The Stochastic Modeling of Purchase Intentions and Behavior
A common objective of social science and business research is the modeling of the relationship between demographic/psychographic characteristics of individuals and the likelihood of certain behaviors for these same individuals. Frequently, data on actual behavior are unavailable; rather, one has available only the self-reported intentions of the individual. If the reported intentions imperfectly predict actual behavior, then any model of behavior based on the intention data should account for the associated measurement error, or else the resulting predictions will be biased. In this paper, we provide a method for analyzing intentions data that explicitly models the discrepancy between reported intention and behavior, thus facilitating a less biased assessment of the impact of designated covariates on actual behavior. The application examined here relates to modeling relationships between demographic characteristics and actual purchase behavior among consumers. A new Bayesian approach employing the Gibbs sampler is developed and compared to alternative models. We show, through simulated and real data, that, relative to methods that implicitly equate intentions and behavior, the proposed method can increase the accuracy with which purchase response models are estimated.
Volume (Year): 44 (1998)
Issue (Month): 2 (February)
|Contact details of provider:|| Postal: |
Web page: http://www.informs.org/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:44:y:1998:i:2:p:188-202. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.