JOURNAL OF REGIONAL AND INTERNATIONAL COMPETITIVENESS JOURNAL OF REGIONAL AND INTERNATIONAL COMPETITIVENESS Журнал региональной и международной конкурентоспособности 2782-1927 84136 REGIONS COMPETITIVENESS REGIONS COMPETITIVENESS REGIONS COMPETITIVENESS Spatial and functional localisation of innovation development in Russian regions: analysis and forecast Spatial and functional localisation of innovation development in Russian regions: analysis and forecast https://orcid.org/0000-0002-9013-6141 Кособуцкая Анна Юрьевна Kosobuckaya Anna Yur'evna anna.rodnina@mail.ru

доктор экономических наук;

doctor of economic sciences;

 https://orcid.org/0000-0002-0039-5060 Трещевский Юрий Игоревич Treschevskiy Yuriy Igorevich utreshevski@yandex.ru

доктор экономических наук;

doctor of economic sciences;

 Воронежский государственный университет Voronezh RU Voronezh State University Voronezh RU 16 06 2024 16 06 2024 3 4 34 44 03 10 2022 21 11 2022 https://chemintech.ru/en/nauka/article/84136/view

Purpose: To identify features of spatial and functional localization of innovation activity of Russian regions, it is necessary to forecast its dynamics, development, and justification of directions and tools of regional innovation policy in the medium term. Research methods: comparative analysis; structuring of the information dataset – virtual clustering method; correlation and regression analysis. Results: we have proposed five indicators characterizing spatial and functional localization of regional innovation development. On the base of them, we formed virtual clusters, including regions with similar values of the parameters under study. We identified the closest representative region to its center for each cluster. Also we used the example of the Yaroslavl Region (region-representative of cluster B) to identify trends by the studied indicators and draw conclusions about the region’s forecasting and development prospects in terms of the basic parameters of innovative development.

Purpose: To identify features of spatial and functional localization of innovation activity of Russian regions, it is necessary to forecast its dynamics, development, and justification of directions and tools of regional innovation policy in the medium term. Research methods: comparative analysis; structuring of the information dataset – virtual clustering method; correlation and regression analysis. Results: we have proposed five indicators characterizing spatial and functional localization of regional innovation development. On the base of them, we formed virtual clusters, including regions with similar values of the parameters under study. We identified the closest representative region to its center for each cluster. Also we used the example of the Yaroslavl Region (region-representative of cluster B) to identify trends by the studied indicators and draw conclusions about the region’s forecasting and development prospects in terms of the basic parameters of innovative development.

 cluster analysis k-means method virtual clusters Russian regions innovation development representative regions trends.

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