Russian regions scientific and technological security monitoring: multi-criteria analysis

The article continues works series devoted to Russian regions’ scientific and technological security monitoring. We’ve developed and verified an approach to Federation’s subjects scientific and technical security multi-criteria assessment. This approach is based Two methods are basic for this specific approach: regions’ Pareto efficiency ranking and its hierarchical cluster analysis. The proposed tools are aimed at information analysis and processing processes improvement during decision-making. It is also instruments for country’s regions scientific and technological security monitoring. Presented methods verification results made it possible to draw a conclusion about regions’ significant stratification in terms of scientific and technological security level. As a multi-criteria assessment part, it was found that in the considered dynamic range, regions generally retain their positions, and Federation subjects transitions within the ranks are insignificant. Should be noted that there is a tendency to ranks equalization and their total number reduce. Meanwhile, hierarchical clustering made it possible to divide country’s regions totality into two clusters. The first cluster includes subjects with scientific and technological security relatively favorable level. The second one consists of regions with relatively low scientific and technical security indicators values. Presented approach further development regards more detailed indicators analysis indicators changes predictive models construction and cause-and-effect relationships identification.

Keywords: scientific and technological security, multicriteria analysis, Pareto ranking, hierarchical clustering, monitoring.


  1. Mityakov, S. N., Mityakov E. S., Murashova N. A., Ladynin A. I. Russian regions scientific and technological security monitoring: index approach Innovacii [Innovations]. 2022. No. 2 (280). Pp. 33–41. (In Russian)
  2. Pareto, V. Compendium of General Sociology: [tr. from Italian] M.: Gos. un-t Vyssh. shk. jekonomiki [State. Univ. Higher School of Economics], 2007. — 511 p. (In Russian)
  3. Economics and Mathematics Encyclopedic Dictionary/Ch. ed. V. I. Danilov-Danilyan. M.: INFRA-M [INFRA-M], 2003. — 688 p. (In Russian)
  4. Lapaev, D. N. Multi-criteria decision making in economics: monograph. — 2nd ed. — Nizhny Novgorod: NGTU [Nizhny Novgorod: NGTU], 2016. — 281 p.
  5. V. V. Podinovsky, V. D. Nogin, Pareto-optimal solutions for multiobjective problems. — M.: Fizmatlit [Fizmatlit], 2007. — 256 p. (In Russian)
  6. Abramov, V. I., Golovin, O. L., Stolyarov, A. D. Methods of searching for Pareto-optimal solutions for the development of smart cities based on their digital counterparts. Sovremennaja jekonomika: problemy i reshenija [Modern Economics: Problems and Solutions]. — 2021. — No. 9 (141). — pp. 8–15. (In Russian)
  7. Grebennikov, V. G. Application of the method of Pareto-optimal projections to the analysis of the regional structure of the Russian economy. Vestnik MIRBIS [MIRBIS Bulletin]. — 2021. — No. 4 (28). — pp. 52–59. (In Russian)
  8. Donichev, O. A., Mishchenko Z. V., Molchanova O. G. Evaluation of the parameters of the formation of a socio-economic cluster based on the Pareto-optimization method. Jekonomicheskij analiz: teorija i praktika [Economic analysis: theory and practice]. — 2014. — No. 6 (357). — pp. 17–24. (In Russian)
  9. Tryon, R. C. Cluster analysis. — London: Ann Arbor Edwards Bros, 1939. — 139 p.
  10. Lomidze, O. N. Cluster analysis in sociological research. Uchenye zapiski Rossijskogo gosudarstvennogo social’nogo universiteta [Scientific Notes of the Russian State Social University]. — 2011. — No. 9 (97). Part 1. — pp. 38–42. (In Russian)
  11. Zholudeva, V. V., Melnichenko N. F., Kozlov G. E. Application of cluster analysis to assess the socio-economic development of regions on the example of the Central Federal District and the Yaroslavl region. Jekonomika, Statistika i Informatika [Economics, Statistics and Informatics]. — 2014. — No. 1. — p. 144–148.
  12. Degtyareva, T. D., Chulkova E. A., Torbina E. S. Study of the differentiation of social development of rural areas. Izvestija Orenburgskogo gosudarstvennogo agrarnogo universiteta [Proceedings of the Orenburg State Agrarian University]. — 2015. — No. 5. — pp. 212–216. (In Russian)
  13. Modenova, A. A., Yakimov I. M. Cluster analysis of Russian regions in terms of scientific and innovative activity. Nauchnye issledovanija: ot teorii k praktike [Scientific research: from theory to practice]. — 2015. — T. 2. — No. 2 (3). — pp. 69–72. (In Russian)
  14. Shmatko, A. D., Gubin S. V. Cluster analysis of the innovative potential of subjects of the Russian Federation. Upravlencheskoe konsul’tirovanie [Management consulting]. — 2020. — No. 3. — pp. 61–72. (In Russian)
  15. Dmitriev, Y., Fraimovich D., Mishchenko Z. Cluster analysis of innovation activities in the regions of the Central Federal District. Vestnik Instituta jekonomiki Rossijskoj akademii nauk [Institute of Economics of the Russian Academy of Sciences Bulletin]. — 2013. — No. 3. — pp. 79–87. (In Russian)
  16. Kuzmin, V. A., Tokarev K. E. Evaluation of threats to economic security by the method of hierarchical synthesis. Sovremennye problemy nauki i obrazovanija [Modern problems of science and education]. — 2013. — No. 2. — P. 357.
  17. Lapaev, D. N., Mityakov E. S. Methods of multi-criteria assessment of the economic security of Russian regions (on the example of the Volga Federal District). Jekonomika, statistika i informatika. Vestnik UMO [Economics, Statistics and Informatics. UMO Bulletin]. — 2013. — No. 4. — pp. 151–154 (In Russian)
  18. Mityakov, S. N., Mityakov E. S., Murashova N. A., Ladynin A. I. Russian regions scientific and technological security monitoring: conceptual aspects Innovacii [Innovations]. 2022. No. 1 (279). Pp. 58–65. (In Russian)
  19. Zhambyu, M. Hierarchical cluster analysis and correspondences. — M.: Finansy i statistika [Finance and statistics], 1988. — 345 p. (In Russian)
  20. Gichiev, N. S. Cluster analysis in the economy: theoretical aspect Regional’nye problemy preobrazovanija jekonomiki [Regional problems of transformation of the economy]. — 2020. — No. 8 (118). — pp. 176–186. (In Russian)
  21. Classification and cluster. Ed. J. Wen Raizina. M.: Mir [Mir], 1980. 390 p. (In Russian)