IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v28y2009i2p239-250.html
   My bibliography  Save this article

Movie Advertising and the Stock Market Valuation of Studios: A Case of “Great Expectations?”

Author

Listed:
  • Amit M. Joshi

    (College of Business Administration, University of Central Florida, Orlando, Florida 32816)

  • Dominique M. Hanssens

    (Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095)

Abstract

Product innovation is the key revenue driver in the motion picture industry. Because major studios typically launch fewer than 20 movies per year, the financial performance of a single release can have a major effect on the studio's profitability. In this paper we study how single movie releases impact the investor valuation of the studio. We analyze the change in postlaunch stock price and predict the direction and magnitude of excess returns based on the revenue expectation built up for a movie release. That expectation is set, in part, by media support; i.e., highly advertised movies are expected to draw larger audiences than others. By using an event-study methodology, we isolate the impact of a movie launch on studio stock price and track the determinants of that change. We examine a comprehensive data set comprising over 300 movies released by the largest studios. Our results indicate a clear between the marketing support received by a movie and the direction and magnitude of its excess stock return post launch. Movies with above average prelaunch advertising have lower postlaunch stock returns than films with below average advertising. Our findings also suggest that movies that are hits at the box office may result in a lowering of stock price if they had high media support because of high performance expectations built up prior to launch. Thus prelaunch advertising plays a dual role of informing consumers about a movie's arrival as well as helping investors form expectations about the studio's profit performance.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormksc:v:28:y:2009:i:2:p:239-250
    DOI: 10.1287/mksc.1080.0392
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1080.0392
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.1080.0392?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. Sunil Gupta & Valarie Zeithaml, 2006. "Customer Metrics and Their Impact on Financial Performance," Marketing Science, INFORMS, vol. 25(6), pages 718-739, 11-12.
    3. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    4. 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.
    5. Kothari, S. P., 2001. "Capital markets research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 105-231, September.
    6. 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.
    7. 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.
    8. Natalie Mizik & Robert Jacobson, 2007. "Myopic Marketing Management: Evidence of the Phenomenon and Its Long-Term Performance Consequences in the SEO Context," Marketing Science, INFORMS, vol. 26(3), pages 361-379, 05-06.
    9. Ball, R & Brown, P, 1968. "Empirical Evaluation Of Accounting Income Numbers," Journal of Accounting Research, Wiley Blackwell, vol. 6(2), pages 159-178.
    10. Jehoshua Eliashberg & Jedid-Jah Jonker & Mohanbir S. Sawhney & Berend Wierenga, 2000. "MOVIEMOD: An Implementable Decision-Support System for Prerelease Market Evaluation of Motion Pictures," Marketing Science, INFORMS, vol. 19(3), pages 226-243, January.
    11. Praveen K. Kopalle & Donald R. Lehmann, 2006. "Setting Quality Expectations When Entering a Market: What Should the Promise Be?," Marketing Science, INFORMS, vol. 25(1), pages 8-24, 01-02.
    12. 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.
    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. Gazley, Aaron & Clark, Gemma & Sinha, Ashish, 2011. "Understanding preferences for motion pictures," Journal of Business Research, Elsevier, vol. 64(8), pages 854-861, August.
    2. 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.
    3. Delre, Sebastiano A. & Panico, Claudio & Wierenga, Berend, 2017. "Competitive strategies in the motion picture industry: An ABM to study investment decisions," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 69-99.
    4. 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.
    5. 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.
    6. 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.
    7. Clement, Michel & Wu, Steven & Fischer, Marc, 2014. "Empirical generalizations of demand and supply dynamics for movies," International Journal of Research in Marketing, Elsevier, vol. 31(2), pages 207-223.
    8. 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.
    9. Moez Hababou & Nawel Amrouche & Kamel Jedidi, 2016. "Measuring Economic Efficiency in the Motion Picture Industry: a Data Envelopment Analysis Approach," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(3), pages 144-158, December.
    10. 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.
    11. Hailin Zhang & Xina Yuan & Tae Ho Song, 2020. "Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective," Electronic Commerce Research, Springer, vol. 20(3), pages 589-608, September.
    12. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
    13. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    14. 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.
    15. 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;The Association for Cultural Economics International, vol. 38(1), pages 71-84, February.
    16. Huang Dongling & Strijnev Andrei & Ratchford Brian, 2015. "Role of Advertising and Consumer Interest in the Motion Picture Industry," Review of Marketing Science, De Gruyter, vol. 13(1), pages 1-40, November.
    17. 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.
    18. 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.
    19. 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.
    20. 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.

    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:28:y:2009:i:2:p:239-250. 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.