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Firm failure processes and components of failure risk: An analysis of European bankrupt firms

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  • Lukason, Oliver
  • Laitinen, Erkki K.

Abstract

This paper aims to extract firm failure processes (FFPs) by using failure risk and rank the importance of failure risk contributors for different stages of FFPs. The dataset is composed of 1234 bankrupt firms from different European countries and three theoretically motivated FFPs are detected. For the dominant FFP found (73% of cases), failure risk becomes high very shortly before bankruptcy is declared. Annual and accumulated profitability are the most important failure risk contributors for these stages of all FFPs, where failure probability exceeds 50%. The obtained results provide important implications for bankruptcy prediction research and practice, especially in terms of identifying the most important financial predictors.

Suggested Citation

  • Lukason, Oliver & Laitinen, Erkki K., 2019. "Firm failure processes and components of failure risk: An analysis of European bankrupt firms," Journal of Business Research, Elsevier, vol. 98(C), pages 380-390.
    • Handle: RePEc:eee:jbrese:v:98:y:2019:i:c:p:380-390
    DOI: 10.1016/j.jbusres.2018.06.025
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    1. Régis Blazy & Bertrand Chopard & Agnès Fimayer, 2008. "Bankruptcy law: a mechanism of governance for financially distressed firms," European Journal of Law and Economics, Springer, vol. 25(3), pages 253-267, June.
    2. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    3. Laitinen, Ek, 1993. "Financial predictors for different phases of the failure process," Omega, Elsevier, vol. 21(2), pages 215-228, March.
    4. N. Crutzen & D. Van Caille, 2008. "The Business Failure Process. An Integrative Model of the Literature," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(3), pages 287-316.
    5. Stewart Thornhill & Raphael Amit, 2003. "Learning About Failure: Bankruptcy, Firm Age, and the Resource-Based View," Organization Science, INFORMS, vol. 14(5), pages 497-509, October.
    6. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    7. Amankwah-Amoah, Joseph, 2016. "An integrative process model of organisational failure," Journal of Business Research, Elsevier, vol. 69(9), pages 3388-3397.
    8. Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
    9. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    10. Inmaculada Jimeno-García & María Araceli Rodríguez-Merayo & María Arantzazu Vidal-Blasco, 2017. "The failure processes and their relation to the business interruption moment," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 9(1), pages 68-83.
    11. Erkki K. Laitinen & Oliver Lukason, 2014. "Do firm failure processes differ across countries: evidence from Finland and Estonia," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 15(5), pages 810-832, November.
    12. N. Crutzen & D. Van Caillie, 2010. "Towards a Taxonomy of Explanatory Failure Patterns for Small Firms: A Quantitative Research Analysis," Review of Business and Economic Literature, Intersentia, vol. 0(4), pages 438-463, December.
    13. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    14. Zorn, Michelle L. & Norman, Patricia M. & Butler, Frank C. & Bhussar, Manjot S., 2017. "Cure or curse: Does downsizing increase the likelihood of bankruptcy?," Journal of Business Research, Elsevier, vol. 76(C), pages 24-33.
    15. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    16. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    17. James, Sharon D., 2016. "Strategic bankruptcy: A stakeholder management perspective," Journal of Business Research, Elsevier, vol. 69(2), pages 492-499.
    18. Julian R. Franks & Kjell G. Nyborg & Walter N. Torous, 1996. "A Comparison of UK, US and German Insolvency Codes," Financial Management, Financial Management Association, vol. 25(3), Fall.
    19. N. Crutzen & D. Van Caillie, 2010. "Towards a Taxonomy of Explanatory Failure Patterns for Small Firms: A Quantitative Research Analysis," Review of Business and Economic Literature, Intersentia, vol. 55(4), pages 438-463, December.
    20. Erkki Laitinen, 1995. "The duality of bankruptcy process in Finland," European Accounting Review, Taylor & Francis Journals, vol. 4(3), pages 433-454.
    21. Mann, Manveer & Byun, Sang-Eun, 2017. "To retrench or invest? Turnaround strategies during a recessionary time," Journal of Business Research, Elsevier, vol. 80(C), pages 24-34.
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    4. Oliver Lukason & Art Andresson, 2019. "Tax Arrears Versus Financial Ratios in Bankruptcy Prediction," JRFM, MDPI, vol. 12(4), pages 1-13, December.
    5. Montserrat Manzaneque-Lizano & Esteban Alfaro-Cortés & Alba María Priego de la Cruz, 2019. "Stakeholders and Long-Term Sustainability of SMEs. Who Really Matters in Crisis Contexts, and When," Sustainability, MDPI, vol. 11(23), pages 1-27, November.
    6. Keijo Kohv & Oliver Lukason, 2021. "What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains," Risks, MDPI, vol. 9(2), pages 1-19, January.
    7. Gehan A. Mousa & Elsayed A. H. Elamir & Khaled Hussainey, 2022. "Using machine learning methods to predict financial performance: Does disclosure tone matter?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(1), pages 93-112, March.
    8. Õie Renata Siimon & Oliver Lukason, 2021. "A Decision Support System for Corporate Tax Arrears Prediction," Sustainability, MDPI, vol. 13(15), pages 1-23, July.
    9. Merendino, Alessandro & Sarens, Gerrit, 2020. "Crisis? What crisis? Exploring the cognitive constraints on boards of directors in times of uncertainty," Journal of Business Research, Elsevier, vol. 118(C), pages 415-430.
    10. Katarina Valaskova & Pavol Durana & Peter Adamko & Jaroslav Jaros, 2020. "Financial Compass for Slovak Enterprises: Modeling Economic Stability of Agricultural Entities," JRFM, MDPI, vol. 13(5), pages 1-16, May.
    11. Katarzyna Boratyńska, 2021. "A New Approach for Risk of Corporate Bankruptcy Assessment during the COVID-19 Pandemic," JRFM, MDPI, vol. 14(12), pages 1-14, December.
    12. Oliver Lukason & María-del-Mar Camacho-Miñano, 2019. "Bankruptcy Risk, Its Financial Determinants and Reporting Delays: Do Managers Have Anything to Hide?," Risks, MDPI, vol. 7(3), pages 1-15, July.
    13. du Jardin, Philippe, 2021. "Forecasting corporate failure using ensemble of self-organizing neural networks," European Journal of Operational Research, Elsevier, vol. 288(3), pages 869-885.
    14. Oliver Lukason & Germo Valgenberg, 2021. "Failure Prediction in the Condition of Information Asymmetry: Tax Arrears as a Substitute When Financial Ratios Are Outdated," JRFM, MDPI, vol. 14(10), pages 1-13, October.
    15. Lily Davies & Mark Kattenberg & Benedikt Vogt, 2023. "Predicting Firm Exits with Machine Learning: Implications for Selection into COVID-19 Support and Productivity Growth," CPB Discussion Paper 444, CPB Netherlands Bureau for Economic Policy Analysis.
    16. Ricarda B. Bouncken & Sascha Kraus & Antonio Lucas Ancillo, 2022. "Management in times of crises: reflections on characteristics, avoiding pitfalls, and pathways out," Review of Managerial Science, Springer, vol. 16(7), pages 2035-2046, October.

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