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Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses

Author

Listed:
  • Róbert Štefko

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

  • 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)

Abstract

The paper deals with methods of predicting bankruptcy of a business with the aim of choosing a prediction method which will have exact results. Existing bankruptcy prediction models are a suitable tool for predicting the financial difficulties of businesses. However, such tools are based on strictly defined financial indicators. Therefore, the Data Envelopment Analysis (DEA) method has been applied, as it allows for the free choice of financial indicators. The research sample consisted of 343 businesses active in the heating industry in Slovakia. Analysed businesses have a significant relatively stable position in the given industry. The research was based on several studies which also used the DEA method to predict future financial difficulties and bankruptcies of studied businesses. The estimation accuracy of the Additive DEA model (ADD model) was compared with the Logit model to determine the reliability of the DEA method. Also, an optimal cut-off point for the ADD model and Logit model was determined. The main conclusion is that the DEA method is a suitable alternative for predicting the failure of the analysed sample of businesses. In contrast to the Logit model, its results are independent of any assumptions. The paper identified the key indicators of the future success of businesses in the analysed sample. These results can help businesses to improve their financial health and competitiveness.

Suggested Citation

  • Róbert Štefko & Jarmila Horváthová & Martina Mokrišová, 2020. "Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses," JRFM, MDPI, vol. 13(9), pages 1-15, September.
    • Handle: RePEc:gam:jjrfmx:v:13:y:2020:i:9:p:212-:d:414399
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    References listed on IDEAS

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    Cited by:

    1. Luminița RUS & Daniela ZĂPODEANU & Carmen SCORȚE & Sorina MOCIAR-COROIU, 2022. "Indicators And 3r-Type Measures In Overcoming Financial Difficulties Of Companies," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 2(2), pages 153-165, December.
    2. Beata Gavurova & Sylvia Jencova & Radovan Bacik & Marta Miskufova & Stanislav Letkovsky, 2022. "Artificial intelligence in predicting the bankruptcy of non-financial corporations," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1215-1251, December.
    3. Michaela Staňková, 2023. "Threshold Moving Approach with Logit Models for Bankruptcy Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1251-1272, March.
    4. Xinlin Wang & Zs'ofia Kraussl & Mats Brorsson, 2024. "Datasets for Advanced Bankruptcy Prediction: A survey and Taxonomy," Papers 2411.01928, arXiv.org.
    5. 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.
    6. Mehmet Civelek & Vladimír Krajèík & Vendula Fialova, 2023. "The impacts of innovative and competitive abilities of SMEs on their different financial risk concerns: System approach," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 327-354, March.

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