Energy Enterprise Risks Analysis Using Fuzzy Logic Methods

<p>In Russia's contemporary conditions, enterprises fail to make the full use of the state-of-the-art financial risks management toolkit. Both diagnosing methods and criterial norms within the mechanism of managing the energy enterprises are not adapted to the current crisis conditions of...

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Bibliographic Details
Main Authors: Nadezda B. Gusareva, Galina I. Andryushchenko, Kristina G. Tsaritova, Vladimir V. Zelenov, Larisa N. Sorokina
Format: Article
Language:English
Published: EconJournals 2019-04-01
Series:International Journal of Energy Economics and Policy
Online Access:https://www.econjournals.com/index.php/ijeep/article/view/7957
Description
Summary:<p>In Russia's contemporary conditions, enterprises fail to make the full use of the state-of-the-art financial risks management toolkit. Both diagnosing methods and criterial norms within the mechanism of managing the energy enterprises are not adapted to the current crisis conditions of economic management, which renders it essential to develop the financial management tools that will take into account the industry-related specific nature and anti-crisis constituent of the organizations. In the work, the opportunity of applying the fuzzy logic method for analyzing the financial risks of energy enterprises in Russia is explored. For this purpose, the analysis and assessment of financial situation have been performed for a modeled energy enterprise and bankruptcy risk of the enterprise has been analyzed using the fuzzy logic method. It is demonstrated that the process of managing financial risks at the enterprise using the fuzzy sets approach is relevant in the contemporary conditions of energy enterprises functioning in Russia. There has been found the problem of having to improve the integrated risk management of energy enterprises.</p><p><strong>Keywords</strong>: Energy enterprise; risk management; financial risks; bankruptcy risk; business activity indicator; concept of economic value added (EVA); fuzzy logic methods</p><p><strong>JEL Classifications: </strong>O13, P28, P48</p><p>DOI: <a href="https://doi.org/10.32479/ijeep.7957">https://doi.org/10.32479/ijeep.7957</a></p>
ISSN:2146-4553