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.

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