Estimating demand for wide assortments of differentiated goods requires the specification of a demand system that is sufficiently flexible. However, flexible models are highly parameterized so estimation requires appropriate forms of regularization to avoid overfitting. In this paper, we study...

In this study, we explore the issue of how to enhance forecast of the box office sales, an all-time question for managers in the motion picture industry. The conceptual core of our approach is the expected sales. The expected sales of agents in the movie market (i.e. screen managers at supply...

We review applications of Bayesian methods to marketing problems. Key aspects of marketing applications include the discreteness of response or outcome data and relatively large numbers of cross-sectional units, each with possibly low information content. The use of informative priors including...

We discuss our experiences teaching Bayesian Statistics to students in doctoral programs in business. These students often have weak backgrounds in mathematical statistics and a predisposition against likelihood-based methods stemming from prior exposure to econometrics. This can be overcome by...

Two Bayesian optimal design criteria for hierarchical linear models are discussed - the psi_beta criterion for the estimation of individual-level parameters beta, and the psi_theta criterion for the estimation of hyper-parameters theta. While the psi_beta criterion involves only the...