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The dynamic of innovation networks: a switching model on technological change

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  • Gabriele Tedeschi
  • Stefania Vitali
  • Mauro Gallegati

Abstract

In this paper, we introduce an agent-based model where heterogeneous firms compare and modify their innovation strategies, so generating an evolving network structure. By implementing dynamic behavioral switching via a fitness mechanism based on agents’ performance, companies can endogenously modify their tactics for technological change and switch among three groups: stand-alone innovators, collaborative innovators and imitators. On the one hand, we study the properties of the emerging networks and we show that they reproduce the stylized facts of innovation networks. Moreover, we focus the analysis on the impact of these three innovation categories on the macro economic aggregate, finding that collaborative companies are those having the highest positive impact on the economic system. On the other hand, we use the model to study the effect of different economic innovation policies in increasing macroeconomic performance. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Gabriele Tedeschi & Stefania Vitali & Mauro Gallegati, 2014. "The dynamic of innovation networks: a switching model on technological change," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 817-834, September.
    • Handle: RePEc:spr:joevec:v:24:y:2014:i:4:p:817-834
    DOI: 10.1007/s00191-014-0374-4
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    3. Na Zhao & Congcong Lei & Hui Liu & Chunlin Wu, 2022. "Improving the Effectiveness of Organisational Collaborative Innovation in Megaprojects: An Agent-Based Modelling Approach," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
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    6. Berardi, Simone & Tedeschi, Gabriele, 2017. "From banks' strategies to financial (in)stability," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 255-272.
    7. Colasante, Annarita, 2016. "Evolution of Cooperation in Public Good Game," MPRA Paper 72577, University Library of Munich, Germany.
    8. Ciola, Emanuele & Turco, Enrico & Gurgone, Andrea & Bazzana, Davide & Vergalli, Sergio & Menoncin, Francesco, 2023. "Enter the MATRIX model:a Multi-Agent model for Transition Risks with application to energy shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    9. Mansour Naser Alraja & Faris Alshubiri & Basel M. Khashab & Mahmood Shah, 2023. "The financial access, ICT trade balance and dark and bright sides of digitalization nexus in OECD countries," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 177-209, June.
    10. Stefan Behfar & Ekaterina Turkina & Thierry Burger-Helmchen, 2017. "Network tie structure causing OSS group innovation and growth," Post-Print hal-02153061, HAL.
    11. Colasante, Annarita, 2017. "Selection of the distributional rule as an alternative tool to foster cooperation in a Public Good Game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 482-492.

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    More about this item

    Keywords

    Innovation network; Preferential attachment; Economic policy; D8; L2; O3; O4;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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