In marketing products with negative externalities, a schedule which specifies an order of consumer purchase decisions is crucial, since in the social network of consumers, the decision of each consumer is negatively affected by the choices of her neighbors. In this paper, we study the problems of finding a marketing schedule for two asymmetric products with negative externalites. The goals are two-fold: maximizing the sale of one product and ensuring regret-free purchase decisions. We show that the maximization is NP-hard, and provide efficient algorithms with satisfactory performance guarantees. Two of these algorithms give regret-proof schedules, i.e. they reach Nash equilibria where no consumers regret their previous decisions. Our work is the first attempt to address these marketing problems from an algorithmic point of view. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Cao, Z., Chen, X., & Wang, C. (2013). How to schedule the marketing of products with negative externalities. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7936 LNCS, pp. 122–133). https://doi.org/10.1007/978-3-642-38768-5_13
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