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0:00
I'm Joe Tidd, and I'm
Professor of Technology
and Innovation
Management at the Science
Policy Research Unit
at the University of Sussex, UK.
This session is about the
diffusion of innovations,
what factors promote and
inhibit the adoption
of innovations?
0:18
Most innovations
fail to be adopted.
The question that
we want to answer
in this session is,
why might that be?
It's very rarely the
inherent innovation,
but more about the
diffusion process,
how it's communicated,
and how it's adopted.
0:33
The diffusion of innovation
is much more than
the simple marketing mix of
price, product, and position.
What diffusion
attempts to do is to
explain how, over
time, an innovation,
for example, product,
service, and idea,
or a business, spreads through
a particular market
or population.
0:51
We're arguing that
the diffusion of
innovations is much more
than simply marketing.
In marketing, you
look at segmentation.
You look at the idea of
innovators versus laggards,
those who adopt early and
those who adopt late.
Then you have the marketing mix.
Things like pricing,
positioning, to try
to promote the adoption
of the focal innovation.
But when we look at the
diffusion of innovations,
we find that these types of
terms are very unhelpful.
Segmentation is not
sufficient and the idea
of innovators and
laggards is not robust.
1:23
There are lots of
different models
of diffusion of innovations,
and they tend to explain
different types of
product or service.
The simplest one,
which we'll all be
familiar with is
the epidemic model.
The idea is that information
about focal innovation spreads
through by observation,
communication, or
direct contact.
The more sophisticated
model which explains
most innovations is the
so called Bass model.
That basically takes a
simple epidemic model
where it's about observation
and communication,
that adds another
process within that,
where adopters make
independent evaluations
and adoption decisions.
The Bass model is probably
the best model to describe
the adoption of consumer
and business to
business innovations.
There are other models
like Bayesian and
Probit that get even
more sophisticated,
but they tend only to explain
certain types of innovation.
You've probably seen this
curve in many marketing texts.
