中文摘要：

于传统创新扩散理论和方法，从网络视角出发与传染病模型相结合，探讨软件产业虚拟集群创新扩散机理。由于软件产业虚拟集群的地域分散性，使其创新扩散活动更加复杂，按照集群成员间联系的紧密程度，将成员间创新扩散关系划分为邻居间的创新扩散、同一子集群内的创新扩散和不同子集群间的创新扩散3个层次。借鉴传染病传播思想，考虑创新扩散潜伏期，将软件产业虚拟集群成员分为潜在创新采纳成员、正在进行创新吸收和转化的成员、采用创新并且可将创新扩散给其他企业的成员和自主创新成员4种类型。于传统的传染病模型，构建软件产业虚拟集群创新扩散模型，讨论不同参数对创新扩散过程的影响，揭示集群创新扩散规律。研究结果表明，邻居关系对创新扩散作用明显；易染系数、潜伏系数越大，创新扩散速度越快；集群网络结构和扩散层次性对创新扩散成员数量、最大值出现的时间均有影响。最后以江苏虚拟软件园为例，验证模型的正确性和适用性。

英文摘要：

Based on traditional innovation diffusion theories and methods and from the perspective of networks and combining in-fectious disease model, innovation diffusion mechanism of software industrial virtual cluster is discussed. Due to the geographicaldispersion of software industrial virtual cluster, innovation diffusion activities are more complicated. According to the close degreeof contact between cluster members, innovation diffusion relationships between members are divided into three levels ： innovationdiffusion between neighbors, members in the same sub-clusters and between members of different sub-clusters. Based on ideas ofinfectious diseases and considering the incubation period of innovation diffusion, members of Software Industrial Virtual Clusterare divided into four types ： members of the potential innovation adoption, absorption and transformation of innovation, innovationadoption and innovation can be spread to other enterprises and the independent innovation. Innovation diffusion model of SoftwareIndustrial Virtual Cluster model is built based on the traditional model of infectious diseases to explore the influence of differentparameters on the innovation diffusion processes and unfold the law of innovation diffusion. The results show that neighbors havean obvious effect on innovation diffusion; increased Tingible coefficient and Latent coefficient increase innovation diffusion veloci-ty; Network structure of the cluster and diffusion hierarchy affect the number of innovation diffusion members and the appearancetime of maximum. Finally, Jiangsu virtual software park as an example is applied to test the correctness and applicability of themodel.