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Planning a TV advertising campaign: A crisp multiobjective programming model from fuzzy basic data

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  • Pérez-Gladish, B.
  • Gonzalez, I.
  • Bilbao-Terol, A.
  • Arenas-Parra, M.

Abstract

This paper proposes a crisp two-objective logarithmic programming model to help companies decide their advertising campaigns on TV networks for mature products. Both objectives are: (a) to achieve the highest audience impact and (b) to reduce advertising costs as much as possible. Information input is fuzzily elaborated from statistical data, the fuzzy variables being defuzzified to introduce them into the crisp model. This fuzzy information is elicited by TV experts (often independent consultants). Although these experts know statistical information on audience in the past, they do not fully trust its predictive ability. The approach leads to the strategic advertisement (ad) placement among different broadcasts. Users (often managers of big companies) should inform the analyst about their advertising campaign budget. From Weber and Fechner-based psychological research, the ad impact during the advertising campaign is measured depending on the logarithm of ad repetitions. The crisp two-objective problem is solved by a tradeoff method subject to TV technical constraints. A case study with real world data is developed.

Suggested Citation

  • Pérez-Gladish, B. & Gonzalez, I. & Bilbao-Terol, A. & Arenas-Parra, M., 2010. "Planning a TV advertising campaign: A crisp multiobjective programming model from fuzzy basic data," Omega, Elsevier, vol. 38(1-2), pages 84-94, February.
  • Handle: RePEc:eee:jomega:v:38:y:2010:i:1-2:p:84-94
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. J. G. Kallberg & W. T. Ziemba, 1983. "Comparison of Alternative Utility Functions in Portfolio Selection Problems," Management Science, INFORMS, vol. 29(11), pages 1257-1276, November.
    3. Luque, Mariano & Miettinen, Kaisa & Eskelinen, Petri & Ruiz, Francisco, 2009. "Incorporating preference information in interactive reference point methods for multiobjective optimization," Omega, Elsevier, vol. 37(2), pages 450-462, April.
    4. Sohn, So Young & Choi, Hong, 2001. "Analysis of advertising lifetime for mobile phone," Omega, Elsevier, vol. 29(6), pages 473-478, December.
    5. Rosbergen, Edward & Pieters, Rik & Wedel, Michel, 1997. "Visual Attention to Advertising: A Segment-Level Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 24(3), pages 305-314, December.
    6. Rosbergen, E. & Pieters, R. & Wedel, M., 1997. "Visual attention to advertising : A segment-level analysis," Other publications TiSEM c77552c4-5b16-4ecb-8a21-2, Tilburg University, School of Economics and Management.
    7. Jeffrey H. Horen, 1980. "Scheduling of Network Television Programs," Management Science, INFORMS, vol. 26(4), pages 354-370, April.
    8. Givon, Moshe & Grosfeld-Nir, Abraham, 2008. "Using partially observed Markov processes to select optimal termination time of TV shows," Omega, Elsevier, vol. 36(3), pages 477-485, June.
    9. John Pratt, 2005. "How Many Balance Functions Does it Take to Determine a Utility Function?," Journal of Risk and Uncertainty, Springer, vol. 31(2), pages 109-127, September.
    10. Rik Pieters & Luk Warlop & Michel Wedel, 2002. "Breaking Through the Clutter: Benefits of Advertisement Originality and Familiarity for Brand Attention and Memory," Management Science, INFORMS, vol. 48(6), pages 765-781, June.
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