 An agent-based model of directed advertising on a social networkCarolina Castaldi and F. Alkemade No 221, Computing in Economics and Finance 2004 from Society for Computational Economics Abstract: Network economics holds the view that individual actions and, in turn aggregate outcomes, are mainly determined by the interaction structure between heterogeneous economic agents. In this paper we study the diffusion of an innovation over a social network. More specifically, we study whether firms that receive only aggregate sales data can learn strategies to increase the size and the speed of the diffusion of their innovation over a network consisting of consumers. In order to do so the firm has to take into account both the characteristics of individual consumers and the topology of the social network. We use evolutionary agent-based experiments to simulate the learning behaviour of the firm and to study the diffusion dynamics. We find that firms can learn directed advertising strategies that take into account both the topology of the social consumer network and the characteristics of the consumer. These learned strategies lead to an increase in both the size and the speed of the innovation diffusion. Keywords: social networks; innovation diffusion; agent-based economics (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf4:221 Access Statistics for this paper More papers in Computing in Economics and Finance 2004 from Society for Computational Economics Contact information at EDIRC. |
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