Izvestiya of Saratov University.

Economics. Management. Law

ISSN 1994-2540 (Print)
ISSN 2542-1956 (Online)


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Language: 
Russian
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Article type: 
Article
UDC: 
51.77+004.9

Modeling the dynamics of regional competitiveness risks

Autors: 
Chernyshova Galina Yuryevna, Saratov State University
Veshneva Irina Vladimirovna, Saratov State University
Rokakh Gleb Evgenievich, Saratov State University
Abstract: 

Introduction. To determine the strategic directions of regional development to increase competitiveness, it is necessary to rely on a systematic analysis of factors and risks, to use modern mathematical modeling tools. To construct dynamic models for assessing the risks of competitiveness, an approach based on the systems of Kolmogorov – Chapman diff erential equations for Markov processes is applied. Theoretical analysis. The article examines the method of applying the logical-probabilistic approach to assessing the risks of regional competitiveness. Empirical analysis. For a comparative assessment of the risks of competitiveness at the stage of preliminary data processing, cluster analysis was applied using a modifi ed k-means method. Based on the hierarchical system of regional competitiveness risks, the system of Kolmogorov – Chapman equations is formed. Dynamic assessment of competitiveness risks was carried out for three basic scenarios. Results. For a selected cluster of 33 Russian regions corresponding to a high level of socio-economic development, predictive estimates of the probabilities of critical events associated with risks of competitiveness were obtained using the example of a separate section. For optimistic, pessimistic and realistic scenarios, numerical assessments of competitiveness risks are obtained for various combinations of critical events. This made it possible to rank the regions by the probability of a decrease in the competitiveness of the regions in the medium term.

Reference: 
  1. Camagni R. On the concept of territorial competitiveness: Sound or misleading? Urban Studies, 2002, vol. 39, pp. 2395–2411.
  2. Bristow G. Critical refl ections on regional competitiveness: Theory, policy and practice. London, Routledge, 2010. 200 p.
  3. Krasnokutskiy P. A., Ugnich E. A., Taranov P. M. Modern Scientifi c and Methodological Approaches to Assessing the Competitiveness of the Region: Application Problems. IOP Conference Series Earth and Environmental Science, 2019, vol. 272, iss. 3, pp. 1755–1315. https://doi.org/10.1088/1755-1315/272/3/032179  
  4. Global Competitiveness Report. Available at: https://www.weforum.org/reports/the-global-competitivenessreport-2020  (accessed 8 November 2021).
  5. The EU Regional Competitiveness Index 2016. Available at: https://ec.europa.eu/regional_policy/sources/docgener/work/201701_regional_competitiveness2016.pdf  (accessed 8 September 2021).
  6. European innovation scoreboard. Available at: https://ec.europa.eu/growth/industry/innovation/facts-figures/scoreboards_e  (accessed 8 September 2021).
  7. Regional innovation scoreboard. Available at: https://ec.europa.eu/growth/industry/innovation/facts-figures/regional_en (accessed 6 September 2021).
  8. AV RCI. Available at: https://av-group.ru/2020/1808/  (accessed 13 October 2021) (in Russian).
  9. Rezchikov A. F., Kushnikov V. A., Jandybaeva N. V. Model for assessing the state of national security in Russia based on the theory of system dynamics. Applied Informatics. 2017, vol. 12, no. 2 (68), pp. 106–117 (in Russian).
  10. Jandybaeva N. V., Kushnikov V. A., Rezchikov A. F., Ivashchenko V. A. Development of an invariant mathematical model for predicting national security indicators of states. Upravlenie razvitiem krupnomasshtabnykh sistem: materialy 12-i Mezhdunarodnoi konferentsii (MLSD’2019, Moskva) [Management of the development of large-scale systems: Proceedings of the twelfth international conference (MLSD’2019, Moscow)]. Moscow, Institut problem upravleniya imeni V. A. Trapeznikov RAN Publ., 2019, pp. 433–436 (in Russian).
  11. Veshneva I., Chernyshova G., Bolshakov A. Regional Competitiveness Research Based on Digital Models Using Kolmogorov – Chapman Equations. In: Kravets A. G., Bolshakov A. A., Shcherbakov M., eds. Society 5.0: Cyberspace for Advanced Human-Centered Society. Studies in Systems, Decision and Control, vol. 333. Cham, Springer, pp. 141–154. https://doi.org/10.1007/978-3-030-63563-3_12  
  12. Ketels C. Recent research on competitiveness and clusters: What are the implications for regional policy? Cambridge Journal of Regions, Economy and Society, 2013, vol. 6, iss. 2, pp. 269–284.
  13. Inshakov O. V. “Development nucleus” in the light of the new factors of production theory. Economic of Contemporary Russia, 2003, no. 1, pp. 11–25 (in Russian).
  14. Veshneva I., Chernyshova G. The scenario modeling of regional competitiveness risks based on the Chapman – Kolmogorov equations. Journal of Physics: Conference Series, 2021, vol. 1784, pp. 012008.
  15. Rosstat. Ofi tsial’naia statistika (Rosstat. Offi cial statistics). Available at: https://rosstat.gov.ru/folder/210/document/13204  (accessed 9 October 2021) (in Russian).
  16. Informatsionno-analiticheskaya sistema FIRA PRO (Information and analytical system FIRA PRO). Available at: https://fira.ru/  (accessed 7 December 2020) (in Russian).
  17. Elkan C. Using the triangle inequality to accelerate kmeans. Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003). Washington DC, 2003, pp. 147–153.
Received: 
20.10.2021
Accepted: 
06.12.2021