Network Structure and Knowledge Transfer

  • Authors:

  • Fangcheng Tang

  • Affiliations:

  • School of Economics and Management, Tsinghua University, Beijing 100084, P.R. China and School of Economics and Management, Xi'an Technological University, Xi'an 710032, P.R. China

  • Venue:
  • ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
  • Year:
  • 2007

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Abstract

This study employs single layer perceptron model (SLPM) to explore how the topological structure of intra-organization networks affects knowledge transfer. The results demonstrate that in the process of knowledge transfer, both the disseminative capacity of knowledge senders and the absorptive capacity of knowledge receivers should be taken into consideration. While hierarchical networks can enable greater numbers of organizational units to acquire knowledge, they reduce the speed and efficiency of knowledge transfer, whereas scale-free networks can accelerate transfer of knowledge among units.