Hruschka, Harald (2017) Multicategory Purchase Incidence Models for Partitions of Product Categories. JOURNAL OF FORECASTING, 36 (3). pp. 230-240. ISSN 0277-6693, 1099-131X
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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 (c) 2016 John Wiley & Sons, Ltd.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BASKET; multicategory purchase models; promotion effects; multivariate probit; Markov chain Monte Carlo; stochastic model search |
| Subjects: | 300 Social sciences > 330 Economics |
| Divisions: | Business, Economics and Information Systems > Institut für Betriebswirtschaftslehre > Lehrstuhl für Marketing (Prof. Dr. Harald Hruschka) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 14 Dec 2018 13:00 |
| Last Modified: | 12 Feb 2019 10:25 |
| URI: | https://pred.uni-regensburg.de/id/eprint/175 |
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