IDEAS home Printed from https://ideas.repec.org/p/pdn/dispap/11.html
   My bibliography  Save this paper

"To infinity and beyond!" A genre-specific film analysis of movie success mechanisms

Author

Listed:
  • Daniel Kaimann

    (University of Paderborn)

Abstract

The objective of this study is the analysis of movie success mechanisms in a genre-specific context. Instead of the examination of all time box office champions, we focus on the two film genres of computer animated and comic book based films. By introducing the concept of the motion-picture marketing mix, which represents a set of tactical marketing tools in order to strengthen a companyÕs strategic customer orientation, we are able to systematically identify key movie success factors. We conduct a cross-sectional empirical analysis across regional distinctions based on dataset that covers a time horizon of more than 30 years. We find empirical evidence that actors with ex ante popularity, award nominations and the production budget represent key movie success mechanisms and significantly influence a movieÕs commercial appeal. Additionally, word-of-mouth creates reputation effects that also significantly affects box office gross.

Suggested Citation

  • Daniel Kaimann, 2014. ""To infinity and beyond!" A genre-specific film analysis of movie success mechanisms," Working Papers Dissertations 11, Paderborn University, Faculty of Business Administration and Economics.
    • Handle: RePEc:pdn:dispap:11
    as

    Download full text from publisher

    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/dispap/DP11.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    3. 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.
    4. 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.
    5. Arthur De Vany & W. David Walls, 2002. "Does Hollywood Make Too Many R-Rated Movies? Risk, Stochastic Dominance, and the Illusion of Expectation," The Journal of Business, University of Chicago Press, vol. 75(3), pages 425-452, July.
    6. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    7. 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.
    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. Daniel Kaimann, 2013. ""To infinity and beyond!"? A genre-specific film analysis of movie success mechanisms," Working Papers CIE 38, Paderborn University, CIE Center for International Economics.
    2. 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.
    3. 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.
    4. Joe Cox & Daniel Kaimann, 2013. "The Signaling Effect of Critics - Evidence from a Market for Experience Goods," Working Papers CIE 68, Paderborn University, CIE Center for International Economics.
    5. Daniel Kaimann & Joe Cox, 2014. "The Signaling Effect of Critics: Do Professionals outweigh Word-of-Mouth? Evidence from the Video Game Industry," Working Papers Dissertations 10, Paderborn University, Faculty of Business Administration and Economics.
    6. 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.
    7. 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.
    8. 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.
    9. Christian Jansen, 2003. "The Performance of German Motion Pictures, Profits, and," Industrial Organization 0302002, University Library of Munich, Germany.
    10. Caroline Elliott & Rob Simmons, 2008. "Determinants of UK Box Office Success: The Impact of Quality Signals," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 33(2), pages 93-111, September.
    11. François A. Carrillat & Renaud Legoux & Allègre L. Hadida, 2018. "Debates and assumptions about motion picture performance: a meta-analysis," Journal of the Academy of Marketing Science, Springer, vol. 46(2), pages 273-299, March.
    12. Allègre Hadida, 2010. "Commercial success and artistic recognition of motion picture projects," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(1), pages 45-80, February.
    13. Brinja Meiseberg & Thomas Ehrmann, 2013. "Diversity in teams and the success of cultural products," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(1), pages 61-86, February.
    14. Christian Jansen, 2005. "The Performance of German Motion Pictures, Profits and Subsidies: Some Empirical Evidence," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 29(3), pages 191-212, August.
    15. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    16. Liuan Wang & Lu (Lucy) Yan & Tongxin Zhou & Xitong Guo & Gregory R. Heim, 2020. "Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study," Information Systems Research, INFORMS, vol. 31(2), pages 537-555, June.
    17. A. E. Scorcu & R. Zanola, 2011. "Survival in the Cultural Market: The Case of Temporary Exhibitions," Working Paper series 36_11, Rimini Centre for Economic Analysis.
    18. C F Elliott & R Simmons, 2007. "Determinants of UK box office success: the impact of quality signals," Working Papers 584026, Lancaster University Management School, Economics Department.
    19. 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.
    20. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.

    More about this item

    Keywords

    Motion-Picture economics; Marketing mix; Key success factors; Film genre; Seemingly unrelated regressions;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:pdn:dispap:11. 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: WP-WiWi-Info (email available below). General contact details of provider: https://edirc.repec.org/data/fwpadde.html .

    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.