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Sytuacja finansowa klubów Ekstraklasy w ujęciu metody DEA

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  • Wyszyński, Artur

Abstract

The aim of this article is to determine the financial standing of Polish Ekstraklasa premier-division soccer clubs. The Data Envelopment Analysis (DEA) model is applied to study technical efficiency ratios based on financial ratios describing the clubs’ financial condition. Statistical and econometric analyses were carried out in order to assess the relationship between performance indicators and the financial situation of the clubs, specifically their liquidity, profitability and debt. This study shows that there is a strong relationship between the condition and efficiency of the clubs. This finding was confirmed by the results of an analysis of the effectiveness of clubs as well as regression analysis. The clubs are classified into two groups: effective and ineffective. Highly effective clubs are in a significantly better financial position than ineffective ones. The current liquidity ratio was the best discriminator separating the clubs into the two groups and having the greatest impact on their growing effectiveness as the three basic financial indicators were analyzed. The impact of the two other indicators, profitability and debt, was much smaller. The discriminant function results were used to determine the financial standing of Ekstraklasa clubs in the 2014/2015 season.

Suggested Citation

  • Wyszyński, Artur, 2017. "Sytuacja finansowa klubów Ekstraklasy w ujęciu metody DEA," Gospodarka Narodowa-The Polish Journal of Economics, Szkoła Główna Handlowa w Warszawie / SGH Warsaw School of Economics, vol. 2017(2), February.
  • Handle: RePEc:ags:polgne:359124
    DOI: 10.22004/ag.econ.359124
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    1. E H Feroz & S Kim & R L Raab, 2003. "Financial statement analysis: A data envelopment analysis approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(1), pages 48-58, January.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. 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.
    4. Jardin, Mathieu, 2009. "Efficiency of French football clubs and its dynamics," MPRA Paper 19828, University Library of Munich, Germany.
    5. Peter Dawson & Stephen Dobson & Bill Gerrard, 2000. "Stochastic Frontiers and the Temporal Structure of Managerial Efficiency in English Soccer," Journal of Sports Economics, , vol. 1(4), pages 341-362, November.
    6. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    7. Wojciech Major, 2015. "Data Envelopment Analysis as an instrument for measuring the efficiency of courts," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 25(4), pages 19-34.
    8. Carlos Pestana Barros & Stephanie Leach, 2006. "Performance evaluation of the English Premier Football League with data envelopment analysis," Applied Economics, Taylor & Francis Journals, vol. 38(12), pages 1449-1458.
    9. Emel, Ahmet Burak & Oral, Muhittin & Reisman, Arnold & Yolalan, Reha, 2003. "A credit scoring approach for the commercial banking sector," Socio-Economic Planning Sciences, Elsevier, vol. 37(2), pages 103-123, June.
    10. Joseph Paradi & Mette Asmild & Paul Simak, 2004. "Using DEA and Worst Practice DEA in Credit Risk Evaluation," Journal of Productivity Analysis, Springer, vol. 21(2), pages 153-165, March.
    11. Hofler, Richard A. & Payne, James E., 1997. "Measuring efficiency in the National Basketball Association1," Economics Letters, Elsevier, vol. 55(2), pages 293-299, August.
    12. Barros, Carlos Pestana & Garcia-del-Barrio, Pedro, 2008. "Efficiency measurement of the English football Premier League with a random frontier model," Economic Modelling, Elsevier, vol. 25(5), pages 994-1002, September.
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