IDEAS home Printed from https://ideas.repec.org/a/kap/jculte/v44y2020i1d10.1007_s10824-019-09350-7.html
   My bibliography  Save this article

Is everybody an expert? An investigation into the impact of professional versus user reviews on movie revenues

Author

Listed:
  • Suman Basuroy

    (The University of Texas at San Antonio)

  • S. Abraham Ravid

    (Yeshiva University
    Lund University)

  • Richard T. Gretz

    (The University of Texas at San Antonio)

  • B. J. Allen

    (University of Arkansas)

Abstract

This study is the first attempt to examine the effect of electronic word of mouth (user reviews) relative to expert reviews on moviegoing decisions. For the first time, we use time-varying data on expert reviews. We find that expert ratings matter much more for moviegoing decisions than user ratings and volume. Our data also show that experts tend to be more critical but more consistent in their reviews than users. We find that experts, but not eWOM, affect wide release moviegoing, contrary to industry thinking. Finally, we show that experts’ reviews matter most when consumers and critics are in closer agreement about the quality of the film. The study uses OLS as well as instrumental variables analysis to account for possible endogeneity.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:jculte:v:44:y:2020:i:1:d:10.1007_s10824-019-09350-7
    DOI: 10.1007/s10824-019-09350-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10824-019-09350-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10824-019-09350-7?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. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    3. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    4. Greene, William, 2011. "Fixed Effects Vector Decomposition: A Magical Solution to the Problem of Time-Invariant Variables in Fixed Effects Models?," Political Analysis, Cambridge University Press, vol. 19(2), pages 135-146, April.
    5. Robin S. Lee, 2013. "Vertical Integration and Exclusivity in Platform and Two-Sided Markets," American Economic Review, American Economic Association, vol. 103(7), pages 2960-3000, December.
    6. Ravid, S Abraham, 1999. "Information, Blockbusters, and Stars: A Study of the Film Industry," The Journal of Business, University of Chicago Press, vol. 72(4), pages 463-492, October.
    7. 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.
    8. Maity, Moutusy & Dass, Mayukh & Malhotra, Naresh K., 2014. "The Antecedents and Moderators of Offline Information Search: A Meta-Analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 233-254.
    9. Imbens, Guido W, 2002. "Generalized Method of Moments and Empirical Likelihood," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 493-506, October.
    10. Moorthy, Sridhar & Ratchford, Brian T & Talukdar, Debabrata, 1997. "Consumer Information Search Revisited: Theory and Empirical Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(4), pages 263-277, March.
    11. Peter E. Rossi, 2014. "Invited Paper —Even the Rich Can Make Themselves Poor: A Critical Examination of IV Methods in Marketing Applications," Marketing Science, INFORMS, vol. 33(5), pages 655-672, September.
    12. Mark B. Houston & Ann-Kristin Kupfer & Thorsten Hennig-Thurau & Martin Spann, 2018. "Pre-release consumer buzz," Journal of the Academy of Marketing Science, Springer, vol. 46(2), pages 338-360, March.
    13. 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.
    14. 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.
    15. 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.
    16. Brian T. Ratchford & Debabrata Talukdar & Myung-Soo Lee, 2007. "The Impact of the Internet on Consumers' Use of Information Sources for Automobiles: A Re-Inquiry," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(1), pages 111-119, March.
    17. 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.
    18. Prendergast, Canice & Stole, Lars, 1996. "Impetuous Youngsters and Jaded Old-Timers: Acquiring a Reputation for Learning," Journal of Political Economy, University of Chicago Press, vol. 104(6), pages 1105-1134, December.
    19. Arthur De Vany & W. David Walls, 2002. "Does Hollywood Make Too Many R-Rated Movies? Risk, Stochastic Dominance, and the Illusion of Expectation," The Journal of Business, University of Chicago Press, vol. 75(3), pages 425-452, July.
    20. Zwiebel, Jeffrey, 1995. "Corporate Conservatism and Relative Compensation," Journal of Political Economy, University of Chicago Press, vol. 103(1), pages 1-25, February.
    21. De Vany, A. & Walls, W.D., 1999. ""Uncertainty in the Movies: Does Star Power Reduce the Terror of the Box Office?"," Papers 98-99-10, California Irvine - School of Social Sciences.
    22. 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.
    23. Holbrook, Morris B, 1999. "Popular Appeal versus Expert Judgments of Motion Pictures," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 26(2), pages 144-155, September.
    24. Urbany, Joel E & Dickson, Peter R & Wilkie, William L, 1989. "Buyer Uncertainty and Information Search," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(2), pages 208-215, September.
    25. S. Ravid & John Wald & Suman Basuroy, 2006. "Distributors and film critics: does it take two to Tango?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 30(3), pages 201-218, December.
    26. Scharfstein, David S & Stein, Jeremy C, 1990. "Herd Behavior and Investment," American Economic Review, American Economic Association, vol. 80(3), pages 465-479, June.
    27. Arthur De Vany & W. Walls, 1999. "Uncertainty in the Movie Industry: Does Star Power Reduce the Terror of the Box Office?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 23(4), pages 285-318, November.
    28. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    29. Liran Einav, 2007. "Seasonality in the U.S. motion picture industry," RAND Journal of Economics, RAND Corporation, vol. 38(1), pages 127-145, March.
    30. 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.
    31. Vithala R. Rao & S. Abraham (Avri) Ravid & Richard T. Gretz & Jialie Chen & Suman Basuroy, 2017. "The impact of advertising content on movie revenues," Marketing Letters, Springer, vol. 28(3), pages 341-355, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marislei Nishijima & Mauro Rodrigues & Thaís Luiza Donega Souza, 2022. "Is Rotten Tomatoes killing the movie industry? A regression discontinuity approach," Applied Economics Letters, Taylor & Francis Journals, vol. 29(13), pages 1187-1192, July.
    2. Jun Pang & Angela Xia Liu & Peter N. Golder, 2022. "Critics’ conformity to consumers in movie evaluation," Journal of the Academy of Marketing Science, Springer, vol. 50(4), pages 864-887, July.
    3. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.

    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. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    2. 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.
    3. 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).
    4. Gaenssle Sophia & Budzinski Oliver & Astakhova Daria, 2018. "Conquering the Box Office: Factors Influencing Success of International Movies in Russia," Review of Network Economics, De Gruyter, vol. 17(4), pages 245-266, December.
    5. 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.
    6. Darlene Chisholm & Víctor Fernández-Blanco & S. Abraham Ravid & W. David Walls, 2015. "Economics of motion pictures: the state of the art," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(1), pages 1-13, February.
    7. 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.
    8. Thorsten Hennig-Thurau & André Marchand & Barbara Hiller, 2012. "The relationship between reviewer judgments and motion picture success: re-analysis and extension," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(3), pages 249-283, August.
    9. Angela Liu & Yong Liu & Tridib Mazumdar, 2014. "Star power in the eye of the beholder: A study of the influence of stars in the movie industry," Marketing Letters, Springer, vol. 25(4), pages 385-396, December.
    10. Steven F. Lehrer & Tian Xie, 2022. "The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success," Management Science, INFORMS, vol. 68(1), pages 189-210, January.
    11. 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.
    12. 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.
    13. Wen-jhan Jane & Wei-peng Chen & Yuan-lin Hsu, 2015. "The impact of deregulation on the movie box office after Taiwan’s entry into the WTO: the difference-in-differences estimation," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 5(2), pages 289-308, December.
    14. Darlene Chisholm & George Norman, 2012. "Spatial competition and market share: an application to motion pictures," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(3), pages 207-225, August.
    15. Anirban Mukherjee & Vrinda Kadiyali, 2018. "The Competitive Dynamics of New DVD Releases," Management Science, INFORMS, vol. 64(8), pages 3536-3553, August.
    16. 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.
    17. 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.
    18. Jordi McKenzie, 2009. "Revealed word-of-mouth demand and adaptive supply: survival of motion pictures at the Australian box office," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 33(4), pages 279-299, November.
    19. Don M. Chance & Eric Hillebrand & Jimmy E. Hilliard, 2008. "Pricing an Option on Revenue from an Innovation: An Application to Movie Box Office Revenue," Management Science, INFORMS, vol. 54(5), pages 1015-1028, May.
    20. Jordi McKenzie, 2010. "Do 'African American' films perform better or worse at the box office? An empirical analysis of motion picture revenues and profits," Applied Economics Letters, Taylor & Francis Journals, vol. 17(16), pages 1559-1564.

    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:kap:jculte:v:44:y:2020:i:1:d:10.1007_s10824-019-09350-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.