IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v24y2005i3p508-517.html
   My bibliography  Save this article

Modeling Movie Life Cycles and Market Share

Author

Listed:
  • 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)

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.

Suggested Citation

  • Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    • Handle: RePEc:inm:ormksc:v:24:y:2005:i:3:p:508-517
    DOI: 10.1287/mksc.1040.0106
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1040.0106
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.1040.0106?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    2. Desiraju, Ramarao & Nair, Harikesh S. & Chintagunta, Pradeep, 2004. "Diffusion of New Pharmaceutical Drugs in Developing and Developed Nations," Research Papers 1950, Stanford University, Graduate School of Business.
    3. Sanjeev Swami & Jehoshua Eliashberg & Charles B. Weinberg, 1999. "SilverScreener: A Modeling Approach to Movie Screens Management," Marketing Science, INFORMS, vol. 18(3), pages 352-372.
    4. Nelson, Phillip J, 1975. "The Economic Consequences of Advertising," The Journal of Business, University of Chicago Press, vol. 48(2), pages 213-241, April.
    5. Ramya Neelamegham & Pradeep Chintagunta, 1999. "A Bayesian Model to Forecast New Product Performance in Domestic and International Markets," Marketing Science, INFORMS, vol. 18(2), pages 115-136.
    6. Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
    7. Thomas J. Steenburgh & Andrew Ainslie & Peder Hans Engebretson, 2003. "Massively Categorical Variables: Revealing the Information in Zip Codes," Marketing Science, INFORMS, vol. 22(1), pages 40-57, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jehoshua Eliashberg & Anita Elberse & Mark A.A.M. Leenders, 2006. "The Motion Picture Industry: Critical Issues in Practice, Current Research, and New Research Directions," Marketing Science, INFORMS, vol. 25(6), pages 638-661, 11-12.
    2. Stefan Stremersch & Jorge Gonzalez & Albert Valenti & Julian Villanueva, 2023. "The value of context-specific studies for marketing," Journal of the Academy of Marketing Science, Springer, vol. 51(1), pages 50-65, January.
    3. Mark J Ferrari & Andrew Rudd, 2008. "Investing in movies," Journal of Asset Management, Palgrave Macmillan, vol. 9(1), pages 22-40, May.
    4. Allègre Hadida, 2010. "Commercial success and artistic recognition of motion picture projects," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(1), pages 45-80, February.
    5. Katherine Goff Inglis & Saeed Zolfaghari, 2017. "A Review of Scheduling Problems and Research Opportunities in Motion Picture Exhibition," Interfaces, INFORMS, vol. 47(2), pages 175-187, April.
    6. Jason M. T. Roos & Ron Shachar, 2014. "When Kerry Met Sally: Politics and Perceptions in the Demand for Movies," Management Science, INFORMS, vol. 60(7), pages 1617-1631, July.
    7. Steven F. Lehrer & Tian Xie, 2022. "The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success," Management Science, INFORMS, vol. 68(1), pages 189-210, January.
    8. Karniouchina, Ekaterina V., 2011. "Impact of star and movie buzz on motion picture distribution and box office revenue," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 62-74.
    9. Gazley, Aaron & Clark, Gemma & Sinha, Ashish, 2011. "Understanding preferences for motion pictures," Journal of Business Research, Elsevier, vol. 64(8), pages 854-861, August.
    10. Amit M. Joshi & Dominique M. Hanssens, 2009. "Movie Advertising and the Stock Market Valuation of Studios: A Case of “Great Expectations?”," Marketing Science, INFORMS, vol. 28(2), pages 239-250, 03-04.
    11. Wu, Chunhua & Weinberg, Charles B. & Wang, Qiyuan & Ho, Jason Y.C., 2022. "Administrative trade barrier: An empirical analysis of exporting Hollywood movies to China," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 1253-1274.
    12. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    13. Jehoshua Eliashberg & Sanjeev Swami & Charles B. Weinberg & Berend Wierenga, 2001. "Implementing and Evaluating SilverScreener: A Marketing Management Support System for Movie Exhibitors," Interfaces, INFORMS, vol. 31(3_supplem), pages 108-127, June.
    14. Don M. Chance & Eric Hillebrand & Jimmy E. Hilliard, 2008. "Pricing an Option on Revenue from an Innovation: An Application to Movie Box Office Revenue," Management Science, INFORMS, vol. 54(5), pages 1015-1028, May.
    15. 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;The Association for Cultural Economics International, vol. 37(3), pages 359-386, August.
    16. Robert E. Krider & Tieshan Li & Yong Liu & Charles B. Weinberg, 2005. "The Lead-Lag Puzzle of Demand and Distribution: A Graphical Method Applied to Movies," Marketing Science, INFORMS, vol. 24(4), pages 635-645, April.
    17. Allègre L. Hadida & Joseph Lampel & W. David Walls & Amit Joshi, 2021. "Hollywood studio filmmaking in the age of Netflix: a tale of two institutional logics," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(2), pages 213-238, June.
    18. Fei Peng & Lili Kang & Sajid Anwar & Xue Li, 2019. "Star power and box office revenues: evidence from China," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 247-278, June.
    19. 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.
    20. Baranchuk Nina & Seetharaman Seethu & Strijnev Andrei, 2019. "Revenue Sharing Vertical Contracts in the Movie Industry: A Theoretical Analysis," Review of Marketing Science, De Gruyter, vol. 17(1), pages 81-116, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:24:y:2005:i:3:p:508-517. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.