The Impact of Urban Knowledge Networks in Facilitating Green Innovation Diffusion: A Multi-Layer Network Study

Against the backdrop of green and sustainable development, green innovation has become a central issue of concern for both society and academia. Based on regional innovation system and network theories, this study conceptualizes the urban knowledge base as a network structure rather than a simple collection of isolated knowledge elements. Using green patent licensing data, a multi-layer network is constructed, and the Exponential Random Graph Model (ERGM) is employed to examine the impact of urban knowledge network structures on city-level innovation diffusion. The study finds that in the green ICT field, cities’ deep embedding in knowledge networks weakens their ability to absorb external innovations, while broad embedding facilitates the introduction of external innovations. In the green transportation field, deep embedding in knowledge networks enhances the absorption of external innovations, whereas broad embedding has no significant effect. In both fields, knowledge combination potential and knowledge uniqueness promote the outward diffusion of local innovations but weaken the inflow of external innovations. This study not only offers theoretical insights into innovation diffusion at the city level but also provides guidance for policymakers in developing targeted urban sustainable development strategies.