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Structuring knowledge transfer from experts to newcomers

Author

Listed:
  • Widad Guechtouli

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Juliette Rouchier

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Magali Orillard

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Purpose – The purpose of this paper is to focus on the process of knowledge transfer within social networks composed of a pool of experts, and newcomers whose aim is primarily to acquire new knowledge, such as communities of practice. The authors wish to understand which communication system and which information about others' knowledge should be provided to get to a better diffusion of knowledge. Design/methodology/approach – Agent‐based models and social network analysis are used and many simulations are run, in which communication mode and information about others' knowledge are varied. Findings – Results emphasize the part played by newcomers in the process of direct knowledge transfer. They constitute additional sources of knowledge and act as intermediaries. Results also show that in a process of indirect transfer of knowledge, they have only little influence on the process of individual learning. These results enable the authors to formulate some recommendations to facilitate knowledge transfer within a knowledge intensive community. Non‐hierarchical structures of communication should be preferred and the participation of newcomers in the activities of the community fully encouraged. Originality/value – This paper combines agent‐based modelling and social networks analysis to investigate the field of knowledge transfer and enables the identification of the key elements in the process of knowledge diffusion within a community of practice. It thus provides some solution to eventual congestion problems in the access to the knowledge held within the community.

Suggested Citation

  • Widad Guechtouli & Juliette Rouchier & Magali Orillard, 2013. "Structuring knowledge transfer from experts to newcomers," Post-Print hal-01499611, HAL.
  • Handle: RePEc:hal:journl:hal-01499611
    DOI: 10.1108/13673271311300741
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    Cited by:

    1. Widad Guechtouli, 2014. "Agent-based modeling of knowledge transfer within social networks," Working Papers 2014-148, Department of Research, Ipag Business School.
    2. Wang, Wenjing & Lu, Shan, 2021. "University-industry innovation community dynamics and knowledge transfer: Evidence from China," Technovation, Elsevier, vol. 106(C).

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    Keywords

    Economie quantitative;

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