Implication of network size and structure on organizations' knowledge transfer

Authors:
Fangcheng Tang;Jifeng Mu;Douglas L. MacLachlan
Affiliations:
School of Economics and Management, Tsinghua University, Beijing 100084, PR China;University of Washington Business School, Box 353200, Seattle, WA 98195-3200, USA;University of Washington Business School, Box 353200, Seattle, WA 98195-3200, USA
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

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Abstract

Past studies have suggested an interaction between knowledge transfer, structural characteristics and behavioral patterns of network organizations. However, most research has explored the process of knowledge transfer from the micro-level perspective, and less attention has been paid to the macro-level dynamic behavior patterns of network-based organization and the micro-macro links in the process of knowledge transfer. In this paper, a virtual experiment (VE) is utilized to explore the interdependence of knowledge transfer and dynamic behavior patterns of network-based organizations on the basis of rules systems. Our model shows that the speed of knowledge transfer and power influence of individuals play dominant roles in the process of knowledge transfer. The larger the network organization and the greater number of the neighbor nodes an organization have, the higher the proportion of nodes that will change their knowledge state.