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| Research on Evolution Dynamic of Collaborative Innovation Network in the Urban Agglomeration of Yangtze River Delta Based on ERGM |
| Wang Haihua1,Sun Qin1,Guo Jianjie2,Du Mei1 |
| (1.School of Management, Shanghai University, Shanghai 200444, China；2.Shanghai Business School， Shanghai 201400, China) |
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Abstract 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.
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Received: 21 January 2021
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