Using daily store-level data to understand price promotion effects in a semiparametric regression model |
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| Institution: | 1. Ordina VisionWorks, P.O. Box 2025, NL-9704 CA Groningen, The Netherlands;2. University of Groningen, Faculty of Economics and Business, Department of Marketing, P.O. Box 800, NL-9700 AV, Groningen, The Netherlands;3. CPB Netherlands Bureau for Economic Policy Analysis, P.O. Box 80510, 2508 GM, Den Haag, The Netherlands;1. The Belk College of Business, University of North Carolina at Charlotte, Charlotte, 28213 U.S.A.;2. Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, 200030, China;3. The Belk College of BusinessUniversity of North Carolina at Charlotte, Charlotte, 28213 U.S.A. |
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| Abstract: | Though it has been widely reported in the marketing literature that temporary price discounts generate substantial short-term sales increase, the shape of the deal effect curve constitutes a key research topic, for which there are still limited empirical results. To address this issue, a semiparametric regression approach is used to model the complex nature of this phenomenon. Our model is developed at the brand level using daily store-level scanner-data, which allows the study of several nonreported promotional effects, such as the influence of the day of the week both in promotional and nonpromotional periods. The results show that the weekend is the most effective in increasing promotional sales and that asymmetric and neighborhood effects hold. However, 9-ending promotional prices are not impactful. |
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