A method to infer coupon availability from coupon redemption in the supermarket scanner panel data |
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| Institution: | 1. School of Politics and Public Administration, Soochow University, No.199 Ren''ai Street, Wuzhong District, Suzhou City, Jiangsu Province, China;2. School of Economics and Management, Nanjing University of Science and Technology, No.200 Xiaolingwei Street, Xuanwu District, Nanjing City, Jiangsu Province, China;3. QUT Business School, Queensland University of Technology, 2 George Street, Brisbane, Queensland, Australia;1. Marketing Academic and Professional Department, ICN Business School, 2 Place de la Défense, 92053, Paris, France;2. School of Business Administration, TELUQ University, 5800 Saint-Denis – Office #11.05, Montreal, QC, H2S 3L5, Canada;3. Marketing Department, ESG UQAM, 315 St Catherine St E, Montreal, Quebec, H2X 3X2, Canada;1. Qatar University, Qatar;2. Liverpool John Moores University, United Kingdom;1. School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, China;2. Department of Management and Management Information Systems, School of Business, University of West Florida, Pensacola, FL, USA;1. Business School Graduate Program (PPAD), Pontifical Catholic University of Parana (PUCPR), Imaculada Conceição, 1155, Zip code 80215-901 Curitiba, PR, Brazil;2. Business Management Graduate Program (DAGA), Department of General Administration and applied, Federal University of Parana (UFPR), 632 Lothário Meissner Ave, Jardim Botânico, Zip code 80210-170 Curitiba, PR, Brazil;3. Industrial and Systems Engineering Graduate Program (PPGEPS), Pontifical Catholic University of Parana (PUCPR), Imaculada Conceição, 1155, Zip code 80215-901 Curitiba, PR, Brazil;4. Electrical Engineering Graduate Program (PPGEE), Department of Electrical Engineering, Federal University of Parana (UFPR), Polytechnic Center, CP 19011, Zip code 81531-980 Curitiba, PR, Brazil |
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| Abstract: | Measuring the impact of coupon availability on consumers’ purchase decisions often poses a problem in forecasting market shares of brands in a retail environment. Because, data on actual coupon availability do not exist or can only be obtained by costly field experiments. The widely used supermarket scanner panel data sets offer information on coupons redeemed by the household for only the specific brand that is bought. However, using the redemption variable introduces bias in brand choice or purchase incidence models because redeeming a coupon implies buying the brand or making the purchase. This study presents a way to infer availability from coupon redemption data and to predict market shares for each brand in a supermarket product category. |
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