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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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    References listed on IDEAS

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    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. 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.
    3. Alan Collins & Chris Hand & Martin C. Snell, 2002. "What makes a blockbuster? Economic analysis of film success in the United Kingdom," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 23(6), pages 343-354.
    4. Steven Albert, 1998. "Movie Stars and the Distribution of Financially Successful Films in the Motion Picture Industry," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 22(4), pages 249-270, December.
    5. Andrew Ainslie & Xavier Drèze & Fred Zufryden, 2005. "Modeling Movie Life Cycles and Market Share," Marketing Science, INFORMS, vol. 24(3), pages 508-517, November.
    6. M. Bagella & L. Becchetti, 1999. "The Determinants of Motion Picture Box Office Performance: Evidence from Movies Produced in Italy," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 23(4), pages 237-256, November.
    7. Holbrook, Morris B, 1999. " Popular Appeal versus Expert Judgments of Motion Pictures," Journal of Consumer Research, Oxford University Press, vol. 26(2), pages 144-155, September.
    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. Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
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    Cited by:

    1. repec:spr:infosf:v:20:y:2018:i:3:d:10.1007_s10796-016-9689-z is not listed on IDEAS
    2. repec:zbw:esthes:157994 is not listed on IDEAS
    3. Gaenssle, Sophia & Budzinski, Oliver & Astakhova, Daria, 2018. "Conquering the box office: Factors influencing success of international movies in Russia," Ilmenau Economics Discussion Papers 113, Ilmenau University of Technology, Institute of Economics.
    4. Ana Suárez-Vázquez & José Quevedo, 2015. "Analyzing superstars’ power using support vector machines," Empirical Economics, Springer, vol. 49(4), pages 1521-1542, December.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. McMahon, James, 2013. "The Rise of a Confident Hollywood: Risk and the Capitalization of Cinema," EconStor Preprints 157854, ZBW - German National Library of Economics.
    10. repec:zbw:caprev:157908 is not listed on IDEAS
    11. repec:eee:ijrema:v:34:y:2017:i:2:p:442-461 is not listed on IDEAS
    12. 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.
    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. 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.
    15. 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.
    16. repec:zbw:espost:157797 is not listed on IDEAS
    17. 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.
    18. 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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