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A Laboratory Experiment of Knowledge Diffusion Dynamics

Author

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  • Piergiuseppe Morone

    (University of Rome 'La Sapienza')

  • Richard Taylor

    (Centre for Policy Modelling, Manchester Metropolitan University Business School)

Abstract

This paper aims to study, by means of a laboratory experiment and a simulation model, some of the mechanisms which 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 which affect the speed and the distribution of knowledge diffusion. We will show how these factors can be classified as follow: (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. We shall also attempt to single out the relative effect of each of the above factors.

Suggested Citation

  • Piergiuseppe Morone & Richard Taylor, 2004. "A Laboratory Experiment of Knowledge Diffusion Dynamics," Experimental 0407004, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpex:0407004
    Note: Type of Document - pdf; pages: 20
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    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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    More about this item

    Keywords

    Knowledge; Network; Small world; Experiment; Simulation.;
    All these keywords.

    JEL classification:

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

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