Inter-City Innovation Network Simulation and Proximity Mechanism from the Perspective of Industrial Knowledge Bases: A Case Study on the Yangtze River Delta Urban Agglomeration

Currently, there is less focus on "knowledge heterogeneity" among different innovation subjects in inter-city innovation network research. Knowledge bases theory has gradually become a new entry point from the perspective of "knowledge heterogeneity" in regional theory and practice research. In this study, we explore the structural characteristics and proximity mechanism of inter-city innovation networks formed by heterogeneous knowledge-based industries, using the Yangtze River Delta Urban Agglomeration as a case study. We theorize knowledge creation logic as having two dimensions, that is, knowledge creation dynamics and economic performance, and develop a framework with a quantitative method to identify the typology of industrial knowledge bases. We use modified gravity models to construct inter-city innovation networks of heterogeneous industries, divided into different knowledge bases in the Yangtze River Delta urban agglomeration from 2005 to 2019. To clarify how these inter-city innovation networks evolve and what effects proximity has on evolution, we conduct social network analysis and implement the Quadratic Assignment Procedure (QAP). The results show the following: (1) Industrial knowledge bases are divided into five types, namely, analytical, symbolic, analytical-synthetic, synthetic-analytical-symbolic, and synthetic-symbolic-analytical. Therefore, innovation networks are also defined as these types. (2) The analytical network outlines a dual-core structure while other network structures are multi-core; the analytical, analytical-synthetic, and synthetic-analytical-symbolic networks are evidently oriented by core cities with administrative or economic functions; the central cities of the subgroups are closely connected, while the core cities of symbolic and synthetic-symbolic-analytical networks vary greatly, and weak connections appear within these subgroups; for the analytical, symbolic, analytical-synthetic, and synthetic knowledge base-dominated network structures, their evolution trends are increasingly compact, "loose-compact-loose", "compact-loose-compact", and relatively stable, respectively. (3) Inter-city innovation links are facilitated by geographical proximity, except for analytical networks. Cognitive proximity and technological proximity have a significant positive impact on innovation links. Institutional proximity contributes to the formation of analytical and analytical-synthetic networks. The interaction between geographical and technological proximity has a significant positive effect on innovation networks. In the analytical, symbolic, and analytical-integrated networks, the interaction of geographical proximity and cognitive proximity induces cities to contact each other. Theoretically, through China's practical application scenarios, this study quantitatively identifies the combination form of industry knowledge base for the first time and further deepens the connotation of knowledge bases theory. Simultaneously, it also addresses the deficiency of attention to the "knowledge heterogeneity" of the innovation subject in research on inter-city innovation networks. Practically, it provides a new perspective for optimizing the allocation of innovation resources for different types of knowledge-based subjects in the Yangtze River Delta urban agglomeration, improving the efficiency of inter-city knowledge circulation, building a differentiated regional innovation system, and formulating innovation governance strategies