Full Citation
Title: Social Learning and Optimal Advertising in the Motion Picture Industry
Citation Type: Dissertation/Thesis
Publication Year: 2008
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Abstract: Social learning is thought to be a key determinant of the demand for movies, the decisions about whether and when to watch a movie. Through social learning, potential movie-goers learn about the quality of a movie from people who have watched the movie. For example, critics, word-of-mouth referrals and the box office performance may offer potential movie consumers some exposure to the quality of a movie prior to making their choices. This can be a double-edged sword for motion picture distributors: when a movie is good, social learning can enhance the effectiveness of movie advertising, but when a movie is bad, it can mitigate the effectiveness. This paper develops an equilibrium model of consumers' movie-going choices and movie distributors' advertising decisions. I develop a structural model for studios' optimal advertising strategies, taking into account the expected social learning process, and a model for consumers' movie demand, given an initial indicator of movie quality (critic ratings) and an initial level of advertising. Consumers are assumed to have uncertainty about movie quality that is resolved over time through Bayesian updating. That process depends on the number of previous viewers and their ratings reported over the Internet. I estimate the model parameters using data pertaining to 236 movies that were shown in theaters nationwide in the U.S. between January 1, 2002 and December . . .
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Authors: Joo, Hailey Hayeon
Institution: University of Pennsylvania
Department: Economics
Advisor: Petra E Todd
Degree: PhD
Publisher Location: Philadelphia, PA
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Data Collections: IPUMS USA
Topics: Other
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