This research was supported by the Deutsche

The literature on store loyalty views a consumer as possessing store loyalty towards a particular store for her/his overall grocery shopping needs. In this study, we show that store loyalty is a category-specific trait of a consumer. In other words, while a given customer may be

In usual practice, brand-choice models are specified and estimated from purchase data, ignoring those observations where category incidence does not occur, i.e. the no-purchase observations. This practice can be problematic if there are unobservable factors that affect both the no-purchase and brand-choice decisions. Under such a correlation, it is important to simultaneously model the no-purchase and brand-choice decisions. This paper is an effort in this direction. We propose a model suitable for scanner panel data in which the nopurchase decision depends on the price, feature and display of each brand in the category and the household’s stock of inventory. This no-purchase model is linked to the brand-choice outcome through marketing-mix covariates and, importantly, through unobservables that affect both outcomes. Model parameters are assumed to be heterogeneous across households with the coefficients in the no-purchase model correlated with those in the brand-choice model in a completely general way. This model formulation is more general than what is possible from either a nested logit model or a translog utility model and from models in which the no-purchase outcome is modeled as an additional outcome with the deterministic component of its utility set equal to zero. Estimation of the proposed model is by Bayesian Markov Chain Monte Carlo methods (Chib and Greenberg 1995, 1998) based on the approach of Albert and Chib (1993). The estimation methods are applied to scanner panel data on the

www.elsevier.com/locate/ijresmar Probabilistic versus random-utility models of state dependence: an empirical comparison P.B. Seetharaman*

Abstract not found

The literature on store loyalty views a consumer as possessing store loyalty toward a particular store for her or his overall grocery shopping needs. In this study, we examine store loyalty as a category-specific trait, i.e., a consumer could be loyal to Store A in category 1, but loyal to Store B in category 2. We call this store-category loyalty (SCL). We enumerate 10 key drivers – variables relating to product assortments and prices of categories across stores, as well as category characteristics – of SCL and their expected effects. In addition, we also discuss the effects of 2 consumer characteristics (demographics) on SCL. We use a Hierarchical Bayes Multinomial Logit (HB-MNL) model to test our hypotheses using an in-home scanning panel dataset of 1321 households in 284 grocery categories across 16 stores over a 53-week period. The results show that a variety of key drivers and consumer characteristics affect SCL in line with our predictions. We illustrate the managerial implications of our findings, for example, by deriving revenue consequences to stores from changing some of the marketing levers, i.e., variables related to product assortments and prices, which are in their control.