Anatomizing Resilience: The Multi-Dimensional Evolution and Drivers of Regional Collaborative Innovation Networks

In an era of intensifying global technological competition and systemic disruptions, the resilience of metropolitan innovation networks has emerged as a cornerstone of sustainable regional development. Based on joint invention patents, this study employs a multi-method analytical framework integrating social network analysis, network motif analysis, a random walk algorithm, and the Exponential Random Graph Model (ERGM) to trace the evolution of resilience across node, structural, and community levels in the Shanghai Metropolitan Area (2011–2020). Our findings reveal a significant trajectory of strengthening resilience, marked not only by a shift from a monocentric to a polycentric structure at the node level but also by a qualitative change in collaborative patterns at the structural level, and enhanced integration at the community level. ERGM analysis identifies policy coordination and industrial upgrading as the most potent drivers of this evolution, with a pivotal finding being that digital connectivity, measured by information proximity, has superseded geographic proximity in facilitating collaboration. This study develops and applies a multi-scale resilience framework, while also extending proximity theory by highlighting the growing importance of policy and information dimensions over geographic distance. It offers actionable insights for building resilient innovation ecosystems in policy-driven metropolitan regions.