marketing communication. The first effect refers to marketing communication that enables consumers to update their prior beliefs and reduce uncertainty about the true quality of the new product through a Bayesian learning process. Because marketing communication affects consumer utility indirectly through perceived product quality, we refer to it as the "indirect Bayesian learning effect," or simply "indirect effect." The second effect consists of all effects that are not indirect (e.g., reminder effects) that influence preferences through goodwill accumulation. Because this effect is manifest in a direct shift in consumer utility, we refer to it as the "direct goodwill effect," or "direct effect."Our empirical analysis uses data from a category of ethical drugs. In the pharmaceutical industry, direct marketing communication with physicians is usually referred to as detailing. Detailing comprises promotional visits made to physicians by pharmaceutical representatives. 1 The main sources of information considered by physicians to inform their current diagnoses and prescription decisions are detailing, meetings and conferences, and feedback from previous prescriptions. Additional sources of information include word of mouth and journal advertising. Our main focus is the effect of detailing on the evolution of physician prefer-

The authors empirically explore the revenue impact of marketing-mix variables and their interactions. The findings include the following: pharmaceutical direct-to-consumer advertising and detailing (sales force) affect demand synergistically, detailing raises price elasticity, and detailing has a higher return on investment than does direct-toconsumer advertising. The authors also discuss other implications and provide future research directions.

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Telephone services are often characterized by the presence of ‘fixed’ plans, involving only a fixed monthly fee, as well as ‘measured’ plans, with both fixed fees and per-unit charges for usage. Consumers are faced with the decisions of which plan to choose and how much to use the phone and these decisions are not, in general, independent. Due to the presence of a time lag between plan choice and usage decisions, consumers are uncertain about usage at the plan-choice stage. We develop a structural discrete/continuous model of plan choice and usage decisions of consumers that accounts for such uncertainty. Prior research has also found that consumers switch less often from fixed plans to measured plans to gain from potential savings than vice versa. Consumer uncertainty regarding their mean usage levels and different rates of learning by consumers in the two plans is a potential explanation for this phenomenon. We extend our discrete/continuous model to account for consumer learning about their mean usage and estimate different rates of learning for the two types of plans. We estimate our model using data from the 1986 Kentucky local telephone tariff experiment. Even in the absence of any price variation over time, we are able to measure the price elasticities both of usage and of choice of plan. Using our parameter estimates, we simulate the effects of the introduction of a metered plan in a market with only a fixed plan and vice versa, on both firm revenues and consumer surplus. We also find that consumers learn very rapidly if they are on the measured plan but learn very slowly when they are on the fixed plan. We investigate an alternative assumption on the nature of the learning process in which only consumers in the measured plan have an opportunity to learn. We find that our empirical results are robust to this change of specification. We conduct counterfactual simulations to simulate enhanced calling plans from the firm and consumer points of view. Additional simulations to measure the value of information in this category are also carried out. We compute the value of both complete information, where the entire uncertainty about future usage is resolved, as well as that of limited information, where the consumer's uncertainty about mean usage is resolved, but the uncertainty about specific month-to-month usage remains. We find that the value of information is modest. We also find that a large proportion of the value of information is that about the mean usage, with the value of the information about a specific month's usage being relatively small. Copyright Springer Science+Business Media, LLC 2007Self-selection, Uncertainty, Value of information, Discrete/continuous models, Learning models, Telecommunications, Optional calling plans,