IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v49y2017i1d10.1007_s10614-015-9540-5.html
   My bibliography  Save this article

Superstars Power, Mining the Paths to Stars’ Persuasion

Author

Listed:
  • Ana Suarez-Vazquez

    (University of Oviedo)

  • Elena Montañés-Roces

    (University of Oviedo)

Abstract

This paper analyzes the influence of star power on the cinema market. The study adopts two gauges of star power, one based on the industry’s opinion and one based on the market’s interest. The article merges contributions in the persuasion and cinema market literatures to examine the influence of star power over spectators. This study use machine learning methods based on support vector ordinal regression to analyze the paths to superstars’ persuasion. The present research shows differences in the persuasion effect of star power based on the industry and star power based on the market. Similarly, there are differences in the influence of star power among men and women. The results of this study help to explain the mixed findings of previous research on superstars’ power.

Suggested Citation

  • Ana Suarez-Vazquez & Elena Montañés-Roces, 2017. "Superstars Power, Mining the Paths to Stars’ Persuasion," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 67-81, January.
    • Handle: RePEc:kap:compec:v:49:y:2017:i:1:d:10.1007_s10614-015-9540-5
    DOI: 10.1007/s10614-015-9540-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-015-9540-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-015-9540-5?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. 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.
    2. 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.
    3. W. Walls, 2009. "Screen wars, star wars, and sequels," Empirical Economics, Springer, vol. 37(2), pages 447-461, October.
    4. 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.
    5. Ignacio Redondo & Morris Holbrook, 2010. "Modeling the appeal of movie features to demographic segments of theatrical demand," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(4), pages 299-315, November.
    6. Alan Collins & Chris Hand, 2005. "Analyzing moviegoing demand: an individual-level cross-sectional approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 26(5), pages 319-330.
    7. Hoyer, Wayne D & Brown, Steven P, 1990. "Effects of Brand Awareness on Choice for a Common, Repeat-Purchase Product," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(2), pages 141-148, September.
    8. Rosen, Sherwin, 1981. "The Economics of Superstars," American Economic Review, American Economic Association, vol. 71(5), pages 845-858, December.
    9. Dapeng Cui & David Curry, 2005. "Prediction in Marketing Using the Support Vector Machine," Marketing Science, INFORMS, vol. 24(4), pages 595-615, January.
    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. Ana Suárez-Vázquez & José Quevedo, 2015. "Analyzing superstars’ power using support vector machines," Empirical Economics, Springer, vol. 49(4), pages 1521-1542, December.
    2. 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.
    3. 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.
    4. Ana Suárez-Vázquez, 2011. "Critic power or star power? The influence of hallmarks of quality of motion pictures: an experimental approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 35(2), pages 119-135, May.
    5. 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.
    6. Michael Lewis & Yeujun Yoon, 2018. "An Empirical Examination of the Development and Impact of Star Power in Major League Baseball," Journal of Sports Economics, , vol. 19(2), pages 155-187, February.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Liyuan Wei, 2006. "—Making Sense of These Million-Dollar Babies—Rationale Behind Superstar Profit Participation Contracts," Marketing Science, INFORMS, vol. 25(6), pages 678-680, 11-12.
    12. Jordi McKenzie, 2010. "How do theatrical box office revenues affect DVD retail sales? Australian empirical evidence," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(3), pages 159-179, August.
    13. 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.
    14. Kyuhan Lee & Jinsoo Park & Iljoo Kim & Youngseok Choi, 0. "Predicting movie success with machine learning techniques: ways to improve accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-12.
    15. Katherine Goff Inglis & Saeed Zolfaghari, 2017. "A Review of Scheduling Problems and Research Opportunities in Motion Picture Exhibition," Interfaces, INFORMS, vol. 47(2), pages 175-187, April.
    16. A. Yeşim Orhun & Sriram Venkataraman & Pradeep K. Chintagunta, 2016. "Impact of Competition on Product Decisions: Movie Choices of Exhibitors," Marketing Science, INFORMS, vol. 35(1), pages 73-92, January.
    17. S. Ravid & Suman Basuroy, 2003. "Managerial Objectives, the R-Rating Puzzle and the Production of Violent Films," Yale School of Management Working Papers ysm383, Yale School of Management.
    18. Sudip Bhattacharjee & Ram D. Gopal & Kaveepan Lertwachara & James R. Marsden & Rahul Telang, 2005. "The Effect of P2P File Sharing on Music Markets: A Survival Analysis of Albums on Ranking Charts," Working Papers 05-26, NET Institute, revised Oct 2005.
    19. Sayantan Ghosh Dastidar & Caroline Elliott, 2020. "The Indian film industry in a changing international market," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 44(1), pages 97-116, March.
    20. Sudip Bhattacharjee & Ram D. Gopal & Kaveepan Lertwachara & James R. Marsden & Rahul Telang, 2007. "The Effect of Digital Sharing Technologies on Music Markets: A Survival Analysis of Albums on Ranking Charts," Management Science, INFORMS, vol. 53(9), pages 1359-1374, September.

    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:compec:v:49:y:2017:i:1:d:10.1007_s10614-015-9540-5. 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.