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Movie stars and box office revenues: an empirical analysis

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  • 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.
  • Handle: RePEc:kap:jculte:v:36:y:2012:i:2:p:141-166
    DOI: 10.1007/s10824-012-9159-5
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    File URL: http://hdl.handle.net/10.1007/s10824-012-9159-5
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    Cited by:

    1. repec:zbw:esthes:157994 is not listed on IDEAS
    2. Ana Suárez-Vázquez & José Quevedo, 2015. "Analyzing superstars’ power using support vector machines," Empirical Economics, Springer, vol. 49(4), pages 1521-1542, December.
    3. Petr A. Parshakov & Kseniya O. Baydina, 2017. "Brands or Uncertainty? An Empirical Test of the Uncertainty of Outcome Hypothesis in Russian Football," HSE Working papers WP BRP 163/EC/2017, National Research University Higher School of Economics.
    4. 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.
    5. Julianne Treme & Zoe VanDerPloeg, 2014. "The Twitter Effect: Social Media Usage as a Contributor to Movie Success," Economics Bulletin, AccessEcon, vol. 34(2), pages 793-809.
    6. 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.
    7. McMahon, James, 2013. "The Rise of a Confident Hollywood: Risk and the Capitalization of Cinema," EconStor Preprints 157854, ZBW - German National Library of Economics.
    8. repec:zbw:caprev:157908 is not listed on IDEAS
    9. repec:eee:ijrema:v:34:y:2017:i:2:p:442-461 is not listed on IDEAS
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. repec:zbw:espost:157797 is not listed on IDEAS
    15. Aloys Prinz & Jan Piening & Thomas Ehrmann, 2015. "The success of art galleries: a dynamic model with competition and information effects," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(2), pages 153-176, May.
    16. repec:kap:asiapa:v:35:y:2018:i:1:d:10.1007_s10490-016-9501-0 is not listed on IDEAS

    More about this item

    Keywords

    Motion picture industry; Box office revenue; Movie stars; L82; Z11;

    JEL classification:

    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature

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