Learing Induced Criticality In Consumers' Adoption Pattern: A Neural Network Approach

The aim of this paper is to lay the foundations of 3 social influence based approach for the diffusion of an innovation or a technological standard. A model built on the principles of a neural network is proposed and a learning procedure is set up, making the network formation endogenous, the strength of connections among agents being determined by their shared histories, Referring to the concept of criticality developed by physicists, it shall be shown that learning, in a social structure, can lead the network to a critical state, called 'learning induced criticality, where some agents are able to exert a macroscopic influence over the network. The distribution of influence spheres' size follows a Pareto law. This approach shows an interesting similatry with that of the social coherence in sociology, whereby individuals within a social structure are led to share a close assessment of a given innovation.