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  • 标题:Determining the potential of organizational structures models of a high-tech cluster
  • 本地全文:下载
  • 作者:Elena Lobova ; Vladimir Postnikov ; Stanislav Rybin
  • 期刊名称:SHS Web of Conferences
  • 印刷版ISSN:2416-5182
  • 电子版ISSN:2261-2424
  • 出版年度:2021
  • 卷号:116
  • 页码:1-4
  • DOI:10.1051/shsconf/202111600018
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:As a rule, during the choice of the most viable organizational structure of a cluster, traditional methods of the assessment of economic efficiency are used, taking into account the influence of financial, production and technological risks. The high level of the fluctuations of social, political, economic and technological impacts of the intercountry level has a strong impact on the result of their production activities. The peculiarities of this influence include the emergence of new institutions of interaction between the subjects of a cluster, the growth of uncertainty within the system and a change in the level of specificity of the assets of its participants. The task to find new tools for the assessment of the potential of economic security of a cluster is becoming urgent. It is necessary to find such tools which would take into account the ability to adapt to technological and geopolitical challenges in the future. Within the framework of this study, the authors developed an algorithm for the assessment of the potential of alternative models of the organizational structure of a high-tech cluster. The important methodological aspect of the process of forecasting the level of adaptability of alternative cluster structures to external changes is the condition for the availability of institutional support to promising areas of technical development. The developed algorithm presupposes the further development of the methods of system analysis and the formation of Institutional Atlases for the parameters of the assessment of the opportunistic behavior risks of subjects or synergistic effects. The use of this algorithm allowed drawing some important intermediate conclusions about the unequal composition and the influence of dominant institutional factors in modeling different organizational structures of a high-tech cluster.
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