Open Access
Issue
E3S Web Conf.
Volume 275, 2021
2021 International Conference on Economic Innovation and Low-carbon Development (EILCD 2021)
Article Number 03071
Number of page(s) 8
Section Environmental Protection and Governance Innovation Technology Research
DOI https://doi.org/10.1051/e3sconf/202127503071
Published online 21 June 2021
  1. Yan F.L. Shiy M. Economic policy uncertainty, financial development and enterprise innovation. [J/OL]. Journal of financial development research, 2021(5)18-26. [Google Scholar]
  2. Wang L.L., Shan Y.K.. Research on the evaluation of financial risk of listed companies by using “Z-score method”-taking coal industry as an example [J]. China business review, 2017 (19): 111-112 [Google Scholar]
  3. Wang M.Q.. 5C evaluation method of accounts receivable management and its supplement [J]. Operation and management, 2017 (07): 29-32 [Google Scholar]
  4. Jiang L. Research on credit risk prediction of supply chain finance based on Cox model [D]. Nanhua University, 2019. [Google Scholar]
  5. Jiang L. L., Li B. Z. Research on financial credit risk of agricultural product supply chain based on improved KMV model [J]. Journal of Fujian agriculture and Forestry University (PHILOSOPHY AND SOCIAL SCIENCES EDITION), 2021, 24 (01): 41-49. [Google Scholar]
  6. Zhang Y. T. Empirical analysis on credit risk measurement of GEM companies based on KMV model [D]. Guizhou University of Finance and economics, 2018. [Google Scholar]
  7. Shi D. C. Empirical analysis on credit risk of mining listed companies based on KMV model [D]. Northwest University for nationalities, 2019. [Google Scholar]
  8. Ge T. F, Bai Z.S. Xu J. Credit risk evaluation of listed companies based on KMV Model -Taking artificial intelligence industry as an example [J]. Journal of Chaohu University, 2020, 22 (06): 45-53. [Google Scholar]
  9. Liu B. Empirical analysis on credit risk measurement of Chinese Listed Companies Based on KMV model [J]. Science, technology and engineering, 2010, 10 (3): 843-843. [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.