2024 Vol. 16 №2

Contemporary Russia’s spatial development is markedly affected by profound geoeconomic and geopolitical shifts, progressively more visible in terms of magnitude and repercussions. For Russia, the positive impact of these changes has become increasingly linked to the emergence of the Greater Eurasia macro-structure. This article aims to develop a contemporary conceptual approach to Greater Eurasia as a socio-geographical mega-structure given Russia’s oppo­sition to the collective West. Additionally, it seeks to identify, using this approach, the strate­gic interests, opportunities and limitations of Russia’s spatial dynamics on the path towards Eurasian continentalism, which promotes transboundary cooperation and mutually supportive co-development of Eurasian states. The focus of this contribution is on the most crucial con­temporary trends and principal contradictions in the transformation of the Russian space. The study provides a picture of the framework of ‘greater’ Eurasian integration, emphasising its connection to intensifying interregional and inter-municipal interactions. A rationale is out­lined for shifting the country’s economic activity towards the east and north, with priorities identified given the inertia of spatial processes and the growing significance of Siberia in the Russian space. The potential and efficiency of prolonging the ‘Moscow-centric’ arrangement of the Russian space are assessed from the perspective of ensuring the multidirectional develop­ment of the latter. Special attention is paid to the ‘municipalisation’ of approaches to the strate­gic planning of Russia’s spatial development in the context of Eurasian continental integration.

A modern innovative economy relies on the continual integration of knowledge and tech­nologies into production, monitoring, and management processes. Therefore, territorial proximity and sectoral complementarity of the activities of scientific, technological and industrial organisations are crucial factors in fostering innovation. This article aims to assess the relationship between a region’s economic and scientific specialisation and the level of its innovative development. The object of the study is the industrial and research profile of Russian regions’ economies with a focus on the strength of connections between them. We identified and measured Russian regions’ industry-specific research, technolog­ical and economic specialisations. Additionally, we described the spatial and structural patterns of interregional distribution and concentration of research, technological and in­novative activities. Methodologically, we compared data on the product output by industry, using the OKVED classification subgroups and information on the costs and implemen­tation of R&D. To gather the latter data, we employed our methodology, which involved juxtaposing GRNTI and OKVED codes. Overall, we analysed data from 17.3 thousand re­search, development and technological projects conducted between 2017 and 2021 across 18 fields. Specialisation coefficients for both the supply and demand of R&D outcomes and production were computed for each region. The econometric analysis made it possible to distinguish four clusters of regions based on their research and industrial specialisation: agro-industrial regions, mechanical engineering regions, precision engineering regions and diversified regions. The study demonstrated a correlation between a region’s innova­tive product output and the structure of its innovative economy.

The suburban area of St. Petersburg stands out as Russia’s most complex in terms of spatial structure, encompassing districts ranging from the suburban imperial residences of the 18th century to low-rise residential zones and modern multi-storey developments of the 21st century. This study concluded that extensive stretches of the administrative border between St. Petersburg and the Leningrad region divide homogeneous territories. Therefore, it makes little academic or practical sense to confine scholarly efforts solely to suburbs situated on one side of this border. The principal factor in delineating the St. Petersburg urban area is the transport accessibility of territories surrounding the city. It was empirically determined that the inner boundary of the suburban area is located approximately within the 40—45-minute isochrone from the city centre, while the outer boundary extends to the 2-hour isochrone. In the conditions of today’s St. Petersburg, a two-hour isochrone corresponds to a 60 km distance. Along with isochrones, the actual boundary of the suburban area is determined by several natural and anthropogenic factors.

In terms of the natural environment, a significant part of the St. Petersburg suburban area is anthropogenic forest-steppe, whose landscapes are radically different from those of the area’s natural southern taiga subzone. The features of the ‘forest steppe’ reach their peak to the southwest and south of St. Petersburg. To the north of the city, the suburban zone is defined by both ‘anthropogenic forest-steppe’ and secondary small-leaved forests that have replaced agricultural lands. Another prominent feature is parks found on the premises of former estates where introduced woody species account for a substantial portion of vegetation. The spatial structure of the suburban area north of St. Petersburg is complicated by large extents of unpopulated areas. Since the 19th century, they have divided the area into two virtually disconnected parts.

This article aims to identify the determinants of the development of national innovation systems in the globalised world and to carry out a cluster analysis of innovation systems of the South Caucasus and Baltic States. To this end, an Innovation System Development Index (ISDI) comprising 46 indicators was developed. The authors employed the macro-clustering method, as well as aggregation and combination techniques for parameters and sub-indices. Additionally, complete-linkage and K-means methods were used to group the countries. Kalinsky-Kharabaz and Duda-Hart indices, as well as dendrograms, were found to be the most effective techniques for producing the novel classification proposed in this contribution. It was demonstrated using the former method that national innovation systems exhibit qualitatively different cluster characteristics and follow different development trends. According to the findings, Estonia ranks first on the index among the study countries with (ISDI = 0.77), while the South Caucasus states form two subgroups. Armenia (ISDI = 0.50) and Georgia (ISDI = 0.53) comprise a relatively developed subgroup, whereas Azerbaijan (ISDI = 0.44) constitutes a separate unit, delivering a less remarkable performance. The latter method revealed that the Baltic States form the most developed cluster group, with Estonia once again at the top of the index (ISDI = 0.85). The Baltic States and the South Caucasus states comprised two separate groups. Except for the patent activity sub-index, Estonia outperforms the other study countries on all sub-indices. Armenia and Georgia rank relatively high on the patent activity sub-index, whereas Azerbaijan performs well on the innovation activity and infrastructural development sub-indices. These findings would allow the South Caucasus countries to draw on the experience of the Baltic states in identifying challenges to the development of their national innovation systems. Overall, the study demonstrated the possibility of classifying the countries of the two post-Soviet regions based on the similarity of national innovation systems.