Izvestiya of Saratov University.

Economics. Management. Law

ISSN 1994-2540 (Print)
ISSN 2542-1956 (Online)
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Language: 
Russian
Heading: 
Management
Article type: 
Article
UDC: 
51.77+004.9
DOI: 
10.18500/1994-2540-2022-22-1-42-52

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.

Key words: 
competitiveness
regions of the Russian Federation
risks
mathematical modeling
clustering
Kolmogorov – Chapman equations
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Received: 
20.10.2021
Accepted: 
06.12.2021