Modeling the financial performance of movies and the market dynamics of cinemas in China

• Main Author: Feng, Fan
• Other Authors: Ravishankar Sharma
• Format: Theses and Dissertations
• Language: English
• Published: 2014
• Subjects: DRNTU::Social sciences::Mass media::Media economics
• Online Access: http://hdl.handle.net/10356/61796
• Institution: Nanyang Technological University

This dissertation investigates the financial performance of movies and the market dynamics of cinemas in China, a fast-growing commercial exhibition marketplace. Movie sales, movie characteristics and cultural contexts are operationalized in ordinary least squares (OLS) regression and quantile regression models to explain the highly varied acceptance across different products released since 2009. The samples in movie analysis comprise most of the widely released motion pictures in China. The dissertation posits that production budgets, sequels, audience ratings, cultural contexts and movie genres can significantly account for the variation in box office (BO) revenue and sales-revenue-to-cost (SRTC) within the Chinese market. Movies produced in countries with similar cultural contexts capture more audiences measured by box office proceeds, but it is noteworthy that SRTC falls at a decreasing rate as cultural differences increase. An increase in production budget generates more sales in China, but reduces the SRTC ratios with other factors controlled. Although aggregate cinema attendance fluctuates with releasing date, this is not always true for an individual movie’s financial success. Quantile regressions provide us with a richer characterization of the relationship, enabling us to analyze the entire distribution of box office proceeds and SRTC ratios, as well as their determinants at key quantiles. The cinema study models the dynamic relationships between cinema attendance and the number of cinema screens in response to changes in predetermined and exogenous variables. These relationships are established and estimated by applying vector autoregression (VAR) and seemingly unrelated regressions (SUR) techniques. The regression analyses are executed over 96 observations spanning from May 2005 to April 2013. It is shown that the cinema market is a complex dynamic system affected by a variety of market and economic factors. It is also indicated that income and admission price do not significantly affect consumers’ movie-going behaviors, whereas they may alter the market expectation of the cinema operators. In recent years, the prevalence of the Internet has further promoted the growth of digital screens and movie consumption in China. This is an area that has to be investigated further.