Network effects and bandwagon effects are both well-known in the study of innovation diffusion. However, their influences on the individual adoption behavior are not the same. In this paper, we distinguish the differences between them from two aspects: the origin of demand and the influenced individuals. Based on the configuration of complex networks, we propose a diffusion model that includes the interactions between network effects and bandwagon effects. It is found that the innovation adoption rates depend closely on the individuals’ preference between bandwagon effects and network effects. And the bandwagon effects are affected by the weight of neighbor relationships. Moreover, the network effects are composed of local network effects and global network effects and a trade-off between them is necessary to improve the diffusion of innovation.
Zhou, Qiping and Yang, Fang, "Innovation Diffusion with Network Effects and Bandwagon Effects Based on Complex Networks" (2020). WHICEB 2020 Proceedings. 23.