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Estimating the potential of collaborating professionals, with an application to the Dutch film industry

Author

Listed:
  • Judith Timmer

    (University of Twente)

  • Richard J. Boucherie

    (University of Twente)

  • Esmé Lammers

    (Makers Op Waarde Geschat)

  • Niek Baër

    (University of Twente)

  • Maarten Bos

    (University of Twente)

  • Arjan Feenstra

    (University of Twente)

Abstract

Professionals often collaborate in projects. Some of these projects require funding, so before the collaboration can start a proposal for the project is submitted. This proposal will then be evaluated by a committee. The goal of the committee is to recognise proposals that are likely to be very successful. In this paper, we introduce a new numerical method to estimate the expected potential of a proposal. This method helps in identifying proposals that may turn out to be the most successful. The estimation is derived from the past performances of the professionals involved and takes into account the uncertainty of a contribution of a professional to a proposal. We apply our method to the Dutch film industry. We estimate the potential of proposals for new films released in 2010. The value of a film depends on the number of visitors in cinemas and the artistic prizes won. Our estimates are very good, indicating that past performances of filmmakers provide a very good indication of the potential of their new film. As a by-product of our method, rankings of producers, directors, and screenwriters of Dutch films up to 2011 are obtained.

Suggested Citation

  • Judith Timmer & Richard J. Boucherie & Esmé Lammers & Niek Baër & Maarten Bos & Arjan Feenstra, 2018. "Estimating the potential of collaborating professionals, with an application to the Dutch film industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 69-95, January.
  • Handle: RePEc:spr:orspec:v:40:y:2018:i:1:d:10.1007_s00291-017-0492-0
    DOI: 10.1007/s00291-017-0492-0
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    References listed on IDEAS

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    1. Márton Mestyán & Taha Yasseri & János Kertész, 2013. "Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    2. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    3. 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.
    4. 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.
    5. Bengt Holmstrom, 1982. "Moral Hazard in Teams," Bell Journal of Economics, The RAND Corporation, vol. 13(2), pages 324-340, Autumn.
    6. Jehoshua Eliashberg & Jedid-Jah Jonker & Mohanbir S. Sawhney & Berend Wierenga, 2000. "MOVIEMOD: An Implementable Decision-Support System for Prerelease Market Evaluation of Motion Pictures," Marketing Science, INFORMS, vol. 19(3), pages 226-243, January.
    7. Darius Palia & S. Abraham Ravid & Natalia Reisel, 2008. "Choosing to Cofinance: Analysis of Project-Specific Alliances in the Movie Industry," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 483-511, April.
    8. W. Walls, 2005. "Modeling Movie Success When ‘Nobody Knows Anything’: Conditional Stable-Distribution Analysis Of Film Returns," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 29(3), pages 177-190, August.
    9. 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.
    10. Jehoshua Eliashberg & Sam K. Hui & Z. John Zhang, 2007. "From Story Line to Box Office: A New Approach for Green-Lighting Movie Scripts," Management Science, INFORMS, vol. 53(6), pages 881-893, June.
    11. Joseph Lampel & Jamal Shamsie, 2003. "Capabilities in Motion: New Organizational Forms and the Reshaping of the Hollywood Movie Industry," Journal of Management Studies, Wiley Blackwell, vol. 40(8), pages 2189-2210, December.
    12. Natasha Zhang Foutz & Wolfgang Jank, 2010. "Research Note—Prerelease Demand Forecasting for Motion Pictures Using Functional Shape Analysis of Virtual Stock Markets," Marketing Science, INFORMS, vol. 29(3), pages 568-579, 05-06.
    13. 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.
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    More about this item

    Keywords

    Proposals from collaborations; Evaluation; Film performance; Dutch films;
    All these keywords.

    JEL classification:

    • Z10 - Other Special Topics - - Cultural Economics - - - General

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