Formation of a Regional Development Strategy According to the Level of Investment Activity of Enterprises

Received January 22, 2018 Revised from February 26, 2019 Accepted April 30, 2019 Available online September 15, 2019 An economic-mathematical model of an integrated assessment of the investment activity of enterprises in the region has been developed. The novelty of the results is determined by the fact that integral indicator is built on the basis of a common base, formed using the characteristics of regional differentiation, derived from theoretically sound models. Оf investments on key economic indicators such as gross regional products, financial results of profitable companies, volume of sales of industrial products, volume of sales of services and volume of sales of innovative products during 20102017 is assessed in the article. In order to study the influence of investments on economic development of regions is used a statistical tool of correlation analysis which displays links between factors and results. According to research, the university regression models are built. Results of the studies indicate that capital investments are not a major factor in providing the profitability of enterprises in almost all regions of Ukraine. The typology of the regions of Ukraine according to the level of investment activity of enterprises by cluster analysis methods is carried out/ The advantage of the developed economic-mathematical model of the integrated assessment of investment activity of enterprises in the region is the possibility of its use in order to form a differentiated investment policy. JEL classification: C 54, E 52, O32, R12. DOI: 10.14254/1800-5845/2019.15-3.8


INTRODUCTION
In today's conditions, economic inequalities in the development of economic agents become an independent factor hindering regional socio-economic development. The main focus of the transformation of the economy is the structural optimization of technical and technological as well as organizational and economic complexes, which is carried out by new methods of managing of investment resources. In this case, the laws of economic development are characterized by uneven economic conditions, periodically arising structural crises and technological changes, nonequilibrium of processes of technical and economic development, uncertainty of technological trajectories.
The structural reorganization of the region's economy is associated with the redistribution of material, labor and financial resources from strategic sectors that are not perspective in the industry, marked as promising and, therefore, priority. The key feature of sustainable development of the region is the investment activity of enterprises, which lies in the area of technology and organization of funds management through the regulatory role of regional authorities in the investment process in the sectors of the economy, and the effectiveness of the state regulation regarding the specific conditions of the reproduction process. The issues of investment development of the region, analysis of its investment environment, allowing to ensure the development of the real sector of the economy are presented in the works of E. Animitsa (2015), G. Kvon et al. (2017), T. Gössling (2007), K. Koschatzky (2003), K. Zum-busch (2013), J. Pires Manso et al. (2015), N. Bryukhovetskaya (2016), O. Аrefieva (2018), and R. Ginevicius et al. (2018). Problems of the development of the region are devoted to the work of such scientists as I. Buleev (2015), S. Aivazian (2018), O. M. Kruk (2013).
The purpose of this article is to consider three key issues: (i) Section 1 outlines the methodological foundations of this study; a brief description of the variables is presented; (ii) the second section presents the evaluation of the parameters and results of the statistical tests for the determination of errors, autocorrelation and multi-collinearity between the explanatory variables, (iii) in the third section, the synthesis of the main conclusions of the study is presented.

FORMATION OF THE BASIS
Proceeding from strategic macroeconomic positions, the problem of regulating the role of the state not only exists, but is also key, and the effectiveness of structural and investment transformations and the sustainability of economic growth depend on how well it will be solved.
In order to determine the relationship between sustainable development of the region and investment activity of enterprises, it is necessary to develop an economic-mathematical model of the integrated assessment of investment activity of enterprises in the region.
The complexity and multidimensionality of the process of developing the economicmathematical model of the integrated assessment of the investment activity of enterprises in the region necessitates the allocation of constituent elements each of which corresponds to their own goals and objectives.
For establishing the relationship between sustainable development of the region and investment activity of these enterprises, it is necessary to develop an economic and mathematical model of the integrated assessment of investment activity of enterprises in the region (Figure 1).
At stage 1, a study of factors that affect the investment activity of enterprises in the region is carried out.
For the objective assessment of the efficiency of investment activity at the regional level, a correlation-regression analysis of the availability, density and significance of the link between investments and a number of indicators characterizing the level of economic development of the region (GRP, financial result of profitable enterprises, volume of industrial products sold, volume of the realized services and costs of enterprises for innovation).
The general indicator reflecting the state of development of the region's economy is the gross regional product (GRP) (Figure 2-3).

ESTIMATES OF PARAMETERS AND OTHER STATISTICAL RESULTS
At stage 2, an estimation is made of the degree of influence of factors on the investment activity of enterprises in the region.
In order to assess the efficiency of investment activity at the level of Donetsk and Luhansk regions, a correlation-and-regression analysis of the connection between investments and GRP has been carried out. The data used for simulation is shown in Figures 2-3.
Analyzing the data, the econometric model of GRP dependence on the volume of capital investments in the economy of Donetsk region is characterized by the following equation: where X1 -volume of capital investments, mln UAH.
The calculated parameters show that with an increase in the volume of investments by 1 million UAH the gross regional product of the Donetsk region increases by an average of 510 thousand UAH.
The investigated model (1) is significant in general, since, according to the Fischer-Snedecour distribution, F = 37,76 ≥ Ftabl. = 3,5 The coefficients of the correlation matrix are close to one, which shows that there is a close direct link between investments and the GRP. At the same time, the determination coefficient (R 2 = 0,8831) is also quite high, which characterizes the strength of correlations of the GRP (Y) with investments (X1).
Analyzing the data, the econometric model of GRP dependence on the volume of capital investments in the economy of the Luhansk region is characterized by the following equation: where X1 -volume of capital investments, mln UAH.
The calculated parameters show that with an increase in the volume of investments by 1 million UAH the gross regionalproduct increases by an average of 182 thousand UAH. The explored model (2) is significant in general, since, according to the Fisher-Snedekor distribution, F = 13,88 ≥ Ftabl. = 3,5 The correlation coefficients R = 0,8574, which show that there is a close direct link between investments and GRP. At the same time, the determination coefficient (R 2 = 0,7362) is also quite high, which characterizes the strength of correlation of GRP (Y) with investments (X1). One of the main indicators of the efficiency of investment in an enterprise is profit. In 2017, the share of profitable enterprises in the Donetsk region amounted to 76,8%, and in Lugansk region -72,1%. When constructing a correlation-and-regression model for assessing the impact of capital Ivan P. Buleev, Natalya Yе. Bryukhovetskaya, Tetyana Yu. Korytko and Olena N. Kruk / Montenegrin Journal of Economics, Vol. 15, No. 3 (2019), 113-124 117 investments on the profitability of enterprises, the financial result was selected before the taxation of profit-making enterprises (Fig. 4).  (3) where X1 -volume of capital investments, mln UAH.
The investigated model (3) is significant in general, since, according to the Fischer-Snedecour distribution, F = 16,72 ≥ Ftabl. = 3,5 The correlation coefficients R = 0,8579, which show that there is a close direct link between investment and financial results of profitable enterprises, the determination coefficient (R 2 = 0,7359) indicates that the variation of profitable enterprises income is determined by 73,59% volumes of capital investments. Analyzing the data, the econometric model of the dependence of the financial result before taxation of enterprises that have gained profit from the volume of capital investments in the economy of the Luhansk region is characterized by the following equation: (4) where X1 -volume of capital investments, mln UAH.
The investigated model (4) is significant in general, since, according to the Fischer-Snedecour distribution, F = 11,32 ≤ Ftabl. = 3,5 The correlation coefficients R = 0,4247, which show that there is a low direct relation between investments and financial results of profitable enterprises, the determination coefficient (R 2 = 0,1804) indicates that the income variation of profitable enterprises is determined by 18,04% volumes of capital investments. The unprofitableness of a large number of enterprises can be explained by the deceleration in the growth of production volumes and sales. The correlation analysis of the interrelation between the capital investment inflow and the volume of industrial products sold in Donetsk and Luhansk regions revealed some trends in the dynamics of these indicators (Fig. 5). The investigated model (5) is significant in general, since, according to the Fisher-Snedekor distribution, F = 55,51 ≥ Ftabl. = 3,5 The correlation coefficients R = 0,9658, which show that there is a close direct link between the investments and the volume of sales, the determination coefficient (R 2 = 0,9328) is also quite high, which characterizes the correlation of the volume of product sales (Y ) with investments (X1). Analyzing the data, the econometric model of the dependence of the volume of the products sales of on the volume of capital investments in the economy of the Luhansk region is characterized by the following equation: where X1 -volume of capital investments, mln UAH.
The investigated model (6) is significant in general, since, according to the Fisher-Snedekor distribution, F = 7,42 ≥ Ftabl. = 3,5 The correlation coefficients R = 0,8062, which show that there is a close direct link between investments and volume of products sales, the determination coefficient (R 2 = 0,66499), characterizing the correlation between the volume of the products sales o (Y) and investments (X1). From 2013 onwards, the dynamics of growth of capital investments into industry in Ukraine tends to decline, which negatively affects the dynamics of the volume of expenses for innovation activity (Fig. 6). The investigated model (7) is significant in general, since, according to the Fisher-Snedecour distribution, F = 4,27 ≥ Ftabl. = 3,5 The correlation coefficients R = 0,6638, which show that there is a direct link between investments and the volume of enterprise expenses for innovation, the determination coefficient (R 2 = 0,4407) indicates that the variation of expenses for innovation activity of enterprises by 44,07 % is determined by the volume of capital investments. Analyzing the data, the econometric model of the dependence of the enterprise's expenses on innovation from the volume of capital investments in the economy of the Luhansk region is characterized by the following equation: where X1 -volume of capital investments, mln UAH.
The investigated model (8) is significant in general, since, according to the Fischer-Snedecour distribution, F = 25,17 ≥ Ftabl. = 3,5 The density of such a connection is confirmed by the results of correlation-and-regression analysis (R = 0,8986). In particular, 80,75% of the change in the volume of enterprise expenses on innovation can be explained by a change in the total volume of capital investment in industry. Among the main reasons for the unsatisfactory investment activity of enterprises in Donetsk and Luhansk regions -firstly, due to the military conflict in the Donetsk region, the investment activity of enterprises from all branches of industry and other spheres of economic activity has significantly decreased. Due to the complications of the technological and production process, the emergence of logistical problems, most enterprises have significantly or completely reduced their activities in the direction of investment activity. Secondly, it is a low ability of enterprises to self-finance. In the structure of capital investments there is a tendency to increase the share of own funds and decrease the share of loans to banks and other loans (increase of the NBU discount rate from 10,25% in 2010 to 14,5% in 2016, and from 02.03.2017 -17,0%), increase in the value of loans in both national and foreign currencies (in USD in 2016, the average weighted interest rate on loans is 8.9% and 21.3% in UAH, and in 2010 -8,9% in USD and 21,3% in UAH). The inability of a part of domestic enterprises due to unprofitableness (the share of unprofitable enterprises in 2017 amounted to 23,2% in the Donetsk region and 27,9% in the Luhansk region) to use the profit for reinvestment, on the one hand, and to reduce the share of bank lending to the real sector, taking into account. The high risk of non-repayment of loans, on the other hand, has led to a decline in investment income in recent years.
Thirdly, a small proportion of the volume of innovative costs in the structure of investments directed to industry. Thus, in Donetsk region, this share in 2016 is 6,7%, in the Lugansk region-0,76%. On the basis of the obtained results of the factors influencing the investment activity of the enterprises of the region, we will construct a linear model of a multiple regression. To ensure comparability, we conduct the normalization of indicators in the interval [0; 1].By means of multiregression modeling, the calculation of the integral indicator of the investment activity of enterprises in the n-th region in the t-th period is calculated; the equation has the form: R = 0,041 + 0,696 Х1 + 0,295Х2 + 0,069Х3 -0,045Х4 (9) where X1 is the gross regional product; X2 -financial result of profitable enterprises; Х3 -the volume of the sold industrial products; X4 -the expenses of enterprises for innovation. Ivan P. Buleev, Natalya Yе. Bryukhovetskaya, Tetyana Yu. Korytko and Olena N. Kruk / Montenegrin Journal of Economics, Vol. 15, No. 3 (2019), 113-124 120 The investigated model (9) is significant in general, since, according to the Fisher-Snedecour distribution, F = 8,75 ≥ Ftabl. = 3,5 The density of such a connection is confirmed by the results of the correlation-regression analysis (R = 0,9597), which shows that there is a close direct link between investments and investigated factors, the determination coefficient (R 2 = 0,9211) is also quite high, characterizing the tightness of the correlation connection. At stage 3. Classification of the regions of Ukraine by the level of investment activity of enterprises by cluster analysis methods in order to identify regional "growth points". At this stage, the formation of a multi-parameter cluster model of the typology of regions according to the level of investment activity of enterprises is carried out. In the first step, it is recommended to use one of the hierarchical methods -the Ward method, using the Euclidean distance as a measure of the degree of similarity. This method leads to the formation of clusters approximately equal to the minimum interstitial cluster dispersion, which are in the form of a hyperspace (Fig. 7). By comparing the actual values of F-statistics (to test the hypothesis of inequality of dispersions) and analyzing the level of significance of p-level, we can conclude that the greatest contribution to the intercluster variability is made by the variables Y, X1, X2, X3, X4. (Table 1). The smallest Euclidian distance is observed between the first and third clusters, and the second cluster is removed as far as possible from other clusters (Table 2). This statement corresponds to reality, since the second cluster represents the regions that are characterized by the highest investment activity. In the second step, as a result of the visual analysis, which shows the number of clusters that are fairly evenly monitored in the voter, it is necessary to cluster the source set of objects by the kaverage method. Its essence lies in the fact that the process of classification begins with the task of some initial conditions -k-randomly chosen by objective, which will serve as standards, that is, the centers of clusters. The idea of the algorithm of the k-average method is to sequentially refine the reference points with the corresponding recalculation of the weights attributed to them.
In order to give an economic interpretation of the resulting clusters, it is necessary from the standardized data to go to the output. Comparison of mean values and mean square deviations for each cluster will allow characterization of each cluster (Table 3). Cluster 1 includes the enterprises of the Dnipropetrovsk region and the city of Kyiv. The average volume of capital investments is 106295.5 million UAH. Cluster 2 includes enterprises of the following areas: Donetsk, Zaporizhya, Kyiv, Lviv, Odessa, Poltava, Kharkiv.
The high investment activity of enterprises included in this cluster is confirmed by the volume of capital investments, which amounted to an average of 19583.4 million UAH. This cluster is characterized by a rather high level of supply of the gross regional product -140090.5 billion UAH , which exceeds the average value in Ukraine -63586.0 billion UAH .
At stage 4, the cluster-rating estimations of the regions are calculated based on the level of investment activity of enterprises Rj. On the basis of the integral indicator, a quantitative estimate of the investment activity of enterprises in the region can be obtained. For this reason, the rating of the given indicator is carried out. Next, the region with the highest rating value is assigned the highest rank 1, followed by rank 2, and so on. The ratio of the received investment activity clusters and the corresponding rating estimations Rj allows us to determine the "marginal" values (formulas (10 -11): The comparison of cluster and rating indicators of Ukrainian enterprises allowed to determine the "marginal" values for each cluster: enterprises with rating ratings Rj more than 0.75 have a high level of investment activity; 0,30 -0,75 -average level and less than 0,30 -low level of investment activity. At stage 5, a strategy for the sustainable development of the region is being developed taking into account the investment activity of enterprises. The advantage of the developed economic-mathematical model of the integrated assessment of investment activity of enterprises in the region is the possibility of its use in order to form a differentiated investment policy (Table 5). Adaptation strategy -developing a strategy for identifying "weak links", achieving an optimal level of performance For the enterprises of the first cluster, it is recommended to use an anti-crisis strategy that includes such elements of policy as effective creation of integrated structures (a set of service and processing enterprises of the agricultural complex, insurance companies, commercial banks, transport enterprises, etc.) with the participation of enterprises that allows to reduce the risks associated with the instability of production, and provides a regular income of the processing and service enterprises of the region, efficient use of available resources.
For the enterprises of the second cluster, it is recommended to use an innovation strategy that includes such elements of policy as the development of resource and raw material potential: supporting the positive dynamics of development by ensuring high competitiveness of enterprises both in the domestic regional market and beyond, for the improvement of the pricing policy, the improvement of the quality of services rendered and other measures, have an impact on competitiveness.
For the enterprises of the third cluster, it is recommended to apply an adaptation strategy that includes such policy elements as: deepening of the integration processes in all productioneconomic formations as a means of attracting investments; it is necessary to change substantially the attitude towards the use of the already established powerful production potential, to concentrate forces and means in the areas that provide the greatest return, to pay special attention to the development of intensive technologies, to reduce product losses at all stages of production; to implement all the proposed measures aimed at achieving a more sustainable development of the region's market, it is necessary to increase the awareness to scientific and technical development.

CONCLUSIONS
Increasing the investment activity of the enterprises in the region is a complex and integrated process. The integrated assessment of the investment activity of enterprises in the region, conducted on the basis of the suggested methodology, showed the effect of capital investments on the indicators characterizing a regional development, and the scale of their changes suggests the presence of relatively close direct interconnections.
Increasing the efficiency of investment activity of regional enterprises requires the development of scientifically sound economic, investment, monetary, fiscal and other policies in the medium and long term. Therefore, further research requires investigation of the reasons for the lack or insignificant impact of investments on the key indicators of economic development and the search for effective tools for improving investment provision in each individual region and in the domestic economy as a whole.