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Two Stochastic Multidimensional Choice Models for Marketing Research
Author(s) -
Carroll J. Douglas,
Soete Geert De,
DeSarbo Wayne S.
Publication year - 1990
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1990.tb01689.x
Subject(s) - pairwise comparison , ideal point , computer science , goodness of fit , statistical model , probabilistic logic , product (mathematics) , point (geometry) , consumer choice , econometrics , mathematics , mathematical optimization , artificial intelligence , machine learning , marketing , business , geometry
Two recently developed probabilistic multidimensional models for analyzing pairwise choice data are introduced, discussed in terms of their differential properties, and extended in several ways. The first one, the wandering vector model, was originally suggested by Carroll [12] and extended by De Soete and Carroll [30]. The second model, called the wandering ideal point model, is a more recently proposed [32] unfolding analog of the wandering vector model. A general maximum likelihood estimation method for fitting the various models described is mentioned, as well as a statistical test for assessing the goodness of fit. Finally, an application of the models is provided concerning consumer choice for some 14 brands of over‐the‐counter analgesics to illustrate how such models can be gainfully utilized for marketing decision making concerning product positioning.