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Blogs, Advertising, and Local-Market Movie Box Office Performance

Author

Listed:
  • Shyam Gopinath

    (David Eccles School of Business, University of Utah, Salt Lake City, Utah 84112)

  • Pradeep K. Chintagunta

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

  • Sriram Venkataraman

    (Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599)

Abstract

We measure the effects of pre- and postrelease blog volume, blog valence, and advertising on the performance of 75 movies in 208 geographic markets in the United States. We attribute the variation in blog effects across markets to differences in demographic characteristics of markets combined with differences across demographic groups in their access and exposure to blogs as well as their responsiveness conditional on access. We study the effects of prerelease factors on opening day box office performance and of pre- and postrelease factors on box office performance one month after release. Our estimation accounts for confounding factors in the measurement of these effects via the use of instrumental variables. We find considerable heterogeneity in the effects across consumer- and firm-generated media and across geographic markets, with gender, income, race, and age driving across-market differences. Release day performance is impacted most by prerelease blog volume and advertising, whereas postrelease performance is influenced by postrelease blog valence and advertising. Across markets, there is more variance in advertising and blog valence (postrelease) elasticities than there is in blog volume (prerelease) elasticities. We identify the top 20 markets in terms of their elasticities to each of these three instruments. Further, we classify markets in terms of their sensitivities across these three instruments to identify the most sensitive markets that studios can target with their limited release strategies. Finally, we characterize the extent to which studios could have improved their limited release strategies by identifying the overlap between the actual release markets and the most responsive ones. We find that at the time of first-release studios cover only 53% of the most responsive advertising markets and 44% of the most responsive markets to prerelease blog volume in their limited release strategies, implying considerable room for improvement if these were the only metrics to assess those strategies. This paper was accepted by Gérard P. Cachon, marketing.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormnsc:v:59:y:2013:i:12:p:2635-2654
    DOI: 10.1287/mnsc.2013.1732
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    References listed on IDEAS

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    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. Sinai, Todd & Waldfogel, Joel, 2004. "Geography and the Internet: is the Internet a substitute or a complement for cities?," Journal of Urban Economics, Elsevier, vol. 56(1), pages 1-24, July.
    3. Dhar, Vasant & Chang, Elaine A., 2009. "Does Chatter Matter? The Impact of User-Generated Content on Music Sales," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 300-307.
    4. 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.
    5. David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
    6. Wolfgang Jank & P. K. Kannan, 2005. "Understanding Geographical Markets of Online Firms Using Spatial Models of Customer Choice," Marketing Science, INFORMS, vol. 24(4), pages 623-634, December.
    7. Goldfarb, Avi & Prince, Jeff, 2008. "Internet adoption and usage patterns are different: Implications for the digital divide," Information Economics and Policy, Elsevier, vol. 20(1), pages 2-15, March.
    8. Jean-Pierre Dubé & Puneet Manchanda, 2005. "Differences in Dynamic Brand Competition Across Markets: An Empirical Analysis," Marketing Science, INFORMS, vol. 24(1), pages 81-95, September.
    9. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    10. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    11. Onishi, Hiroshi & Manchanda, Puneet, 2012. "Marketing activity, blogging and sales," International Journal of Research in Marketing, Elsevier, vol. 29(3), pages 221-234.
    12. Sanjeev Dewan & Jui Ramaprasad, 2012. "Research Note ---Music Blogging, Online Sampling, and the Long Tail," Information Systems Research, INFORMS, vol. 23(3-part-2), pages 1056-1067, September.
    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.
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