Psychological indicators cross-classification based of innovation adoption: On need for cognition and need for change

Predicting how and when consumers will switch from a current familiar brand to anew option is a matter of concern for every level of new product introduction-from brand extensions to "really new" discontinuous innovations. In this article, we build on the innovativeness literature by investigating the degree to which 2 consumer characteristics, the need for cognition (N-cog) and the need for change (N-change), help explain individuals' propensity to choose new innovations versus status quo options. We demonstrate that by separating N-cog and N-change and cross-classifying; individuals based on these attributes, 4 unique patterns of change behavior emerge. A large-scale choice study was conducted by surveying metropolitan residents about changes in telecommunication services (local, long distance, and cellular). We use a latent class model to uncover the segmentation structure in the choice data, using the constructs as concommitant variables in the segment classification portion of the econometric model. The results show that the predicted theoretical structure explains observed data and can be used to significantly increase the predictive power of models of change behavior.