BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Tomczak Sebastian (Wrocław University of Science and Technology, Wrocław, Poland)
General Bankruptcy Prediction Models for the Visegrád Group. The Stability over Time
Operations Research and Decisions, 2023, vol. 33, no. 4, s. 171-187, rys., tab., bibliogr. 29 poz.
Kondycja finansowa, Zarządzanie przedsiębiorstwem, Prognozowanie upadłości przedsiębiorstwa, Upadłość przedsiębiorstwa, Przedsiębiorstwo budowlane
Financial condition, Enterprise management, Enterprises bankruptcy forecasting, Enterprise bankruptcy, Construction company
Managers of enterprises must constantly face the continual changes on the market and fight for survival in a world of high competition. Therefore, it is important to systematically monitor the company's financial condition. This will help to identify problems and give specific time to take corrective action. Bankruptcy prediction models are usually constructed for local goals. The purpose of the article is to build not only regional but also general discriminant and logit models for the SMEs operating in the construction industry in Visegrád Group countries. A total of 32 unique models were built and verified along with the Altman model for emerging markets. The paper also contributes to the literature by assessing the stability of the constructed models over time, which the models' authors do not usually measure. The results showed that regional models are characterized by higher accuracy than general ones. However, general models can be adapted to the analyzed Visegrád Group with an accuracy of approximately 90%. The G1 LR model can be considered the best model, as it has relatively high accuracy and over-time stability. (original abstract)
The Main Library of the Cracow University of Economics
Full text
  1. Altman, E. I., and Hotchkiss, E. Corporate Financial Distress and Bankruptcy. John Wiley & Sons, New York, 1993.
  2. Altman, E. I., Iwanicz-Drozdowska, M., Laitinen, E. K., and Suvas, A. Financial distress prediction in an international context: A review and empirical analysis of Altman's Z-Score model. Journal of International Financial Management & Accounting 28, 2 (2017), 131-171.
  3. Balina, R., and Bąk, M. J. Discriminant analysis as a method of prediction of enterprises bankruptcy with consideration of industry aspects. Wydawnictwo Naukowe Intellect, 2016 (in Polish).
  4. Durica, M., Valaskova, K., and Janoskova, K. Logit business failure prediction in V4 countries. Engineering Management in Production and Services 11, 4 (2019), 54-64.
  5. Ékes, S. K., and Koloszár, L. The efficiency of bankruptcy forecast models in the Hungarian SME sector. Journal of Competitiveness 6, 2 (2014), 56-73.
  6. Hosmer Jr, D. W., Lemeshow, S., and Sturdivant, R. X. Applied logistic regression, John Wiley & Sons, 2013.
  7. Iwanowicz, T. Empirical verification of the mechanical transferability of the Altman model to the conditions of the Polish economy and the sectoral universality of models. Zeszyty Teoretyczne Rachunkowości, 96 (152) (2018), 63-79 (in Polish).
  8. Karas, M., and Reznakova, M. Predicting the bankruptcy of construction companies: a CART-based model. Engineering Economics 28, 2 (2017), 145-154.
  9. Karas, M., and Srbová, P. Predicting bankruptcy in construction business: Traditional model validation and formulation of a new model. Journal of International studies 12, 1 (2019), 283-296.
  10. Kisielinska, J. The effectiveness of corporate bankruptcy models. Economic and Regional Studies 9, 1 (2016), 5-17.
  11. Klieštik, T., Vrbka, J., and Rowland, Z. Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis. Equilibrium. Quarterly Journal of Economics and Economic Policy 13, 3 (2018), 569-593.
  12. Korol, T. The implementation of fuzzy logic in forecasting financial ratios. Contemporary Economics 12, 2 (2018), 165-187.
  13. Kováčová, M., and Klieštik, T. Logit and probit application for the prediction of bankruptcy in Slovak companies. Equilibrium. Quarterly Journal of Economics and Economic Policy 12, 4 (2017), 775-791.
  14. Kováčová, M., Klieštik, T., Kubala, P., Valasková, K., Radišić, M., and Borocki, J. Bankruptcy models: Verifying their validity as a predictor of corporate failure. Polish Journal of Management Studies 18, 1 (2018), 167-179.
  15. Kovácová, M., Klieštik, T., Valaskova, K., Durana, P., and Juhászová, Z. Systematic review of variables applied in bankruptcy prediction models of Visegrad group countries. Oeconomia Copernicana 10, 4 (2019), 743-772.
  16. Kowalak, R. Assessing the financial health of an enterprise in a bankruptcy risk study. Ośrodek Doradztwa i Doskonalenia Kadr, 2008 (in Polish).
  17. Kristóf, T. The application of casebased reasoning to predict the bankruptcy of domestic micro-enterprises. Statisztikai Szemle 96, 11-12 (2018), 1109-1128 (in Hungarian).
  18. Mączyńska, E., and Zawadzki, M. Discriminatory prediction models for bankruptcy of enterprises. Ekonomista 2 (2006), 205-235 (in Polish).
  19. Nyitrai, T. Dynamization of bankruptcy models via indicator variables. Benchmarking: An International Journal 26, 1 (2019), 317-332.
  20. Pavlicko, M., Durica, M., and Mazanec, J. Ensemble model of the financial distress prediction in Visegrad group countries. Mathematics 9, 16 (2021), 1886.
  21. Pisula, T. An ensemble classifier-based scoring model for predicting bankruptcy of Polish companies in the Podkarpackie Voivodeship. Journal of Risk and Financial Management 13, 2 (2020), 37.
  22. Pražák, T., and Gongol, T. Bankrupcy models in the business environment of Visegrad group countries. Economic Mamagement Innovetion 13, 3 (2021), 37-51.
  23. Ptak-Chmielewska, A. Bankruptcy prediction of small-and medium-sized enterprises in Poland based on the LDA and SVM methods. Statistics in Transition. New Series 22, 1 (2021), 179-195.
  24. Radosiński, E. Introduction to Reporting, Analytics and Financial Informatics. Wydawnictwo Naukowe PWN, 2010 (in Polish).
  25. Svabova, L., Kramarova, K., and Durica, M. Prediction model of firms financial distress. Ekonomicko-manazerske spektrum 12, 1 (2018), 16-29.
  26. Tomczak, S. K. The early warning system. Journal of Management and Financial Sciences 7, 16 (2014), 51-74.
  27. Tomczak, S. K. Multi-class models for assessing the financial condition of manufacturing enterprises. Contemporary Economics 14, 2 (2020), 219-236.
  28. Tomczak, S. K., and Radosiński, E. The effectiveness of discriminant models based on the example of the manufacturing sector. Operations Research and Decisions 27, 3 (2017), 81-97.
  29. Tomczak, S. K., and Staszkiewicz, P. Cross-country application of manufacturing failure models. Journal of Risk and Financial Management 13, 2 (2020), 34.
Cited by
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu