IDEAS home Printed from https://ideas.repec.org/a/bpj/revmkt/v13y2015i1p1-40n2.html
   My bibliography  Save this article

Role of Advertising and Consumer Interest in the Motion Picture Industry

Author

Listed:
  • Huang Dongling

    (Lally School of Management, Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY 12180)

  • Strijnev Andrei
  • Ratchford Brian

    (Naveen Jindal School of Management, University of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080, USA)

Abstract

Advertising is commonly used as a major marketing tool by many firms to support their new product release. Quantifying the effectiveness of pre-release advertising campaigns, however, is both challenging, since no sales data are available, and costly, because of the need to conduct consumer surveys. This is especially true for movie industry for which the majority of advertising dollars are spent before the movie’s release. Using the recent availability of online data on consumer search behaviors on a popular website dedicated to the movie industry, we construct a consumer interest measure to help the decision makers evaluate their advertising effectiveness. We build a dynamic model to show how this cost-efficient measure of consumer interest can be used to capture pre-release advertising dynamics, and the impact of advertising on weekly movie revenues starting with the opening week. Using a procedure based on Naik, Mantrala, and Sawyer (1998) and controlling for endogeneity, we estimate response, forgetting and wear-out of pre-release and post-release advertising for a large sample of movies. Our empirical results show that advertising generates goodwill, and that the resulting goodwill is associated with increased revenues. Our results suggest that big-budget movies can increase advertising effectiveness by making small adjustments to their advertising dynamics, but that spending more advertising dollars will likely not be effective. The data on the evolution of consumer interest can be a valuable and inexpensive tool for measuring advertising effectiveness and understanding sales dynamics.

Suggested Citation

  • 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.
    • Handle: RePEc:bpj:revmkt:v:13:y:2015:i:1:p:1-40:n:2
    DOI: 10.1515/roms-2014-0005
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/roms-2014-0005
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/roms-2014-0005?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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. Prasad A. Naik & Murali K. Mantrala & Alan G. Sawyer, 1998. "Planning Media Schedules in the Presence of Dynamic Advertising Quality," Marketing Science, INFORMS, vol. 17(3), pages 214-235.
    3. 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.
    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. Ho, Jason Y.C. & Dhar, Tirtha & Weinberg, Charles B., 2009. "Playoff payoff: Super Bowl advertising for movies," International Journal of Research in Marketing, Elsevier, vol. 26(3), pages 168-179.
    6. 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.
    7. Duan, Wenjing & Gu, Bin & Whinston, Andrew B., 2008. "The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry," Journal of Retailing, Elsevier, vol. 84(2), pages 233-242.
    8. 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.
    9. Frank M. Bass & Norris Bruce & Sumit Majumdar & B. P. S. Murthi, 2007. "Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship," Marketing Science, INFORMS, vol. 26(2), pages 179-195, 03-04.
    10. 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.
    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. Suman Basuroy & S. Abraham Ravid & Richard T. Gretz & B. J. Allen, 2020. "Is everybody an expert? An investigation into the impact of professional versus user reviews on movie revenues," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 44(1), pages 57-96, March.
    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. 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.
    4. 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.
    5. 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.
    6. Gazley, Aaron & Clark, Gemma & Sinha, Ashish, 2011. "Understanding preferences for motion pictures," Journal of Business Research, Elsevier, vol. 64(8), pages 854-861, August.
    7. Kim, Ho & Bruce, Norris I., 2018. "Should sequels differ from original movies in pre-launch advertising schedule? Lessons from consumers' online search activity," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 116-143.
    8. 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.
    9. 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.
    10. Bae, Giwoong & Kim, Hye-jin, 2019. "The impact of movie titles on box office success," Journal of Business Research, Elsevier, vol. 103(C), pages 100-109.
    11. 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.
    12. 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.
    13. Angela (Xia) Liu & Tridib Mazumdar & Bo Li, 2015. "Counterfactual Decomposition of Movie Star Effects with Star Selection," Management Science, INFORMS, vol. 61(7), pages 1704-1721, July.
    14. Marchand, André & Hennig-Thurau, Thorsten & Wiertz, Caroline, 2017. "Not all digital word of mouth is created equal: Understanding the respective impact of consumer reviews and microblogs on new product success," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 336-354.
    15. Divakaran, Pradeep Kumar Ponnamma & Palmer, Adrian & Søndergaard, Helle Alsted & Matkovskyy, Roman, 2017. "Pre-launch Prediction of Market Performance for Short Lifecycle Products Using Online Community Data," Journal of Interactive Marketing, Elsevier, vol. 38(C), pages 12-28.
    16. Brianna JeeWon Paulich & V. Kumar, 2021. "Relating entertainment features in screenplays to movie performance: an empirical investigation," Journal of the Academy of Marketing Science, Springer, vol. 49(6), pages 1222-1242, November.
    17. Shyam Gopinath & Jacquelyn S. Thomas & Lakshman Krishnamurthi, 2014. "Investigating the Relationship Between the Content of Online Word of Mouth, Advertising, and Brand Performance," Marketing Science, INFORMS, vol. 33(2), pages 241-258, March.
    18. 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.
    19. 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.
    20. Delre, Sebastiano A. & Luffarelli, Jonathan, 2023. "Consumer reviews and product life cycle: On the temporal dynamics of electronic word of mouth on movie box office," Journal of Business Research, Elsevier, vol. 156(C).

    More about this item

    Statistics

    Access and download statistics

    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:bpj:revmkt:v:13:y:2015:i:1:p:1-40:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.