The technology adoption lifecycle is a sociological model that is an extension
of an earlier model called the diffusion process, which was originally published
in 1957 by Joe M. Bohlen, George M. Beal and Everett M. Rogers at Iowa State
University and which was originally published only for its application to
agriculture and home economics). building on earlier research conducted
there by Neal C. Gross and Bryce Ryan. Their original purpose was to track the
purchase patterns of hybrid seed corn by farmers.
Beal, Rogers and Bohlen together developed a model called the diffusion
process and later Everett Rogers generalized the use of it in his widely
acclaimed book, Diffusion of Innovations, describing how new ideas
and technologies spread in different cultures. Others have since used the
model to describe how innovations spread between states in the U.S.
The technology adoption lifecycle model describes the adoption or acceptance of
a new product or innovation, according to the demographic and psychological
characteristics of defined adopter groups. The process of adoption over
time is typically illustrated as a classical normal distribution or "bell
curve." The model indicates that the first group of people to use a new
product is called "innovators," followed by "early adopters." Next come the early
and late majority, and the last group to eventually adopt a product are called
"laggards". The demographic and psychological
profiles of each adoption group were originally specified by the North
Central Rural Sociology Committee, Subcommittee for the Study of the
Diffusion of Farm Practices. The report summarised the categories as:
innovators – had larger farms, were more educated, more prosperous and more
risk-oriented early adopters – younger, more educated,
tended to be community leaders, less prosperous
early majority – more conservative but open to new ideas, active in community
and influence to neighbours late majority – older, less educated,
fairly conservative and less socially active
laggards – very conservative, had small farms and capital, oldest and least
educated Adaptations of the model
The model has spawned a range of adaptations that extend the concept or
apply it to specific domains of interest.
In his book Crossing the Chasm, Geoffrey Moore proposes a variation of the
original lifecycle. He suggests that for discontinuous or disruptive innovations,
there is a gap or chasm between the first two adopter groups, and the early
majority. In Educational technology, Lindy McKeown
has provided a similar model describing the ICT uptake in education. In medical
sociology, Carl May has proposed Normalization Process Theory that shows
how technologies become embedded and integrated in health care and other
kinds of organisation. Wenger, White and Smith, in their book
Digital habitats: Stewarding technology for communities, talk of technology
stewards: people with sufficient understanding of the technology
available and the technological needs of a community to steward the community
through the technology adoption process. Rayna and Striukova propose that the
choice of initial market segment has crucial importance for crossing the
chasm, as adoption in this segment can lead to a cascade of adoption in the
other segments. This initial market segment has, at the same time, to
contain a large proportion of visionaries, to be small enough for
adoption to be observed from within the segment and from other segment and be
sufficiently connected with other segments. If this is the case, the
adoption in the first segment will progressively cascade into the adjacent
segments, thereby triggering the adoption by the mass-market.
Examples One way to model product adoption is to
understand that people's behaviors are influenced by their peers and how
widespread they think a particular action is. For many format-dependent
technologies, people have a non-zero payoff for adopting the same technology
as their closest friends or colleagues. If two users both adopt product A, they
might get a payoff a > 0; if they adopt product B, they get b > 0. But if one
adopts A and the other adopts B, they both get a payoff of 0.
A threshold can be set for each user to adopt a product. Say that a node v in a
graph has d neighbors: then v will adopt product A if a fraction p of its
neighbors is greater than or equal to some threshold. For example, if v's
threshold is 2/3, and only one of its two neighbors adopts product A, then v
will not adopt A. Using this model, we can deterministically model product
adoption on sample networks. See also
Bass diffusion model Technology acceptance model
Technology lifecycle Diffusion
Diffusion of innovations Crossing the Chasm
Matching Person & Technology Model Hype cycle
Lazy User Model Early adopter
Notes ^ Bohlen, Joe M.; Beal, George M., "The
Diffusion Process", Special Report No. 18 1: 56–77.
http:www.soc.iastate.edupubSP18.pdf ^ Gross, Neal C. The diffusion of a
culture trait in two Iowa townships. M.S. Thesis, Iowa State College, Ames.
^ Ryan, Bryce, and Neal C. Gross “The diffusion of hybrid seed corn in two
Iowa communities.” Rural Sociology 8: 15–24. RS(E)
^ Ryan, Bryce, and Neal C. Gross Acceptance and diffusion of hybrid corn
seed in two Iowa communities. Research Bulletin 372, Agricultural Experiment
Station, Ames, Iowa. ^ Beal, George M., Everett M. Rogers,
and Joe M. Bohlen "Validity of the concept of stages in the adoption
process." Rural Sociology 22(2):166–168. ^ Rogers, Everett M.. Diffusion of
Innovations, Glencoe: Free Press. ^ Savage, Robert L.. "Diffusion Research
Traditions and the Spread of Policy Innovations in a Federal System" Publius
15: 1–27. ^ Pencil metaphor
^ Wenger, E.; White, N.; Smith, J.D.. Digital habitats: Stewarding technology
for communities. Portland, OR: CPsquare. ISBN 978-0-9825036-0-7.
^ Rayna, Thierry, Striukova, Ludmila and Landau, Samuel, Crossing the Chasm or
Being Crossed Out: The Case of Digital Audio Players. International Journal of
Actor-Network Theory and Technological Innovation, Vol. 1, No. 3, pp. 36-54,
July-September 2009. Available at SSRN: http:ssrn.com/abstract=1392691
^ Von Ahn, Luis. Science of the Web lectures at Carnegie Mellon University.