Bright Lights, Risky Business: A Longitudinal Study of Broadway Show Success

• Activity Number: 78
• Type: Contributed
• Date/Time: Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): Lan Nygren*+ and Kjell Nygren and Jeffrey Simonoff
• Companies: Rider University and ImpactRx, Inc. and New York University
• Keywords: Theater, Broadway, Longitudinal hierarchical Bayes model, informative dropout, capacity constraint

Abstract

Using a long panel of nine years data, we investigate the factors that are useful to predict the weekly attendance at Broadway shows. This is accomplished by developing a longitudinal model taking into account the capacity constraints and informative dropout in a hierarchical Bayes framework. The weekly show attendance is modeled using a re-parameterized gamma distribution with parameters representing opening week performance, timing of peak performance and decay rate. Our research indicates that opening week performance is strongly related to the show type, whether a show is a revival, and the number of star actors. Shows that received positive reviews from New York Times take longer time to reach peak performance. Weekly demand declines faster for a play and more slowly for a show that received a positive review from USA Today. The impact of Tony Nominations tends to vary substantially across shows, although generally they tend to shift demand upwards.