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Modeling Movie Life Cycles and Market Share

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Author Info

  • Andrew Ainslie

    ()
    (UCLA Anderson School of Management, 110 Westwood Plaza, Room B412, University of California, Los Angeles, Los Angeles, California 90095)

  • Xavier Drèze

    ()
    (Wharton School, University of Pennsylvania, 3730 Walnut Street, Suite 700, Philadelphia, Pennsylvania 19104)

  • Fred Zufryden

    ()
    (Marshall School of Business, Marketing Department, Accounting Building 301G, University of Southern California, Los Angeles, California 90089-0443)

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    Abstract

    We examine box-office sales in the context of a market share model. This is accomplished by developing a combination of a sliding-window logit model and a gamma diffusion pattern in a hierarchical Bayes framework. We show that accounting for the full choice set available every week not only increases the fit of weekly movie sales but also leads to parameter estimates that depict a richer picture of the movie industry. We show that movie studios appear to have a good understanding of the products they produce, knowing when to support them and when not to. We also show that the effect of the number of opening week screens is overestimated in traditional models. Our research indicates that actors have a direct and directors an indirect effect on consumers’ movie choice. Releasing a movie contemporaneously with other movies of the same genre adversely affects box-office performance all around. Releasing a movie against movies of the same Motion Picture Association of America (MPAA) rating hurts its sales in the beginning, but there is a displacement effect, which leads to a less severe sales loss in the long run.

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    File URL: http://dx.doi.org/10.1287/mksc.1040.0106
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    Bibliographic Info

    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 24 (2005)
    Issue (Month): 3 (November)
    Pages: 508-517

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    Handle: RePEc:inm:ormksc:v:24:y:2005:i:3:p:508-517

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    Related research

    Keywords: entertainment marketing; motion picture distribution and exhibition; movie choice; new product research;

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    Cited by:
    1. Fernanda Gutierrez-Navratil & Victor Fernandez-Blanco & Luis Orea & Juan Prieto-Rodriguez, 2014. "How do your rivals’ releasing dates affect your box office?," Journal of Cultural Economics, Springer, vol. 38(1), pages 71-84, February.
    2. Xinlei Chen & Yuxin Chen & Charles Weinberg, 2013. "Learning about movies: the impact of movie release types on the nationwide box office," Journal of Cultural Economics, Springer, vol. 37(3), pages 359-386, August.
    3. Sina Henningsen & Rebecca Heuke & Michel Clement, 2011. "Determinants of Advertising Effectiveness: The Development of an International Advertising Elasticity Database and a Meta-Analysis," BuR - Business Research, German Academic Association for Business Research, vol. 4(2), pages 193-239, December.
    4. Randy Nelson & Robert Glotfelty, 2012. "Movie stars and box office revenues: an empirical analysis," Journal of Cultural Economics, Springer, vol. 36(2), pages 141-166, May.
    5. Gazley, Aaron & Clark, Gemma & Sinha, Ashish, 2011. "Understanding preferences for motion pictures," Journal of Business Research, Elsevier, vol. 64(8), pages 854-861, August.
    6. Elberse, Anita & Anand, Bharat, 2007. "The effectiveness of pre-release advertising for motion pictures: An empirical investigation using a simulated market," Information Economics and Policy, Elsevier, vol. 19(3-4), pages 319-343, October.
    7. Tirtha Dhar & Guanghui Sun & Charles Weinberg, 2012. "The long-term box office performance of sequel movies," Marketing Letters, Springer, vol. 23(1), pages 13-29, March.

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