Technology epidemics

When a new technology is invented, the number of people who are using it is often small for a while, then increases quickly, then slows down. Some earlier posts showed the emergence pattern in different countries of ICT technologies (for example, here).

There are competing explanations how the characteristic S-curve arises. One is that people start using the technology as they are exposed to it by other users. When there are few people using the technology, not too many people are exposed to it and it spreads slowly. When more people are using it, exposure is greater and spread is faster until almost everyone is using it and so spread slows again. Other explanations are based on the speed of the technology's acceptance or to its skill requirements and the distribution of people's skills.

The explanations give the same predicted curves, but the implications for technology policy are different. If technology spread is limited by exposure, then a policymaker may best promote it by publicity or other measures to increase knowledge of it. If on the other hand, spread is limited by skills, then training is the best way of promoting it.

For readers interested in the mathematical models, Wikipedia has a page on them here. The derivations corresponding to each of the above explanations would be a little different, but the outcomes are similar. The models are also used in modelling disease spread, so are very useful for comparatively little work.