Multicategory Purchase Incidence Models for Partitions of Product Categories |
| |
| Authors: | Harald Hruschka |
| |
| Affiliation: | Faculty of Economics, University of Regensburg, Germany |
| |
| Abstract: | We analyze multicategory purchases of households by means of heterogeneous multivariate probit models that relate to partitions formed from a total of 25 product categories. We investigate both prior and post hoc partitions. We search model structures by a stochastic algorithm and estimate models by Markov chain Monte Carlo simulation. The best model in terms of cross‐validated log‐likelihood refers to a post hoc partition with two groups; the second‐best model considers all categories as one group. Among prior partitions with at least two category groups a five‐group model performs best. Effects on average basket value differ for the model with five prior category groups from those for the best‐performing model in 40% and 24% of the investigated categories for features and displays, respectively. In addition, the model with five prior category groups also underestimates total sales revenue across all categories by about 28%. Copyright © 2016 John Wiley & Sons, Ltd. |
| |
| Keywords: | multicategory purchase models promotion effects multivariate probit Markov chain Monte Carlo stochastic model search |
|
|
