  We consider a network of interacting agents and we model the process of
choice on the adoption of a given innovative product by means of
statistical-mechanics tools. The modelization allows us to focus on the effects
of direct interactions among agents in establishing the success or failure of
the product itself. Mimicking real systems, the whole population is divided
into two sub-communities called, respectively, Innovators and Followers, where
the former are assumed to display more influence power. We study in detail and
via numerical simulations on a random graph two different scenarios:
no-feedback interaction, where innovators are cohesive and not sensitively
affected by the remaining population, and feedback interaction, where the
influence of followers on innovators is non negligible. The outcomes are
markedly different: in the former case, which corresponds to the creation of a
niche in the market, Innovators are able to drive and polarize the whole
market. In the latter case the behavior of the market cannot be definitely
predicted and become unstable. In both cases we highlight the emergence of
collective phenomena and we show how the final outcome, in terms of the number
of buyers, is affected by the concentration of innovators and by the
interaction strengths among agents.
