An agent-based model of directed advertising on a social network
AbstractNetwork 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.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 221.
Date of creation: 11 Aug 2004
Date of revision:
social networks; innovation diffusion; agent-based economics;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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