Abstract

The two main influences leading to adoption at the individual consumer level are marketing communication and interpersonal communication. Although evidence of the effect of these two influences is abundant at the market level, there is a paucity of research documenting the simultaneous effect of both influences at the individual consumer level. Thus, the primary objective of this paper is to fill the gap in the literature by documenting the existence and magnitude of both influences at the individual customer level while controlling for unobserved temporal effects. The pharmaceutical industry provides an appropriate context to study this problem. It has been conjectured that adoption and usage patterns of a new drug by physicians—“contagion”—acts as a “consumption externality,” as it allows a given physician to learn about the efficacy and use of the drug. In addition, pharmaceutical companies target individual physicians via marketing activities such as detailing, sampling, and direct-to-consumer advertising. Our data contain the launch of a new drug from an important drug category. We chose two unrelated markets (Manhattan and Indianapolis) for our empirical analysis. We model an individual physician's decision to adopt a new drug in a given time period as a binary choice decision. This decision is modeled as a function of temporal trends (linear and quadratic) and individual physician-level contagion and marketing activity (both individual level and market level). Our contagion measure aggregates the adoption behavior of geographically near physicians for each physician in our sample. Our results from the Manhattan market indicate that both targeted communication and contagion have an effect on the individual physician's adoption decision. A major challenge is to rule out alternative explanations for the detected contagion effect. We therefore carry out a series of tests and show that this effect persists even after we control for the effects of time, individual salespeople, other marketing instruments, local market effects, and the effects of some institutional factors. We believe that our contagion effect arises because the consumption externality is stronger for geographically close physicians. We discuss some underlying processes that are probably giving rise to the contagion effect we detected. Finally, we compute the social multiplier of marketing and find it to be about 11%. We also use the estimated parameters to compare the relative effect of contagion and targeted marketing. We find that marketing plays a large (relative) role in affecting early adoption. However, the role of contagion dominates from month 4 onward and, by month 17 (or about half the duration of our data), asymptotes to about 90% of the effect.

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