Innovation Diffusion among Case-based Decision-makers

TL;DR

This paper models how innovation spreads among decision-makers with case-based reasoning, highlighting the effects of innovation type and social network structure on diffusion speed and pattern.

Contribution

It introduces a model of innovation diffusion incorporating social network effects and case-based decision-making, analyzing how various factors influence diffusion dynamics.

Findings

Radical innovations have higher initial adoption speed but slower acceleration.

Stronger social ties and exposure to early adopters accelerate diffusion.

Lower homophily in social networks also speeds up innovation spread.

Abstract

This paper analyzes a model of innovation diffusion with case-based individuals a la Gilboa and Schmeidler (1995,1996,1997), who decide whether to consume an incumbent or a new product based on their and their social neighbors' previous consumption experiences. I analyze how diffusion pattern changes with individual characteristics, innovation characteristics and social network. In particular, radical innovation leads to higher initial speed but lower acceleration compared to increment innovation. Social network with stronger overall social tie, lower degree of homophily or higher exposure of reviews from early adopters speed up diffusion of innovation.