Modeling movie life cycles and market share

We examine box-office sales in the context of a market share model. This is accomplished by developing a combination of a sliding-window logit model and a gamma diffusion pattern in a hierarchical Bayes framework. We show that accounting for the full choice set available every week not only increases the fit of weekly movie sales but also leads to parameter estimates that depict a richer picture of the movie industry. We show that movie studios appear to have a good understanding of the products they produce, knowing when to support them and when not to. We also show that the effect of the number of opening week screens is overestimated in traditional models. Our research indicates that actors have a direct and directors an indirect effect on consumers' movie choice. Releasing a movie contemporaneously with other movies of the same genre adversely affects box-office performance all around. Releasing a movie against movies of the same Motion Picture Association of America (MPAA) rating hurts its sales in the beginning, but there is a displacement effect, which leads to a less severe sales loss in the long run.