Innovation diffusion in networks: the microeconomics of percolation

We implement a diffusion model for an innovative product in a market with a structure of social relationships. Diffusion is described with a percolation approach in the price space. Percolation shows a phase transition from a diffusion to a no-diffusion regime. This has strong implications for market demand and pricing. We study the effect of network structure on market diffusion efficiency by considering a number of cases, such as one-dimensional and two-dimensional lattices, small worlds, Poisson networks and Scale-free networks. We consider two measures of diffusion efficiency: the size of diffusion and the diffusion time-length. We find that network connectivity “spreading” is the most important factor for the size of diffusion. Clustering is ineffective. This means that societies with higher dimensionality are better markets for diffusion. This result is most evident for the size of diffusion, while a short average path-length is more important for the speed of diffusion. Endogenous learning curves shift the percolation threshold to higher prices, and constitute an endogenous mechanism of price discrimination. The best market strategy of innovation diffusion is to start with high price and allow for a learning curve.