Analysis of Russian Regions Innovative Competitiveness Dynamics Using Fuzzy Methods

Chernyshova, Galina; Piunova, Ekaterina; Veshneva, I.V.

doi:10.1007/978-3-030-95112-2_10

Cited by 3 publications

(2 citation statements)

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“…The choice of metric when ranking alternatives is essential to this approach. The proposed ranking algorithm uses various metrics (Euclidean, Hamming, Manhattan, Hausdorff, Bray-Curtis, Tanimoto-Jaccard, Zhuravlev) [37]. The final rating is based on the results obtained for individual metrics.…”

Section: Applying Multi-criteria Evaluation Methods Fuzzy Electre IImentioning

confidence: 99%

“…An empirical analysis of the development of Italian regions for the period of 1952-1995 was carried out using the Markov chain approach [34]. Approaches, methods, and algorithms using the concept of Markov models for assessing the risks of loss of competitiveness with various scenarios in the example of Russian regions have been further developed [35][36][37].…”

Section: Introductionmentioning

confidence: 99%

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Methodology for Assessing the Risks of Regional Competitiveness Based on the Kolmogorov–Chapman Equations

Chernyshova,

Veshneva,

Firsova

et al. 2023

Mathematics

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The relevance of research on competitiveness at the meso level is related to the contemporary views of a region as an essential element of the economic space. The development of forecasting and analytical methods at the regional level of the economy is a key task in the process of strategic decision making. This article proposes a method of quantitative assessment of the risks of regional competitiveness. The novelty of this approach is based on both a fixed-point risk assessment and scenario-based predictive analysis. A hierarchical structure of indicators of competitiveness of regions is offered. A method based on the Kolmogorov–Chapman equations was used for the predictive estimation of risks of regional competitiveness. The integrated risk assessment is performed using the modified fuzzy ELECTRE II method. A web application has been implemented to assess the risks of competitiveness of Russian regions. The functionality of this application provides the use of multi-criteria decision-making methods based on a fuzzy logic approach to estimate risks at a specified time, calculating the probability of risk events and their combinations in the following periods and visualizing the results. Approbation of the technique was carried out for 78 Russian regions for various scenarios. The analysis of the results obtained provides an opportunity to identify the riskiest factors of regional competitiveness and to distinguish regions with different risk levels.

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Section: Applying Multi-criteria Evaluation Methods Fuzzy Electre IImentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%