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A blueprint for success in the US film industry

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  • Stephanie Brewer
  • Jason Kelley
  • James Jozefowicz

Abstract

This article analyses motion picture box-office gross revenue using a cross-section of films from 1997 to 2001. The dependent variable is total domestic box-office revenue. The independent variables investigated include: production budget; peak number of screens that the film was shown on in theaters; Consumer price index for movie tickets; personal income; season and year of the release in theaters; a measure of pre-existing audience; aggregate critic rating; MPAA rating; genre; word-of-mouth recommendation; the presence of popular stars and the award nominations. A distinction is made in the analysis between information available to the public prior to the release of the film in theaters (ex ante) and information available to the public after the film opens in theaters (ex post). Results for the ex ante ordinary least squares (OLS) regression reveal positive impacts of budget, summer and holiday release dates, critical reviews, sequels and several genres on gross revenue. Significant, positive determinants in the ex post OLS regressions include budget, the peak number of screens, sequels, critical reviews, summer and holiday releases, word-of-mouth, award nominations and star power.

Suggested Citation

  • Stephanie Brewer & Jason Kelley & James Jozefowicz, 2009. "A blueprint for success in the US film industry," Applied Economics, Taylor & Francis Journals, vol. 41(5), pages 589-606.
    • Handle: RePEc:taf:applec:v:41:y:2009:i:5:p:589-606
    DOI: 10.1080/00036840601007351
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    1. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, Decembrie.
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    Cited by:

    1. Kim, Taegu & Hong, Jungsik & Kang, Pilsung, 2015. "Box office forecasting using machine learning algorithms based on SNS data," International Journal of Forecasting, Elsevier, vol. 31(2), pages 364-390.
    2. Wei, Liyuan & Yang, Yupin, 2022. "An empirical investigation of director selection in movie preproduction: A two-sided matching approach," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 888-906.
    3. Venkat Kuppuswamy & Peter Younkin, 2020. "Testing the Theory of Consumer Discrimination as an Explanation for the Lack of Minority Hiring in Hollywood Films," Management Science, INFORMS, vol. 66(3), pages 1227-1247, March.
    4. Daekook Kang, 2021. "Box-office forecasting in Korea using search trend data: a modified generalized Bass diffusion model," Electronic Commerce Research, Springer, vol. 21(1), pages 41-72, March.
    5. Caroline Elliott & Rob Simmons, 2008. "Determinants of UK Box Office Success: The Impact of Quality Signals," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 33(2), pages 93-111, September.
    6. Krishnan Jeesha & Sumod S D & Prashant Premkumar & Shovan Chowdhury, 2018. "Does Story Really Matter In The Movie Industry? : PreProduction Stage Predictive Models," Working papers 284, Indian Institute of Management Kozhikode.
    7. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    8. David Lang & David Switzer & Brandon Swartz, 2011. "DVD sales and the R-rating puzzle," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 35(4), pages 267-286, November.
    9. Thorsten Hennig-Thurau & André Marchand & Barbara Hiller, 2012. "The relationship between reviewer judgments and motion picture success: re-analysis and extension," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(3), pages 249-283, August.
    10. Julianne Treme & Lee A. Craig, 2013. "Celebrity star power: Do age and gender effects influence box office performance?," Applied Economics Letters, Taylor & Francis Journals, vol. 20(5), pages 440-445, March.
    11. Darren Filson & James H. Havlicek, 2018. "The performance of global film franchises: installment effects and extension decisions," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(3), pages 447-467, August.
    12. Kang, Lili & Peng, Fei & Anwar, Sajid, 2022. "All that glitters is not gold: Do movie quality and contents influence box-office revenues in China?," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 492-510.
    13. Sayantan Ghosh Dastidar & Caroline Elliott, 2020. "The Indian film industry in a changing international market," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 44(1), pages 97-116, March.
    14. Ahyun Kim & Silvana Trimi & Sang-Gun Lee, 2021. "Exploring the key success factors of films: a survival analysis approach," Service Business, Springer;Pan-Pacific Business Association, vol. 15(4), pages 613-638, December.
    15. Juan Prieto-Rodriguez & Fernanda Gutierrez-Navratil & Victoria Ateca-Amestoy, 2015. "Theatre allocation as a distributor’s strategic variable over movie runs," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(1), pages 65-83, February.
    16. Hofmann, Julian & Clement, Michel & Völckner, Franziska & Hennig-Thurau, Thorsten, 2017. "Empirical generalizations on the impact of stars on the economic success of movies," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 442-461.
    17. Caroline Elliott & Palitha Konara & Haiyi Ling & Chengang Wang & Yingqi Wei, 2018. "Behind film performance in China’s changing institutional context: The impact of signals," Asia Pacific Journal of Management, Springer, vol. 35(1), pages 63-95, March.

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