In multidimensional unfolding multidimensional scaling (MDS) procedures, the predicted utility of a brand for a consumer is inversely related to the distance between that consumer's ideal point and the brand position in the derived space. Most MDS models treat all brands the same regardless of...

This paper presents a multidimensional scaling model that is estimated on pick any/N choice data, and accommodates a broad range of context effects. The methodology estimates a set of parameters capturing the direction and magnitude of the context effects, as well as the locations of brands and...

The authors present a new measurement methodology of perceived value, based on latent structure multidimensional scaling, that derives simultaneously the underlying dimensions of the perceived value of various brands and market segment heterogeneity in terms of how such value evaluations are...

Proper market segmentation schemes should address not only how to develop feasible schemes of homogeneous market segments within designated managerial, institutional, and environmental restrictions, but also how to construct such schemes simultaneously in conjunction with associated resource...

This paper is concerned with the spatial representation of market structure calibrated on actual or intended choice data. Previous models developed for that purpose accommodate consumer heterogeneity by estimating parameters for each consumer, typically using the method of maximum likelihood....

We present a new Bayesian formulation of a vector multidimensional scaling procedure for the spatial analysis of binary choice data. The Gibbs sampler is gainfully employed to estimate the posterior distribution of the specified scalar products, bilinear model parameters. The computational...

We introduce a multidimensional scaling procedure that attempts to derive a spatial representation of stimuli unconfounded by the effect of subjects' degrees of familiarity with these stimuli. The proposed model assumes that stimulus unfamiliarity produces a tendency for a subject to anchor...

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...

This paper provides a general Structural Equation finite Mixture Model and algorithm (STEMM). Substantively, the model allows the researcher to simul­taneously treat heterogeneity and form groups in the context of a postulated causal (i.e., simultaneous equation regression) structure in which...

Multidimensional unfolding (MDU) is one of the most powerful conceptual and methodological tools used in marketing for product positioning analysis. Unfortunately, the majority of the commercial software programs available for performing such analyses (especially nonmetric analyses) suffer from...