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ARTS PLAN: A Model Based System for Use in Planning a Performing Arts Series

Author

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  • Charles B. Weinberg

    (Stanford University)

  • Kenneth M. Shachmut

    (McKinsey and Company, London)

Abstract

This paper is concerned with the application of marketing and management science to some of the problems involved in managing a series of performing arts presentations. Although some of the decisions are largely "artistic" and not subject to formal analytic procedures, many other decisions can be aided by model-based procedures. This paper describes some of the analytic procedures which are being used by the management of one performing arts series. The starting point for ARTS PLAN is dummy variable regression analysis of historical data which leads to a prediction of attendance at future performances. This prediction can be overridden by the manager if he or she disagrees with the forecast The forecast is then embedded in an interactive model which can be used for planning a season or for deciding which events to promote in a season already planned.

Suggested Citation

  • Charles B. Weinberg & Kenneth M. Shachmut, 1978. "ARTS PLAN: A Model Based System for Use in Planning a Performing Arts Series," Management Science, INFORMS, vol. 24(6), pages 654-664, February.
    • Handle: RePEc:inm:ormnsc:v:24:y:1978:i:6:p:654-664
    DOI: 10.1287/mnsc.24.6.654
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    Cited by:

    1. Jonathan Corning & Armando Levy, 2002. "Demand for Live Theater with Market Segmentation and Seasonality," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 26(3), pages 217-235, August.
    2. 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.
    3. Sanjeev Swami & Jehoshua Eliashberg & Charles B. Weinberg, 1999. "SilverScreener: A Modeling Approach to Movie Screens Management," Marketing Science, INFORMS, vol. 18(3), pages 352-372.
    4. 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.
    5. Tseng Peggy H. & Kulkarni Gauri, 2013. "Examining the Dynamics of Consumer Interest and Live Performance Event TicketSales in the Presence of a Critical Industry-Wide Event," Review of Marketing Science, De Gruyter, vol. 11(1), pages 33-53, November.

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