Journal section "Reviews"

Investigating the Approaches to National Innovation Systems Modeling

Volchik V.V., Maslyukova E.V., Panteeva S.A.

Volume 14, Issue 5, 2021

Volchik V.V., Maslyukova E.V., Panteeva S.A. Investigating the approaches to national innovation systems modeling. Economic and Social Changes: Facts, Trends, Forecast, 2021, vol. 14, no. 5, pp. 135–150. DOI: 10.15838/esc.2021.5.77.8

DOI: 10.15838/esc.2021.5.77.8

Abstract   |   Authors   |   References
The article analyzes some modern approaches to modeling national innovation systems that are presented in scientific literature. We use modern methods for analyzing bibliography and preparing literature reviews: co-occurrence, and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) method. With the help of this approach we conduct relational analysis of documents by systematizing and arranging keywords into special semantic clusters that reflect interest in modeling national innovation systems. The research focuses on mathematical models of national innovation systems and models that use empirical quantitative data analyzed with the help of various econometric methods based on the Russian specifics of economic development. In this regard, when searching for and analyzing relevant sources, we used the filters “Russian innovation system”, “national innovation system and Russia”. We have revealed that the majority of publications focuses on such aspects as digitalization, neo-industrialization, innovation policy and technology. We identify four directions for modeling national innovation systems: macroeconomic modeling of innovation systems, modeling of growth based on the development of innovation systems, modeling of innovative activity of firms, modeling of institutional factors contributing to the development of innovation systems. The national innovation system is modeled mainly through the use of indicators related to patenting, the volume of exports and the production of innovations. Factors determining the development of national innovation systems in this context include R&D and innovation expenses, investment in technology, education, infrastructure, human resources and the quality of human capital. Conclusions on the analyzed models often do not coincide regarding the role of the state in financing innovations, the role of various elements of the institutional structure of the economy, such as intellectual property rights and mechanisms for their protection, as well as the role of political factors. On the other hand, the conclusions are consistent in terms of the impact of innovation on economic growth and development: we note a positive correlation with indicators reflecting the development of national innovation systems


innovation, economic growth, economic policy, institutional structure, national innovation system, Russian innovation system

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