Open Access
Issue
SHS Web of Conf.
Volume 92, 2021
The 20th International Scientific Conference Globalization and its Socio-Economic Consequences 2020
Article Number 02005
Number of page(s) 8
Section Behavioral Economics and Decision-Making
DOI https://doi.org/10.1051/shsconf/20219202005
Published online 13 January 2021
  1. Kliestik, T., Misankova, M., Valaskova, K., Svabova, L. (2018). Bankruptcy prevention: new effort to reflect on legal and social changes. Science and Engineering Ethics, 24(2), 791-803. [Google Scholar]
  2. Beyer, A., Guttman, I., Marinovic, I. (2019). Earnings Management and Earnings Quality: Theory and Evidence. Accouting Review, 94(4), 77-101. [CrossRef] [Google Scholar]
  3. Degeorge, F., Patel, J., Zeckhauser, R. (1999). Earnings Management to Exceed Thresholds. Journal of Business, 72(1), 1-33. [CrossRef] [Google Scholar]
  4. Khuong, N. V., Liem, N. T., Minh, M. T. H. (2020). Earnings management and cash holdings: Evidence from energy firms in Vietnam. Journal of International Studies, 13(1), 247-261. [CrossRef] [Google Scholar]
  5. Dechow, P. M., Skinner, D. J. (2000). Earnings Management: Reconciling the Views of Accounting Academics, Practitioners, and Regulators. Retrieved from: http://papers.ssrn.com/sol3/Delivery.cfm/000324309.pdf?abstractid=218959&mirid=1 [Google Scholar]
  6. Rezaee, Z. (2005). Causes, consequences, and deterrence of financial statement fraud. Critical Perspectives on Accounting, 16(3), 277-298. [CrossRef] [Google Scholar]
  7. Mulford, Ch. W., Comiskey, E. E. (2003). The Financial Numbers Game: detecting creative accounting practices. New York: John Wiley & Sons. [Google Scholar]
  8. Burgstahler, D., Eames, M. (2006). Management of Earnings and Analysts’ Forecasts to Achieve Zero and Small Positive Earnings Surprises. Journal of Business Finance & Accounting, 33(5-6), 633-652. [CrossRef] [Google Scholar]
  9. Podhorska, I., Siekelova, A., Olah, J. (2019). Earnings Analysis of SMEs: A Case Study in Slovakia. Proceedings of the 33rd International-Business-Information-Management-Association (pp. 8706-8718). Norristown: International Business Information Management Association – Ibima. [Google Scholar]
  10. Svabova, L., Kramarova, K., Chutka, J., Strakova, L. (2020). Detecting earnings manipulation and fraudulent financial reporting in Slovakia. Oeconomia Copernicana, 11(3), 485-508. [CrossRef] [Google Scholar]
  11. Mulford, Ch. W. (2002). The financial number game: detecting creative account practices. New York: John Wiley & Sons. [Google Scholar]
  12. 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), 74-92. [CrossRef] [Google Scholar]
  13. 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. [CrossRef] [Google Scholar]
  14. Ionescu, L. (2019). Would Taxing the Robots Curtail Technological Advancement or Mitigate the Risks of Automation?. Contemporary Readings in Law and Social Justice, 11(1), 33–38. [CrossRef] [Google Scholar]
  15. Ullmann, R., Watrin, C. (2017). Detecting Target-Driven Earnings Management Based on the Distribution of Digits. Journal of Business Finance & Accounting, 44(1-2), 63-93. [CrossRef] [Google Scholar]
  16. Hecht, B., Valaskova, K., Kral, P., Rowland, Z. (2019). The Digital Governance of Smart City Networks: Information Technology-driven Economy, Citizen-centered Big Data, and Sustainable Urban Development. Geopolitics, History, and International Relations, 11(1), 128–133. [CrossRef] [Google Scholar]
  17. Brazel, J. F., Jones, K. L., Zimbelman, M. F. (2009). Using Nonfinancial Measures to Assess Fraud Risk. Journal of Accounting Research, 47(5), 1135-1166. [CrossRef] [Google Scholar]
  18. Healy, P. (1985). The Effect of Bonues Schemes on Accounting Decisions. Journal of Accounting & Economics, 7(1-3), 85-107. [CrossRef] [Google Scholar]
  19. DeAngelo, L. E. (1986). Accounting Numbers as Market Valuation Substitutes: A Study of Management Buyouts of Public Stockholders. The Accounting Review, 61(3), 400-420. [Google Scholar]
  20. Beneish, M. D. (1997). Detecting GAAP Violation: Implications for Assessing Earnings Management among Firms with Extreme Financial Performance. Journal of Accounting and Policy, 16(3), 271-309. [CrossRef] [Google Scholar]
  21. Mantone, P. S. (2013). Using analytics to detect possible fraud: tools and techniques. Hoboken: Wiley & Sons. [CrossRef] [Google Scholar]
  22. Kourilova, J., Drabkova, Z., Vlckova, M. (2016). Methods: AHP, CFEBT, DMFCA as a possible identification of errors and fraud in accounting. Ceske Budejovice: University of South Bohemia in Ceske Budejovice, Faculty of Economics. [Google Scholar]
  23. Indiana University (2020). Beneish M-Score. Retrieved from: https://apps.kelley.iu.edu/Beneish/MScore/MScoreInput [Google Scholar]
  24. Blazek, R., Durana, P., Valaskova, K. (2020). Creative accounting as an apparatus for reporting profits in agribusiness. Journal of Risk and Financial Management, 13(11), 261. [CrossRef] [Google Scholar]

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