Implications for Asymmetry, Nonproportionality, and Heterogeneity in Brand Switching from Piece-wise Exponential Mixture Hazard Models
开发了一类分段指数混合风险模型，用于分析品牌转换行为，允许营销变量的效应随时间非比例变化，并识别不同转换和重复购买行为的细分市场，在番茄酱扫描面板数据中验证了模型对不对称性、非比例性和异质性的解释力。
The authors develop a class of mixtures of piece-wise exponential hazard models for the analysis of brand switching behavior. The models enable the effects of marketing variables to change nonproportionally over time and can, simultaneously, be used to identify segments among which switching and repeat buying behavior differ. Several forms of asymmetry in brand switching are accommodated. The authors provide an application to the analysis of scanner panel data on ketchup, which illustrates the implications for asymmetry, nonproportionality, and heterogeneity. The results show that the model predicts purchases and purchase timing in holdout data better than the models proposed by Kamakura and Russell (1989) and Vilcassim and Jain (1991).