Brand and store managers are anxious to obtain high “loyalty,” as operationalized by repeat purchase behaviour. In this paper, we introduce the Repeated Binary Logit (RBL) model, which analyses directly the impact of covariates on repeat purchase, and which can be described as an extension of traditional logistic regression. We present empirical applications of RBL, and we discuss its relationships to several classical models.
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