General model on transition, tipping points and crossing the chasm

Just a small general model on tipping points (using the Bass function that can be found e.g. in Sterman's 'Business Dynamics'). The model distinguishes between first movers, early adopters and the tipping point of an adaption by the majority of potential adopters. Getting from early adopters to the majority can be named 'crossing the chasm' (by G.A. Moore). The model can be used for both, explorative qualitative modeling of factors the hinder and foster the tipping point or a continuation of the quantitative modeling of effects that describe when a tipping point might not be reached, e.g. because of incidents that make the change less attractive and thus even reverse it (e.g. the use of electric vehicles currently suffers a low adoption rate (and thus slow pace of infrastructure development) that urges some early adopters to return to gasoline cars).
If you widen the time span of the simulation and lower the diffusion rates you can show nicely the deception phase Diamandis/Kotler describe in 'Bold: How to grow ....'
However, wishing for the exponential development and a tipping point is easy, exploring what might hinder it is the real task. For this I recommend applying the KNOW-WHY Method and asking for psychological motives for people to change, namely the possibility to feel integration and/or development or even of threatening one's feeling of integration through the possible change. Feel free to ask for more :-)

Here - or in the table below - you see how starting with 2 first movers followed by 20 early adopters the majority starts to adopt in a s-shaped curve.

Either quantitatively or qualitatively you might continue to ask for factors that determine the attractiveness, the communication and the possible fall backs.