Binary decisions with multiple factors for different preference thresholds

Abstract

We model the binary decisions of a population N having different preference thresholds subjected to an increasing number of factors considered, n, before the individual decides whether to take the action or not in a certain event. We examine the implication of this variation in the number of factors to the number of action-takers. We find that for a uniformly-distributed preference thresholds with a small finite number of factors, the rate of action-takers follow the Irwin-Hall distribution. We apply the action-takers as instigators to random, Watts-Strogatz and Barabasi-Albert network, and examine the portion they influenced in those networks.