2003
DOI: 10.1016/s0378-8733(02)00050-3
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Statistical analysis of network data—an application to diffusion of innovation

Abstract: General methodology is developed here to deal with the association between a a binary variable and network connections with or without confounding covariates. Also the case when the network is observed at several time periods is treated. As an application we consider the diffusion of organic farming in the province of North Karelia in Finland. It turns out that organic farms are more clustered than would be expected under pure random allocation. The neighborhood effect remains when adjusting for the production… Show more

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Cited by 64 publications
(39 citation statements)
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“…Moreover, even within this area, clustered patterns of adoption were evident on the landscape, that seem to grow out of farmer-to-farmer interactions in the Kickapoo Valley region of this study [40]. This pattern of clustering of organic dairy farmers was also evident in other geographic areas [41,42]. In this particular region, there is a growing proportion of dairy farms being owned by Amish farmers (about 10% of the state's dairy) [43].…”
Section: Bounded Rationality In Organic Dairy Adoption Decisionssupporting
confidence: 48%
“…Moreover, even within this area, clustered patterns of adoption were evident on the landscape, that seem to grow out of farmer-to-farmer interactions in the Kickapoo Valley region of this study [40]. This pattern of clustering of organic dairy farmers was also evident in other geographic areas [41,42]. In this particular region, there is a growing proportion of dairy farms being owned by Amish farmers (about 10% of the state's dairy) [43].…”
Section: Bounded Rationality In Organic Dairy Adoption Decisionssupporting
confidence: 48%
“…Finally, (real and virtual) social networks matter for the establishment of new consumption patterns. They can contribute significantly to a diffusion of consumers' behavioral patterns and values (Robertson et al 1996;Valente 1996;Nyblom et al 2003;Deffuant et al 2005). Recent studies show that attitudes are substantial for the development of social relationships and that, in turn, social relationships considerably influence behavior and attitudes.…”
Section: Innovation In Knowledgebased Societiesmentioning
confidence: 99%
“…However, these models are very restrictive because they imply an absence of asymmetries, intransitivity or subgroups in the existing relationships in the network. Nyblom et al (2003) have put forward a recent application of this type of model. Beyond these general models, the effects of technology-based networks on innovative behaviour and attitudes can also be predicted by analysing the structure of relations at different levels: nodal (individual), diadic, triadic, subgroup and whole network (Cf.…”
Section: Spatial Proximitymentioning
confidence: 99%