Research on the Formation Mechanism of Enterprises' AI Technology Collaborative Innovation Network
DOI:
https://doi.org/10.62051/y0hqsr42Keywords:
AI collaborative innovation network; Temporal Exponential Random Graph Model (TERGM); network evolution mechanism; peer effect.Abstract
Based on the invention patent data in the AI field jointly applied by enterprises in Chinese mainland from 2015 to 2024, this paper constructs a dynamic collaborative innovation network and employs the Temporal Exponential Random Graph Model (TERGM) to explore the formation mechanism of enterprises' AI innovation collaborative relationships. Considering both endogenous and exogenous factors affecting network construction, it incorporates structural dependence, temporal dependence, node characteristics, and exogenous network covariates into the model framework. The results show that the formation of enterprises' AI collaborative innovation relationships is influenced by the peer effect, and network evolution presents characteristics of structural self-organization and path dependence. This study helps to understand the evolution of AI innovation collaborative networks and provides theoretical support for the allocation of innovation resources and the formulation of relevant policies.
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