The authors investigate how critics affect the box office performance of films and how the effects may be moderated by stars and budgets. The authors examine the process through which critics affect box office revenue, that is, whether they influence the decision of the film going public (their role as influencers), merely predict the decision (their role as predictors), or do both. They find that both positive and negative reviews are correlated with weekly box office revenue over an eight-week period, suggesting that critics play a dual role: They can influence and predict box office revenue. However, the authors find the impact of negative reviews (but not positive reviews) to diminish over time, a pattern that is more consistent with critics' role as influencers. The authors then compare the positive impact of good reviews with the negative impact of bad reviews to find that film reviews evidence a negativity bias; that is, negative reviews hurt performance more than positive reviews help performance, but only during the first week of a film's run. Finally, the authors examine two key moderators of critical reviews, stars and budgets, and find that popular stars and big budgets enhance box office revenue for films that receive more negative critical reviews than positive critical reviews but do little for films that receive more positive reviews than negative reviews. Taken together, the findings not only replicate and extend prior research on critical reviews and box office performance but also offer insight into how film studios can strategically manage the review process to enhance box office revenue.

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Prior research demonstrates that adding decoys to choice sets can increase choice shares of brands similar to decoys while reducing shares of brands dissimilar to decoys. Such effects have been dubbed attraction effects and violate the principles of independence of irrelevant alternatives (IIA) and regularity. We report a metaanalysis that, in addition to revealing heretofore unsupported range effects, demonstrates an effect of brand quality. Decoys reduce shares of lower-quality competitors more than they reduce shares of higher-quality competitors. Moreover, whereas IIA is violated throughout, regularity is violated only when higher-quality brands are targeted. Decoys increase shares of higher-quality brands but typically do not increase shares of lower-quality brands. To assess the generalizability of the meta-analytic pattern, we tested decoy effects on two distinct populations in a large experiment. The more traditional population replicated the meta-analytic pattern (standard asymmetry) while the more nontraditional population reversed it. These findings suggest that while the standard asymmetry is replicable, it may not generalize to all market segments. A dding alternatives to choice sets yields systematic effects. Consider choice sets 1 and 2. Alternatives (i.e., decoys) such as C can reduce A's choice share and increase B's. Brand B apparently benefits relative to A because B, but not A, is now clearly superior to some other alternative (C). Increases in B's share are called attraction effects and violate two related assumptions underlying many choice models (Huber, Payne, and Puto 1982): (1) that choices are independent of irrelevant alternatives (IIA), and (2) that adding an alternative cannot increase choice shares of an original alternative (the principle of regularity).

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