Spatial Patterns of Innovation Geography: Knowledge Generation Domain in Russia

The study is designed to capture the patterns in the spatial distribution of knowledgegeneration domain in the Russian Federation. The main objective of the paper is to assess thelevel of regional divergence in the context of the knowledge economy and to evaluate theintegration of public higher education institutions (HEIs) into regional innovation systems. Design/methodology/approach: The study is based on quantitative and qualitative analyses ofstatistical data of the National university ranking and the Russian cluster observatory project.The HEIs are clustered into quartiles by the aggregate score acquired in the ranking and groupedby regions. Knowledge capital of regions is compared to industry clusters. Findings: Results confirm a significant accumulation of knowledge capital in the two majorcities of the country – Moscow and Saint-Petersburg, both in terms of quantity and quality.With that, all major urban agglomerations feature HEIs in the ranking. Some regions activelyinvolve HEIs in collaboration with industry, while others are not despite similar focus. Research/practical implications: Publicly funded HEIs are a major resource of regionalauthorities to strategize on innovation development. Awareness of complementarities andinvolvement of knowledge-generating institutions and industry clusters enables to grasp theactual status of the regional innovation system, and enable adaptive policy measures. Originality/value: This is the first empirical study in the context of Russia that uses the dataon quality assessment of national HEIs form the knowledge geography perspective.Universities are considered as the contributors to the knowledge capital of regional innovationsystems, while the methodological approach applied enables to evaluate their potential andactual inclusion in collaboration with industry clusters.