Multilevel transfer of innovations: Cognitive modeling to decision support in managing the economic growth

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An essential aspect of the country’s economic growth is the transfer of innovation, which is very important nowadays. The innovative projects can be implemented through it at the level of households, companies, institutions, and local communities. The transfer of innovations is intended to cause a cumulative effect and stimulate economic growth. It is important to determine the influence of different factors on this process and consider the feedbacks in the “enterprise-region-state” system, which will increase the level of control over the process. The paper aims to find scientific instruments for managing the multilevel transfer of innovations, representing the connections between factors that act as catalysts/inhibitors of that process. The proposed methodology uses systems analysis, indicative analysis, and cognitive modeling (Fuzzy Cognitive Maps (FCM)). Based on the study results, a cognitive model was formed based on identifying the “strength of impact” of connections between elements that determine the level of influence of the micro- and macro-environment factors of the innovation multilevel transfer. From a practical point of view, this allows obtaining forecasts of its behavior under different management actions. To implement the research results, it is necessary to determine management tools that will allow stakeholders in the system “enterprise-region-state” to make a transfer of innovations most effective. It demonstrates the need for further research in this area and assessing the potential consequences of management decisions for economic growth.

Acknowledgment
This research was funded by a grant from the Ministry of Education and Science of Ukraine “Modelling the Transfer of Eco-Innovations in the Enterprise-Region-State System: Impact on Ukraine’s Economic Growth and Security” (No. 0119U100364).

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    • Figure 1. Multilevel and intersectoral transfer of innovations (authors’ view)
    • Figure 2. Results of the 1-14 iterations
    • Figure 3. Cognitive map of multilevel transfer of innovations in Ukraine
    • Table 1. The share of financing of R&D expenses in the total volume of R&D expenses by sector
    • Table 2. The values according to the “strength of impact”
    • Conceptualization
      Olena Shkarupa
    • Funding acquisition
      Olena Shkarupa, Viktoriia Boronos
    • Methodology
      Olena Shkarupa
    • Project administration
      Olena Shkarupa
    • Resources
      Olena Shkarupa, Viktoriia Boronos, Dmytro Vlasenko, Kostiantyn Fedchenko
    • Supervision
      Olena Shkarupa
    • Writing – original draft
      Olena Shkarupa
    • Formal Analysis
      Viktoriia Boronos, Dmytro Vlasenko
    • Investigation
      Viktoriia Boronos, Kostiantyn Fedchenko
    • Writing – review & editing
      Viktoriia Boronos
    • Data curation
      Dmytro Vlasenko, Kostiantyn Fedchenko
    • Software
      Dmytro Vlasenko