关键词: 创新扩散, 社会学习, 规范压力, 复杂社会网络, 多智能体仿真, innovation diffusion, social learning, normative pressure, complex social network, agent-based simulation

Abstract: The innovation diffusions are macro dynamics emerging from the micro adoption decisions of potential adopters. By using complex social networks as innovation diffusion modeling carriers, this paper established the innovation adoption decision and diffusion mechanisms of potential adopters under the influences of social learning and normative pressure, and then the agent-based simulation method was used to study how the micro factors influence the macro innovation diffusions. The results show that the ultimate adoption percentage is highest and the diffusion speed is fastest under the scale-free social network. The evaluation strategies of potential adopters of innovation related information will significantly influence the adoption percentage. The increase of the adoption percentage at the initial time can accelerate innovation diffusion speed, but it can not continuously raise the ultimate adoption percentage. Both the too innovative and too conservative behaviors of the opinion leaders go against the increase of ultimate adoption percentages. The influences of different kind of initial adopters on the ultimate adoption percentage and the influences of opinion leaders’ innovativeness on the innovation diffusion speed depend on social networks’ topology structures. The results can be used as guidance for formulating innovation promotion strategies.