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Optimum Advertising and Goodwill under Uncertainty

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  • Charles S. Tapiero

    (Hebrew University, Jerusalem, Israel)

Abstract

This paper extends past studies of advertising based on goodwill to include the probabilistic effects of advertising and forgetting. A stochastic advertising model for a monopoly firm is constructed and resolved for specific forms of feedback advertising policy. Further, a diffusion-approximation model is also suggested. Using these models, we derive optimum advertising policies of the open-loop and feedback type. The essential implications of the paper are: (i) advertising is a “risky investment” in goodwill, substituting current certain expenditures for uncertain profits; (ii) risk-averse firms will advertise less and risk-taking firms more; (iii) large risk-aversion and forgetting rates both lead to the standard competitive result in advertising.

Suggested Citation

  • Charles S. Tapiero, 1978. "Optimum Advertising and Goodwill under Uncertainty," Operations Research, INFORMS, vol. 26(3), pages 450-463, June.
    • Handle: RePEc:inm:oropre:v:26:y:1978:i:3:p:450-463
    DOI: 10.1287/opre.26.3.450
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    Cited by:

    1. Lundgren, Tommy & Olsson, Rickard, 2008. "How Bad is Bad News? Assessing the Effects of Environmental Incidents on Firm Value," Sustainable Investment and Corporate Governance Working Papers 2008/1, Sustainable Investment Research Platform.
    2. Alessandra Buratto & Luca Grosset, 2006. "A communication mix for an event planning: a linear quadratic approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(3), pages 247-259, September.
    3. Mesak, Hani I. & Ellis, T. Selwyn, 2009. "On the superiority of pulsing under a concave advertising market potential function," European Journal of Operational Research, Elsevier, vol. 194(2), pages 608-627, April.
    4. Daniel Adelman & Angelo J. Mancini, 2016. "Optimality of Quasi-Open-Loop Policies for Discounted Semi-Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1222-1247, November.

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