IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v22y2023i3d10.1057_s41272-022-00392-9.html
   My bibliography  Save this article

Revenue implications of celebrities on Broadway theatre

Author

Listed:
  • Kyle D. S. Maclean

    (Western University)

  • Fredrik Ødegaard

    (Western University)

Abstract

Live entertainment revenue management practices depend upon understanding the most salient drivers of shifts in demand. Motivated by the increasing usage of dynamic pricing on Broadway, we explore factors that impact revenue in live theatre. Based on a fixed effects model and a novel dataset of revenues and actor usage, we estimate the revenue impact that celebrity actors have on Broadway shows. We find that weeks that have a celebrity are associated with an increase in revenue of approximately $250 k. The two major acting awards—Tony and Academy (the Oscars)—were found to have a non-significant impact on weekly revenue. We discuss implications on Revenue Management practices.

Suggested Citation

  • Kyle D. S. Maclean & Fredrik Ødegaard, 2023. "Revenue implications of celebrities on Broadway theatre," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(3), pages 207-218, June.
  • Handle: RePEc:pal:jorapm:v:22:y:2023:i:3:d:10.1057_s41272-022-00392-9
    DOI: 10.1057/s41272-022-00392-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-022-00392-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1057/s41272-022-00392-9?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. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    2. 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.
    3. 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.
    4. Shu Han & S. Abraham Ravid, 2020. "Star Turnover and the Value of Human Capital—Evidence from Broadway Shows," Management Science, INFORMS, vol. 66(2), pages 958-978, February.
    5. Randy Nelson & Robert Glotfelty, 2012. "Movie stars and box office revenues: an empirical analysis," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(2), pages 141-166, May.
    6. Lin, Kyle Y., 2006. "Dynamic pricing with real-time demand learning," European Journal of Operational Research, Elsevier, vol. 174(1), pages 522-538, October.
    7. Pascal Courty & Luke Davey, 2020. "The Impact of Variable Pricing, Dynamic Pricing, and Sponsored Secondary Markets in Major League Baseball," Journal of Sports Economics, , vol. 21(2), pages 115-138, February.
    8. 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.
    9. William L. Cooper & Tito Homem-de-Mello & Anton J. Kleywegt, 2015. "Learning and Pricing with Models That Do Not Explicitly Incorporate Competition," Operations Research, INFORMS, vol. 63(1), pages 86-103, February.
    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. 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. 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.
    3. Ana Suárez-Vázquez & José Quevedo, 2015. "Analyzing superstars’ power using support vector machines," Empirical Economics, Springer, vol. 49(4), pages 1521-1542, December.
    4. Caroline Elliott & Palitha Konara & Haiyi Ling & Chengang Wang & Yingqi Wei, 2018. "Behind film performance in China’s changing institutional context: The impact of signals," Asia Pacific Journal of Management, Springer, vol. 35(1), pages 63-95, March.
    5. Kyuhan Lee & Jinsoo Park & Iljoo Kim & Youngseok Choi, 2018. "Predicting movie success with machine learning techniques: ways to improve accuracy," Information Systems Frontiers, Springer, vol. 20(3), pages 577-588, June.
    6. Thorsten Hennig-Thurau, 2004. "Spielfilme als Anlageobjekte: Die Höhe des Filmbudgets als Grundlage der Investitionsentscheidung," Schmalenbach Journal of Business Research, Springer, vol. 56(2), pages 171-188, March.
    7. Darren Filson & James H. Havlicek, 2018. "The performance of global film franchises: installment effects and extension decisions," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(3), pages 447-467, August.
    8. 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.
    9. Kang, Lili & Peng, Fei & Anwar, Sajid, 2022. "All that glitters is not gold: Do movie quality and contents influence box-office revenues in China?," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 492-510.
    10. 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.
    11. Fei Peng & Lili Kang & Sajid Anwar & Xue Li, 2019. "Star power and box office revenues: evidence from China," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 247-278, June.
    12. 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.
    13. Judy Ma & Dongling Huang & M. Kumar & Andrei Strijnev, 2015. "The impact of supplier bargaining power on the advertising costs of movie sequels," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(1), pages 43-64, February.
    14. 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.
    15. Selvaretnam, Geethanjali & Yang, Jen-Yuan, 2015. "Factors Affecting the Financial Success of Motion Pictures: What is the Role of Star Power?," SIRE Discussion Papers 2015-19, Scottish Institute for Research in Economics (SIRE).
    16. Daniel Kaimann, 2014. "Combining Qualitative Comparative Analysis and Shapley Value Decomposition: A Novel Approach for Modeling Complex Causal Structures in Dynamic Markets," Working Papers Dissertations 12, Paderborn University, Faculty of Business Administration and Economics.
    17. Fan, Liu & Zhang, Xiaoping & Rai, Laxmisha, 2021. "When should star power and eWOM be responsible for the box office performance? - An empirical study based on signaling theory," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    18. Frederick Derrick & Nancy Williams & Charles Scott, 2014. "A two-stage proxy variable approach to estimating movie box office receipts," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 38(2), pages 173-189, May.
    19. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers Dissertations 13, Paderborn University, Faculty of Business Administration and Economics.
    20. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers CIE 84, Paderborn University, CIE Center for International Economics.

    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:pal:jorapm:v:22:y:2023:i:3:d:10.1057_s41272-022-00392-9. 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.palgrave.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.