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Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models

Author

Listed:
  • Tijana Matejić

    (Faculty of Organizational Sciences, University of Belgrade, 11000 Belgrade, Serbia)

  • Snežana Knežević

    (Faculty of Organizational Sciences, University of Belgrade, 11000 Belgrade, Serbia)

  • Vesna Bogojević Arsić

    (Faculty of Organizational Sciences, University of Belgrade, 11000 Belgrade, Serbia)

  • Tijana Obradović

    (Faculty of Organizational Sciences, University of Belgrade, 11000 Belgrade, Serbia)

  • Stefan Milojević

    (Audit, Accounting, Financial and Consulting Services Company “Moodys Standards” Ltd., 11000 Belgrade, Serbia)

  • Miljan Adamović

    (Pharmacy Institution “Zdravlje Lek”, 11000 Belgrade, Serbia)

  • Aleksandra Mitrović

    (Faculty of Hotel Management and Tourism in Vrnjačka Banja, University of Kragujevac, 36210 Vrnjacka Banja, Serbia)

  • Marko Milašinović

    (Faculty of Hotel Management and Tourism in Vrnjačka Banja, University of Kragujevac, 36210 Vrnjacka Banja, Serbia)

  • Dragoljub Simonović

    (Faculty of Organizational Sciences, University of Belgrade, 11000 Belgrade, Serbia)

  • Goran Milošević

    (Faculty of Law, University of Novi Sad, 21000 Novi Sad, Serbia)

  • Marko Špiler

    (Faculty of Organizational Sciences, University of Belgrade, 11000 Belgrade, Serbia)

Abstract

In this paper, we assess the impact of the COVID-19 crisis on the bankruptcy risk of a sample of 100 hotel companies and, consequently, on the hotel industry in the Republic of Serbia. The assessment applies to the period, 2019–2026, with the use of the data on the financial indicators for 2015–2020. Five novel structural time-series models, which have the indicators derived from Altman’s EM Z″-score model as predictors, were used, and a new conceptual framework for assessing bankruptcy risk is provided. The framework expands the applicability of credit-risk-scoring models to multiyear predictions, and it takes into account the dynamism of the transitions of the firms among Altman’s risk zones. The predictions that were obtained when the Springate and Zmijewski scores were applied along with the Altman Z″-scores demonstrate the fair applicability of the scores for the models that are introduced here. The results of the models were confirmed by 270 artificial neural networks and they were compared to the results of the classical time-series models. The crisis started to have a negative effect on bankruptcy risk in 2020, and this effect is expected to rise until 2023; currently, in 2022, the highest number of hotel companies may be headed for bankruptcy. Amelioration in the position of the companies cannot be expected before 2024; however, even in 2026, the risk of bankruptcy will remain high when compared to the pre-COVID-19 period and, thus, the surviving companies will become more fragile to any further exogenous changes. These results provide a basis for the adaption of state-supported measures and business policies in order to withstand the crisis and to ensure sustainability.

Suggested Citation

  • Tijana Matejić & Snežana Knežević & Vesna Bogojević Arsić & Tijana Obradović & Stefan Milojević & Miljan Adamović & Aleksandra Mitrović & Marko Milašinović & Dragoljub Simonović & Goran Milošević & Ma, 2022. "Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models," Sustainability, MDPI, vol. 14(8), pages 1-44, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4680-:d:793437
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    as
    1. Sasivimol Meeampol & Polwat Lerskullawat & Ausa Wongsorntham & Phanthipa Srinammuang & Vimol Rodpetch & Rungsimaporn Noonoi, 2014. "Applying Emerging Market Z-Score Model to Predict Bankruptcy: A Case Study of Listed Companies in the Stock Exchange of Thailand (Set)," Human Capital without Borders: Knowledge and Learning for Quality of Life; Proceedings of the Management, Knowledge and Learning International Conference 2014,, ToKnowPress.
    2. Li, Ka Leung & Wong, Hoi Ying, 2008. "Structural models of corporate bond pricing with maximum likelihood estimation," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 751-777, September.
    3. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    4. Reisz, Alexander S. & Perlich, Claudia, 2007. "A market-based framework for bankruptcy prediction," Journal of Financial Stability, Elsevier, vol. 3(2), pages 85-131, July.
    5. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    6. Nicoleta Bărbuță-Mișu & Mara Madaleno, 2020. "Assessment of Bankruptcy Risk of Large Companies: European Countries Evolution Analysis," JRFM, MDPI, vol. 13(3), pages 1-28, March.
    7. Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
    8. Black, Fischer & Cox, John C, 1976. "Valuing Corporate Securities: Some Effects of Bond Indenture Provisions," Journal of Finance, American Finance Association, vol. 31(2), pages 351-367, May.
    9. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    10. Judson Boomhower, 2019. "Drilling Like There's No Tomorrow: Bankruptcy, Insurance, and Environmental Risk," American Economic Review, American Economic Association, vol. 109(2), pages 391-426, February.
    11. Pierre-Olivier Gourinchas & Ṣebnem Kalemli-Özcan & Veronika Penciakova & Nick Sander, 2020. "SME Failures Under Large Liquidity Shocks: An Application to the COVID-19 Crisis," NBER Working Papers 27877, National Bureau of Economic Research, Inc.
    12. Bosiljka Srebro & Bojan Mavrenski & Vesna Bogojević Arsić & Snežana Knežević & Marko Milašinović & Jovan Travica, 2021. "Bankruptcy Risk Prediction in Ensuring the Sustainable Operation of Agriculture Companies," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    13. Altman, Edward I., 2005. "An emerging market credit scoring system for corporate bonds," Emerging Markets Review, Elsevier, vol. 6(4), pages 311-323, December.
    14. Jarmila Horváthová & Martina Mokrišová, 2018. "Risk of Bankruptcy, Its Determinants and Models," Risks, MDPI, vol. 6(4), pages 1-22, October.
    15. Pierre-Olivier Gourinchas & Ṣebnem Kalemli-Özcan & Veronika Penciakova & Nick Sander, 2020. "COVID-19 and SME Failures," FRB Atlanta Working Paper 2020-21, Federal Reserve Bank of Atlanta.
    16. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    17. Muhammad Ramadhani Kesuma & Felisitas Defung & Anisa Kusumawardani, 2021. "Bankruptcy Prediction And Its Effect On Stock Prices As Impact Of The COVID-19 Pandemic," Technium Social Sciences Journal, Technium Science, vol. 25(1), pages 567-582, November.
    18. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    19. Ryan Niladri Banerjee & Enisse Kharroubi & Ulf Lewrick, 2020. "Bankruptcies, unemployment and reallocation from Covid-19," BIS Bulletins 31, Bank for International Settlements.
    20. Zhang, Hanyuan & Song, Haiyan & Wen, Long & Liu, Chang, 2021. "Forecasting tourism recovery amid COVID-19," Annals of Tourism Research, Elsevier, vol. 87(C).
    21. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    22. Lilia Aleksanyan & Jean-Pierre Huiban, 2016. "Economic and financial determinants of firm bankruptcy:evidence from the French food industry," Review of Agricultural, Food and Environmental Studies, INRA Department of Economics, vol. 97(2), pages 89-108.
    23. Taffler, Richard J., 1984. "Empirical models for the monitoring of UK corporations," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 199-227, June.
    24. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    25. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    26. Rohitash Chandra & Yixuan He, 2021. "Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-32, July.
    27. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    28. Krishna Chaitanya V, 2005. "Measuring Financial Distress of IDBI Using Altman Z-Score Model," The IUP Journal of Bank Management, IUP Publications, vol. 0(3), pages 7-17, August.
    29. Antonio Pelaez-Verdet & Pilar Loscertales-Sanchez, 2021. "Key Ratios for Long-Term Prediction of Hotel Financial Distress and Corporate Default: Survival Analysis for an Economic Stagnation," Sustainability, MDPI, vol. 13(3), pages 1-17, January.
    30. Maria de Lurdes Calisto & Jorge Umbelino & Ana Gonçalves & Cláudia Viegas, 2021. "Environmental Sustainability Strategies for Smaller Companies in the Hotel Industry: Doing the Right Thing or Doing Things Right?," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
    31. World Bank, 2020. "Doing Business 2020," World Bank Publications - Books, The World Bank Group, number 32436.
    32. Barbara Siuta-Tokarska, 2021. "SMEs during the COVID-19 Pandemic Crisis. The Sources of Problems, the Effects of Changes, Applied Tools and Management Strategies—The Example of Poland," Sustainability, MDPI, vol. 13(18), pages 1-13, September.
    33. Joanna Wieprow & Agnieszka Gawlik, 2021. "The Use of Discriminant Analysis to Assess the Risk of Bankruptcy of Enterprises in Crisis Conditions Using the Example of the Tourism Sector in Poland," Risks, MDPI, vol. 9(4), pages 1-11, April.
    34. Abel Elizalde, 2006. "Credit Risk Models II: Structural Models," Working Papers wp2006_0606, CEMFI.
    35. María Escribano-Navas & German Gemar, 2021. "Gender and Bankruptcy: A Hotel Survival Econometric Analysis," Sustainability, MDPI, vol. 13(12), pages 1-13, June.
    36. Abel Elizalde, 2006. "Credit Risk Models III: Reconciliation Reduced – Structural Models," Working Papers wp2006_0607, CEMFI.
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    1. Jasna Gačić & Stefan Milojević & Snežana Knežević & Miljan Adamović, 2023. "Financial Literacy of Managers in Serbian Health Care Organizations as a Path to Sustainability," Sustainability, MDPI, vol. 15(7), pages 1-26, April.
    2. Marko Špiler & Tijana Matejić & Snežana Knežević & Marko Milašinović & Aleksandra Mitrović & Vesna Bogojević Arsić & Tijana Obradović & Dragoljub Simonović & Vukašin Despotović & Stefan Milojević & Mi, 2022. "Assessment of the Bankruptcy Risk in the Hotel Industry as a Condition of the COVID-19 Crisis Using Time-Delay Neural Networks," Sustainability, MDPI, vol. 15(1), pages 1-54, December.

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