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An Easily Implemented Framework for Forecasting Ticket Sales to Performing Arts Events

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  • Daniel S. Putler
  • Shilpa Lele

Abstract

This paper presents an easily used framework for modeling ticket sales to performing arts and entertainment events. Unlike existing efforts in this area, our framework allows us to: (1) model demand for events that consist of more than a single performance; (2) account for the influence of promotional effort on ticket sales; and (3) account for "sellouts" of some performances. The framework is applied to ticket sales for a university theater company, where it predicts ticket sales well in both an estimation and holdout sample. We discuss how the framework has influenced the company's marketing decisions.

Suggested Citation

  • Daniel S. Putler & Shilpa Lele, 2003. "An Easily Implemented Framework for Forecasting Ticket Sales to Performing Arts Events," Marketing Letters, Springer, vol. 14(4), pages 307-320, December.
    • Handle: RePEc:kap:mktlet:v:14:y:2003:i:4:p:307-320
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    Citations

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    Cited by:

    1. Ana Suárez-Vázquez, 2011. "Critic power or star power? The influence of hallmarks of quality of motion pictures: an experimental approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 35(2), pages 119-135, May.
    2. Liu, Hsiu-Wen, 2024. "Mining spatial-temporal patterns from customer data to improve forecasting of customer flow across multiple sites," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    3. Ateca-Amestoy, Victoria & Prieto-Rodriguez, Juan, 2013. "Forecasting accuracy of behavioural models for participation in the arts," European Journal of Operational Research, Elsevier, vol. 229(1), pages 124-131.
    4. Hong Chen, 2010. "Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 310-331, April.
    5. Kamakura, Wagner A. & Schimmel, Carl W., 2013. "Uncovering audience preferences for concert features from single-ticket sales with a factor-analytic random-coefficients model," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 129-142.

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