Financial threat profiles of industrial enterprises in Poland




financial threat, bankruptcy, early warning systems, risk management, enterprise crisis


Research background: The nature of bankruptcy has been the subject of interest for economic theories, both positive?identifying relationships between bankruptcy and other economic categories ? and normative, shaping the rules for the proper regulation of bankruptcy. In turn, the functioning of an enterprise in conditions of risk, financial threat, and finally a crisis that could lead to bankruptcy, are of interest to management. The interpenetration of these two dimensions provided the motivation for this study, which assumes a bottom-up approach: from individual results to summarised multi-sectional comparisons.

Purpose of the article: The purpose of the research was to evaluate the level, directions of change, and structure of the degree of financial threat in industrial enterprises. The period under analysis was 2007?2018 and the whole population of industrial enterprises in Poland (15,999 entities) was examined. The enterprises were small and medium-sized enterprises (SMEs) as well as large enterprises (LEs). The financial analysis covered macro-, meso-, and microeconomic levels.

Methods: The analysis was conducted using a comparative approach and financial threat predictions obtained from the original multivariable logit model. Heat maps were used to evaluate the intensity of changes in financial threat. The displacement of objects in structures was studied, ordered, and classified. Four normative standards of threat scenarios were defined and then used to evaluate similarities in the profiles of the structures examined, using the similarity measure. The ranking and its variability were analysed in the assessment of profiles.

Findings & value added: As the result of the research, properties were described and profiles were determined for the structures in terms of the degree of threat and its correlation with rate of bankruptcy and creating added value. The originality of the research comes from the use of novel dynamic logit models. The added value is a unique study on the entire population of industrial enterprises in the national economy and a methodology for identifying financial threat profiles and their similarity at subsequent aggregation levels (the micro-, meso-, and macro-levels). This made it possible to derive patterns and regularities for economic policy and guidelines for business management.


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Altman, E. I. (1993). Corporate financial distress and bankruptcy. A complete guide to predicting & avoiding distress and profiting from bankruptcy. New York: John Wiley & Sons Press.

Altman, E. I., & Narayanan, P. (1997). An international survey of business failure classification models. Financial Markets, Institutions and Instruments, 6(2), 1?57. doi: 10.1111/1468-0416.00010.

Altman, E. I., Sabato, G., & Wilson, N. (2010). The value of non-financial information in small and medium-sized enterprise risk management. Journal of Credit Risk, 2(6), 95?127. doi: 10.21314/JCR.2010.110.

Ansoff, H. I. (1985). Strategic management. Warszawa: PWE Press.

Antonowicz, P. (2007). Methods of evaluation and economic and financial condition of enterprises. Gdańsk: ODiDK.

Argenti, J. (1976). Corporate collapse. The causes and symptoms. London: McGraw?Hill Book.

Back, B., Laitinen, T., Hekanaho, J., & Sere, K. (1997). The effect of sample size on different failure prediction methods. Turku Centre for Computer Science, TUCS Technical Report, 155, 1?23.

Bărbu?ă-Mi?u, N., & Codreanu, E.-S. (2014). Analysis and prediction of the bankruptcy risk in romanian building sector companies. Ekonomika, 93(2), 131?146. doi: 10.15388/EKON.2014.2.3542.

Bărbu?ă-Mi?u, N., & Madaleno, M. (2020). Assessment of bankruptcy risk of large companies, European countries evolution analysis. Journal of Risk and Financial Management, 13(3), 58. doi: 10.3390/jrfm13030058.

Beaver, W. H. (1968). Alternative accounting measures as predictors of failure. Accounting Review, 43(1), 113?122. doi: 10.2307/244122.

Cabała, P. (2008). Enterprise early warning systems. Kraków: Uniwersytet Ekonomiczny w Krakowie.

Crocford, G. N. (1982). The bibliography and history of risk management. Geneva Papers on Risk and Insurance, 7(2), 169?179. doi: 10.1057/gpp.1982.10.

Cultrera L., & Brédart X. (2016). Bankruptcy prediction: the case of Belgian SMEs. Review of Accounting and Finance, 15(1), 101?119. doi: 10.1108/RAF-06-2014-0059.

Drucker, P. F. (2010). The practice of management. New York: Harper Business.

Fijorek, K., Kaczmarek, J., Kolegowicz, K., & Krzemiński, P. (2011). The concept of research on the state and performance of enterprises for the purpose of the Rapid Reaction Instrument. Assumptions of the "Early Warning System" solution - Methods and tools for monitoring the economy in the microeconomic component. Kraków: Małopolska Szkoła Administracji Publicznej Uniwersytetu Ekonomicznego w Krakowie.

Fijorek, K., & Sokołowski, A. (2012). Separation?resistant and bias?reduced logistic regression: STATISTICA macro. Journal of Statistical Software, 47, 1?12. doi: 10.18637/jss.v047.c02.

Firth, D. (1993). Bias reduction of maximum likelihood estimates. Biometrika, 80(1), 27?38. doi: 10.2307/2336755.

Greiner, L. E. (1972). Evolution and revolution as organizations grow. Harvard Business Review, 7/8, 37?46. doi: 10.1111/j.1741-6248.1997.00397.x.

Gupta, J., Barzotto, M., & Khorasgani, A. (2018). Does size matter in predicting SMEs failure? International Journal of Finance and Economics. Advance online publication. doi: 10.2139/ssrn.2638485.

Hadasik, D. (1998). Bankruptcy of companies in Poland and methods of forecasting it. Zeszyty Naukowe, Akademia Ekonomiczna w Poznaniu, 153, 1?198.

Hafiz, A. A., Lukumon, O. O., Hakeem, A. O., Vikas K., Saheed, O. A., Olugbenga, O. A., & Muhammad, B. (2018). Systematic review of bankruptcy prediction models: towards a framework for tool selection. Expert Systems with Applications, 94, 164?184. doi: 10.1016/j.eswa.2017.10.040.

Hosmer, D. W., & Lemeshow, S. (1989). Applied logistic regression. New York: John Wiley & Sons Publishing.

Hudáková, M., & Dvorský, J. (2018). Assessing the risks and their sources in dependence on the rate of implementing the risk management process in the SMEs. Equilibrium. Quarterly Journal of Economics and Economic Policy, 13(3), 543?567. doi: 10.24136/eq.2018.027.

Jajuga, K. (2006). Statistical models of early warning - formal methods. Barometr Regionalny, 6, 52?55. Retrieved from 06_07jajuga.pdf.

Juszczyk, S. (2010). Forecasting of bankruptcy of enterprises. Ekonomista, 5, 701?728.

Kaczmarek, J. (2010). Counteracting the crisis in the economies of new EU member states in the context of the development of integration processes. In M. Lanfranchi (Ed.). The community integration process between Eastern and Southern Europe. Messina: Edizioni Dr. Antonino Sfaneni, 19?39.

Kaczmarek, J. (2014). A crisis and a treat vs. the financial security aspects of going concern. Economic Horizons, 16, 195?209. doi: 10.5937/ekonhor1403 195K.

Kaczmarek, J. (2019). The mechanisms of creating value vs. financial security of going concern - sustainable management. Sustainability, 11(8), 2278, 1?24. doi: 10.3390/su11082278.

Kanapickiene R., & Marcinkevicius R. (2014). Possibilities to apply classical bankruptcy prediction models in the construction sector in Lithuania. Economics and Management, 19(4). doi: 10.5755/j01.em.19.4.8095.

Kaplan, R., & Norton, D. (2006). The balanced scorecard: translating strategy into action. Boston: Harvard Business Press.

Kharbanda, O. P., & Stallworthy, E. A. (1985). Corporate failure. Prediction, panacea and prevention. London?New York: McGraw?Hill.

Kliestik, T., Vrbka, J., & Rowland, Z. (2018). Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis. Equilibrium. Quarterly Journal of Economics and Economic Policy, 13(3), 569?593. doi: 10.24136/eq. 2018.028.

Kovacova, M., Kliestik, T., Valaskova, K., Durana, P., & Juhaszova, Z. (2019). Systematic review of variables applied in bankruptcy prediction models of Visegrad group countries. Oeconomia Copernicana, 10(4), 743?772. doi: 10.2413 6/oc.2019.034.

Lam, J. (1985). Ten predictions for risk management. RMA Journal, 5, 84?85.

Long, S. J. (1997). Regression models for categorical and limited dependent variables. London: Thousand Oaks, SAGE Publications.

Obłój, K. (1987). Organisational crises. Przegląd Organizacji, 1, 7?14.

Odunaiya, T. (2013). A study of the accuracy of bankruptcy prediction models: can impending bankruptcies on the UK high street be predicted? University of Westminster.

Platt, H. D., & Platt, M. B. (2002). Predicting corporate financial distress: reflection on choice?based sample bias. Journal of Economics and Finance, 26(2), 184?199. doi: 10.1007/BF02755985.

Pozzoli M., & Paolone F. (2017). Corporate financial distress. A study of the Italian manufacturing industry. Cham: Springer. doi: 10.1007/978-3-319-67355-4.

Prusak, B. (2005). Modern methods of forecasting financial risks for companies. Warszawa: Difin.

Quinn, B., & Cameron, K. (1983). Organizational life cycles and shifting criteria of effectiveness: some preliminary evidence. Management Science, 29(1), 33?51. doi: 10.1287/mnsc.29.1.33.

Rappaport, A. (1998). Creating shareholder value: a guide for managers and investors. New York, USA: The Free Press.

Senbet, L. W., & Wang, T. Y. (2012). Corporate financial distress and bankruptcy: a survey (foundations and trends in finance). Boston: Now Publishers Inc.

Slatter, S., & Lovett, D. (1999). Corporate recovery: managing companies in distress. Frederick (MD): Beard Books.

Smart, C. F., Thompson, W. A., & Vertinsky, I. (1978). Diagnosing corporate effectiveness and susceptibility to crisis. Journal of Business Administration, 9, 57?96.

Smith, M., & Liou, D. (2007). Industrial sector and financial distress. Managerial Auditing Journal, 22(4), 376?391. doi: 10.1108/02686900710741937.

Sobczyk, E. J., Kaczmarek, J., Fijorek, K., & Kopacz, M. (2020). Efficiency and financial standing of coal mining enterprises in Poland in terms of restructuring course and effects. Gospodarka Surowcami Mineralnymi, 36(2), 127?152. doi: 10.24425/gsm.2020.132565.

Špička, J. (2013). The financial condition of the construction companies before bankruptcy. European Journal of Business and Management, 5(23), 160?169.

Svabova, L., & Durica, M. (2019). Being an outlier: a company non-prosperity sign? Equilibrium. Quarterly Journal of Economics and Economic Policy, 14(2), 359?375. doi: 10.24136/eq.2019.017.

Syamni, G., Majid, M. S. A., & Siregar, W. V. (2018). Bankruptcy prediction models and stock prices of the coal mining industry in Indonesia. Etikonomi, 17(1). doi: 10.15408/etk.v17i1.6559.

Tobback, E., Bellotti, T., Moeyersoms, J., Stankova, M., & Martens, D. (2017). Bankruptcy prediction for SMEs using relational data. Decision Support Systems, 102, 69?81. doi: 10.1016/j.dss.2017.07.004.

Valaskova, K., Kliestik, T., & Kovacova, M. (2018). Management of financial risks in Slovak enterprises using regression analysis. Oeconomia Copernicana, 9(1), 105?121. doi: 10.24136/oc.2018.006.

Weibel, P. F. (1973). The value of criteria to judge credit worthiness in the lending of banks. Stuttgart: Bern.

Winston, W., Angrisani, D. P., & Goldman, R. L. (1997). Predicting successful hospital mergers and acquisitions: a financial and marketing analytical tool, New York: Routledge.

Zelek, A. (2003). Corporate crisis management - a strategic perspective. Warszawa: Instytut Organizacji i Zarządzania w Przemyśle ?ORGMASZ?.




How to Cite

Kaczmarek, J., Alonso, S. L. N., Sokołowski, A., Fijorek, K., & Denkowska, S. (2021). Financial threat profiles of industrial enterprises in Poland. Oeconomia Copernicana, 12(2), 463–498.