|
Activity Number:
|
237
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Tuesday, July 31, 2007 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Bayesian Statistical Science
|
| Abstract - #309584 |
|
Title:
|
Disentangling Preferences, Inertia, and Learning in Brand Choice Models
|
|
Author(s):
|
Sangwoo Shin*+ and Sanjog Misra and Dan Horsky
|
|
Companies:
|
University of Rochester and University of Rochester and University of Rochester
|
|
Address:
|
Simon Graduate School of Business, Rochester, NY, 14607,
|
|
Keywords:
|
Preferences ; Learning ; Choice ; Heterogeneity ; Scanner ; RJMCMC
|
|
Abstract:
|
Using a unique dataset that contains stated preferences and actual purchase data for the same group of consumers we attempt to untangle the effects of preference heterogeneity and state dependence, and to determine the exact nature of the latter. We propose a hierarchical model in which consumers are heterogeneous in the order of the brand choice process as well as in their preferences and responsiveness to marketing mix. The proposed model is designed to encompass three different types of consumer experience based behavior: zero-order, inertia, and learning. We apply a Reversible Jump MCMC sampling scheme to sample across component processes and a Metropolis-Hastings/Gibbs step within each component process. Our results suggest that the extent of state dependence/preference heterogeneity is spuriously over/underestimated in the absence of preference information.
|
