Internal settings, external linkages, and urban innovation: A dynamic configurational analysis

The role of cities as innovation machines is shaped by both internal settings and external linkages, yet empirical evidence on how multiple internal and external factors interact across regions and over time remains limited. Using data on 253 Chinese cities over three periods spanning 2006–2020, this study conducted a multi-period fuzzy-set qualitative comparative analysis to investigate the configurational effects of internal and external factors on urban innovation in a spatiotemporal context. The results indicated that: (1) no individual internal or external factor constituted a necessary condition for attaining high and low urban innovation performance, but R&D expenditure and market size have become increasingly essential over time; (2) multiple but equally effective configurations coexisted for both high and low urban innovation performance, while the two types of configurations exhibited different evolutionary trajectories; (3) there existed four urban innovation modes, including persistent-high, transient-high, emerging-high, and continuous-low modes. By tracing configurational patterns across regions and over periods, this study provides empirical evidence on the dynamic causal complexity of urban innovation and offers novel insights for designing context-specific urban innovation strategies.