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The effect of structural disparities on knowledge diffusion in networks: an agent-based simulation model

Author

Listed:
  • Matthias Mueller

    (University of Hohenheim)

  • Kristina Bogner

    (University of Hohenheim)

  • Tobias Buchmann

    (University of Hohenheim)

  • Muhamed Kudic

    (Stifterverband
    University of Bremen)

Abstract

We apply an agent-based simulation approach to explore how and why typical network characteristics affect overall knowledge diffusion properties. To accomplish this task, we employ an agent-based simulation approach (ABM) which is based on a “barter trade” knowledge diffusion process. Our findings indicate that the overall degree distribution significantly affects a network’s knowledge diffusion performance. Nodes with a below-average number of links prove to be one of the bottlenecks for an efficient transmission of knowledge throughout the analysed networks. This indicates that diffusion-inhibiting overall network structures are the result of the myopic linking strategies of the actors at the micro level. Finally, we implement policy experiments in our simulation environment in order to analyse consequences of selected policy interventions. This complements previous research knowledge on diffusion processes in innovation networks.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jeicoo:v:12:y:2017:i:3:d:10.1007_s11403-016-0178-8
    DOI: 10.1007/s11403-016-0178-8
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    Cited by:

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    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. Ivan Savin, 2021. "On optimal regimes of knowledge exchange: a model of recombinant growth and firm networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(3), pages 497-527, July.
    4. Juana Castro & Stefan Drews & Filippos Exadaktylos & Joël Foramitti & Franziska Klein & Théo Konc & Ivan Savin & Jeroen van den Bergh, 2020. "A review of agent‐based modeling of climate‐energy policy," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(4), July.
    5. Yun, JinHyo Joseph & Ahn, Heung Ju & Lee, Doo Seok & Park, Kyung Bae & Zhao, Xiaofei, 2022. "Inter-rationality; Modeling of bounded rationality in open innovation dynamics," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    6. Zhang, Qi & Wu, Xifeng & Chen, Yu, 2022. "Is economic crisis an opportunity for realizing the low-carbon transition? A simulation study on the interaction between economic cycle and energy regulation policy," Energy Policy, Elsevier, vol. 168(C).
    7. 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.
    8. Wu, Haizhen & Han, Zhao'an & Zhou, Yong, 2021. "Optimal degree of openness in open innovation: A perspective from knowledge acquisition & knowledge leakage," Technology in Society, Elsevier, vol. 67(C).
    9. Muhamed Kudic & Matthias Müller & Tobias Buchmann & Andreas Pyka & Jutta Günther, 2021. "Network dynamics, economic transition, and policy design—an introduction," Review of Evolutionary Political Economy, Springer, vol. 2(1), pages 1-8, April.
    10. Lei Xu & Ronggui Ding & Lei Wang, 2022. "How to facilitate knowledge diffusion in collaborative innovation projects by adjusting network density and project roles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1353-1379, March.

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