EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 92 (2021) SHS Web of Conf., 92 (2021) 08017 References
Open Access
Issue
SHS Web of Conf.
Volume 92, 2021
The 20th International Scientific Conference Globalization and its Socio-Economic Consequences 2020
Article Number 08017
Number of page(s) 8
Section Economic Sustainability
DOI https://doi.org/10.1051/shsconf/20219208017
Published online 13 January 2021
  1. Adamko, P., Chutka, J. (2020). Company bankruptcy and its prediction in conditions of globalization. In T. Kliestik (Eds.), 19th International scientific conference globalization and its socio-economic consequences 2019 - Sustainability in the global-knowledge economy (Article Number 05002). Rajecke Teplice: SHS Web of Conferences. [Google Scholar]
  2. Siekelova, A., Kovalova, E., Ciurlău, C.F. (2019). Prediction financial stability of Romanian production companies through Altman Z-score. Ekonomicko-manazerske spektrum, 13(5), 89-97. [CrossRef] [Google Scholar]
  3. Valaskova, K., Durana, P., Adamko, P., Jaros, J. (2020). Financial Compass for Slovak Enterprises: Modeling Economic Stability of Agricultural Entities. Journal of Risk and Financial Management, 13(5), 92. [CrossRef] [Google Scholar]
  4. Kliestik, T., Valaskova, K., Lazaroiu, G., Kovacova, M., Vrbka, J. (2020). Remaining Financially Healthy and Competitive: The Role of Financial Predictors. Journal of Competitiveness, 12(1), 74. [CrossRef] [Google Scholar]
  5. Kral, P., Musa, H., Lazaroiu, G., Misankova, M., Vrbka, J. (2018). Comprehensive assessment of the selected indicators of financial analysis in the context of failing companies. Journal of International Studies, 11(4), 282-294. [CrossRef] [Google Scholar]
  6. Valaskova, K., Kliestik, T., Kovacova, M. (2018). Management of financial risks in Slovak enterprises using regression analysis. Oeconomia Copernicana, 9(1), 105–121. [CrossRef] [Google Scholar]
  7. Cisko, S., Kliestik, T. (2013). Financial management II. Žilina: EDIS. [Google Scholar]
  8. Delina, R., Packova, M. (2013). Prediction bankruptcy models validation in Slovak business environment. E & M Ekonomie a management, 16(3), 101-112. [Google Scholar]
  9. Gavurova, B., Packova, M., Misankova, M., Smrcka, L. (2017). Predictive potential and risks of selected bankruptcy prediction models in the Slovak business environment. Journal of Business Economics and Management, 18(6), 1156-1173. [CrossRef] [Google Scholar]
  10. Kovacova, M., Kliestikova, J. (2017). Modelling bankruptcy prediction models in Slovak companies. In: Vachal, J., Vochozka, M., Horak, J. (Eds.), Innovative Economic Symposium 2017 (Ies2017): Strategic Partnership in International Trades (Article Number 01013). Ceske Budejovice: SHS Web Conference. [Google Scholar]
  11. Camska, D. (2012). National view of bankruptcy models. In: Loster, T., Pavelka, T. (Eds.), 6th International Days of Statistics and Economics (268-278). Prague: Proceedings Paper. [Google Scholar]
  12. Misankova, M., Zvarikova, K., Kliestikova, J. (2017). Bankruptcy Practice in Countries of Visegrad Four. Economics and Culture, Sciendo, 14,(1), 108-118. [CrossRef] [Google Scholar]
  13. Adamko, P., Svabova, L. (2016). Prediction of the risk of bankruptcy of Slovak companies. In: Culik. M., Proceedings of 8th International Scientific Conference Managing and Modelling of Financial Risks (pp. 15-20). Ostrava: Proceedings Paper. [Google Scholar]
  14. Rybarova D., Braunova M., Jantosova L. (2016). Analysis of the Construction Industry in the Slovak Republic by Bankruptcy Model. In: McKenna, B., Ardabili, F.S., Faghih, N.(Eds.), 3rd International Conference on New Challenges in Management and Organization: Organization and Leadership (pp. 298-306 ). U Arab Emirates: Procedia Social and Behavioral Sciences. [Google Scholar]
  15. Neumaier, I., Neumaierovaa, I. (2005). Index IN 05. In: European financial systems (pp. 143-148). Brno: Proceeding. [Google Scholar]
  16. Chrastinova, Z. (1998). Methods of economic creditworthiness evaluation and prediction of financial situation of agricultural holdings. Bratislava: VUEPP. [Google Scholar]
  17. Karpac, D., Bartosova, V. (2020). The verification of prediction and classification ability of selected Slovak prediction models and their emplacement in forecasts of financial health of a company in aspect of globalization. In: Kliestik, T. (Eds.), 19th International Scientific Conference Globalization and Its Socio-Economic Consequences - Sustainability in the Global-Knowledge Economy (Article Number 06010). Rajecke Teplice: SHS Web of Conferences. [Google Scholar]
  18. Durica, M., Svabova, L. (2017). Comparative analysis of financial distress prediction models for Slovak companies. In: Slavickova, P. (Eds.), Knowledge for market use: people in economics - decisions, behavior and normative models : international scientific conference proceedings (pp. 102-108). Olomouc: Proceedings Paper. [Google Scholar]
  19. Gurcik, L. (2002). G-index – the financial situation prognosis method of agricultural enterprises. Agricultural Economics, 48, 373-378. [Google Scholar]
  20. Gulka, M. (2016). Predictive Model of Corporate Failure in the Slovak Business Environment. Forum Statisticum Slovacum, 12(1), 16‐22. [Google Scholar]
  21. Klempaiova, N., Bohdalova, M. (2018). Comparison of Gulka’s Model and Model IN05 on Sample of Slovak Industrial Companies. In: Nesleha, J., Hampl, F., Svoboda, M. (Eds.), 15th International Scientific Conference on European Financial Systems 2018 (pp. 259-266). Brno: Proceedings Paper. [Google Scholar]
  22. Gavurova, B., Janke, F., Packova, M., Pridavok, M. (2017). Analysis of impact of using the trend variables on bankruptcy prediction models performance. Journal of Economics, 65(4), 370-383. [Google Scholar]
  23. Durica, M., Frnda, J., Svabova, L. (2019). Decision tree based model of business failure prediction for Polish companies. Oeconomia Copernicana, 10(3), 453-469. [CrossRef] [Google Scholar]
  24. Durica, M., Podhorska, I., Durana, P. (2019). Business failure prediction using cart-based model: A case of Slovak companies. Ekonomicko-manazerske spektrum, 13(1), 51-61. [CrossRef] [Google Scholar]
  25. Svabova, L., Durica, M., Podhorska, I. (2018). Prediction of Default of Small Companies in the Slovak Republic. Economics and Culture, Sciendo, 15(1), 88. [CrossRef] [Google Scholar]
  26. Kovacova, M., Kliestik, T. (2017). Logit and Probit application for the prediction of bankruptcy in Slovak companies. Equilibrium, Quarterly Journal of Economics and Economic Policy, 12(4), 775-791. [Google Scholar]
  27. Mas’ud, A., Manaf, N. A. A., Saad, N. (2019). Trust and power as predictors to tax compliance: Global evidence. Economics and Sociology, 12(2), 192-204. [CrossRef] [Google Scholar]
  28. 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. [Google Scholar]
  29. Podhorska, I. (2020). Evaluation Of The Financial Health Of Non-profit Organizations: A Case Study In The Slovak Republic. In: 55thInternational Scientific Conference on Economic and Social Development (pp. 708-716). Varazdin: Varazdin Development and Entrepreneurship Agency [Google Scholar]
  30. Mazanec, J., Bartosova, V. (2019). The effectiveness of artificial neural networks in prediction of financial vulnerability in Slovak non-profit sector. In: M.L. Simic, B. Crnkovic (Eds). 8th International scientific symposium economy of eastern Croatia - vision and growth (pp. 618-633). Osijek: Medunarodni Znanstveni Simpozij Gospodarstvo Istocne Hrvatske-Jucer Danas Sutra. [Google Scholar]
  31. Kovacova, M., Kliestik, T. Kubala, P., Valaskova, K., Radisic, M., Borocki, J. (2018) Banktruptcy models: verifying their validity as a predictor of corporate failure. Polish journal of management studies, 18 (1), 167-179. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.