ABSTRACT. The paper investigates the issues of evaluating structural changes in the regions' economic development based on the comprehensive index assessment technology. The impact of the Covid-19 pandemic on regional development and changes in the regional structure is considered. The authors propose the use of block convolution to design a comprehensive index based on a set of metric initial indicators that characterize the regions' economic development. Grouping the set of initial indicators is carried out based on the method of an extreme grouping of parameters and the method of principal components. A weighted linear additive convolution was used to develop partial composite indices and an economic development comprehensive index. The practical approbation was carried out for the regions of Ukraine according to the data of 9 months of 2019 and the same period of 2020. To establish the regions' structure, we used the division of the comprehensive index values into intervals and further distributing regions into classes according to the level of economic development. There is a general decrease in the value of the integrated indicator in 2020, caused by the impact of the Covid-19 pandemic. However, no significant changes in the structure of the regions were detected, which indicates an equally negative impact of the pandemic for all regions of Ukraine.

ABSTRACT. This article examines the behavior of the consumer price index in Ukraine for the period from January 2010 to September 2020. The characteristics of the initial time series, the analysis of autocorrelation functions made it possible to reveal the tendency of their development and the presence of annual seasonality. To model the behavior of the consumer price index and forecast for the next months, two types of models were used: the additive ARIMA*ARIMAS model, better known as the model of Box-Jenkins and the exponential smoothing model with the seasonality estimate of Holt-Winters. As a result of using the STATISTICA package, the most adequate models were built, reflecting the monthly dynamics of the consumer price index in Ukraine. The inflation forecast was carried out on the basis of the Holt-Winters model, which has a minimum error.

ABSTRACT. The relevance of the research subject is explained by a fundamental change in the conditions of existence and development of agents of the digital economy, limited knowledge about their behavior under conditions of quarantine restrictions. The aim of the research is to study the series of the dynamics of the price of bitcoin and the frequency of online requests for bitcoin as an indicator of the behavior of agents of the digital economy using the methods of qualitative recurrent analysis. The types of constructed time series plots of the price of bitcoin and the frequency of requests for bitcoin are defined as drift with a superimposed linearly gradually increasing sequence, which indicates the unpredictability of the behavior of digital economy agents with a gradual stabilization in new quality trend. The scientific novelty of the research results lies in the proven connection between the series of bitcoin price dynamics and the frequency of online requests for bitcoin, tracking changes in the behavior of digital economy agents before and after the introduction of quarantine restrictions. The procedure for conducting a qualitative recurrence analysis of the series of dynamics is generalized, which takes into account the specifics of the formation of the frequency of online requests for bitcoin, the price and the behavioral aspect of its formation. The practical value lies in defining the characterization of the behavior model of digital economy agents under conditions of quarantine restrictions. The behavior of digital economy agents in the context of COVID-2019 requires further research, in particular, using cross-recurrent analysis methods.

ABSTRACT. The permanent state of the financial crisis has predictably brought to the forefront such traditional problem of banking as problem loans. This research aims to work out an econometric approach to the solution of the problem of loans terms’ rescheduling. For this purpose, we, firstly, treated credit as a bank’s investment project with cashflows’ chart including initial outflow (principal) and following inflows represented by loan payments. Secondly, we combined the schematic representation of loan’s cashflows with NPV formula accustomed to loan’s cashflows and it allowed to create the econometric models for three types of loan: classic, annuity, serial. Thirdly, for the case when borrower breaks a loan’s payment schedule and it leads to the reduction of loan’s NPV and loss of the wealth of bank’s shareholders, respectively, we outlined the special compensative models of cashflows where default in payment is interpreted by the lender as an additional forced loan. We suggested modifying the loan terms (interest rate or effective period of the loan agreement) for the rest of payment periods. Fourthly, we laid the special compensative models of forced loans’ cashflows a top corresponded initial cashflows of loans and this has made it possible to get the formulas calculating the modified interest rate and the additional number of loans’ payment periods with the aid of backward calculation. As a result, we developed the econometric models of the loan terms’ modifications based on the prolongation of the initial credit period and the increasing of the initial interest rate.

ABSTRACT. The important factor of business sustainability is human capital. In this regard, there is a need to estimate human potential, concerning the effectiveness of its management and commercialization probability. The current research problem lays upon human potential management and the possibility of its commercialization. The paper aims to provide scientific support on human potential and human capital theories, concerning their connection within the system of sustainable business development. The research methodology is based on theoretical and methodological approaches of Ukrainian and foreign experts from the last ten years, reflecting human capital and human potential concepts, taking into account business needs. The main part of the research highlights the special status of human potential, based on its specific characteristics, including network effects, the ability to convert human potential benefits into significant social and economic effects, hybrid and multiplicative. The paper proposes a new methodological approach on technology for human potential commercialization and management. Human potential commercialization measurement is offered as a new model to assess the significance of human potential and its managerial effectiveness estimation. The study results can be used within programs for sustainable and social business development. More extensive study is required to prove the proposed methodological approach effectiveness within different sectors and branches.

ABSTRACT. An up-to-date issue of a modern metallurgical enterprise is the increase of its energy efficiency, which is related, first of all, with energy saving. Therefore, the purpose of this paper is to develop a model for forecasting the metallurgical enterprise power system consumption and its experimental testing based on the "Electrometallurgical Plant “Dniprospetsstal” named after A. M. Kuzmin data. In order to build a forecasting model, a neural network apparatus in the MATLAB system was used and it was done in two stages. At the first stage, as an experiments series result, the optimal architecture and algorithm of neural network training were determined. In the second stage, the dependence of the modeling graphs load error from the influence of daily consumption graphs is identified. The MATLAB software package has been adapted for the needs of “Dniprospetsstal” named after A. M. Kuzmin. Neural networks designed in this way can be used to solve applied issues of electrometallurgy, in particular, the long-term estimation of time series of hourly power for the 24 hours ahead.

ABSTRACT. Many tasks in economic research are based on arithmetic calculations of indicators that reflect the state of economic development. The general incompleteness of publicly available data, designed to solve such problems, has led to the emergence of numerous decision support systems based on fuzzy arithmetic. The article presents a study on the approach aimed at integrating fuzzy information about economic indicators into economic models. The definition of arithmetic operations on fuzzy values is given, and the methods of obtaining the resulting fuzzy indicators with the help of some software tools are considered. Analytical and numerical methods of obtaining the resulting indicators in the form of fuzzy numbers are described and analyzed. A direct calculation algorithm for all arithmetic operations is proposed, utilized, and used for the evaluation of resulting indicators. Also, analytical and numerical methods for obtaining fuzzy results are considered in the article, and some of them are proposed for utilization. On the example of economic indicators used in the labor rationing, the results of an evaluation of some indicators for a technological operation in the form of fuzzy numbers were obtained by different methods and compared. The practical recommendations, given in the article, on the use of fuzzy arithmetic in decision support systems outline the directions of further research.

ABSTRACT. Productivity and economic growth are key factors to maintain and improve the competitiveness of nations in the global market. The paper analyzes the prospects for the competitiveness of Ukrainian exports in the terms of pandemic circumstances and post-pandemic recovery of the global economy. The prospects for strengthening the competitiveness of Ukraine's economy evaluating based on the modified approach for assessing the revealed comparative advantage. The dynamics and structure of major industries exports were estimating. The research result proved that the growth of innovative products in the iron and steel industry increases its competitiveness in the world market. The established reduction of the identified comparative advantages index for the main exports positions reflects the presence of structural and technological lags in the modern structure of the national economy and requires economic policy measures aimed at long-term action. Respectively, the main goals of contemporary national economic policy aimed at promoting the export competitiveness of Ukrainian products (goods & services) have to be the stimulating of R&D, infrastructure modernization and capital deepening.

ABSTRACT. The relevance of the chosen topic is related to the growing interest of researchers in technologies and mechanisms of growth of new touristic opportunities in the smart era of society, features of its impact on national policies in order to achieve strategic socio-economic goals of the countries both for domestic territories and along the path of development of geoeconomic strategies in the global space. In addition the relevance of the research direction is enhanced by the fact that tourism is one of the sectors of the world economy that has suffered the most from restrictions on movement during the pandemic crisis. The European Commission has recently presented a series of proposals setting out the foundations of the EU economy and society suitable for the digital age, outlining the development of a genuine European data space and offering a European approach to new technologies. The new industrial strategy and the SME strategy (adopted on March 10, 2020) identify the path to digital transformation to empower industry and small and medium-sized enterprises. The latest strategic communication of the European Commission “Tourism and Transport for 2020 and beyond” emphasizes the role of digital transformation and sustainability. This involves investing in digital skills and promoting digital innovation, as well as linking the tourism business and businesses to existing data spaces, technology providers, and community actors at the local and regional levels. To determine the possibilities of further development of the industry, ithe article proposes a factor model of the total revenue from tourism activities, taking into account regional changes in tourist flow, provide recommendations for the effective development of the industry with account of future trands of tourism industry and ecosystem development. These issues are equally pertinent both for tourism, given the advantages innovative, new technologies can bring to tourism destinations and for businesses, local communities and travellers. They can facilitate tourism management both at destination and business level, contributing to balanced and sustainable growth of tourism in post Pandemic time. New smart technologies can help businesses provide more personalised services and therefore enhance the tourism experience

ABSTRACT. In the paper discusses the use of big data as a tool to increase data transfer speed while providing access to multidimensional data in the process of forecasting product sales in the market. In this paper discusses modern big data tools that use the MapReduce model. The big data presented in this article is a single, centralized source of information across your entire domain. In the paper also proposes the structure of a marketing analytics system that includes many databases in which transactions are processed in real time. For marketing forecasting of multidimensional data in Matlab, a neural network is considered and built. For training and building a network, it is proposed to construct a matrix of input data for presentation in a neural network and a matrix of target data that determine the output statistical information. Input and output data in the neural network is presented in the form of a 5x10 matrix, which represents static information about 10 products for five days of the week. The application of the Levenberg-Marquardt algorithm for training a neural network is considered. The results of the neural network training process in Matlab are also presented. The obtained forecasting results are given, which allows us to conclude about the advantages of a neural network in multivariate forecasting in real time.

ABSTRACT. The purpose of the study was to develop theoretical and methodological background and to make practical offers for solving the problem of financial and economic security management of critical infrastructure in terms of personnel and strategic aspects. The list of reasons and circumstances of necessity of maintenance of financial and economic security of objects of critical infrastructure and its management is established. The definition of financial and economic security of a critical infrastructure object is offered. The peculiarities of the interpretation of the concept of financial and economic security for the needs of critical infrastructure are summarized. Two levels of financial and economic security management of critical infrastructure objects are distinguished ‒ state (external) level and internal level ‒ and an explanation of the differences in financial and economic security management at each of them is provided. The risks caused by quarantine restrictions for the state of financial and economic security of critical infrastructure objects have been identified. As a main result of the study the TARGET model for strategic management of financial and economic security of critical infrastructure objects is proposed. Practical value of the proposed in the study TARGET model for strategic management of financial and economic security of critical infrastructure objects – it will be the basis for developing strategic documents for stabilizing and further developing and maintaining high functionality of critical infrastructure of Ukraine. As an additional result of the study proposals on the basics of personnel policy formation for the need to ensure financial and economic security of critical infrastructure objects in a global pandemic and quarantine restrictions are made. The novelty of proposed personnel policy is in a fact that it contains such modern components as staff training; employee incentives; overcoming resistance to change; staff involvement in solving various issues; staff discipline; leadership, partnership and teamwork; time management and self-management; staff safety, staff digital literacy

ABSTRACT. The research material proposes the use of decision support information-analytical technology in discharge military personnel employment, which, in contrast to the usual processing of survey results, makes it possible to obtain more information for decision-making. Adherence to such an approach in the development of public administration mechanisms increases the likelihood that in the case of their implementation in the country there will be positive changes, as they will indirectly take into account the availability of necessary resources. Information and analytical technology to support decisions in the field of labor economics substantiates the development of the example of discharged military personnel social welfare. According to the content, the developed decision support information-analytical technology in the field of labor economics provides for the following components: formation of social protection mechanisms; development of a questionnaire on the use of the appropriate mechanism; statistical analysis of survey results (generation of empirical distributions of answers to questions relative frequencies; comparison of answers medians; correspondences analysis; factor analysis; analysis of hierarchies); meaningful interpretation; decision making.

ABSTRACT. Cryptocurrencies refer to a type of digital asset that uses distributed ledger, or blockchain technology to enable a secure transaction. Like other financial assets, they show signs of complex systems built from a large number of nonlinearly interacting constituents, which exhibits collective behavior and, due to an exchange of energy or information with the environment, can easily modify its internal structure and patterns of activity. We review the econophysics analysis methods and models adopted in or invented for financial time series and their subtle properties, which are applicable to time series in other disciplines. Quantitative measures of complexity have been proposed, classified, and adapted to the cryptocurrency market. Their behavior in the face of critical events and known cryptocurrency market crashes has been analyzed. It has been shown that most of these measures behave characteristically in the periods preceding the critical event. Therefore, it is possible to build indicators-precursors of crisis phenomena in the cryptocurrency market.

ABSTRACT. In this study, we present the computational method for risk assessment of the socio-economic development of regions. An attempt has been made to develop a method for the determination of integral risk indicators of socio-economic development based on the joint use of the methods of factor analysis and expert evaluation. This approach has increased the reliability of the calculations and made it possible to analyze the influence of socio-economic indicators on the risk level of socio-economic development. The integral risk indicator shows the effect of the inconsistency in the level of factor provision on the socio-economic development of the j-th region (district) in comparison with the general situation in the country (regions). The closer the value of integral risk indicator is to 1, the higher the level of risk in this region. Using Kyiv region districts as an example, the process of risk assessment for regional socio-economic development has been considered. The results obtained in this investigation demonstrate that the presented computational method solves the problem of formalization of risk assessment for the socio-economic development of regions.

ABSTRACT. The article discusses the Modeling of grain transportation in the system of grain processing industries. The question of determining the need of vehicles for the maintenance of agricultural work is of great national economic importance. It is associated with the problem of the effective use of material and cash resources, land and labor in grain farming. Calculations show that the cost of purchasing machines and operating costs can be reduced by 20-30% due to the correct selection and use of technology. Proper organization of the export of the grown grain crop plays an important role in improving the efficiency of the grain receiving enterprises (GRE) and the entire sector of the economy, as it contributes to a relative reduction in all transportation costs, improving the quality and safety of grain, reducing the cost of harvesting, improving the economic relations between the grain processing industries in the process of transportation and procurement works in a short time. The resulting task is a difficult experimental task. Known linear programming methods are not applicable for its solution

ABSTRACT. The article is devoted to the study of blockchain technology in the financial sphere of Ukraine, as well as accounting and audit of their application in domestic and international practice. The article contains data on the prospects of blockchain development in the world and in Ukraine, as well as information on the peculiarities of the use of such technologies in the perspective areas – accounting and audit. The article argues that the development of blockchain technology will enable the transition to more modern methods and techniques, which in turn will allow to modernize the accounting and auditing system. The principle of triple entry as a major component of blockchain technology in accounting is emphasized. One of the most promising areas of application of blockchain is accounting for accounts payable and receivable, tax accrual and payment, record keeping and documentation. The article highlights the advantages and disadvantages of using blockchain technology in the financial sphere of Ukraine.

ABSTRACT. The overview of the country’s trade with all the continents during the period of 2000-2019 is given. The description of the commodity structure of exports/imports of goods, with particular attention to the industrial products, is followed by the detailed analysis of Ukraine’s foreign trade in 2020. The decrease in Ukraine’s foreign trade in 2020 by 6.4% is fully consistent with the projected WTO reduction of world trade in 2020 by 9.2%. Although COVID-19 had negative impact on Ukraine’s trade with the EU and the EAEU, it contributed to closer trade ties with Asia, improving Ukraine’s trade balance. The actions of the state and the national business elite should primarily be aimed at solving the problems of increasing the volume and improving the commodity structure of Ukraine’s foreign trade with emphasis on the development of transport system for exporting agricultural and food products to the developed countries of the West and to the prospective economies of the East and the South. It is essential, on the one hand, to focus on the inflows of FDI and their appropriate use, and, on the other hand, on the active participation of Ukraine in the formation of GVCs, global production networks. In the modern world, in the conditions of the Fourth industrial revolution, the economy finds itself transformed due to these fundamental changes. The optimization of foreign trade relations of Ukraine will not only improve the country’s economy, but also enable Ukraine to become a better functioning element of the global economic system.

ABSTRACT. The paper carries out the strategic analysis of innovative possibilities of Zaporizhzhia region’s industrial complex and investigates the indicators of innovative activity of industrial complexes of Zaporizhzhia region and Ukraine by Harrington’s generalized desirability function. The evaluation results prove the “good” ability and readiness of the industrial complex of Zaporizhzhia region and Ukraine to carry out effective innovation activities. However, according to the comparative assessment of the innovative activity of Zaporizhzhia region’s industrial complex and Ukraine’s one, Zaporizhzhia region’s industrial complex is found to lag 9.2% behind Ukraine’s. A cluster development strategy is suggested to improve the innovative development management of Zaporizhzhia region’s industrial complex

ABSTRACT. In modern world economy resort recreations - one of the most high-profitable industries of managing. Ukraine owns the powerful resort and recreational potential, effective development of which can bring a real economic benefit. For this purpose, it is necessary to form a system concept for the development of such industry, which are integral part of the economic transformations. The purpose of the article consists in development of approach to modeling of transformations strategy development of resort-recreation systems in which transformation acts as their internal and necessary part. As a result of research, the concept of transformation strategy development was grounded, as a certain period of cyclic dynamics, and the scenarios of origin of catastrophe, development and introduction of innovations is got. The offered approach assumes opportunity to consider development of economy of resort-recreation systems as process of transformation change of strategies. On this basis the model based on theory of catastrophes, which allows carrying out the scenario description of transformation strategies of resort-recreation systems is constructed.

ABSTRACT. The article discusses the optimization models for the use of agricultural aviation when performing chemical works. The question of determining the need of vehicles for the maintenance of agricultural work is of great national economic importance. It is associated with the problem of the effective use of material and cash resources, land and labor in grain farming. Calculations show that the cost of purchasing machines and operating costs can be reduced by 20-30% due to the correct selection and use of technology. Of particular importance is the use of aviation technology in the conditions of intensification of grain production. Aviachemical method is firmly established in the technology of cultivation of grain crops. First of all, this is due to the fact that, compared to ground-based methods, the aero-chemical method of chemization of agriculture has a number of technical and economic advantages, including a higher quality and uniformity of chemicals, eliminates mechanical damage to crops, and less dependence on the physical and geographical conditions of the area, allows to obtain significant savings of chemicals and fuel, reduces the time of work

ABSTRACT. Machine learning (ML) methods are effective tools for analysis of many actual problems in modern banking. Increasing growth of data and rapid digitalization underpin the acceleration of ML implementation. These processes are especially noticeable in consumer banking because banks have millions of the retail customers. The first goal of our research is to form an extended review ML application in consumer banking. From one side we have identified the most developed ML methods, which are applied in this segment (for example different types of regressions, fuzzy clustering, neural network, principal component analysis etc.). From the other side, we point out two multi-purpose tools used by banks in consumer segment intensively, namely scoring and clustering. Secondly, our goal is to present some innovative applications of ML methods to the analysis of each task. This includes several applications for scoring models and fuzzy clustering application. All applications are oriented to make banks business processes more effective. Considered applications were realised on real data from the Ukrainian banking industry.

ABSTRACT. The purpose of the article is to substantiate the possibility and necessity of the central bank's monetary policy to stimulate investment and economic growth for developing economies on the example of the investment sphere and monetary policy in Belarus. It was determined that the impact of monetary regulation on investment and economic growth is achieved in the course of the central bank's activities to maintain indicators of price and financial stability which reflect favourable conditions for investment. Price stability is achieved through the implementation of various central bank strategies such as targeting the exchange rate, money supply and inflation. These strategies are defined as the objectives of monetary policy. The article discusses the advantages of monetary regulation in comparison with fiscal regulation, and also contains an analysis of its practical implementation in the Republic of Belarus in the period 2000-2019. As a result of the study the economic and financial results of the strategies applied at different stages were determined, their consequences for the economy were substantiated, and the strategies that best affect the financial and economic indicators in the country were identified. For countries with a small open economy which includes Belarus maintaining price and financial stability is complemented by a set of measures to reduce the devaluation expectations of market entities and create a favorable foreign economic environment.

ABSTRACT. Unemployment and inflation are among the most critical phenomena facing both developed and developing countries due to their harmful social, economic, and political effects. The Egyptian monetary policy's main objective is to maintain a low inflation rate in the medium run to keep the confidence and a high rate of investment and economic growth. At the same time, economists argue that targeting a low- rate of inflation may increase unemployment. Although the classical Philips curve indicates a trade-off between inflation and unemployment, several empirical studies have argued that the relationship between inflation and unemployment depends on the shocks' source and lagged responses. The main objective of this paper is to examine the relationship between inflation and Egypt's unemployment rate. We used time-series data from 1980 to 2018, where a vector autoregressive (VAR) model and the Impulse response function tool (IRF) were employed. The results show that inflation has a positive relationship with GDP while negatively affecting the unemployment rate.

ABSTRACT. The focus of this study to measure the varying irreversibility of stock markets. A fundamental idea of this study is that financial systems are complex and nonlinear systems that are presented to be non-Gaussian fractal and chaotic. Their complexity and different aspects of nonlinear properties, such as time ir- reversibility, vary over time and for a long-range of scales. Therefore, our work combines econometrical and econophysical approaches to measure the com- plexity and irreversibility of the time series. Econometrical approaches include Guzik’s index, Porta’s index, Costa’s index, and based on complex networks measures. Multiscale time irreversibility index and based on entropy measures approaches are taken as econophysical. Our study presents that the correspond- ing measures can be used as indicators or indicator-precursors of crisis states in stock markets.

ABSTRACT. The article is devoted to the study and comparative analysis of the stock quotes dynamics for the world's leading companies in the IT sector and the entertainment industry. Today, these areas are developing the fastest and most powerful, which attracts the attention of investors around the world. This is due to the rapid development of digital communication technologies, the growth of intellectualization and individualization of goods and services, and so on. These spheres have strong development potential, but the question to how their companies' stock quotes respond to the impact of such a natural but crisis phenomenon as the COVID19 pandemic remains open. Based on the nonlinear paradigm of the financial markets dynamics, the paper considers and conducts a comprehensive fractal analysis of the quotations dynamics for six leading companies (Apple Inc., Tesla Inc., Alphabet Inc., The Walt Disney Company, Sony Corporation, Netflix) in this area before and during the COVID-19 pandemic. As a result of the application of the rescaled range analysis (R\S-analysis), the presence of the persistence property and long-term memory in the stock quotes dynamics for all companies and its absence in their time series of profitability was confirmed. The application of the method of sequential R\S-analysis made it possible to construct fuzzy sets of memory depths for the considered time series and to deepen the analysis of the dynamics due to the quantitative characteristics calculated on their basis. Taking into account the characteristics of memory depth in the dynamics of quotations made it possible to conduct a comparative analysis of the dynamics, both under the influence of the natural crisis situation and in terms of investing in different terms. The peculiarities of the delayed profitability dynamics of quotations for each of the companies are also taken into consideration and compared. The developed recommendations can be used in investment activities in the stock market.

ABSTRACT. The article considers the theoretical and methodological foundations of forest industry research. The analysis of indicators of the forest industry of the Khmelnytskyi region and Ukraine is carried out. To do this, a list of indicators and methods of their collection for the study of the forest industry. Since the state of ecology and forestry in Ukraine is not in the best condition, it is objectively necessary to use methods of economic and mathematical modeling of forest management, which would take into account environmental, economic, and social factors, which will quickly implement the principles of sustainable development in forest management. The dynamics of forestry indicators is estimated. Models of dynamics of indicators of forest branch are developed; the received forecasts are analyzed and recommendations on forest management in the region are given. It is determined that with an increase in investment in the development of the forest industry by 1per, we can expect an increase in the volume of the logging market by 524632.5 points. The results of the study can serve as a basis for management decisions on the management of forestry indicators.

ABSTRACT. The study is devoted to solving the scientific problem of optimizing the retail trade in the production and sale of two types of products, taking into account the change in potential demand for products. The economic and mathematical model of the production activity of the enterprise was developed taking into account logistics and market demand. The logistics scheme takes into account all the main links of the logistics system, as well as the connections between them. The considered scheme makes it possible to take into account the diversification of products manufactured by the enterprise. The mathematical model is designed for discrete time. A numerical optimization method has been developed for this mathematical model. Optimal solutions are found and investigated for such cases: demand for products remains unchanged throughout the entire life cycle of the project; demand for products of the first type abruptly decreases by 20% in the 300th period, and for products of the second type remains unchanged; the enterprise increases the retail trade network for the first type of goods by 20% in the 300th period; the company can choose the moments of transformation of retail chains for each type of product independently. The dynamics of the main characteristics of drugs was calculated for all considered cases. A comparative analysis of economic efficiency for the studied cases has been performed. Proved the economic efficiency of optimization of the retail network.

ABSTRACT. The phenomenon of the international investment activity in the context of globalization is investigated in the article. Foreign direct investment is the most important basis for further analysis of the world economy. The article discusses the current trends of the foreign direct investment flows with an emphasis on their geographical location. In particular, the inflows of FDI by region and national economies are considered. The specific features of modern factors of the foreign investments’ distribution by regions are determined. The study shows that some methodological approaches are useful in determining the level of national economies’ interconnection of the linked processes of international capital flows. The clustering method was used for the analysis of foreign investments and the minimum spanning trees for the selected groups of countries were constructed. From the defined list of countries, one group with similar trends in the FDI movement has been distinguished. The article stipulates that countries should consider the need for their active involvement in globalization processes and contribute to the formation of a favourable investment environment within the country.

ABSTRACT. The article analyzes some aspects of quality control and efficiency of electronic educational and methodological complexes of educational disciplines usage in the educational process. Analysis of the implementation of e-learning and of user work allows to build a model of student’s work, identify the disadvantages of both organizational and technological plan and take timely steps to eliminate them. The solution to this problem should include a comprehensive approach to ensure an objective result. Google Analytics tools, Moodle Learning Management System tools, the teacher’s surveys to monitor the quality of e-learning in an institution proves its efficiency and allows to see the full advantages and disadvantages of ongoing e-learning in an institution, plan and implement further development and improving e-learning. The analysis of the effectiveness of e-courses usage should be carried out in a comprehensive manner, using the monitoring tools of the educational process adopted in the educational institution. Such as surveys for teachers and students, analysis of success, etc. The specifics of e-learning, the Moodle Learning Management System tools and third-party services for collecting statistics and analyzing user activity in the Learning Management System should be taken into account.

ABSTRACT. Theoretical and methodological studies of quantitative measurement problems of the outcome economic indicators in corporate management are examined in the article. The author 's vision of scientific exploraction as one of corporate management optimisation directions is offered and the basis of such direction as profit margin calculation methodology is presented. It's also suggested to solve problems of quantitative measurement of basis economic processes by using allocation of fixed costs in proportion to profit margin. It is proved that in case of multi-ashortment production one of the most effective corporate management approach to cost estimation and pricing is the profit margin concept. One of the advantages of proposed profit margin concept is the availability of special tools revealing the resources that allow covering fixed costs and generating profit with a given level of cost-effectiveness. The obtained results can be applied as element of corporate management of manufacturing enterprises and companies.

ABSTRACT. The article considers the problem of optimizing the financial condition of oil and gas companies. The offered methods of optimization of a financial condition by scientists from different countries are investigated. It is determined that the financial condition of the enterprise depends on the effectiveness of the risk management system of enterprises. It is proved that the enterprises of the oil and gas complex need to develop a system for risk management to ensure the appropriate financial condition. The financial condition is estimated according to the system of certain financial indicators, the integrated indicator of financial condition assessment is constructed using the method of taxonomy. According to the results of the calculation of the integrated indicator, it is concluded that this indicator does not have a stable trend. On the basis of the conducted researches it is offered to carry out optimization of an integral indicator of a financial condition with use of genetic algorithm in the MatLab environment. Based on the obtained results, recommendations of the management of the researched enterprises on increase of management efficiency are given.

ABSTRACT. In present paper, time series models of revenues and expenses of general and special local budget fund in Zaporizhzhia City Council for 2017-2020 are built. The possibility of forecasting time series has been investigated on the example of local budget revenues and expenses. The concept of assessing the level of management control which consists of information-analytical circuit, analysis and modeling circuit, and decision-making circuit has been proposed. The best options for absolute and comparative economic efficiency of accounting and economic expenses of management control have been substantiated. The forecast for calculating the absolute and comparative economic efficiency of management control on the data of Zaporizhzhia City Council is shown and the annual economic effect from its implementation is calculated. The SPSS Statistics data analysis package is used for data processing, test assumption and building the future strategy.

ABSTRACT. The article proposes an economic-mathematical model for determining a comprehensive risk assessment of the investment project of the enterprise which are based on the approaches of A. Nedosekin. The model is built using fuzzy logic and takes into account the probability of occurrence of each of the identified risks and the level of impact of each of them on the project. The probability of risk is set by experts in the form of points and converted into linguistic terms, and the level of influence of each of them on the project – the ratio of benefits and is determined using Fishburne scales. The proposed Project Risk Model consists of the following stages: formation of initial data using expert opinions; construction of a hierarchical project risk tree; determination of weight coefficients (Fishburne weights) of project risks; selection and description of membership function and linguistic variables; conversion of input data provided by experts from a score scale into linguistic terms; recognition of qualitative input data on a linguistic scale; determination of a complex indicator of investment project risks; interpretation of a complex indicator. The developed model allows managing the risks of the project to maximize the probability of its successful implementation, to compare alternative projects and choose less risky, to minimize the level of unforeseen costs of the project.

ABSTRACT. The article considered the assessment of the sustainability of the export flow of Ukraine. It was determined that the markets of Slovakia, the Russian Federation, Germany, Poland and Lithuania possess long-term memory. Also, the main factors that affect the sustainability of export have been analyzed. Among cultural factors, a weak correlation was demonstrated by Long Term Orientation, Indulgence and Power Distance according to the Geert Hofstede method. At the same time, the cultural patterns according to the Shalom H. Schwartz method did not show a correlation with the long-term memory of product export. On the stability of the export flow, the role of the linguistic distance and the factor of the diaspora presence have been assessed. It was proved that the gravitational effect has the greatest impact on the stability of export; Power Distance, linguistic distance and the factor of the diaspora presence have the negligible impact as well.

ABSTRACT. In the article considered the issues of constructing a classic SWOT analysis matrix, forming a list of key factors of the external and internal environment to assess the degree of their impact on the activities of real enterprises of Ukraine, improving the method of conducting SWOT analysis through the use of scientifically based scales and indicators. The thesis justified that SWOT analysis and other classic strategic management tools are conceptually described, and their use causes many approaches to their mathematical formalization and use. We propose our own approach to quantifying the strengths and weaknesses of the enterprise, external threats and opportunities at the main ten stages. The focus is on step-by-step calculation of integrated indicators for the main groups of SWOT analysis and their qualitative interpretation. Examples of implementation of SWOT analysis for a real enterprise are given. The company's strengths and weaknesses were identified. External capabilities and threats were analyzed. To assess the importance of indicators, a pairwise comparison technique was used, which provides for the estimation of indicators based on the average geometric value according to T. Saati. This made it possible to prioritize factors within the SWOT analysis methodology. Four quadrants are filled at the intersection of strengths/weaknesses, opportunities/threats and four types of potential strategies for the enterprise are described in the field defining: guidelines for the strategic development of the company; strategic advantages of the company; guidelines for the internal transformation of the enterprise; Limiting strategic development. Using a quantitative approach made it possible to build a SPACE matrix of strategy selection.

ABSTRACT. The paper deals with the methods of assessing the level of sustainable development of the integrated technogenic system as a family of models for eco-economic and socio-humanitarian management of technogenic economic objects. The economic approach to modeling a sustainable development is considered, which consists of the optimal use of limited resources and applies natural, energy and resource-saving technologies to generate aggregate income. At the same time, the transition to the information society leads to a change in the structure of aggregate capital in favor of human, increasing intangible flows, flows of information and intellectual property. The problem of sustainable development through 7 main assets (capitals) that support the viability of socio-environmental and economic systems is considered. The concept of sustainable development, the system of global dimensions of sustainable development and the level of sustainable development are defined. The presented methodology for the formation of humanitarian component of technogenic regional production uses available statistic data. Application of these methods will improve efficiency of managerial decisions in the technogenic regional production management, maximize benefits from the use of innovations and define strategic innovative directions for regional development.

ABSTRACT. As a result of research, the concept of a flexible evolutionary model is proposed, which with the help of machine learning allows obtaining the most successful strategy for the development of human capital. The proposed conceptual and methodological approach to machine learning of the process of assessing human capital of enterprises, taking into account the cognitive psychology of man and reflective attitudes in the human environment, can increase the effectiveness of decision-making in the field of human capital development management. The training involves indicators of return on investment in the individual, in the types of components of human capital, which are characterized by properties (creativity, competence, purposefulness, communication, motivation), where between their varieties there are appropriate reflective relationships. The main difficulty of this approach to the choice of alternative solutions for finding options for the use of human capital is the correct selection of indicators of significance (return) of contributions to the development of types of human capital, on the basis of which cycles occur of systemic learning. This approach can simplify the search for and developments of human capital development strategies, present alternative ways, and simplify management decisions.

ABSTRACT. Investments in environmental protection are crucial for achieving the goals of building green econ omy. The purpose of the study is, firstly, to assess the state and trends of Ukrainian companies investments for environmental purposes; secondly, to identify the determinants of the impact on the volume of environmental protection investments; finally, to determine presence / absence of a link between environmental investments and financial performance of companies. The initial data for the study were obtained from published statistical reports for the period from 2010 till 2019. Methods of analysis for testing hypotheses are descriptive and correlation-regression ones. It was found out that the selected independent variables (belonging to environmentally damaging activities, revenue and financial results of the companies) are positively correlated with the volume of costs and investments in environmental protection of Ukrainian companies. The hypothesis of environmental investments positive impact on the financial profitability of companies has not been confirmed. Environmental policy in Ukraine concerning implementation of “green” growth strategy is defined as a reflective one due to a number of economic and political factors.

ABSTRACT. The article deals with the analysis the current state of migration in the context of globalization and identifies the most important corridors for the labour movement. The main donor countries of migrants are developing countries, with low socio-economic indicators, difficult environmental conditions and high levels of poverty. According to forecasts, the most migratory flows will take place in the countries of North America and in Europe, which is due to rising trends in unemployment in the countries of the «third world» and the demand for cheap labour, changes in the structure of the economies of developed countries, changes in labour market demand. The main world regional corridors in 1990-2019 have been identified through statistical analysis. And their growing and declining trends. The need to use economic and mathematical modelling techniques to analyse and determine the migration attractiveness of recipient countries in an uncertain environment has been substantiated. It has been shown that fuzzy logic tools are the most effective in this case. Based on the results of the simulation using the Mamdani method, the world’s attractiveness rating for migration is calculated, which with a «high» thermo leads such countries as Italy, France, United Arab Emirates. The findings suggest that migrants are attracted by countries with the lowest inflation rates, high and average GDP per capita and average or low taxation levels.