UK: У статті проаналізовано алгоритм стратегічного прогнозування активізації інноваційного розвитку регіону. Побудовано й розраховано множинно-регресійну багатофакторну модель інноваційного розвитку регіону, яка враховуватиме підходи до збереження природного навколишнього середовища. За результатами проведених розрахунків визначено, що найбільший вплив на інноваційний розвиток регіону має стан екологічної ситуації в ньому. Застосування запропонованої моделі дасть змогу прогнозувати подальші зміни рівня інноваційного розвитку регіону на основі збереження природного навколишнього середовища територіальної системи.
EN: The article is devoted to the research of the algorithm of strategic forecasting of activation of innovative development of the region, which is based first of all on the fact that the innovative potential can be considered as an integral criterion of innovative development. Also, this criterion is to summarize the indicators of potential development at the levels of regional governance and the structure of the innovation potential at the same time. In the process of research it is substantiated that in forecasting the innovative development of the region, an important role is played by the assessment of its innovative potential, which allows
to increase the reliability of forecasts and create general additional data from methods with a set of existing ones. The use of effective assessment tools helps to improve product quality and ensure the competitiveness of the region as a whole. In order to determine the regional measurement of innovation development between the indicator and the factors, a correlation is used, which means the dependence of two random variables, the Spearman rank correlation coefficient is also considered, which helps to estimate how satisfactory the relationship between two variables can be using a monotone function. A multi-regression
multi-factor model of innovative development of the region was built and calculated, using the tool "Regression of the MS Excel data analysis package" a regression analysis was performed, where the coefficient of determination is R2 = 97, which indicates high accuracy of its selection, as it is very close to 1, this means that 97% of the variation of the dependent variable Y is determined by the variation of the independent variables X, thus the constructed econometric multifactor model is adequate to reality. According to the results of the calculations, it is determined that the greatest impact on the innovative development of the region has the state of the ecological situation in it. The application of the proposed model will allow predicting further changes in the level of innovative development of the region based on the preservation of the natural environment of the territorial system.
