The article discusses the features of several methods for assessing the innovation potential of a region. Based on the experience of researchers and aiming to address the main shortcomings, a new assessment methodology is proposed by the author. Within this approach, an analysis of indicators that characterize the innovation potential of manufacturing industries in Moscow from 2017 to 2022 was conducted using the method of multivariate static analysis – the principal component analysis. The proposed analysis tool and system of innovation indicators are based on the concept of multidimensionality, which allowed us to avoid limitations when evaluating indicators and consider the variety of factors affecting innovation potential. This approach also allowed us to identify key interdependencies between determining factors, which manifest themselves according to the “assessment-results-development” principle. It should be noted that these relationships are influenced by various factors, leading to the formation of complex, multidimensional, and multifactorial dependencies that are characteristic of the innovative development system. These dependencies manifest themselves as nonlinear effects of dynamically changing factors over time. As a result of this study, key indicators have been identified, both quantitatively and qualitatively. In future research cycles, we will aim to develop indicators for advanced development, with the goal of creating positive economic growth dynamics that will help us stay ahead of market trends. This will involve effectively using innovations and adapting to changes in the innovation ecosystem.
Skurydin et al. (Tue,) studied this question.
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