IDEAS home Printed from https://ideas.repec.org/a/spr/orspec/v40y2018i1d10.1007_s00291-017-0492-0.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00291-017-0492-0
    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/s00291-017-0492-0?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. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Bengt Holmstrom, 1982. "Moral Hazard in Teams," Bell Journal of Economics, The RAND Corporation, vol. 13(2), pages 324-340, Autumn.
    8. 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.
    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 & 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.
    11. 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.
    12. 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.
    13. 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.
    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. 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.
    2. 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.
    3. Clement, Michel & Wu, Steven & Fischer, Marc, 2014. "Empirical generalizations of demand and supply dynamics for movies," International Journal of Research in Marketing, Elsevier, vol. 31(2), pages 207-223.
    4. Wei, Liyuan & Yang, Yupin, 2022. "An empirical investigation of director selection in movie preproduction: A two-sided matching approach," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 888-906.
    5. 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.
    6. Ronny Behrens & Natasha Zhang Foutz & Michael Franklin & Jannis Funk & Fernanda Gutierrez-Navratil & Julian Hofmann & Ulrike Leibfried, 2021. "Leveraging analytics to produce compelling and profitable film content," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(2), pages 171-211, June.
    7. 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.
    8. Darlene Chisholm & Víctor Fernández-Blanco & S. Abraham Ravid & W. David Walls, 2015. "Economics of motion pictures: the state of the art," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(1), pages 1-13, February.
    9. 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.
    10. Moez Hababou & Nawel Amrouche & Kamel Jedidi, 2016. "Measuring Economic Efficiency in the Motion Picture Industry: a Data Envelopment Analysis Approach," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(3), pages 144-158, December.
    11. Ana Suárez-Vázquez & José Quevedo, 2015. "Analyzing superstars’ power using support vector machines," Empirical Economics, Springer, vol. 49(4), pages 1521-1542, December.
    12. 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.
    13. W. D. Walls, 2009. "The Market for Motion Pictures in Thailand: Rank, Revenue, and Survival at the Box Office," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 8(2), pages 115-131, August.
    14. W. D. Walls & Jordi McKenzie, 2020. "Black swan models for the entertainment industry with an application to the movie business," Empirical Economics, Springer, vol. 59(6), pages 3019-3032, December.
    15. 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.
    16. Liye Ma & Alan L. Montgomery & Param Vir Singh & Michael D. Smith, 2014. "An Empirical Analysis of the Impact of Pre-Release Movie Piracy on Box Office Revenue," Information Systems Research, INFORMS, vol. 25(3), pages 590-603, September.
    17. 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.
    18. Davide Lauria & Wyatt D. Phillips, 2021. "Insuring Hollywood: A Movie Returns Index and the American Stock Market," JRFM, MDPI, vol. 14(5), pages 1-33, April.
    19. 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.
    20. 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.

    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

    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:spr:orspec:v:40:y:2018:i:1:d:10.1007_s00291-017-0492-0. 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.