Abstract
The article assesses the level of financial and economic potential of industrial enterprises using analytical and synthetic processing of its components (budgetary-resource, financial-investment, safety-oriented, borrowed, credit-market, investment, innovative-technological and riskadaptive) based on cluster analysis carried out for each group of selected indicators. For the assessment, real statistical reporting of the largest enterprises in the Kharkov region in terms of industrial potential was used. Analytical and synthetic processing for each of the components was carried out in accordance with the following stages: justification of the goals of cluster analysis, selection of a measure of distance between cluster indicators; choosing a clustering method and deciding on the number of clusters; assessment of cluster reliability; interpretation of clusters; distribution of industrial enterprises by level of financial and economic potential; comparison of levels of financial and economic potential and formulation of conclusions. The consistent implementation of the above stages made it possible to reflect the main trends in the dynamics of financial and economic potential level of grouping objects in the total number of enterprises at different indicators levels (high, medium, and low). During the analyzed period, industrial enterprises had the largest percentage of a high level of budget-market (86%), borrowed (49%) and investment (46%) components. At the same time, the average level was not significant and ranged from 14 to 34% among the studied components. A low level of financial and economic potential was also observed, the highest value (66%) was characteristic of the innovation and technological component, and the lowest value (1%) was observed for the budgetary and resource component. The results of the assessment are the basis for identifying current factors and threats that affect the industrial enterprises level of financial and economic potential, developing a strategy for their further development and justifying effective management decisions.
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