• motion picture industry;
  • forecasting;
  • distribution planning;
  • theater selection;
  • optimization

We consider the distribution planning problem in the motion picture industry. This problem involves forecasting theater-level box office revenues for a given movie and using these forecasts to choose the best locations to screen a movie. We first develop a method that predicts theater-level box office revenues over time for a given movie as a function of movie attributes and theater characteristics. These estimates are then used by the distributor to choose where to screen the movie. The distributor's location selection problem is modeled as an integer programming-based optimization model that chooses the location of theaters in order to optimize profits. We tested our methods on realistic box office data and show that it has the potential to significantly improve the distributor's profits. We also develop some insights into why our methods outperform existing practice, which are crucial to their successful practical implementation.