Innovations Spread more Like Wildfires than Like Infections

Abstract

Conventional theory says that innovations first diffuse slowly, then at faster paces, and finally at asymptotically declining rates. Economists and others explain such behavior with a variety of logistic models. Early models like the contagion model derive their predictive power from reliance on the history of the variables they are trying to predict. New social learning models improve the dynamics of diffusion across heterogeneous populations, while other studies propose various modifications. However, these extensions of the logistic and related models are still too orderly in structure and outcome. In reality one can expect both order from disorder and disorder from order. The argument of this paper is that innovations spread more like wild fire than like systematic epidemics. This analogy is no mere conjecture; some environments are more susceptible to catching fire than others. Just as the rate of the spread of fire is a function of fuel and other factors, so too is the spread of innovations, only that in the latter case the fuel is human population. Human population in general is a necessary fodder for the spread of innovations. The sufficient condition is the quality of the population which can favor or disfavor the spread of innovations, which explains why there are some random chances of finding islands untouched by fire surrounded by a sea of fire devastation.

Keywords: Innovation spread, logistic model, derivative Gompertz, diffusion of innovations

JEL Classification: O31, D8, M3, Z00