A Nonlinear Optimization Model of Advertising Budget Allocation across Multiple Digital Media Channels

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dc.contributor.authorPark, Sung-Hyuk
dc.contributor.authorLee, Minhyung
dc.contributor.authorKim, Kitae
dc.contributor.authorShin, Dongwook
dc.date.accessioned2021-12-24T17:37:21Z
dc.date.available2021-12-24T17:37:21Z
dc.date.issued2022-01-04
dc.description.abstractThe goal of advertisers in the digital marketing industry is to optimize their advertising budgets. Such a budget allocation problem plays a key role in maximizing advertising performance from different marketing channels under planned advertising investment. This study aimed to design a budget-performance-based nonlinear programming model to find an optimized solution for the advertising budget allocation problem. The empirical analysis results of a leading e-business company’s advertising performance data show that the proposed non-LP model generates an optimized solution. The proposed model allows marketers to simulate expected advertising returns, such as conversions or revenues from different channels within their budget constraints.
dc.format.extent8 pages
dc.identifier.doi10.24251/HICSS.2022.272
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79604
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectTechnology and Analytics in Emerging Markets (TAEM)
dc.subjectadvertising
dc.subjectconversion
dc.subjectoptimization
dc.subjectperformance
dc.subjectrevenue maximization
dc.titleA Nonlinear Optimization Model of Advertising Budget Allocation across Multiple Digital Media Channels
dc.type.dcmitext

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