Andrii Butyrskyi

The article presents a methodology for developing the marketing strategy for the adoption of optimal managerial solutions by means of smart analytics. Such issues as marketing strategy modeling methods; software products based on the integration of smart analytics; optimal choosing electro mobile and others have been considered. The main subject of the article is constructing an optimal decision-making model using a combination of classical statistical and mathematical methods and models, as well as modern information technologies including methods of smart analytics. The conceptual scheme of the effective marketing management has been created according to the structural components: information, statistical, mathematical, analytical and technological etc. The structure and main features of every component have been considered in detail. The created conceptual scheme of the effective management was demonstrated through the simple example of optimal choosing electro mobile. To investigate sales on electro mobiles Ukrainian market a set of factors has been considered. According to them the correlation and cluster analyses have been conducted. The main factors, which are the most influent for the price of electro mobile on Ukrainian market have been revealed. All considered models of electro cars have been divided onto three groups depending on the characteristics price–quality.

Managing and evaluating the probability of bankruptcy of Ukrainian enterprises is one of the most complex and relevant problems of the economy and management. In the context of Ukraine’s integration into the international space, there is an arising issue of assessing the bankruptcy of Ukrainian enterprises that meets international financial standards and allows administering this process. A qualitative assessment of the bankruptcy of an enterprise is possible only using artificial intelligence methods – the fuzzy sets method, which allows including qualitative and quantitative indicators to the model for assessing bankruptcy of enterprises in Ukraine. The aim of the article is to improve the existing method for assessing the probability of bankruptcy of Ukrainian enterprises on the basis of the fuzzy sets method, which will include indicators of international financial reporting and allow more efficient administration and management of this process. The subject of the research is the process of formalizing the method of the enterprise bankruptcy assessment in accordance with the indicators of International Financial Reporting Standards. The study offers a mechanism for a comprehensive assessment of the probability of bankruptcy of Ukrainian enterprises with the use of the methods of fuzzy sets, which is based on international financial indicators: current ratio, payable turnover ratio, equity turnover ratio, return on assets, equity-to-debt ratio. The mechanism allows quickly managing bankruptcy conditions. In order to administer the economic activity of the bankrupt enterprises, based on the theory of a fuzzy sets, a system of enterprises management takes into account the international financial reporting.

Small and medium-sized enterprises (SMEs) create more than half of the added value, providing about two-thirds of employment in most countries. However, they need more liquidity, access to credit resources, and significant outstanding loans. This study aims to identify the impact of interest rates on outstanding loans of enterprises on their structure as a way to prevent bankruptcy. The correlation-regression analysis used OECD statistical data for 2008‒2019 sampling individual countries; it showed an ambiguous situation between the interest rate and the share of outstanding loans of SMEs in the overall structure of outstanding loans. The paper verified constructed regression equations and estimated their parameters. The regression equations for Belgium, the Czech Republic, Estonia, and Latvia are statistically reliable. Thus, in Belgium and the Czech Republic, a negative relationship was recorded (r = –0.822; D = 0.675; r = –0.9274; D = 0.794; F-criterion > Ft, respectively), and in Estonia and Latvia – a positive one (r = 0.876; D = 0.767; F-criterion > F•Ft; r = 0.800; D = 0.641; F-criterion > Ft , respectively). Australia, Italy, Slovakia, and France practically do not have a corresponding relationship. The regression equations make it possible to estimate the change in the level of interest rate on the share of outstanding loans of enterprises in the overall structure of outstanding loans, make predictions of the corresponding performance indicator, and develop measures of restoring the solvency of enterprises as an essential task of preventing their bankruptcy.