Forecasting ticket revenue is done by theaters of all sizes; for non-profit theatre companies accurate forecasting is valuable when allocating company resources and budgeting. If companies can accurately identify and predict what elements in a particular production contribute to higher box office revenue, then they can leverage those elements and potentially increase revenue. Not only is forecasting necessary but the collection and maintenance of data enable organizations to gain insight about the effect of their programming. Analyzing ticket sales by using linear regression analysis is an opportunity to statistically verify the drivers of ticket sales and presents an opportunity for non-profit theaters to justify the maintenance of standardized databases. Through analysis of data from a prominent American regional theatre this paper investigates the use and interpretation of linear regression analysis with a variety of programmatic and market variables.
The main takeaways of this inquiry are as follows:
• There is a body of research verifying regression as an analysis tool for non-profit theatres; this inquiry is supported by and adds to that body of research.
• A demand forecast model, like this regression analysis, is more effective than a supply forecast model for predicting the number of tickets sold.
• The model proposed is easy to use, but heavily relies on year dummy variables to account for macroeconomic factors.
• This type of regression modeling is useful as a what-if analysis.
• The model has enough predictive power to ensure that non-profit theatres maintain a positive operating budget holding expense and fundraising factors constant.
• The demand for single tickets is dependent on programming decisions, pricing decisions, and market reviews.
|Commitee:||Behzad, Banafsheh, Song, Reo|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 81/1(E), Masters Abstracts International|
|Subjects:||Arts Management, Business administration|
|Keywords:||Data analysis, Forecasting, Non-profit, Regression, Theatre arts, Ticket|
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