Marketing Models of Consumer Demand
AbstractMarketing researchers have used models of consumer demand to forecast future sales; to describe and test theories of consumer behavior; and to measure the response to marketing interventions. The basic framework typically starts from microfoundations of expected utility theory to obtain a statistical system that describes consumers' choices over available options, and to thus characterize product demand. The basic model has been augmented significantly to account for quantity choice decisions; to accommodate purchases of several products on a single purchase occasion (multiple discreteness and multi-category purchases); and to allow for asymmetric switching between brands across different price tiers. These extensions have enabled researchers to bring the analysis to bear on several related marketing phenomena of interest. This paper has three main objectives. The first objective is to articulate the main goals of demand analysis-forecasting, measurement and testing--and to highlight the desiderata associated with these goals. Our second objective is describe the main building blocks of individual-level demand models. We discuss approaches built on direct and indirect utility specifications of demand systems, and review extensions that have appeared in the marketing literature. The third objective is to explore interesting emerging directions in demand analysis including considering demand-side dynamics; combining purchase data with primary information; and using semiparametric and nonparametric approaches. We hope researchers new to this literature will take away a broader perspective on these models and see potential for new directions in future research.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Stanford University, Graduate School of Business in its series Research Papers with number 2072.
Date of creation: Nov 2010
Date of revision:
Contact details of provider:
Postal: Stanford University, Stanford, CA 94305-5015
Phone: (650) 723-2146
Web page: http://gsbapps.stanford.edu/researchpapers/
More information through EDIRC
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jean-Pierre H. Dubé & Günter J. Hitsch & Pradeep K. Chintagunta, 2010. "Tipping and Concentration in Markets with Indirect Network Effects," Marketing Science, INFORMS, vol. 29(2), pages 216-249, 03-04.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.