Diffusion Dynamics in Small-World Networks with Heterogeneous Consumers

Abstract

"Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases. However, while epidemiological models describe infection in terms of transmissibility and susceptibility, we propose a diffusion model that explicitly includes consumer decision-making affected by social influences and word-of-mouth processes. In our computational model consumers' probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives in his/her personal social networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption as linear, we can study how the speed of the diffusion depends on the network structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness in the network. The speed is low in regular networks, it increases in small-world networks and finally it becomes low again in random networks. Second, we show that heterogeneity helps the diffusion. Alteris paribus and varying the degree of heterogeneity in the population of agents results show that the more heterogeneous the population, the faster the speed of the diffusion. These results contribute to marketing strategies for the launch and the dissemination of new products and technologies."