基于随机网络的创新扩散研究

基于ER随机图模型建立创新扩散网络,通过虚拟潜在采纳个体的决策过程,研究了创新潜在采纳主体行为、扩散网络结构与性质对创新微观采纳和宏观扩散的影响。实验结果表明,内部影响和外部影响共同决定一个成功的创新扩散。潜在采纳个体越倾向于从同质邻居个体处获取创新的评价信息,创新的扩散深度越大。随着潜在采纳者数量的增大,创新扩散的深度呈现周期性波动的特点。潜在采纳者的平均邻居数、扩散网络的聚集系数和平均路径长度与创新扩散的深度存在非单调的变化关系。创新潜在采纳主体行为、扩散网络结构与创新扩散的速度无关。实验结果有助于创新推广者制定有效的创新营销策略。

Study of Innovation Diffusion by Using Stochastic Network

Innovation diffusion network was built by ER stochastic graph model.Explored were the influence of the behaviors from innovation adoption individuals and the network structure on the innovation micro-adoption and macro-diffusion.The experiment results show that successful innovation diffusion will be determined by internal and external influences.The larger tendency of the potential adoption individual getting the innovation evaluation information from his/her homogenous neighborhoods,the larger the adoption rate is.With the increasing of the number of potential adoption individual,the adoption rate fluctuates periodically.The network structure and individual behaviors have nothing to do with the diffusion speed.These results are benefit to innovators' promoting their innovations.