Innovative development of regions is a key factor that determines the level of competitiveness of the economies of all countries in the world. This article uses statistical tools to assess the level of innovative development of the regions of the Russian Federation. The purpose of the work is to assess the innovative development of the subjects of Russia for the period 2010–2020. Objectives of the study: (1) to study the main parameters of innovative development of the subjects of the Russian Federation; (2) to conduct a typology of Russian regions by the level of innovative development on the basis of cluster analysis. The selected time interval (2010–2020) was a period of increasing turbulent flows of development of socio-economic processes at the global, national and regional levels. Cluster analysis was used to identify spatial and functional features of innovative development of Russian regions. The obtained analytical calculations confirm a high degree of differentiation between the Russian regions by all key indicators of innovative development. The results of grouping regions on the basis of cluster analysis showed that there are four clusters based on the sum of normalized indicators, reflecting different levels of innovative development in Russian regions. The analysis revealed that most of the regions belong to the groups with moderate and low levels of innovative development. The regions of the Central and Volga Federal Districts have the highest level of innovative development, while the regions located in the north of the European part of Russia, the North Caucasus, the south of eastern Siberia and the Far East, as well as “new” regions, have a low level. The results of the study can be implemented by regional authorities for systematic monitoring of the level of innovative development of regions, making managerial decisions and developing mechanisms to ensure innovation activity in the regions.

The formation of a unified innovation space is a key challenge for deepening Eurasian integration. This study aims to develop the concept of asymmetric complementarity by investigating how the structural asymmetry between the NIS of Russia and Kazakhstan can be transformed from a source of imbalance into a basis for strategic synergy. Based on a mixed methodology that includes quantitative analysis of data from the Global Innovation Index (GII) 2025, SWOT analysis, and scenario modeling, two divergent models were identified. Russia’s NIS is defined as “compensatory disbalanced” (strong human capital with weak institutions), while Kazakhstan’s NIS is defined as “institutionally focused with knowledge deficit” (relatively developed institutions with critically low R&D investment). The theoretical contribution of this work lies in developing the concept of asymmetric complementarity, which demonstrates that the identified structural differences create a foundation for synergistic cooperation. The practical conclusions are aimed at transitioning from rule harmonization to network capability integration, including the creation of distributed excellence centers, the development of “soft” type supranational infrastructure, and the implementation of the “innovative accounting” principle.

The impact of advanced production clusters and integrated large markets on regional economic development under conditions of accelerated globalisation and transformation of technological and economic processes has been comprehensively analysed. Clusters are presented as geographically localised systems of interconnected interaction between enterprises, research organisations and educational institutions involved in cooperation and competition, which contributes to the generation and diffusion of innovations, productivity growth and strengthening of regional competitiveness. The theoretical basis of the research is the concepts of clusters developed by Michael Porter, which considers geographically concentrated structures as key elements in achieving sustainable competitive advantages. The role of clusters in the effect of intersectoral integration, efficiency of resource allocation and intensification of technological processes through the realisation of synergetic potential has been revealed. In addition, attention is paid to the function of integrated markets in removing barriers to the flow of factors of production and goods, which significantly increases the efficiency of regional economic systems. Despite the significant achievements of the cluster approach, the authors emphasise the insufficient study of a number of aspects of interaction between cluster structures and integrated markets, as well as the complex effects arising on their basis. The findings are significant for further study of regional competitiveness, economic integration and long-term sustainability of territorial socio-economic development.

In the current conditions of economic development, the formation of innovative sectoral development is provided on the basis of the global implementation of human capital. In the situation of economic crises due to the instability of the external environment, human capital is the only source and resource for innovative changes in economic processes. Therefore, we propose to consider the indicator "human capital" as the basis for major innovative changes in the growth of modern Russian economy, which has been investigated in this article. The actualization of modern innovation policy, which includes guidelines for the development of the Russian Federation towards an innovation-technologically developed path, has determined the particular importance of the "human capital" indicator. The authors have highlighted the methodology for investigating the synergy of these research aspects. In the paper a conclusion is drawn, that taking into account imperfection of existing conceptual positions concerning a role and value of the human capital in the course of forming of innovative branch development for the purpose of increase of innovative activity of all participants of branch economic system and maintenance of influence on intensive development of branches and complexes, it is necessary to provide objective revision of traditional approaches of branch development research. The given research will allow increasing innovative activity of all participants of branch industrial-economic system. At the same time, human potential acts as the main driving force and asset of ensuring sustainable and intensive sectoral development, determines the opportunities of sectoral production and economic systems for the formation of diversification directions The structural and logical scheme of ensuring innovative sectoral development, which includes the stages of innovative development, such as the stage of forming prerequisites for innovative sectoral development, the stage of realization of human potential in the industry, the stage of realization of aggregate.

Background. In modern conditions the economic success of regional development is determined by the speed of managerial responses to changes and challenges in the external environment. The purpose of the study was to develop an algorithm for classifying socio-economic systems according to the level of management of innovation potential of the regions, as part of the long-term objectives of building a competitive economy, which is an important factor in achieving technological sovereignty of the country. Materials and methods. When compiling the dataset of actual values of the integral level of performance of the tools of management of innovation potential of socio-economic mesosystems the analytics of Leontief Centre – AV Group Consortium (LC-AV), based on the data of Rosstat version 2022 on the data of 2020–2021 was used. The article applied methods of univariate clustering based on the Fisher algorithm, hierarchical cluster analysis, k-means clustering, fuzzy clustering. Euclidean distance was used to assess dissimilarity, Ward's method of agglomeration was used, centring was not performed, truncation was determined based on the adapted Hartigan index. Results. An 8-stage process of selecting an effective data clustering algorithm is proposed for application. Identification of 85 socioeconomic mesosystems of the Russian Federation using the author's methodology of classification by the level of innovation potential management is carried out. Conclusions. In the matrix of balanced scientific and technological development the influence of innovation potential management factors on five groups of socio-economic mesosystems clusters (strong, medium-strong, medium, medium-weak and weak innovators) was investigated, which will give further opportunity to develop managerial decisions regarding the development of differentiated strategies and policies adapted to the needs and characteristics of each mesosystem in order to improve competitiveness, technological sovereignty and quality of life.