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Advertising Budget Allocation under Uncertainty

Author

Listed:
  • Duncan M. Holthausen, Jr.

    (North Carolina State University)

  • Gert Assmus

    (Dartmouth College)

Abstract

This article presents a model for the allocation of an advertising budget to geographic market segments, or territories, when the sales response to advertising in each segment is characterized by a probability distribution. It is shown that allocation decisions that are based on the expected sales response may be associated with a relatively large degree of risk and, therefore, non-optimal to a risk-averse manager. The model derives an "efficient frontier" in terms of the expected profit and its variance resulting from alternative budget allocations. The manager then chooses the optimal allocation based on his/her preference function.

Suggested Citation

  • Duncan M. Holthausen, Jr. & Gert Assmus, 1982. "Advertising Budget Allocation under Uncertainty," Management Science, INFORMS, vol. 28(5), pages 487-499, May.
    • Handle: RePEc:inm:ormnsc:v:28:y:1982:i:5:p:487-499
    DOI: 10.1287/mnsc.28.5.487
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    Citations

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    Cited by:

    1. Yang, Chaolin & Xiong, Yi, 2020. "Nonparametric advertising budget allocation with inventory constraint," European Journal of Operational Research, Elsevier, vol. 285(2), pages 631-641.
    2. Symitsi, Efthymia & Markellos, Raphael N. & Mantrala, Murali K., 2022. "Keyword portfolio optimization in paid search advertising," European Journal of Operational Research, Elsevier, vol. 303(2), pages 767-778.
    3. Yanwu Yang & Baozhu Feng & Joni Salminen & Bernard J. Jansen, 2022. "Optimal advertising for a generalized Vidale–Wolfe response model," Electronic Commerce Research, Springer, vol. 22(4), pages 1275-1305, December.
    4. Caio Waisman & Brett R. Gordon, 2023. "Multi-cell experiments for marginal treatment effect estimation of digital ads," Papers 2302.13857, arXiv.org, revised Jan 2024.
    5. Sönke Albers, 1998. "Regeln für die Allokation eines Marketing-Budgets auf Produkte oder Marktsegmente," Schmalenbach Journal of Business Research, Springer, vol. 50(3), pages 211-235, March.
    6. Yanwu Yang & Daniel Zeng & Yinghui Yang & Jie Zhang, 2015. "Optimal Budget Allocation Across Search Advertising Markets," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 285-300, May.
    7. Hamidreza Koosha & Amir Albadvi, 2020. "Allocation of marketing budgets to maximize customer equity," Operational Research, Springer, vol. 20(2), pages 561-583, June.
    8. Yong-Wu Zhou & Chuanying Chen & Yuanguang Zhong & Bin Cao, 2020. "The allocation optimization of promotion budget and traffic volume for an online flash-sales platform," Annals of Operations Research, Springer, vol. 291(1), pages 1183-1207, August.
    9. Kamrad, Bardia & Lele, Shreevardhan S. & Siddique, Akhtar & Thomas, Robert J., 2005. "Innovation diffusion uncertainty, advertising and pricing policies," European Journal of Operational Research, Elsevier, vol. 164(3), pages 829-850, August.
    10. AgralI, Semra & Geunes, Joseph, 2009. "Solving knapsack problems with S-curve return functions," European Journal of Operational Research, Elsevier, vol. 193(2), pages 605-615, March.
    11. Jinglong Dai & Hanwei Li & Weiming Zhu & Jianfeng Lin & Binqiang Huang, 2024. "Data-Driven Real-time Coupon Allocation in the Online Platform," Papers 2406.05987, arXiv.org, revised Jun 2024.

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