A Parsimonious Predictive Model of Movie Performance: A Managerial Tool for Supply Chain Members

Mustafa Canbolat, Kyongsei Sohn, John T. Gardner

Source Title: International Journal of Operations Research and Information Systems (IJORIS)11(4)

ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781799806561|DOI: 10.4018/IJORIS.2020100103

MLA

Canbolat, Mustafa, et al. "A Parsimonious Predictive Model of Movie Performance: A Managerial Tool for Supply Chain Members." IJORIS vol.11, no.4 2020: pp.46-61. http://doi.org/10.4018/IJORIS.2020100103

APA

Canbolat, M., Sohn, K., & Gardner, J. T. (2020). A Parsimonious Predictive Model of Movie Performance: A Managerial Tool for Supply Chain Members. International Journal of Operations Research and Information Systems (IJORIS), 11(4), 46-61. http://doi.org/10.4018/IJORIS.2020100103

Chicago

Canbolat, Mustafa, Kyongsei Sohn, and John T. Gardner. "A Parsimonious Predictive Model of Movie Performance: A Managerial Tool for Supply Chain Members," International Journal of Operations Research and Information Systems (IJORIS) 11, no.4: 46-61. http://doi.org/10.4018/IJORIS.2020100103

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Abstract

In this paper, the authors develop a parsimonious model that offers early prediction of potential success of a movie. In order to achieve this, a broad look at the drivers of movie success is required. Supply chain members will be making decisions regarding movie popularity with regard to licensing contracts, forecasting toy purchases, cross-promotions, etc. at varying times before a movie is released. A simple forecasting approach using publicly available data could improve supply chain decision making. Prior literature suggested that the virtual movie stock market, HSX, was a good predictor. Using a small set of variables including view counts, likes, and dislikes did offer some predictive value. However, HSX produces a forecast that dominates prior models while using a single readily available public data. Further, the HSX-based prediction showed consistency and convergence across a significant breadth of time.