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

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.