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A linear programming model to revenue management for advertising in mass media

Kewen Pan, Stephen Chi Hang Leung, Di Xiao

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Owning to the similarities in the nature of their business operations, it should be possible to apply the successful experience of airline revenue management to mass media advertising. However, one of the salient differences between airlines and mass media advertising is rarely highlighted, i.e. the network structure of length of continuance or the displacement effect. The advertisers go from the first continuance to the last continuance in a consecutive period. The coming in demand for multi-time continuances and lengths of continuance are stochastic in nature. In this paper, we propose a network optimisation model for advertising revenue management under an uncertain environment. The network optimisation is in a stochastic programming formulation so as to capture the randomness of the unknown demand (unknown number of coming-ins and length of continuances). We also discuss strategies for advertising revenue management to take into account different pricing policies: cancellations, early ends, extended continuance and overbooking and pricing correlation. It is shown that our proposed model can be modified to adopt these strategic considerations. Copyright © 2011 Inderscience Enterprises Ltd.
    Original languageEnglish
    Pages (from-to)145-156
    JournalInternational Journal of Revenue Management
    Volume5
    Issue number2-3
    DOIs
    Publication statusPublished - May 2011

    Research Keywords

    • Advertising management
    • Revenue management
    • Stochastic programming

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