Open Access
Issue
SHS Web Conf.
Volume 62, 2019
17th International Scientific Conference “Problems of Enterprise Development: Theory and Practice” 2018
Article Number 03002
Number of page(s) 4
Section Reserves for Increasing the Usage Efficiency of the Innovation and Investment Potential of Industrial Enterprises
DOI https://doi.org/10.1051/shsconf/20196203002
Published online 15 March 2019
  1. А.N. Ryakhovskaya, S.E. Kovan, Anti-crisis management: a modern concept and the main instrumentarium. Managerial Science, 5(3), 45-55. DOI: 10.26794/2304-022X-2015--3-45-55 (2015). [Google Scholar]
  2. A.V. Azizov, D.S. Ramazanovna, A brief analysis of the dynamics of bankruptcies in the Russian Federation, individual regions and forms of business. NOVAINFO, 1(45). 74-82 [in Rus.] (2016). [Google Scholar]
  3. N.T. Hill, S.E. Perry, S. Andes, Evaluating firms in financial distress: An event history analysis. Journal of Applied Business Research (JABR), 12(3). 60-71. DOI: 10.19030/jabr.v12i3.5804 (2011). [CrossRef] [Google Scholar]
  4. D.O. Konovalova, Improving the financial sustainability of enterprises as a direction of crisis management. PhD dissertation. Moscow: AHO HPE “Russian Academy of entrepreneurship» [in Rus.] (2015). [Google Scholar]
  5. A.V. Filyushina, Innovative tools of crisis management. Innovation Management, 4, 71-81 [in Rus.] (2015). [Google Scholar]
  6. E. Altman, E. Hotchkiss, Corporate financial distress and bankruptcy: Predict and avoid bankruptcy, analyze and invest in distressed debt, 3rd Edition. New York, NY: John Wiley and Sons, Ltd (2005). [CrossRef] [Google Scholar]
  7. G.D. Bordeianu, R. Florin, M.D. Paraschivescu, W. Pâvâloaia, Analysis models of the bankruptcy risk. Economy Transdisciplinarity Cognition, XIV(1), 248-259 (2011). [Google Scholar]
  8. D.J. Lacombe, S.G. McIntyre, Hierarchical spatial econometric models in regional science. Regional Research Frontiers, Advances in Spatial Science: The Regional Science Series, 2, 151-167. DOI: 10.1007/978-3-319-50590-9 (2017). [Google Scholar]
  9. L. Mandru, A. Khashman, C. Carstea, The diagnosis of bankruptcy risk using score function. In L.A. Zadeh, J. Kacprzyk, N. Mastorakis, et al. (Eds.), Proceeding of the 9th WSEAS international conference on artificial intelligence, knowledge engineering and data base (pp.83-88). Cambridge, UK: University of Cambridge (2010). [Google Scholar]
  10. S.A. Gorbatkov, S.A. Farkhieva, Sensitivity of a neural network dynamic method for evaluating bankruptcies in management models for restructuring a corporation’s credit debt. Naukovedenie, 8(2). 1-20. DOI: 10.15862/67TVN216 [in Rus.] (2016). [Google Scholar]
  11. I.G. Kukukina, Accounting and analysis of bankruptcies. Moscow, Russia: Finance and Statistics [in Rus.] (2014). [Google Scholar]
  12. G.A. Khaidarshina, Methods for assessing the risk of bankruptcy of an enterprise. Extended abstract of PhD dissertation. Moscow: Financial Academy under the Government of the Russian Federation [in Rus.] (2009). [Google Scholar]

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