长三角城市群协同创新网络演化动力研究：基于指数随机图模型

利用2009-2018年长三角城市群产学研联合申请专利数构建协同创新网络，建立指数随机图模型（ERGM），预测长三角城市群协同创新网络演化动力。实证结果表明，协同创新网络存在传递性，倾向于形成中介-2路径的开放式三角形结构；城市拥有的知识元素属性、经济发展水平和科研投入力度会对网络演化产生差异化影响；知识邻近性和组织邻近性在长三角城市群协同创新网络关系形成中始终发挥积极作用，制度邻近性和社会邻近性在网络演化前期发挥积极作用，但是伴随协同创新的深入，二者不利于协同创新网络合作关系形成。因此，政府应该引导各城市因地制宜制定创新战略，发挥各自资源与产业优势，助力构建高效交互的协同创新网络。

Research on Evolution Dynamic of Collaborative Innovation Network in the Urban Agglomeration of Yangtze River Delta Based on ERGM

Using the patent search and analysis website of State Intellectual Property Office, we construct a collaborative innovation network based on the data of joint patent application for industry-university-research collaborative innovation in urban agglomeration of Yangtze river delta from 2009 to 2018. Using the exponential random graph model (ERGM), it empirically analyzes the effects of institution, knowledge, organization and social proximity on the formation of innovative cooperative relationships within collaborative innovation network. In this paper, the hypothesis variables affecting collaborative innovation are proposed from multiple dimensions, such as the network endogenous structure, inter-city relationship properties, and urban individual properties, and the exponential random graph model (ERGM) is established to predict the evolution dynamics of collaborative innovation networks in Yangtze river delta city clusters. The results show that collaborative innovation network has transitive characteristics and tends to form an open triangle structure with intermediary -2 path. The attributes of knowledge elements owned by cities, the level of economic development and the investment in scientific research will have different effects on network evolution. Knowledge proximity and organizational proximity have always played an active role in the generation of collaborative innovation network relations in the Yangtze River Delta urban agglomeration, while institutional proximity and social proximity played an active role in the early stage of network evolution. However, the deepening of collaborative innovation between cities, institutional proximity and social proximity weakened the formation of cooperative relations, which was not conducive to the evolution of the network. Therefore, the government should guide cities to formulate innovation strategies according to local conditions, give play to their respective resources and industrial advantages, and help to build the efficient and interactive collaborative innovation networks.