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Agent modelling of cluster formation processes in regional economic systems

Author

Listed:
  • Boush, G. D.
  • Kulikova, О. Ðœ.
  • Shelkov, I. К.

Abstract

The subject matter of this research is the processes of the spontaneous clustering in the regional economy. The purpose is the development and approbation of the modeling algorithm of these processes. The hypothesis: the processes of spontaneous clustering in the social and economic environment are supposed to proceed not linearly, but intermittently. The following methods are applied: agent imitating modeling with an application of FOREL and k-means algorithms. The modeling algorithm is realized in the Python 3 programming language. The course regularities of clustering processes in the region are revealed: 1) the clustering processes are intensifying, the production uniformity is increasing; 2) the increase of the level of production uniformity leads to the leveling of customer behavior; 3) the producers of high-differentiated production reduce the level of its differentiation or leave the cluster; 4) the stages of steady functioning are illustrative for clustering processes, their change is followed with arising of bifurcation points; 5) the activation of clustering processes in regional economy leads to the revenue increase of the cluster participants, each of producers and of consumers, and to the growth of synergetic effect values. These results testify the nonlinearity of processes of clustering and ambiguity of their effects. The following conclusions have been drawn: 1) a modeling of the processes of spontaneous clustering in regional economy has showed that they proceed not linearly, a steady progressive development is followed with leaps; 2) the clustering of regional economy leads to the growth of the efficiency indicators of activities of cluster-concerned entities; 3) initiation and activation of the clustering processes requires a certain environment.

Suggested Citation

  • Boush, G. D. & Kulikova, О. Ðœ. & Shelkov, I. К., 2016. "Agent modelling of cluster formation processes in regional economic systems," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 2(1), pages 89-101.
    • Handle: RePEc:aiy:journl:v:2:y:2016:i:1:p:89-101
    DOI: 10.15826/recon.2016.2.1.008
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    References listed on IDEAS

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    1. Giuseppe Arbia & Giuseppe Espa & Danny Quah, 2009. "A class of spatial econometric methods in the empirical analysis of clusters of firms in the space," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 81-103, Springer.
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    Cited by:

    1. Vladimir Kolmakov & Aleksandra Polyakova & Svetlana Karpova & Alla Golovina, 2019. "Cluster Development Based on Competitive Specialization of Regions," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(1), pages 270-284.
    2. Nina I. LARIONOVA & Tatyana V. YALYALIEVA & Dmitry L. NAPOLSKIKH, 2018. "Global Competitiveness, Neoindustrialization And Innovative Clusters: International Indicators And Trends Of Russian Federation," Revista Galega de Economía, University of Santiago de Compostela. Faculty of Economics and Business., vol. 27(2), pages 125-138.
    3. Shamis, V. A. & Kulikova, O. M. & Neiman, S. Y. & Usacheva, E. V., 2017. "Agent modeling of advertising impact on the regional economic cluster lifecycle," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 3(4), pages 203-212.
    4. Viktoria V. Akberdina & Andrey I. Volodin & Roman V. Gubarev & Evgeniy I. Dzyuba & Fanil’ S. Fayzullin, 2020. "Models of public investment management at regional level," Upravlenets, Ural State University of Economics, vol. 11(1), pages 45-56, March.

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