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What reviews foretell about opening weekend box office revenue: the harbinger of failure effect in the movie industry

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Listed:
  • Pantelis Loupos

    (University of California Davis)

  • Yvette Peng

    (University of California Davis)

  • Sute Li

    (University of California Davis)

  • Hao Hao

    (University of California Davis)

Abstract

We empirically investigate the harbinger of failure phenomenon in the motion picture industry by analyzing the pre-release reviews written on movies by film critics. We find that harbingers of failure do exist. Their positive (negative) pre-release movie reviews provide a strong predictive signal that the movie will turn out to be a flop (success). This signal persists even for the top critic category, which usually consists of professional critics, indicating that having expertise in a professional domain does not necessarily lead to correct predictions. Our findings challenge the current belief that positive reviews always help enhance box office revenue and shed new light on the influencer-predictor hypothesis. We further analyze the writing style of harbingers and provide new insights into their personality traits and cognitive biases.

Suggested Citation

  • Pantelis Loupos & Yvette Peng & Sute Li & Hao Hao, 2023. "What reviews foretell about opening weekend box office revenue: the harbinger of failure effect in the movie industry," Marketing Letters, Springer, vol. 34(3), pages 513-534, September.
  • Handle: RePEc:kap:mktlet:v:34:y:2023:i:3:d:10.1007_s11002-023-09665-8
    DOI: 10.1007/s11002-023-09665-8
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    References listed on IDEAS

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    1. Luís Cabral & Gabriel Natividad, 2016. "Box-Office Demand: The Importance of Being #1," Journal of Industrial Economics, Wiley Blackwell, vol. 64(2), pages 277-294, June.
    2. Márton Mestyán & Taha Yasseri & János Kertész, 2013. "Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    3. Waldfogel, Joel, 2003. "Preference Externalities: An Empirical Study of Who Benefits Whom in Differentiated-Product Markets," RAND Journal of Economics, The RAND Corporation, vol. 34(3), pages 557-568, Autumn.
    4. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    5. 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.
    6. 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.
    7. Tingting Song & Jinghua Huang & Yong Tan & Yifan Yu, 2019. "Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms," Service Science, INFORMS, vol. 30(1), pages 191-203, March.
    8. Jehoshua Eliashberg & Sam K. Hui & Z. John Zhang, 2007. "From Story Line to Box Office: A New Approach for Green-Lighting Movie Scripts," Management Science, INFORMS, vol. 53(6), pages 881-893, June.
    9. Peter Boatwright & Suman Basuroy & Wagner Kamakura, 2007. "Reviewing the reviewers: The impact of individual film critics on box office performance," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 401-425, December.
    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.
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