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Whereas this data contains information on how different segments of consumers
perceive an electric car, and what their intentions are towards adoption of an electric
car, these data do not show the social complexities associated with the diffusion of
electric cars. With diffusion we refer to the adoption of a new product or behavior
over time in a population. Diffusion remains a problematic theoretical concept be-
cause the precise definition of a successful or failing diffusion is not possible due to
the open ending of the process. Whereas empirical analysis of diffusion processes
require an ex-post analysis, only in the hypothetical case where 100% of a population
adopts, one can speak of a completed diffusion process. Moreover, in many situations
diffusions can be said to fail, e.g. when a new product is not being adopted and pro-
duction is being discontinued. However, this does not exclude the possibility of a later
success. In this paper we consider diffusion to refer to the process and factors sur-
rounding the spreading of new products or behaviours in a population.
Social processes play a key role in the success or a failure of diffusion (e.g., Garcia
& Jager, 2011), which may involve personal awareness of a new product that emerges
from growing adoption of the product; as well as change in normative pressures that
triggers acquisition of information about the new product, and so on.
Two complexities are of special interest in this context. First, due to the uncertainty
and limited knowledge of many consumers concerning the electric car they are more
likely to (be) discuss(ed), and opinions and attitudes may spread fast through the so-
cial networks. This diffusion of experiences and attitudes hence is very sensitive to
both negative and positive experiences consumers have, and opinion leaders may
have a strong impact on the success or failure of the diffusion process (see e.g. Van
Eck, Jager & Leeflang, 2011). A recent example is the turmoil about the negative
review of the Tesla car in the New York Times, which apparently resulted from a
reviewer deliberately trying to exhaust the batteries to make the story dramatic (Brod-
er, 2013). These stories may propagate in further discussions on the risk of ending up
with a flat battery.
A second complexity arises from the fact that during a diffusion process (which is
essentially a theoretical construct) the context of the decision making is changing. If a
certain proportion of consumers adopts an electric car, the uncertainty on its perfor-
mance will decrease, as well as the norms concerning its acceptability. Hence con-
sumers that initially are very hesitant of switching to an electric car may at a later
stage change their attitude.
Agent based models are known to offer a suitable tool for exploring these com-
plexities. In this project our aims are to work towards what we call “adaptive policy”
for complex systems. This implies that policy is developed for different segments, and
assuming that the segments have a different switching moment and sensitivities, adap-
tive policy is tailor-cut and is aimed at identifying and targeting those consumer
groups at the moment in time when they are at the brink of adoption. The theory of
innovation diffusion of Rogers (1993) acknowledges that the adoption of novel prod-
ucts can be driven by different needs. So, for some consumers applies that they have a
strong need to distinguish themselves from the others (anti conformism), which in
turn stimulates them to be among the first adopting an electric car, even (or especial-
ly) when the performance of this car is inferior to that of a traditional fuel car. Other
