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A laboratory experiment of knowledge diffusion dynamics

In: Innovation, Industrial Dynamics and Structural Transformation

Author

Listed:
  • Andrea Morone

    (University of Bari)

  • Piergiuseppe Morone

    (University of Napoli “L’Orientale”)

  • Richard Taylor

    (Manchester Metropolitan University)

Abstract

This paper aims to study, by means of a laboratory experiment and a simulation model, some of the mechanisms that dominate the phenomenon of knowledge diffusion in the process that is called ‘interactive learning’.We examine how knowledge spreads in different networks in which agents interact by word of mouth. We define a regular network, a randomly generated network and a small world network structured as graphs consisting of agents (vertices) and connections (edges), situated on a wrapped grid forming a lattice. The target of the paper is to identify the key factors that affect the speed and the distribution of knowledge diffusion. We will show how these factors can be classified as follows: (1) learning strategies adopted by heterogeneous agents; (2) network architecture within which the interaction takes place; (3) geographical distribution of agents and their relative initial levels of knowledge; (4) network size. We shall also attempt to single out the relative effect of each of the above factors.

Suggested Citation

  • Andrea Morone & Piergiuseppe Morone & Richard Taylor, 2007. "A laboratory experiment of knowledge diffusion dynamics," Springer Books, in: Uwe Cantner & Franco Malerba (ed.), Innovation, Industrial Dynamics and Structural Transformation, pages 283-302, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-49465-2_15
    DOI: 10.1007/978-3-540-49465-2_15
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    Cited by:

    1. Mueller, Matthias & Bogner, Kristina & Buchmann, Tobias & Kudic, Muhamed, 2015. "Simulating knowledge diffusion in four structurally distinct networks: An agent-based simulation model," Hohenheim Discussion Papers in Business, Economics and Social Sciences 05-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    2. Matthias Mueller & Kristina Bogner & Tobias Buchmann & Muhamed Kudic, 2017. "The effect of structural disparities on knowledge diffusion in networks: an agent-based simulation model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 613-634, October.
    3. Torben Klarl, 2014. "Knowledge diffusion and knowledge transfer revisited: two sides of the medal," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 737-760, September.
    4. 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.
    5. Bogner, Kristina, 2019. "Knowledge networks in the German bioeconomy: Network structure of publicly funded R&D networks," Hohenheim Discussion Papers in Business, Economics and Social Sciences 03-2019, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    6. Raisi, Hossein & Baggio, Rodolfo & Barratt-Pugh, Llandis & Willson, Gregory, 2020. "A network perspective of knowledge transfer in tourism," Annals of Tourism Research, Elsevier, vol. 80(C).

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    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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