Cebollada Calvo, Javier
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Cebollada Calvo
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Javier
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Gestión de Empresas
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INARBE. Institute for Advanced Research in Business and Economics
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Publication Open Access An investigation of multichannel shopping behavior: evolution in a grocery retailer in Spain(Nova Science Publications, 2015) Arce Urriza, Marta; Cebollada Calvo, Javier; Villanueva Orbaiz, María Luisa; Gestión de Empresas; Enpresen KudeaketaE-commerce in Spain is growing year by year, boosted mainly by the positive evolution of three variables such as: the percentage of Internet users, the proportion of Internet shoppers, and the average online spending per shopper. However, although grocery retailers were among the first marketers to incorporate the Internet as an additional shopping channel online grocery shopping in Spain is still low. In this work we analyze the evolution of the online shopping behavior for groceries for the same groups of clients of one of the major grocery retailers in Spain in a 4 years elapsed time. This chain was a pioneer selling groceries online, opening its online store in 2001. To do so, we analyze the purchase behavior of the clients per channel (offline and online), and the characteristics of the shopping baskets per client at each purchase occasion or trip. We also classify customers evaluating their use of the two channels.Publication Open Access Online category pricing at a multichannel grocery retailer(Elsevier, 2019) Cebollada Calvo, Javier; Chu, Yanlai; Jiang, Zhiying; Gestión de Empresas; Enpresen KudeaketaAs the importance of online grocery shopping increases, both pure-play online grocers and multichannel grocers are likely to be interested in setting optimal prices for their online stores. We use a unique household scanner panel dataset to investigate how a grocery retailer with both online and offline stores can set prices for its online store. We observe the same households shopping interchangeably at the online and offline stores of the same grocery chain and investigate their purchase behavior in specific product categories. We find that across three product categories, these households exhibit lower price sensitivities when shopping online than offline. In addition, a household's price sensitivity is inversely related to distance to the closest physical store. We compute the retailer's category profit-maximizing prices for the online store and explore several alternative pricing schemes that are consistent with the retailer's current price image. We find that the retailer can substantially increase its profits from online operations by fine tuning its current pricing policy. Given the estimated inverse relationship between price sensitivity and store distance, we investigate online zone pricing as a price discrimination tool based on residential location and find that the retailer can further improve store profits. We examine the potential mechanism to assign zones and determine the optimal number of pricing zones.