| Issue |
E3S Web Conf.
Volume 371, 2023
International Scientific Conference “Fundamental and Applied Scientific Research in the Development of Agriculture in the Far East” (AFE-2022)
|
|
|---|---|---|
| Article Number | 02059 | |
| Number of page(s) | 11 | |
| Section | Innovations in Energy Efficiency for Buildings and Structures | |
| DOI | https://doi.org/10.1051/e3sconf/202337102059 | |
| Published online | 28 February 2023 | |
Environmental analysis in bankruptcy diagnosing (the case of construction companies)
1 Peter the Great Saint-Petersburg Polytechnic University, Politekhnicheskaya ul., 29, 195251 Saint-Petersburg, Russian Federation
2 College of Hospitality Industry Management, Suan Sunandha Rajabhat University, 1 U-Thong Nok rd., Dusit, Bangkok, Thailand
* Corresponding author: denis.se@ssru.ac.th
The instability of the economic situation, combined with the systematically important nature of the construction industry, attracts attention to the financial viability of construction companies constituting the basis for the successful implementation of their activities in market conditions. The article examines the bankruptcy statistics of Russian construction companies, analyzes the issues of assessing and predicting insolvency and discusses the utility of applying well-known models, in particular, the Altman’s modified five-factor model, in Russian situation. The dynamics of the financial indicators used in the model and Altman's Z-score for construction companies belonging to the “construction of buildings” sector and different in scale of activity are analyzed. The groups of companies are represented by the conditional companies having the median value of all indicators, Conclusions are drawn regarding the probability of bankruptcy for companies belonging to different groups, and regarding the directions for improving the methods for diagnosing the bankruptcy of construction companies.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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