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Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion

This study documents an investigation into the adoption and diffusion of eave tubes, a novel mosquito vector control, during a large-scale scientific field trial in West Africa. The diffusion of innovations (DOI) and the integrated model of behavior (IMB) were integrated (i.e., innovation attributes...

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Detalles Bibliográficos
Autores principales: Smith, Rachel A, Kim, Youllee, Zhu, Xun, Doudou, Dimi Théodore, Sternberg, Eleanore D., Thomas, Matthew B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Routledge 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176755/
https://www.ncbi.nlm.nih.gov/pubmed/29447581
http://dx.doi.org/10.1080/10810730.2018.1434259
Descripción
Sumario:This study documents an investigation into the adoption and diffusion of eave tubes, a novel mosquito vector control, during a large-scale scientific field trial in West Africa. The diffusion of innovations (DOI) and the integrated model of behavior (IMB) were integrated (i.e., innovation attributes with attitudes and social pressures with norms) to predict participants’ (N = 329) diffusion intentions. The findings showed that positive attitudes about the innovation’s attributes were a consistent positive predictor of diffusion intentions: adopting it, maintaining it, and talking with others about it. As expected by the DOI and the IMB, the social pressure created by a descriptive norm positively predicted intentions to adopt and maintain the innovation. Drawing upon sharing research, we argued that the descriptive norm may dampen future talk about the innovation, because it may no longer be seen as a novel, useful topic to discuss. As predicted, the results showed that as the descriptive norm increased, the intention to talk about the innovation decreased. These results provide broad support for integrating the DOI and the IMB to predict diffusion and for efforts to draw on other research to understand motivations for social diffusion.