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Modeling of the Natural Resources’ Intensive Use Regions’ Innovative Development: Problems of Circumpolar Area Innovative System Formation

  • Taisya Pogodaeva
  • Dmitry RudenkoEmail author
  • Daria Zhaparova
Conference paper
Part of the Eurasian Studies in Business and Economics book series (EBES, volume 4)

Abstract

The ideas of regional innovative development and the role of innovations in promoting economic growth are discussed. This study examines the differentiation and unevenness of regional development as well as a significant imbalance of regional innovation systems in Russia. The regions have been clustered in two directions “the research potential” and “the innovative performance,” which has allowed not only to estimate the stage of innovative development, but also to qualitatively identify existing imbalances in them. The cluster analysis of the Arctic regions has emphasized strong and weak sides and has carried out the typology of regions into some group for stimulation of innovative development and eliminating the narrow places and ensures continuity of the innovation cycle.

Keywords

Circumpolar area Innovative potential Innovative performance Innovations 

Notes

Acknowledgments

The article is prepared on the basis of research carried out with the financial support of the grant RGNF (project №15-32-01350) “Innovative development of the Tyumen region’s circumpolar area: the possibility of localization and the effects of inter-regional cooperation.”

References

  1. Association of Innovative Regions of Russia. (2014). Regional innovation development rating. [pdf] AIRR. Accessed July 1, 2015, from http://ruitc.ru/upload/iblock/84b/reyting_innovatsionnykh-regionov-_sayt_.pdf
  2. Avilova, V. V., Andreev, E. M., Garifiev, I. Z., Zinudova, R. I., & Burganova, L. A. (2013). Regions of Russia: Knowledge society as a condition for implementation of the strategy of modernization. [e-book] Moscow: KNITU. Accessed July 1, 2015, from http://www.directmedia.ru/book_259394_regionyi_rossii_obschestvo_znaniya_kak_uslovie_realizatsii_strategii_modernizatsii_i_innovats/
  3. Balakrishnan, P. V., Cooper, M. C., Jacob, V. S., & Lewis, P. A. (1994). A study of the classification capabilities of neural networks using unsupervised learning: A comparison with K-means clustering. Psychometrika, 59(4), 509–525.CrossRefGoogle Scholar
  4. Capello, R., & Lenzi, C. (2013). Territorial patterns of innovation: A taxonomy of innovative regions in Europe. The Annals of Regional Science, 51(1), 119–154.CrossRefGoogle Scholar
  5. Clarysse, B., & Muldur, U. (1999). Regional cohesion in Europe? An analysis of how EU public RTD support influences the techno-economic regional landscape. [pdf] European Commission. Accessed July 1, 2015, from ftp://ftp.cordis.europa.eu/pub/indicators/docs/ind_wp_um1.pdf
  6. De Bruijn, P., & Lagendijk, A. (2005). Regional innovation systems in the Lisbon strategy. European Planning Studies, 13(8), 1153–1172.CrossRefGoogle Scholar
  7. Florida, R. (2007). The rise of the creative class: And how it’s transforming work, leisure, community and everyday life. Moscow: Classica XXI.Google Scholar
  8. Furman, J. L., Porter, M. E., & Stern, S. (2002). The determinants of national innovative capacity. Research Policy, 31(6), 899–933.CrossRefGoogle Scholar
  9. Gokhberg, L. (Eds.). (2014). Regional innovation development rating: Analytical report. [pdf] Moscow: National Research University—Higher School of Economics (HSE). Accessed July 1, 2015, from http://cluster.hse.ru/doc/Innovation%20in%20the%20RF%20regions.2nd%20edition.pdf
  10. Gusev, A. B. (2009). Rating the innovative development of the Russian regions. [online] Kapital-rus. Accessed July 1, 2015, from http://www.kapital-rus.ru/articles/article/2574
  11. Hollanders, H. (2006). European regional innovation scoreboard 2006. [pdf] UNU-MERIT. Accessed July 1, 2015, from http://digitalarchive.maastrichtuniversity.nl/fedora/get/guid:a2baed37-ee71-41aa-b40c-eaea7eafc7e2/ASSET1
  12. Kozyrev, V. V. (2007). On the mechanism of the program of innovative development of the Russian Federation implementation (from the perspective of scientific and technical staff’s experience). Innovations, 3, 17–26.Google Scholar
  13. Medvedev, V. S., & Potemkin, V. G. (Eds.). (2002). Neuron nets. Matlab 6. Moscow: DIALOGMIFI.Google Scholar
  14. Murtagh, F. (1996). Neural networks for clustering. In P. Arabie, L. Hubert, & G. De Soete (Eds.), Clustering and classification (pp. 235–269). Singapore: World Scientific.CrossRefGoogle Scholar
  15. Navarro M, Gibaja J. J., Aguado R., & Bilbao-Osorio B. (2008). Patterns of innovation in the EU-25 regions: A typology and policy recommendations. [pdf] European Commission. Accessed July 1, 2015, from http://www.orkestra.deusto.es/images/publicaciones/archivos/000283_WPS2008-04_English_version.pdf
  16. Pogodaeva, T., Zhaparova, D., Ruenko, D., & Skripnjuk, D. (2015). Innovations and socio-economic development: Problems of the natural resources intensive use regions. Mediterranean Journal of Social Sciences, 6(1), 129–135.Google Scholar
  17. Russian Federation Federal State Statistics Office. (2015). Regions of Russia: Economic and social indicators. [online] FSSO. Accessed July 1, 2015, from http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156
  18. Wintjes, R. & Hollanders, H. (2010). The regional impact of technological change in 2020. Synthesis report. [pdf] UNU-MERIT. Accessed July 1, 2015, from http://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/2010_technological_change.pdf

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Taisya Pogodaeva
    • 1
  • Dmitry Rudenko
    • 1
    Email author
  • Daria Zhaparova
    • 1
  1. 1.Department of International Economics and BusinessTyumen State UniversityTyumenRussia

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