Agent-based modeling of knowledge transfer within social networks
AbstractIn this paper, we study both processes of direct and indirect knowledge transfer, from a modelling perspective, using agent-based models. In fact, there are several ways to model knowledge. We choose to study three different representations, and try to determine which one allows to better capture the dynamics of knowledge diffusion within a social network. Results show that when knowledge is modelled as a binary vector, and not cumulated, this enables us to observe some heterogeneity in agents' learning and interactions, in both types of knowledge transfer.
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Bibliographic InfoPaper provided by Department of Research, Ipag Business School in its series Working Papers with number 2014-148.
Length: 24 pages
Date of creation: 25 Feb 2014
Date of revision:
knowledge model; knowledge transfer; social networks; communication.;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-03-22 (All new papers)
- NEP-CBE-2014-03-22 (Cognitive & Behavioural Economics)
- NEP-CMP-2014-03-22 (Computational Economics)
- NEP-GTH-2014-03-22 (Game Theory)
- NEP-KNM-2014-03-22 (Knowledge Management & Knowledge Economy)
- NEP-SOC-2014-03-22 (Social Norms & Social Capital)
- NEP-URE-2014-03-22 (Urban & Real Estate Economics)
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