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Should sequels differ from original movies in pre-launch advertising schedule? Lessons from consumers' online search activity

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  • Kim, Ho
  • Bruce, Norris I.

Abstract

Sequels have become a profitable strategy in the U.S. motion picture industry because of their strong name recognition. However, while the established positioning of a sequel may help insulate it from competing firms' advertising messages, its familiarity may cause moviegoers to be more easily satiated with advertising from the sequel. Therefore, this study examines how sequels differ from original concept movies in terms of their ad effectiveness. We focus our analysis on pre-launch periods, given these periods' importance in shaping the financial outcomes of motion pictures. We consider the weekly online search volume of a movie as a measure of consumer interest in it, and thus as an intermediate response to pre-launch advertising. We then develop a model that assumes ad effectiveness can decline, due to copy and repetition wearout, and increase, due to forgetting, over time. We find that copy wearout is greater for original movies, while repetition wearout and forgetting are greater for sequels. These findings suggest that sequels should allocate more in early pre-launch periods and less immediately before release, relative to originals, to maximize pre-launch consumer interest.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ijrema:v:35:y:2018:i:1:p:116-143
    DOI: 10.1016/j.ijresmar.2017.12.006
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    as
    1. Raj, S P, 1982. "The Effects of Advertising on High and Low Loyalty Consumer Segments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(1), pages 77-89, June.
    2. Punj, Girish N & Staelin, Richard, 1983. "A Model of Consumer Information Search Behavior for New Automobiles," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(4), pages 366-380, March.
    3. 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.
    4. Norris I. Bruce, 2008. "Pooling and Dynamic Forgetting Effects in Multitheme Advertising: Tracking the Advertising Sales Relationship with Particle Filters," Marketing Science, INFORMS, vol. 27(4), pages 659-673, 07-08.
    5. 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.
    6. 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.
    7. Brian T. Ratchford & Narasimhan Srinivasan, 1993. "An Empirical Investigation of Returns to Search," Marketing Science, INFORMS, vol. 12(1), pages 73-87.
    8. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    9. McAlister, Leigh, 1982. "A Dynamic Attribute Satiation Model of Variety-Seeking Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(2), pages 141-150, September.
    10. Jun B. Kim & Paulo Albuquerque & Bart J. Bronnenberg, 2010. "Online Demand Under Limited Consumer Search," Marketing Science, INFORMS, vol. 29(6), pages 1001-1023, 11-12.
    11. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    12. Basuroy, Suman & Chatterjee, Subimal, 2008. "Fast and frequent: Investigating box office revenues of motion picture sequels," Journal of Business Research, Elsevier, vol. 61(7), pages 798-803, July.
    13. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    14. Burmester, Alexa B. & Becker, Jan U. & van Heerde, Harald J. & Clement, Michel, 2015. "The impact of pre- and post-launch publicity and advertising on new product sales," International Journal of Research in Marketing, Elsevier, vol. 32(4), pages 408-417.
    15. Srinivasan, Narasimhan & Ratchford, Brian T, 1991. "An Empirical Test of a Model of External Search for Automobiles," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(2), pages 233-242, September.
    16. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    17. Kim, Ho & Hanssens, Dominique M., 2017. "Advertising and Word-of-Mouth Effects on Pre-launch Consumer Interest and Initial Sales of Experience Products," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 57-74.
    18. 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.
    19. Nelson, Philip, 1974. "Advertising as Information," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 729-754, July/Aug..
    20. Beatty, Sharon E & Smith, Scott M, 1987. "External Search Effort: An Investigation across Several Product Categories," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(1), pages 83-95, June.
    21. Dennis H. Gensch & Ulf Peter Welam, 1973. "An Optimum Budget Allocation Model for Dynamic, Interacting Market Segments," Management Science, INFORMS, vol. 20(2), pages 179-190, October.
    22. Onishi, Hiroshi & Manchanda, Puneet, 2012. "Marketing activity, blogging and sales," International Journal of Research in Marketing, Elsevier, vol. 29(3), pages 221-234.
    23. Guiyang Xiong & Sundar Bharadwaj, 2014. "Prerelease Buzz Evolution Patterns and New Product Performance," Marketing Science, INFORMS, vol. 33(3), pages 401-421, May.
    24. Shyam Gopinath & Pradeep K. Chintagunta & Sriram Venkataraman, 2013. "Blogs, Advertising, and Local-Market Movie Box Office Performance," Management Science, INFORMS, vol. 59(12), pages 2635-2654, December.
    25. 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.
    26. 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.
    27. Sanjay Sood & Xavier Drze, 2006. "Brand Extensions of Experiential Goods: Movie Sequel Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 33(3), pages 352-360, October.
    28. Chib, Siddhartha, 1992. "Bayes inference in the Tobit censored regression model," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 79-99.
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