In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate...

The segmentation of customers on multiple bases is a pervasive problem in marketing research. For example, segmentation service providers partition customers using a variety of demographic and psychographic characteristics, as well as an array of consumption attributes such as brand loyalty,...

Random coefficients choice models are seeing widespread adoption in marketing research, partly because of their ability to generate household-level parameter estimates with limited data. However, the power of such models may tempt researchers to trust that they continue to produce reasonable...

This study compares the effectiveness of statistical model-based (MB) clustering methods with that of more commonly used non model-based (NMB) procedures in three important contexts: the traditional cluster analysis problem in which a set of consumer characteristic variables is used to form...

There is theoretical and empirical evidence that consumers have limited cognitive resources and thus cannot maintain direct preferences for each choice alternative on the store shelves. Instead, they likely form their overall preferences for choice alternatives by evaluating the attributes...