Working Paper: CEPR ID: DP2146
Authors: Paul A. Geroski
Abstract: The literature on new technology diffusion is vast, and it spills over many conventional disciplinary boundaries. This paper surveys this literature by focussing on alternative explanations of the dominant stylized fact in this are: namely, that the usage of new technologies over time typically follows an S-curve. The most commonly found model which is used to account for this model is the so-called epidemic model, which builds on the premise that what limits the speed of usage is the lack of information available about the new technology, how to use it and what it does. The leading alternate model is often called the probit model, which follows from the premise that different firms, with different goals and abilities, are likely to want to adopt the new technology at different times. In this model, diffusion occurs as firms of different types gradually adopt it. There are actually many ways to generate an S-curve, and the third class of models which we examine are models of density dependence popularized by population ecologists. In these models, the twin forces of legitimation and competition help to establish new technologies and then ultimately limit their take-up. Finally, we looks at models in which the initial choice between different variants of the new technology affect the subsequent diffusion speed of the chosen technology. Such models often rely on information cascades, which drive herd like adoption behaviour when a particular variant is finally selected.
Keywords: technology diffusion; epidemics; probit models; density dependence; information cascades
JEL Codes: L00; L60
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| speed of information spread (D83) | rate of technology adoption (O33) |
| lack of users to inform potential adopters (O36) | rate of technology adoption (O33) |
| more users emerge (D16) | rate of technology adoption (O33) |
| legitimation processes (P37) | rate of technology adoption (O33) |
| competition among firms (L13) | rate of technology adoption (O33) |
| returns from early adoption diminish (J26) | rate of technology adoption (O33) |
| individual firm characteristics (L25) | rate of technology adoption (O33) |
| larger firms with more resources (L25) | rate of technology adoption (O33) |