New technologies often enter the market at a competitive disadvantage. While they may seem to promise future advantages such as lower costs, environmental friendliness, or higher performance, initially they may be significantly more expensive than incumbent technologies or face teething problems. While much lower prices seem to be attainable in the future due to learning curve cost reductions that increase rapidly with the scale of diffusion of the technology, there is a chicken and egg problem, even when some consumers may be willing to pay a premium for the new technology. Drawing on recent percolation models of diffusion (Salomon et al. 2000, Frenken et al. 2006, Höhnisch et al. 2006) that combine the contagion aspect of agents distributed on a network, with the heterogeneity of agent characteristics, we develop a complex-dynamics model of new technology diffusion. Agents adopt when the price falls below their random reservation price drawn from an iid lognormal distribution, but only when one of their neighbors on the network has already adopted. Combined with a power-law learning curve for the price as a function of the cumulative number of adopters, this may lead to delayed adoption for a certain range of initial conditions. Using agent-based simulations we explore when a limited subsidy or ongoing R&D investment can trigger diffusion that would otherwise not happen. The introduction of such policies seems to be effective for a given high initial price level only for learning economies in a certain range. Outside this range, the diffusion of a new technology either never takes off or the subsidies are unnecessary. The range of exponents of the learning curve—0.2-0.3—corresponds ex post rather nicely with observations on successful innovations.

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1. A percolation model of the product lifecycle