The effect of data preprocessing on a retail price optimization system
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- 作者：Timo P. Kunza ; 1 ; t.p.kunz@lancaster.ac.uk" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Sven F. Cronea ; 1 ; s.crone@lancaster.ac.uk" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Joern Meissnerb ; 2 ; joern.meissner@the-klu.org" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Revenue management ; Price optimization system ; Retail pricing ; Demand modeling ; Retail scanner data
- 刊名：Decision Support Systems
- 出版年：2016
- 出版时间：April 2016
- 年：2016
- 卷：84
- 期：Complete
- 页码：16-27
- 全文大小：1775 K
文摘
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The effect of the two popular data preprocessing techniques, pruning and aggregation, on a retail price optimization system is analyzed.
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The study uses real retail scanner data as well as synthetically data generated within empirical valid parameter bounds.
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The decision support system is based on different configurations of combining a multinomial choice market share model with a linear category model.
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The interplay of the system components is analyzed and the loss in profit optimality induced by the data preprocessing techniques is quantified.
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Data pruning and aggregation affect the optimality of retail prices differently, depending on the underlying data and model conditions.