Influence sociale et diffusion de l'innovation

Steyer, Alexandre; Zimmermann, Jean-Benoît

doi:10.4000/msh.2929

Cited by 14 publications

(13 citation statements)

References 14 publications

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“…Elle permet de faire le lien entre un objet et l'évaluation ou le jugement émis par un individu. L'attitude des consommateurs envers des produits ou objets a une forte valeur prédictive sur les comportements (Perugini et al, 2010), notamment dans le cas d'innovations (Steyer et Zimmermann, 2004), dans la prise de décision (Arcuri et al, 2008 ;Bodenhausen et Todd, 2010 ;Fazio, 2002), le choix d'une marque (Courbet et Fourquet-Courbet, 2005) et les comportements d'achat et d'usage (Madhavaram et Appan, 2010 ;Maison et al, 2004 ;Wänke et al, 2002).…”

Section: L'attitudeunclassified

Modélisation du risque de la nouveauté perçue sur la perception d’une marque innovante

Hetet

Moutot

Mathieu

2015

RFGI

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Cet article présente une recherche sur le risque de la nouveauté perçue sur la perception des consommateurs d’une marque innovante. Basée sur une revue de la littérature dans le domaine de la perception des innovations, un modèle d’analyse intégrant différentes dimensions a été proposé. Il intègre l’analyse de l’innovativité des consommateurs, mais également la mesure des attitudes implicites qui permettent l’enrichissement de la recherche. L’implémentation d’une expérimentation sur un échantillon représentatif de la population et l’analyse des données à l’aide des équations structurelles permettront de proposer une validation du modèle.

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Section: L'attitudeunclassified

Modélisation du risque de la nouveauté perçue sur la perception d’une marque innovante

Hetet

Moutot

Mathieu

2015

RFGI

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“…A social network can therefore be defined as the result of relations that agents maintain among themselves, relative to a given question and not the exogenous variable of a given infrastructure (institutional, communications, etc. ), likely to sustain these relations (Steyer and Zimmermann, 2004). Hence, this structure based on affinity has more of a horizontal influence, capable of surpassing the top-down influence of mass media.…”

Section: The Limitations Of Mass Media and The Role Of Social Influencementioning

confidence: 99%

Web User Opinions as an Information Source. What Impact on Cinema Attendances?

Belvaux

Marteaux

2007

Recherche et Applications en Marketing (English Edition)

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Digital communication technologies such as the Internet intensify and accelerate the phenomenon of information diffusion by social exchange. The aim of this paper is to assess whether product introduction strategies should be modified in the light of this phenomenon. We conducted an empirical analysis on the movie market to compare the ability of web user opinions with classic indicators such as the mass media and critics to predict box-office takings. The results show that all three variables influence movie attendances. Promotion of a movie has no influence on web user opinions, but critics are influenced negatively for low-budget movies and positively for large-budget movies. Critic and web user advice merges only for large-budget movies.

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“…Network neighbors may influence each other to make similar choices, but conversely, agents might decide to reinforce or reduce their interactions depending on their affinitiy, that is the similarity of their decisions, leading to a complex interplay between network evolution and adoption. This approach has been taken for example by Steyer and Zimmermann [40]. However, the more basic question of how a fixed network structure influences this type of coordination process is already interesting.…”

Section: Motivationsmentioning

confidence: 99%

Diffusion of Innovations on Community Based Small Worlds: The Role of Correlation between Social Spheres

Tanimura

2010

SSRN Journal

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SummaryWhich types of networks favor the diffusion of innovations in the sense that an innovation whose intrinsic benefits are greater than those of an established choice will be able to replace the latter when it is initially used only by a small fraction of a large population? For deterministic and regular networks there are characterizations, based on a coordination game model of the diffusion of innovations. Here we study this question for a class of irregular random networks, Small world networks, which are of interest as more realistic models of social networks. We consider a random graph model based on a community structure, in which the choice of a parameter allows us to obtain as special cases several well known models, in particular Watts' Small world. We show that there are different types of Small World graphs some which favor diffusion, others that do not. Our study suggests that the kinds of ties that exist between different communities of an individual play an important role. We interpret Watts' Small World as one with high correlation between social spheres of individuals and favorable to diffusion. In other Small Worlds where the communities of individuals are uncorrelated diffusion succeeds only for very large payoff benefits in favor of the innovation. Abstract: Which types of networks favor the diffusion of innovations in the sense that an innovation whose intrinsic benefits are greater than those of an established choice will be able to replace the latter when it is initially used only by a small fraction of a large population? For deterministic and regular networks there are characterizations, based on a coordination game model of the diffusion of innovations. Here we study this question for a class of irregular random networks, Small world networks, which are of interest as more realistic models of social networks. We consider a random graph model based on a community structure, in which the choice of a parameter allows us to obtain as special cases several well known models, in particular Watts' Small world. We show that there are different types of Small World graphs some which favor diffusion others that do not. Our study suggests that the kinds of ties that exist between different communities of an individual play an important role. We interpret Watts' Small World as one with high correlation between social spheres of individuals and favorable to diffusion. In other Small Worlds where the communities of individuals are uncorrelated diffusion succeeds only for very large payoff benefits in favor of the innovation. Keywords

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Influence sociale et diffusion de l'innovation

Cited by 14 publications

References 14 publications

Modélisation du risque de la nouveauté perçue sur la perception d’une marque innovante

Modélisation du risque de la nouveauté perçue sur la perception d’une marque innovante

Web User Opinions as an Information Source. What Impact on Cinema Attendances?

Diffusion of Innovations on Community Based Small Worlds: The Role of Correlation between Social Spheres

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