Article ID: | iaor20082669 |
Country: | United States |
Volume: | 53 |
Issue: | 6 |
Start Page Number: | 881 |
End Page Number: | 893 |
Publication Date: | Jun 2007 |
Journal: | Management Science |
Authors: | Eliashberg Jehoshua, Zhang Z. John, Hui Sam K. |
Keywords: | forecasting: applications, decision: applications |
Movie studios often have to choose among thousands of scripts to decide which ones to turn into movies. Despite the huge amount of money at stake, this process – known as green-lighting in the movie industry – is largely a guesswork based on experts’ experience and intuitions. In this paper, we propose a new approach to help studios evaluate scripts that will then lead to more profitable green-lighting decisions. Our approach combines screenwriting domain knowledge, natural-language processing techniques, and statistical learning methods to forecast a movie’s return on investment (ROI) based only on textual information available in movie scripts. We test our model in a holdout decision task to show that our model is able to significantly improve a studio’s gross ROI.