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Conficuration of enterprise networks

Author

Listed:
  • Aleksandr M. Batkovskiy

    (JSC "Central Research Institute of Economy Management and Information Systems "Electronics", Russian Federation)

  • Pavel A. Kalachikhin

    (All-Russian Institute of Scientific and Technical Information (VINITI), Russian Federation)

  • Elena G. Semenova

    (Saint Petersburg State University of Aerospace Instrumentation, Russian Federation)

  • Yury F. Telnov

    (Plekhanov Russian University of Economics, Russian Federation)

  • Alena V. Fomina

    (JSC "Central Research Institute of Economy Management and Information Systems "Electronics", Russian Federation)

  • Viktor M. Balashov

    (Scientific and Production Enterprise "Radar MMS", Russian Federation)

Abstract

In the study, we consider the methods for optimizing the configuration of the network structure of enterprises based on the theory of fuzzy sets. These methods allow customizing the value chain in such a way as to maximize the likelihood of the success of a joint project to create innovative products. A strategic decision to change the configuration of the network structure is made based on an analysis of deviations of the generalized capabilities from the generalized requirements for the enterprise and its closest neighbors along the value chain. This optimization principle allows changing the configuration, taking into account the interests of participants in the network structure as a whole. We have formulated the task of developing tools for enterprise engineering based on intelligent decision support technologies and multi-agent systems. The approach to justifying decisions in the conditions of lack and incompleteness of the initial data on the basis of soft models is an alternative to existing traditional methods. The proposed network structure optimization model will allow effective strategic planning, supporting flexible management mechanisms at the strategic and operational levels. The research results show that it is possible to improve the efficiency of interaction between enterprises united by common goals by using services that allow enterprises to find information about their potential partners.

Suggested Citation

  • Aleksandr M. Batkovskiy & Pavel A. Kalachikhin & Elena G. Semenova & Yury F. Telnov & Alena V. Fomina & Viktor M. Balashov, 2018. "Conficuration of enterprise networks," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(1), pages 311-328, September.
    • Handle: RePEc:ssi:jouesi:v:6:y:2018:i:1:p:311-328
    DOI: 10.9770/jesi.2018.6.1(19)
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    References listed on IDEAS

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    Cited by:

    1. O. Karasev & A.V. Beloshitsky & S.S. Trostyansky & A.O. Krivtsova, 2018. "National Innovation Systems: A Case Study of the Leading Developing Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 713-723.
    2. Viacheslav B. Dziundziuk & Oleksandr A. Kotukov & Dmytro V. Hryn & Eugene V. Kotukh, 2020. "Spread of virtual communities as a potential threat to state security and sustainable well-being," RIVISTA DI STUDI SULLA SOSTENIBILITA', FrancoAngeli Editore, vol. 0(2 suppl.), pages 7-18.

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    More about this item

    Keywords

    business model; network structure; value chain; key competencies; clusters; technology transfer;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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