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Moneyball for TV: A Model for Forecasting the Audience of New Dramatic Television Series

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Listed:
  • Starling D. Hunter III
  • Ravi Chinta
  • Susan Smith
  • Awais Shamim
  • Alya Bawazir

Abstract

The specific objective of the present study is to develop and test an early-stage, empirical model for predicting the audience of new television series. We test our model on a sample of 107 new dramatic television series that debuted on one of the four major US television networks during the 2010-2014 seasons. In particular we examine the role of three previously untested predictors of the performance of new television shows, all of which can be known prior to the decision to greenlight the pilot script. Those three are the originality of the concept of the show, the track record of success of the show¡¯s creative team, and the size of the conceptual network created from the teleplay of the pilot episode.

Suggested Citation

  • Starling D. Hunter III & Ravi Chinta & Susan Smith & Awais Shamim & Alya Bawazir, 2016. "Moneyball for TV: A Model for Forecasting the Audience of New Dramatic Television Series," Studies in Media and Communication, Redfame publishing, vol. 4(2), pages 13-22, December.
  • Handle: RePEc:rfa:smcjnl:v:4:y:2016:i:2:p:13-22
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    References listed on IDEAS

    as
    1. 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.
    2. Basuroy, Suman & Chatterjee, Subimal, 2008. "Fast and frequent: Investigating box office revenues of motion picture sequels," Journal of Business Research, Elsevier, vol. 61(7), pages 798-803, July.
    3. 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.
    4. Richard E. Caves, 2003. "Contracts Between Art and Commerce," Journal of Economic Perspectives, American Economic Association, vol. 17(2), pages 73-83, Spring.
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    Cited by:

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    2. Van Reeth, Daam, 2019. "Forecasting Tour de France TV audiences: A multi-country analysis," International Journal of Forecasting, Elsevier, vol. 35(2), pages 810-821.

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    More about this item

    Keywords

    television; network analysis; pilot episodes; ratings; audience; dramatic series; content analysis; forecasting;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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