Local Neighborhoods As Early Predictors of Innovation Adoption

We investigate whether certain network neighborhoods are reliable predictors of overall network adoption. We show analytically that for success-failure predictions, random samples are less useful than specific clusters in the network. The empirical results show that certain neighborhoods do predict adoption better than random and stratified samples.



Citation:

Jacob Goldenberg , Sangman Han , Donald R. Lehmann , Jangyuk Lee, Kyung Young Ohk , and Daniel Shapira (2012) ,"Local Neighborhoods As Early Predictors of Innovation Adoption", in NA - Advances in Consumer Research Volume 40, eds. Zeynep Gürhan-Canli, Cele Otnes, and Rui (Juliet) Zhu, Duluth, MN : Association for Consumer Research, Pages: 232-235.

Authors

Jacob Goldenberg , Hebrew University of Jerusalem, Israel
Sangman Han , Sungkyunkwan University, South Korea
Donald R. Lehmann , Columbia University, USA
Jangyuk Lee, Sungkyunkwan University, South Korea
Kyung Young Ohk , Sungkyunkwan University, South Korea
Daniel Shapira , Sungkyunkwan University, South Korea



Volume

NA - Advances in Consumer Research Volume 40 | 2012



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