Abstract
A firm launching a new product in an existing category can leverage comparative messages to provide information to customers and to distinguish it from others. Incumbents, on the other hand, benefit less from comparative messaging as this could be interpreted as providing legitimacy to the entrant. In our empirical context in a pharmaceutical category, we see both incumbents and entrants employing comparative messages during their detailing visits. To incorporate the effects of comparative messaging, we develop a learning model of doctor prescription behavior. The model has three distinguishing features relative to the standard Bayesian learning framework. First, the information efficiency associated with the detailing visits differ across message formats (comparative vs. non-comparative) and brands. Second, comparative messages from competing brands can “jam” or disrupt a doctor’s learning of a drug’s quality. Finally, the doctors can “forget” the quality of a drug with the time elapsed from the last prescription. We estimate the model using a physician panel in a therapeutic category with one existing and two new drugs. We estimate the proposed model in a Hierarchical Bayesian framework. Counterfactual experiment characterizes the impact of banning comparative messages, a practice followed in many countries other than the U.S.
Published Version
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