Network multipliers and the Optimality of Indirect Communication

We study the problem of a firm M which wishes to inform a community of individuals about its product. Information travels within the community because of the social interactions between individuals. Our interest is in understanding how the firm can incorporate the network of social interactions in the design of its communication strategy. We study a model of undirected networks and start by showing that social interactions appear in the payoff of the firm in the form of a network multiplier. We establish that the network multiplier is an increasing function of both the mean and the variance in the distribution of connections of the network. This implies in particular that denser and more dispersed degree distributions are better for the firm. We then show that the degree distribution of the neighbor first order dominates the degree distribution of a node at large and so it is always better for a firm to use indirect communication, i.e., viz. picking the neighbor of a node rather than a node itself as the target of communication. Finally, we show that the advantages of indirect communication are increasing with dispersion in the degree distribution.