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dc.contributor.authorReimer, Kerstinen_US
dc.contributor.authorAlbers, Sönkeen_US
dc.date.accessioned2011-10-25T13:48:20Z-
dc.date.available2011-10-25T13:48:20Z-
dc.date.issued2011-10-25T13:48:20Z-
dc.identifier.urihttp://hdl.handle.net/10419/50730-
dc.description.abstractPredicting online customer repeat purchase behavior by accounting for the marketing-mix plays an important role in a variety of empirical studies regarding individual customer relationship management. A number of sophisticated models have been developed for different forecasting purposes based on a – mostly linear – combination of purchase history, so called Recency-Frequency-Monetary Value (RFM)-variables and marketing variables. However, these studies focus on a high predictive validity rather than ensuring that their proposed models capture the original effects of marketing activities. Thus, they ignore an explicit relationship between the purchase history and marketing which leads to biased estimates in case these variables are correlated. This study develops a modeling framework for the prediction of repeat purchases that adequately combines purchase history data and marketing-mix information in order to determine the original impact of marketing. More specifically, we postulate that RFM already captures the effects of past marketing activities and the original marketing impact is represented by temporal changes from the purchase process. Our analysis highlights and confirms the importance of adequately modeling the relationship between RFM and marketing. In addition, the results show superiority of the proposed model compared to a model with a linear combination of RFM and marketing variables.en_US
dc.language.isoengen_US
dc.publisherZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft Kiel und Hamburgen_US
dc.relation.ispartofseriesArbeitspapiere des Instituts für Betriebswirtschaftslehre, CAU Kiel-
dc.subject.jelM3en_US
dc.subject.jelC4en_US
dc.subject.ddc330-
dc.subject.keywordRepeat Purchase Forecasting Modelsen_US
dc.subject.keywordMarketing Actionsen_US
dc.subject.keywordGeneralized Bass Modelen_US
dc.subject.keywordMedia Downloadsen_US
dc.titleModeling Repeat Purchases in the Internet when RFM Captures Past Influence of Marketingen_US
dc.typeWorking Paperen_US
dc.identifier.ppn682420638-
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:esprep:50730-
Appears in Collections:Working and Discussion Papers / Arbeits- und Diskussionspapiere, EconStor Direct
Arbeitspapiere des Instituts für Betriebswirtschaftslehre, CAU Kiel

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