AJS Volume 110 Number 4 (January 2005): 000–000 PROOF 1

2005 by The University of Chicago. All rights reserved.
0002-9602/2005/11004-000X$10.00
Friday Mar 11 2005 04:47 PM AJS v110n4 080254 VML
An Individual-Based Model of Innovation
Diffusion Mixing Social Value and Individual
Benefit
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Guillaume Deffuant, Sylvie Huet, and Fre´de´ric Amblard
Laboratoire d’Inge´nierie pour les Syste`mes Complexes
The authors propose an individual-based model of innovation dif-
fusion and explore its main dynamical properties. In the model,
individuals assign an a priori social value to an innovation which
evolves during their interactions with the “relative agreement” in-
fluence model. This model offers the possibility of including a mi-
nority of “extremists” with extreme and very definite opinions. In-
dividuals who give a high social value to the innovation tend to
look for information that allows them to evaluate more precisely
the individual benefit of adoption. If the social value they assign is
low, they neither consider the information nor transmit it. The main
finding is that innovations with high social value and low individual
benefit have a greater chance of succeeding than innovations with
low social value and high individual benefit. Moreover, in some
cases, a minority of extremists can have a very important impact
on the propagation by polarizing the social value.
INTRODUCTION
The agent-based model of innovation diffusion described in Deffuant
(2001) and Deffuant et al. (2002b) was initially targeted on the diffusion
of green practices among farmers. We applied it to different types of green
practices (e.g., landscape maintenance, reduction of inputs) from different
study zones in Europe. In this article, we present an evolution of this
model and consider its application to more general processes of innovation
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We warmly thank all the participants in the IMAGES project who were involved in
the development of earlier versions of the model. We also thank the AJS reviewers
for their very relevant remarks and criticisms. This work was carried out in a project
funded by the European Commission (IMAGES project, FAIR 3 CT 2092). Direct
correspondence to Guillaume Deffuant, Laboratoire d’Inge´nierie pour les Syste`mes
Complexes, Cemagref-Grpt de Clermont-Ferrand, 24 Avenue des Landais-BP50085,
F-63172 Aubie`re Cedex, France. E-mail: guillame.deffuant@cemagref.fr
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American Journal of Sociology
PROOF 2
diffusion like the mobile phone, the Internet, contraception, organic prod-
ucts, genetically modified organisms, and cloning.
We refer to innovation diffusion in a sense close to the one proposed
by Valente (1995): “Diffusion of innovations is the spread of new ideas,
opinions, or products throughout a society, thus diffusion is a commu-
nication process in which adopters persuade those who have not yet
adopted to adopt.” More precisely, our model is designed for innovations
in which both social values and individual payoff are considered. For
instance, farmers give green practices promoted and supported by the
European commission a social value according to their opinion about
environmental preservation and the image they have of their work. If
they are interested in the green practices, they try to get information to
evaluate the individual benefit of adoption, including an evaluation of
the work to be done and whether the subsidies cover the costs or not.
The final adoption is based on a trade-off between both social value and
individual benefit. We believe that such behavior is fairly general and
can be extended to other innovations. For instance, in considering the
adoption of a mobile phone, a social value can be taken into account as
well as more strictly individual benefits or risks for health.
The most popular model of innovation diffusion, the threshold model
(Granovetter 1978), already considers the trade-off between a social value
and an individual benefit from the innovation. In this model, the social
value is directly related to the proportion of adopters in the individual’s
social network, representing the diffusion as a contagion process (Rogers
1983). When the number of adopters increases in the network of peers,
the pressure for adoption increases. The threshold is the proportion of
adopters in the individual’s social network that is necessary to convince
him or her to adopt. This theory has been applied to very different sub-
jects: farming innovations, family planning practices, medical technology,
policy innovation, and language (see Rogers [1983] for a comprehensive
review).
Threshold models were particularly used and studied in the social sim-
ulation research field, which aims at reproducing social dynamics in com-
puter models (Gilbert and Conte 1995; Bousquet et al. 1993; Gilbert and
Troitzsch 1999), because it happens that threshold models fit exactly into
the most popular type of social simulation model: automata networks.
Automata networks can be used to simulate the threshold model of in-
novation diffusion or new product growth in marketing. Each automaton
represents an individual in a social system, and the links of the graph
can represent working relations, friendship, or any type of contact; the
binary state of the automaton corresponds to the adoption or nonadoption
of the innovation. Blume (1993, 1995) and Ellison (1993) consider autom-
ata networks implementing the threshold model, in which the threshold
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