In the social sciences, it is often useful to introduce latent variables and use structural equation modeling to quantify relations among observable and latent variables. This paper presents a manual, describing how to estimate structural equation models in a Bayesian approach with R. Parameter...

Distributional assumptions for random utility models play an important role in relating observed product attributes to choice probabilities. Choice probabilities derived with independent errors have the IIA property, which often does not match consumer behavior and leads to inaccurate source of...

Research in marketing, and business in general, involves understanding when effect-sizes are expected to be large and when they are expected to be small. Understanding the contexts in which consumers are sensitive to offers, and variables such as price, is an important aspect of merchandising,...