Diffusion Processes on Complex Networks

In this paper we apply agent-based methodology on an issue that is fundamental for economic prosperity and growth: the diffusion of innovations. The diffusion of innovations is one of the topics where agent-based simulation is an extremely fruitful method allowing not only the observation of stable states but also the process and development of the diffusion. Furthermore, empirical studies revealed that the topological structure of interactions among individuals importantly influences the diffusion’s course and outcomes. We analyze diffusion outcomes for five different topologies, assuming markets where individuals are highly influenced by the adoption decision of their peers and innovations are introduced into the markets in two different ways: mass media campaigns and seeding procedures. Our results indicate that the topology of the relations among individuals importantly influences the speed and development of the diffusion process as well as final market penetration. Scale free topology seems to promote fast innovation diffusion, at the same time being characterized by the high uncertainty of the diffusion outcomes. Less heterogeneous networks (small worlds, two-dimensional lattice and ring) yield a much slower diffusion of the innovation, at the same time being much less unpredictable than scale free topology.