding Risk Factors in Business Performance

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  • Jarmila Horváthová

    (Faculty of Management, University of Prešov, Konštantínova 16, 080 01 Prešov, Slovakia)

  • Martina Mokrišová

    (Faculty of Management, University of Prešov, Konštantínova 16, 080 01 Prešov, Slovakia)

  • Mária Vrábliková

    (Faculty of Management, University of Prešov, Konštantínova 16, 080 01 Prešov, Slovakia)

Abstract

The purpose of this study was to emphasize that the Data Envelopment Analysis (DEA) method is an important benchmarking tool which provides necessary information for improving business performance. To fulfil the abovementioned goal, we used a sample of 48 Slovak companies involved in the field of heat supply. As their position in the economic and social environment of the country is essential, considerable attention should be paid to improving their performance. In addition to the DEA method, we applied the Best Value Method (BVM). We found that DEA is a highly important benchmarking tool, as it provides benchmarks for units that have problems with performance and helps us to reveal risk performance factors. The DEA method also allows us to determine target values of indicators. The originality of this paper is in its comparison of the results of the BVM and the DEA methods.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:5:p:221-:d:554437
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    References listed on IDEAS

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    1. Bożena Kaczmarska, 2010. "The data anvelopment analysis method in benchmarking of technological incubators," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 20(1), pages 79-95.
    2. Rossi, Martin A., 2001. "Technical change and efficiency measures: the post-privatisation in the gas distribution sector in Argentina," Energy Economics, Elsevier, vol. 23(3), pages 295-304, May.
    3. William W. Cooper & Lawrence M. Seiford & Joe Zhu, 2011. "Data Envelopment Analysis: History, Models, and Interpretations," 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 1-39, Springer.
    4. 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.
    5. Bala Krishnamoorthy & Christine D'Lima, 2014. "Benchmarking as a measure of competitiveness," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 4(3), pages 342-359.
    6. Farsi, Mehdi & Filippini, Massimo & Kuenzle, Michael, 2007. "Cost efficiency in the Swiss gas distribution sector," Energy Economics, Elsevier, vol. 29(1), pages 64-78, January.
    7. Ittner, Christopher D. & Larcker, David F. & Randall, Taylor, 2003. "Performance implications of strategic performance measurement in financial services firms," Accounting, Organizations and Society, Elsevier, vol. 28(7-8), pages 715-741.
    8. Li, Yongjun & Liang, Liang & Chen, Yao & Morita, Hiroshi, 2008. "Models for measuring and benchmarking olympics achievements," Omega, Elsevier, vol. 36(6), pages 933-940, December.
    9. An, Qingxian & Tao, Xiangyang & Xiong, Beibei, 2021. "Benchmarking with data envelopment analysis: An agency perspective," Omega, Elsevier, vol. 101(C).
    10. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    11. Róbert Štefko & Petra Vašaničová & Sylvia Jenčová & Aneta Pachura, 2021. "Management and Economic Sustainability of the Slovak Industrial Companies with Medium Energy Intensity," Energies, MDPI, vol. 14(2), pages 1-15, January.
    12. Nicoleta Bărbuță-Mișu & Mara Madaleno & Vasile Ilie, 2019. "Analysis of Risk Factors Affecting Firms’ Financial Performance—Support for Managerial Decision-Making," Sustainability, MDPI, vol. 11(18), pages 1-19, September.
    13. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    14. Zhilong Tian & Suttapong Ketsaraporn, 2013. "Performance benchmarking for building best practice in business competitiveness and case study," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 12(1), pages 40-55.
    15. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    16. Ruiz, José L. & Sirvent, Inmaculada, 2019. "Performance evaluation through DEA benchmarking adjusted to goals," Omega, Elsevier, vol. 87(C), pages 150-157.
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