Influence of Human Capital on Innovative Development of Regions

  • M. V. DubovikEmail author
  • R. V. Gubarev
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 139)


Stronger differentiation of the RF regions in terms of the innovative development level is largely determined by “weak” human capital. Clustering of regions and forecasting of their innovative development in the mid-term perspective (using the method of self-organizing maps) is carried out on the basis of neural simulation by way of forming an adequate Bayesian assembly of dynamic neural networks. As a result of the conducted empirical research, it was found that nowadays polarization of Russian regions according to the innovative development level is characteristic. Among the factors hampering innovative development, the following hold a special place: human capital components, education of different levels, health care, social stratification of the society, and stronger differentiation of incomes. The process of transforming a triple helix of innovations into a quadruple one is going on abroad; it involves interaction of not only the state, science, business community, but the civil society of the country, as well. As a result of the conducted empirical study, it was found that certain positive changes in the cluster structure of the country’s regions took place over the years of 2014–2015, in particular, the number of outsider regions regarding the level of innovative development decreased. At the same time, the results of forecasting in the mid-term perspective speak for a certain slowdown in innovative development of such leading regions as Moscow and St.-Petersburg. It was also established, that, e.g., the Republic of Bashkortostan, having a significantly high potential of innovative development, realizes it poorly because of the low quality of human capital.


Human capital Innovative development of regions Quadruple helix and triple helix of innovations 



The article was written with the financial support from the grant of the Russian Foundation for Basic Research 18-010-00461 “Neural Simulation of Evaluating Innovative Development of Russian Regions”.


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Authors and Affiliations

  1. 1.Plekhanov Russian University of EconomicsMoscowRussia

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