Technological Diffusion and Disruption

Abstract

This chapter is about how technologies, after they have been implemented in a product or service, are adopted by users and how they diffuse into society. Generally, once technologies have reached at least TRL 8, they move to TRL 9. TRL stands for Technology Readiness Level and this is a commonly used scale between 1 and 9 to track technologies as they gradually mature from a laboratory environment to deployment in the field. This chapter initially focuses on the initial diffusion of technologies (Rogers, Diffusion of innovations, The Free Press, A Division of Simon & Schusters Inc., 1962). However, technologies are also abandoned and replaced by other newer technologies over time. If this happens quickly or unexpectedly and affects a whole economic sector, we talk about technological “disruption.” A kind of paralysis by owners of incumbent technologies due to this phenomenon of technological disruption has been described as the “Innovator’s Dilemma” by Christensen (The innovator’s dilemma – when new technologies cause great firms to fail, Harvard Business Review Press, 1997). The adoption, rejection, diffusion, and eventual abandonment of technologies is a crucial phenomenon that needs to be understood in detail to do meaningful roadmapping.

When considering technology diffusion and disruption, such as the adoption of electric appliances like refrigerators instead of ice boxes (Utterback, Mastering the Dynamics of Innovation. Harvard Business School Press, Boston, 1994) or communications via the Internet instead of hand-written letters, we often forget that many “old” technologies don’t disappear completely but persist for decades (or even centuries) in niche applications. We still use ice boxes on camping trips, and some of us still write physical letters on paper (at least on special occasions). Also, there are those, because of geographical isolation, religious belief, or concerns for the environment, who choose not to adopt modern technologies at all.

Appendix

7.1.1 Matlab Code for Agent-Based Simulation of Technology Diffusion

% simple Rogers-type agent-based diffusion model N=10000 ; % population size a=zeros(N,1) ; % initially all are non-adopters T=100 ; % time periods C=1; % number of contacts per time period n=0.5+(1/6)*randn(N,1); % create Gaussian distribution of population [fa,ind]=min(n); a(ind)=1; % find and set initial adopter for t=1:T; % loop over all time periods inda=find(a); % find all adopters at this time step A(t)=length(inda); % record the number of adopters at time t for inda2=1:length(inda); % loop over all current adopters indr=randi(N,C,1); % create random contacts this time period for inda3=1:length(indr); % loop over all random contacts nr=rand(1); % generate uniform random decision variable if n(indr(inda3))<=nr && a(indr(inda3))==0; % test adopt a(indr(inda3))=1; % nr adopts end end end end