Multiple Peer Effects in the Diffusion of Innovations on Social Networks : A Simulation Study

The influence of peer effects on the diffusion of innovations has been extensively studied. However, the underlying mechanisms of peer effects are generally understudied. Gaps in this knowledge could lead to misestimation of peer effects and inefficient interventions. This study examined the role of three types of specific peer effects -- information effect, experience effect, and externality effect -- in the adoption of innovation in rural China. By referring to the diffusion process of a rural innovation, we developed a simulation model that incorporated multiple peer effects on a multiplex network. The model allowed us to estimate the influence of each specific effect and to investigate the interplay of the positive and negative directions of the effects. The main results of simulated experiments were the following: (1) a negative information effect in the system caused the diffusion of innovation to vary around a middle-level rate, which resulted in a fluctuating diffusion curve rather than a commonly found S-shaped one; (2) in the case of full diffusion, experience effect significantly shaped the diffusion process at an earlier stage, while externality effect mattered more at a later stage; and (3) network properties (i.e., connectivity, transitivity, and network distance) provided indirect influence on diffusion through specific peer effects. Overall, our study illustrated the need to understand specific underlying causal mechanisms when studying peer effects. Simulation studies provide an effective approach to generate such understanding