The creation and sharing of user-generated content such as product reviews has become increasingly “social,” particularly in online communities where members are connected. While some online communities have used monetary rewards to motivate product review contributions, empirical evidence regarding the effectiveness of such rewards remains limited. We examine the possible moderating effect of social connectedness (measured as the number of friends) on publicly offered monetary rewards using field data from an online review community. This community saw an (unexpected) overall decrease in total contributions after introducing monetary rewards for posting reviews. Further examination across members finds a strong moderating effect of social connectedness. Specifically, contributions from less-connected members increased by 1,400%, while contributions from more-connected members declined by 90%. To corroborate this effect, we rule out multiple alternative explanations and conduct robustness checks. Our findings suggest that token-sized monetary rewards, when offered publicly, can undermine contribution rates among the most connected community members. Data and the online appendix are available at https://doi.org/10.1287/mksc.2016.1022

This paper argues that the pharmaceutical industry represents an exciting opportunity to carry out academic research. The nature of the industry allows researchers to answer new questions, develop new methodologies for answering these questions as well as to apply existing methodology to new data. The paper opens with some industry background, then provides a brief overview of some important research areas and discusses the open questions in each area. Issues of data type and availability are also discussed. Copyright Springer Science + Business Media, Inc. 2005pharmaceutical marketing, patient compliance, response models, new products, physician networks, pharmaceutical pricing,

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The authors develop a method to quantify the benefits of individuallevel targeting when the data reflect firm strategic behavior-that is, when firms (1) are engaged in targeting and (2) take into account the actions of competing firms. This article studies a pharmaceutical firm's decision on the allocation of detailing visits across individual physicians. For this analysis, the authors develop, at the individual level, a model of prescriptions and a model of detailing. Using physician panel data, they estimate, at the physician level, the parameters of the prescription and detailing models jointly using full-information Bayesian methods. The results suggest that accounting for firm strategic behavior improves profitability by 14%-23% compared with segment-level targeting. In addition, ignoring firm strategic behavior underestimates the benefit of individual-level targeting significantly. The authors provide reasons for this finding. They also carry out several robustness checks to test the validity of the modeling assumptions.

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