An aggregate contextual choice model for estimating demand for new products from a laboratory choice experiment

An aggregate contextual choice model (ACCM) is presented and 2 alternative error theories are developed that lead to multinomial maximum likelihood and least-squares estimation procedures. The model is used to estimate demand for 2 new product concepts in a reduced design laboratory choice experimen...

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Bibliographic Details
Published in:Journal of business research 1991-11, Vol.23 (3), p.201-218
Main Authors: Lakshmi-Ratan, Ramnath A., Lanning, Steven G., Rotondo, John A.
Format: Article
Language:English
Subjects:
Comparative studies
Consumer behavior
Decision making models
Demand
Laboratories
Predictions
Product development
Regression analysis
Theory
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Summary:An aggregate contextual choice model (ACCM) is presented and 2 alternative error theories are developed that lead to multinomial maximum likelihood and least-squares estimation procedures. The model is used to estimate demand for 2 new product concepts in a reduced design laboratory choice experiment. The results of the comparison between the ACCM and the Luce constant utility model strongly favor the context-sensitive model over the Luce model. Furthermore, it is shown that the context-sensitive model is easily transformed so that the least-squares method produces results that are very close to maximum likelihood estimates.
ISSN:0148-2963
1873-7978
DOI:10.1016/0148-2963(91)90030-2