Analysis of U.S. Box Office Revenue Predictors


Added on  2019-09-20

4 Pages748 Words371 Views
Analysis of U.S. Box Office Revenue PredictorsAbstractThis paper examines the effect of various predictor variables domestic box office revenue. The sample space in this study is comprised of the top 30 highest-grossing English films produced in the United States of all time. Regression results indicate that the amount of positive and negative reviews, along with the release date are all statistically insignificant based on their low p-values from the regression analysis output. IntroductionThe rising costs of movie productions have resulted in motion picture studios seeking to understand the determinants of a successful and large revenue generating movie. The purpose of this research is to analyze the film industry with a concentration on the determinants of domestic box office revenue for English language movies. The importance of the film industry cannot be ignored based on the twenty-nine billion dollars in industry revenue in 2015.Data and ModelThe primary source of data for this study is the Rotten Tomatoes website. Rotten Tomatoes has a unique rating system that summarizes positive or negative reviews of accredited film critics for each motion picture. In addition to providing a system of aggregate reviews, Rotten Tomatoes also contains information pertaining to box office revenue, release date, and film ratings. Our model for this study is specified as:Where Y is the domestic box office earnings, .....................
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Our hypothesis for this study is specified as:Null Hypothesis: H0: β1 = β2 = ... = βp-1 =0. The initial assumption is that there is no relation between the amount of positive and negative movie reviews along with the time of release to the domestic box office revenues.Alternative Hypothesis: H1: At least one βi is ≠ 0. At least one of the independent variables is useful in explaining or predicting domestic box office revenues.Predictors of Domestic Box Office RevenueThe variables “Positive Reviews” and “Negative Reviews” are the number of approval ordisapproval ratings for a film by a leading group of movie reviewers. Conventional wisdom suggests that critical reviews are extremely important to the popularity of movies, especially in the early stages of a release. Positive reviews are expected to attract consumers and identify quality, while negative reviews are expected to limit the interest of the influential early adopters. The multiple regression analysis revealed that neither the amount of positive or negative reviews were statistically significant in predicting a film’s box office revenue.ConclusionThe most important result of the study is the observation that the amount of positive and negative reviews, along with the release date were all statistically insignificance based on their high p-values from the regression analysis. The p-values of the predictor variables, low R2 value,
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