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Research Note—Prerelease Demand Forecasting for Motion Pictures Using Functional Shape Analysis of Virtual Stock Markets

Listed author(s):
  • Natasha Zhang Foutz


    (McIntire School of Commerce, University of Virginia, Charlottesville, Virginia 22904)

  • Wolfgang Jank


    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

Registered author(s):

    Prerelease demand forecasting is one of the most crucial yet difficult tasks facing marketers in the $60 billion motion picture industry. We propose functional shape analysis (FSA) of virtual stock markets (VSMs) to address this long-standing challenge. In VSMs, prices of a movie's stock reflect the dynamic demand expectations prior to the movie's release. Using FSA, we identify a small number of distinguishing shapes, e.g., the last-moment velocity spurt, that carry information about a movie's future demand and produce early and accurate prerelease forecasts. We find that although forecasting errors from the existing methods, e.g., those that rely on movie features, can be as high as 90.87%, our approach results in an error of only 4.73%. Because demand forecasting is especially useful for managerial decision making when provided a movie's release, we further demonstrate how our method can be used for early forecasting and compare its power against alternative approaches. We also discuss the theoretical implications of the discovered shapes that may help managers identify indicators of a potentially successful movie early and dynamically.

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    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 29 (2010)
    Issue (Month): 3 (05-06)
    Pages: 568-579

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    Handle: RePEc:inm:ormksc:v:29:y:2010:i:3:p:568-579
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    1. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    2. 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.
    3. Martin Spann & Bernd Skiera, 2003. "Internet-Based Virtual Stock Markets for Business Forecasting," Management Science, INFORMS, vol. 49(10), pages 1310-1326, October.
    4. Ledyard Tucker, 1958. "Determination of parameters of a functional relation by factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(1), pages 19-23, March.
    5. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    6. Ashish Sood & Gareth M. James & Gerard J. Tellis, 2009. "Functional Regression: A New Model for Predicting Market Penetration of New Products," Marketing Science, INFORMS, vol. 28(1), pages 36-51, 01-02.
    7. Min Ding & Young-Hoon Park & Eric T. Bradlow, 2009. "Barter Markets for Conjoint Analysis," Management Science, INFORMS, vol. 55(6), pages 1003-1017, June.
    8. Wang, Shanshan & Jank, Wolfgang & Shmueli, Galit, 2008. "Explaining and Forecasting Online Auction Prices and Their Dynamics Using Functional Data Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 144-160, April.
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