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Percolation approach to simulation of a sustainable network economy structure

Author

Listed:
  • Mira A. Kantemirova

    (Gorsky State Agrarian University, Russian Federation)

  • Mira A. Kantemirova

    (North Ossetian State Medical Academy, Russian Federation)

  • Zaur L. Dzakoev

    (North Ossetian State University, Russian Federation)

  • Zara R. Alikova

    (North Ossetian State Medical Academy, Russian Federation)

  • Sergei R. Chedgemov

    (North Ossetian State Medical Academy, Russian Federation)

  • Sergei R. Chedgemov

    (North Ossetian State University, Russian Federation)

  • Zarina V. Soskieva

    (North Ossetian State Medical Academy, Russian Federation)

  • Zarina V. Soskieva

    (Gorsky State Agrarian University, Russian Federation)

Abstract

This study is aimed at the application of the percolation theory to simulation of a sustainable network organization of the economy in conditions of high uncertainty of the external environment. The methods for investment and cost recovery efficiency calculation in order to achieve synergy are used in the course of networks formation. The methods of graph theory and one-dimensional percolation are used herein. The conceptual content of the modified percolation approach to the analysis and simulation of network structures is specified. The controlled process of network formation offers the possibility to form the percolation cluster on the basis of minimization of its length (the shortest path). The formation regularities of two types of a percolation cluster (internal and cross-border) as the basis for the creation of the appropriate network structures are revealed. The examples of the applied problems, which study the percolation based on lattice cells (lattice coupling problem), are considered herein. The results of empirical approbation of the proposed approach in the field of services with the description of the algorithm for the networks and a cluster formation are presented. The transition from the random Bernol's percolation (based on random selection of cells) in favor of the correlated percolation is justified.

Suggested Citation

  • Mira A. Kantemirova & Mira A. Kantemirova & Zaur L. Dzakoev & Zara R. Alikova & Sergei R. Chedgemov & Sergei R. Chedgemov & Zarina V. Soskieva & Zarina V. Soskieva, 2018. "Percolation approach to simulation of a sustainable network economy structure," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 5(3), pages 502-513, March.
    • Handle: RePEc:ssi:jouesi:v:5:y:2018:i:3:p:502-513
    DOI: 10.9770/jesi.2018.5.3(7)
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    References listed on IDEAS

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    1. Mahendra Piraveenan & Mikhail Prokopenko & Liaquat Hossain, 2013. "Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-14, January.
    2. Baggio Rodolfo & Sheresheva Marina, 2014. "Network approach in economics and management: The interdisciplinary nature," Working Papers 0011, Moscow State University, Faculty of Economics.
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    Cited by:

    1. Yelena Petrenko & Elena Vechkinzova & Viktor Antonov, 2019. "Transition from the industrial clusters to the smart specialization: a case study," Insights into Regional Development, VsI Entrepreneurship and Sustainability Center, vol. 1(2), pages 118-128, June.
    2. Yelena Petrenko & Elena Vechkinzova & Viktor Antonov, 2019. "Transition from the industrial clusters to the smart specialization: a case study," Post-Print hal-02163010, HAL.

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    More about this item

    Keywords

    percolation; percolation theory; cluster; networks;
    All these keywords.

    JEL classification:

    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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