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Schumpeterian Competition, Technological Regimes and Learning through Knowledge Spillover

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  • Klaus Wersching

    (Department of Business Administration and Economics - Department of Business Administration and Economics)

Abstract

This paper builds upon [Winter, 1984] in which the author discusses two views of Schumpeter on competition. Specifically, technological regimes and the role of knowledge spillovers for innovation are examined. An agent-based simulation model is formulated which captures the relevant aspect of competition between firms in an innovative industry. Results of the simulation runs indicate that at first, the technological development in terms of process and product innovations is better in an industry that is characterized by Schumpeter Mark II conditions. But the improved technological development is connected with higher prices and profits, which could be interpreted as a trade-off between static and dynamic efficiency. Second, in both scenarios market and industry concentration rises over time, showing a strong separation between successful firms and those lagging behind in technological terms. And third, surprisingly firms in a Schumpeter Mark I regime seem to be more technologically specialized. Furthermore, this article proves that a replication of simulation models is possible and useful.

Suggested Citation

  • Klaus Wersching, 2010. "Schumpeterian Competition, Technological Regimes and Learning through Knowledge Spillover," Post-Print hal-00849408, HAL.
    • Handle: RePEc:hal:journl:hal-00849408
    DOI: 10.1016/j.jebo.2010.05.005
    Note: View the original document on HAL open archive server: https://hal.science/hal-00849408
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    Cited by:

    1. Patrick Mellacher, 2021. "Growth, Inequality and Declining Business Dynamism in a Unified Schumpeter Mark I + II Model," Papers 2111.09407, arXiv.org, revised Nov 2023.
    2. Michael P. Schlaile & Johannes Zeman & Matthias Mueller, 2021. "It’s a Match! Simulating Compatibility-based Learning in a Network of Networks," Economic Complexity and Evolution, in: Michael P. Schlaile (ed.), Memetics and Evolutionary Economics, chapter 0, pages 99-140, Springer.
    3. Savin, Ivan & Egbetokun, Abiodun, 2016. "Emergence of innovation networks from R&D cooperation with endogenous absorptive capacity," Journal of Economic Dynamics and Control, Elsevier, vol. 64(C), pages 82-103.
    4. Spyros Arvanitis & Florian Seliger & Martin Woerter, 2020. "Knowledge Spillovers, Competition and Innovation Success," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(5), pages 1017-1041, October.
    5. Theo C.M.J. van de Klundert, 2013. "Capitalism and Democracy," Books, Edward Elgar Publishing, number 15248.
    6. Claudius Gräbner & Anna Hornykewycz, 2022. "Capability accumulation and product innovation: an agent-based perspective," Journal of Evolutionary Economics, Springer, vol. 32(1), pages 87-121, January.
    7. Aistleitner, Matthias & Gräbner, Claudius & Hornykewycz, Anna, 2021. "Theory and empirics of capability accumulation: Implications for macroeconomic modeling," Research Policy, Elsevier, vol. 50(6).
    8. Safarzyńska, Karolina & Frenken, Koen & van den Bergh, Jeroen C.J.M., 2012. "Evolutionary theorizing and modeling of sustainability transitions," Research Policy, Elsevier, vol. 41(6), pages 1011-1024.
    9. Moutinho, Ricardo & Au-Yong-Oliveira, Manuel & Coelho, Arnaldo & Manso, José Pires, 2015. "Beyond the “Innovation's Black-Box”: Translating R&D outlays into employment and economic growth," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 45-58.
    10. Julia Hartmann & Stephan Vachon, 2018. "Linking Environmental Management to Environmental Performance: The Interactive Role of Industry Context," Business Strategy and the Environment, Wiley Blackwell, vol. 27(3), pages 359-374, March.
    11. Richard Arena, 2017. "Schumpeter and Schumpeterians on competition: some policy implications," Journal of Evolutionary Economics, Springer, vol. 27(1), pages 161-186, January.
    12. Katharina Fellnhofer, 2017. "Facilitating entrepreneurial discovery in smart specialisation via stakeholder participation within online mechanisms for knowledge-based policy advice," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1296802-129, January.

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    More about this item

    Keywords

    D83; L1; O31; O33; Innovation; Technological Regimes; Knowledge Spillover; Agent-based Simulation; Industry Dynamics;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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