We propose a utility-theoretic brand-choice model that accounts for four different sources of state dependence: 1. effects of lagged choices (), 2. effects of serially correlated error terms in the random utility function (), 3. effects of serial correlations between utility-maximizing alternatives on successive purchase occasions of a household (), and 4. effects of lagged marketing variables (). Our proposed model also allows habit persistence to be a function of lagged marketing variables, while accommodating the effects of unobserved heterogeneity in household choice parameters. This model is more flexible than existing state-dependence models in marketing and labor econometrics. Using scanner panel data, we find structural state dependence to be the most important source of state dependence. Marketing-mix elasticities are systematically understated if state-dependence effects are incompletely accounted for. The Seetharaman and Chintagunta (1998) model is shown to recover spurious variety-seeking effects while overstating habit-persistence effects. Ignoring habit persistence type 1 leads to an underestimation, while ignoring habit persistence type 2 leads to an overestimation of structural state-dependence effects. We find lagged promotions to have carryover effects on habit persistence. Ignoring one or more sources of state dependence underestimates the total incremental impact of a sales promotion. We draw implications for manufacturer pricing.brand choice, state dependence, habit persistence, lagged choices, lagged utilities, serial correlation, distributed lags, marketing carryover, random utility

Brand choices over time are dictated not just by households' intrinsic brand preferences, but also by marketing variables and state dependence effects. The authors examine brand choice behavior across five product categories as a function of these variables. Choice within a category is modeled with a multinomial probit model. A Bayesian variance components approach is used to model the covariation of household response parameters across categories. The model enables the authors to identify similarities in households' state dependence effects across categories. On the basis of purchase data from a panel of 785 households, they also (1) estimate the correlations between household parameters for the marketing mix and state dependence, (2) study whether state dependence effects diminish over time, (3) investigate whether state dependence for a household is related to its demographic and behavioral characteristics, and ( 4) analyze whether category variables influence state dependence.The results indicate that households display similar state dependence effects across the five categories, with two categories exhibiting significantly lower state dependence levels than the other three. Furthermore, significant correlations exist between state dependence effects and marketing mix sensitivities. A household's level of brand choice inertia diminishes with time elapsed since the previous purchase. State dependence is influenced by shopping behavior variables but not by demographics.

No abstract

The authors examine factors that affect product-usage compliance, or the act of using a product as it is intended to be used. They develop a conceptual model of compliant behavior as a function of four main constructs: (1) salience/mindfulness, (2) the consumer's costs and benefits of compliant behavior, (3) advertising and distribution cues to action, and (4) the perceived threats associated with noncompliant behavior. They test the model using a regression mixture model of compliant behavior calibrated on unique panel data from four categories of pharmaceutical drugs that are used to treat chronic (i.e., lifelong) ailments. The findings include insights into the dynamics of product compliance: The data support the proposed four-stage evolution of compliant behavior between consecutive service provider (e.g., doctor) interventions. For marketers, the authors find substantial heterogeneity across consumers for the effects of cues from advertising and distribution. For example, in some segments, advertising has a positive impact on compliance (directly and/or by heightening responsiveness to product-efficacy evaluations), whereas in other segments, its effect is negative. Thus, the authors shed new light on the effects of advertising, which has both strong advocates and opponents in the pharmaceutical industry. Determinants of Product-Use Compliance BehaviorCompliance is the conformity or adapting to another person's wishes, to a rule, or to necessity. Areas of interest regarding compliance and its applications to consumer marketing include compliance with social programs and with a product's intended use. In professional services contexts such as health care, lack of compliance can negatively affect manufacturers, service providers, and users (The Wall Street Journal 2003). For manufacturers, noncompliance can lower a product's perceived performance, thus leading to decreased consumer satisfaction. In pharmaceuticals, the loss in future sales due to brand switching and negative word-of-mouth as a result of perceived product failure caused by noncompliance has been estimated to cost companies $15 billion to $20 billion annually (Beavers 1999).

The authors propose an empirical procedure to investigate the pricing behavior of manufacturers and retailers in the presence of state-dependent demand. Rather than assuming that firms are perfectly forward looking and therefore solving accordingly for dynamic equilibriums that would arise in the presence of state dependence, the authors systematically evaluate whether boundedly rational firms indeed look ahead when they set prices and, if so, to what extent. They illustrate the procedure using household-level scanner-panel data on breakfast cereals and replicate the substantive results using data on ketchup. The authors find that (1) omission of state dependence in demand biases inference of firm behavior (i.e., tacit collusion is erroneously inferred when firms are competitive); (2) observed retail prices are consistent with a pricing model in which both manufacturers and retailers are forward looking (i.e., they incorporate the effects of their current prices on their future profits), but firms have short time horizons when setting prices (i.e., they look ahead by only one period, suggesting that firms are boundedly rational in their dynamic pricing behavior); and (3) even a myopic pricing model of firms that accounts for state dependence in demand is a reasonable approximation of the observed prices in the market.