Against the backdrop of widening regional disparities and the rapid expansion of digital connectivity, understanding the relationship between new quality productive forces (NQPF) and urban–rural integration requires a systemic and network-based perspective. This study approaches urban–rural integration from a complex adaptive system perspective embedded in dynamic interregional networks. Using panel data from 31 Chinese provinces from 2014 to 2024, we construct composite indices for NQPF and urban–rural integration and combine two-way fixed-effects models, static Spatial Durbin Models (SDM), and dynamic-network two-way fixed-effects spatial-lag specifications. This framework helps examine local associations, network-based spillover patterns, and heterogeneous system responses. The results show that: (1) urban–rural integration exhibits significant spatial clustering, with Moran’s I becoming positive and statistically significant after 2016, reflecting persistent structural imbalances within the regional system; (2) the static SDM results show that NQPF is positively associated with urban–rural integration both locally and through spatial indirect linkages; (3) compared with conventional static geographic matrices, the dynamic network-based spatial weights provide additional information on evolving interregional linkages shaped by economic proximity, digital capability similarity, and factor mobility; and (4) under the dynamic network-based specification, NQPF remains positively associated with network exposure in connected provinces, with heterogeneous patterns across regions. More stable local associations are observed in high-connectivity and eastern regions, while the low-connectivity group and central–western regions appear to benefit more from network-based linkages. These findings suggest that the relationship between NQPF and urban–rural integration is embedded in a spatially connected and network-conditioned regional system. By integrating spatial econometrics with a complex systems perspective, this study provides a complementary framework for understanding regional transformation in the digital era.
Dong et al. (Thu,) studied this question.