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

Kewen Pan, Stephen Chi Hang Leung and Di Xiao

International Journal of Revenue Management, 2011, vol. 5, issue 2/3, 145-156

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.

Keywords: airline revenue management; advertising management; stochastic programming; linear programming; modelling; mass media advertising; uncertainty; pricing policies. (search for similar items in EconPapers)
Date: 2011
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