Diffusion By Learning
Innovation is terribly important; it is why we are rich. But how exactly does innovation happen? An awful lot of innovation seems to happen via diffusion, i.e., spreading one at a time via a network of who knows who. A recent AER paper considers three possible diffusion processes:
[Consider] situations where the [innovation diffusion] dynamics are driven from within; that is, there are internal feedback effects from prior to future adopters. …
1. Contagion. People adopt when they come in contact with others who have already adopted; that is, innovations spread much like epidemics.
2. Social influence. People adopt when enough other people in the group have adopted; that is, innovations spread by a conformity motive.
3. Social learning. People adopt once they see enough empirical evidence to convince them that the innovation is worth adopting, where the evidence is generated by the outcomes among prior adopters. Individuals may adopt at different times due to differences in their prior beliefs, amount of information gathered, and idiosyncratic costs.
Social learning is consistent with the observed pattern of diffusion of hybrid corn, although we cannot say that it was the sole explanatory factor. We can also say with some confidence, however, that inertia and contagion were probably not the sole explanatory factors, and given Griliches’s findings neither was social influence.
I’ve been watching this innovation process up close for several years, as prediction markets slowly spread through the corporate world. One might hope that we had central technology experts, and once they approved a new tech, everyone would adopt it. No way. People don’t believe something works until they’ve seen it work in something pretty close to their situation. A media story about something far away just doesn’t say much.