  In this paper, we tackle the problem of innovation spreading from a modeling
point of view. We consider a networked system of individuals, with a
competition between two groups. We show its relation to the innovation
spreading issues. We introduce an abstract model and show how it can be
interpreted in this framework, as well as what conclusions we can draw form it.
We further explain how model-derived conclusions can help to investigate the
original problem, as well as other, similar problems. The model is an
agent-based model assuming simple binary attributes of those agents. It uses a
majority dynamics (Ising model to be exact), meaning that individuals attempt
to be similar to the majority of their peers, barring the occasional purely
individual decisions that are modeled as random. We show that this simplistic
model can be related to the decision-making during innovation adoption
processes. The majority dynamics for the model mean that when a dominant
attribute, representing an existing practice or solution, is already
established, it will persists in the system. We show however, that in a two
group competition, a smaller group that represents innovation users can still
convince the larger group, if it has high self-support. We argue that this
conclusion, while drawn from a simple model, can be applied to real cases of
innovation spreading. We also show that the model could be interpreted in
different ways, allowing different problems to profit from our conclusions.
