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Correcting Audience Externalities in Television Advertising

Author

Listed:
  • Kenneth C. Wilbur

    (Rady School of Management, University of California, San Diego, California 92093)

  • Linli Xu

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

  • David Kempe

    (Department of Computer Science, University of Southern California, Los Angeles, California 90033)

Abstract

When a television advertisement causes viewers to switch channels, it reduces the audience available to subsequent advertisers. This audience loss is not reflected in the advertisement price, resulting in an audience externality. The present article analyzes the television network's problem of how to select, order, and price advertisements in a break of endogenous length in order to correct audience externalities. It proposes the Audience Value Maximization Algorithm (AVMA), which considers many possible advertisement orderings within a dynamic programming framework with a strategy-proof pricing mechanism. Two data sets are used to estimate heterogeneity in viewer-switching probabilities and advertiser willingness-to-pay parameters in order to evaluate the algorithm's performance. A series of simulations shows that AVMA typically maximizes audience value to advertisers, increases network revenue relative to several alternatives, and runs quickly enough to implement.

Suggested Citation

  • Kenneth C. Wilbur & Linli Xu & David Kempe, 2013. "Correcting Audience Externalities in Television Advertising," Marketing Science, INFORMS, vol. 32(6), pages 892-912, November.
  • Handle: RePEc:inm:ormksc:v:32:y:2013:i:6:p:892-912
    DOI: 10.1287/mksc.2013.0807
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    References listed on IDEAS

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