An assessment of regional innovation system efficiency in Russia: the application of the DEA approach

Stepan Zemtsov and Maxim Kotsemir

Scientometrics, 2019, vol. 120, issue 2, No 2, 375-404

Abstract: Abstract The main aim of this study is to compare Russian regions according to their ability to create new technologies efficiently and to identify factors that determine these differences over a long period of time. We apply data envelopment analysis (DEA) to assess the relationship between the results of patenting and resources of a regional innovation system (RIS). Unlike previous studies, we apply the DEA method over a long period, comparing regions to one another and over time. In general, RIS efficiency in Russia increased during the period, especially in the least developed territories. There was significant regional differentiation. The most efficient RIS were formed in the largest agglomerations with leading universities and research centers: the cities Moscow and Saint Petersburg and the Novosibirsk, Voronezh, and Tomsk regions. Econometric calculations show that RIS efficiency was higher in technologically more developed regions with the oldest universities and larger patent stock. Time is a crucial factor for knowledge accumulation and creating links between innovative agents within RIS. Entrepreneurial activity was also a significant factor because it helps to convert ideas and research into inventions and new technologies and it enhances the interaction between innovative agents. It is advantageous to be located near major innovation centres because of more intensive interregional knowledge spillovers. Public support of more efficient regions can lead to a more productive regional innovation policy.

Keywords: Patent activity; Regional innovation systems; Russian regions; Data envelopment analysis; DEA; R&D expenditures; Human capital (search for similar items in EconPapers)
JEL-codes: O30 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-019-03130-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:120:y:2019:i:2:d:10.1007_s11192-019-03130-y

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-019-03130-y

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().