Abstract

Innovations often spread by the communication of information among potential adopters. In the marketing literature, the standard model of new product diffusion is generated by information contagion: agents adopt once they hear about the existence of the product from someone else. In social learning models, by contrast, an agent adopts only when the perceived advantage of the innovation - as revealed by the actions and experiences of prior adopters - exceeds a threshold determined by the agent's prior beliefs. We demonstrate that learning with heterogeneous priors generates adoption curves that have an analytically tractable, closed-form solution. Moreover there is a simple statistical test that discriminates between this type of process and a contagion model. Applied to Griliches' classic results on the adoption of hybrid corn, this test shows that learning with heterogeneous priors does a considerably better job of explaining the data than does the contagion model.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.