Evolution and Driving Mechanisms of Urban Networks in Northeast China: Based on County-level Enterprise Networks

Urban networks have become an indispensable perspective in the study of regional urban systems. Exploring the evolutionary characteristics of urban networks in Northeast China holds substantial significance for uncovering the mechanisms driving urban system evolution and optimizing regional spatial structure. By employing Temporal Exponential Random Graph Models (TERGM), this paper examines the spatiotemporal evolution and drivers of urban networks in Northeast China. Specifically, the network was constructed using data on inter-regional investment relations of large enterprises among 291 county-level administrative units from 1996 to 2023.Research findings: 1) the strength and scope of urban network connections in Northeast China have continued to increase, but a polarized core-periphery structure exists. The network connections between municipal districts constitute the basic framework of the urban network in the region, while the connections between municipal districts and county-level cities are primarily one-way, lacking bidirectional network connections. 2) The evolution of urban networks in Northeast China is influenced by both endogenous and exogenous driving mechanisms. Endogenous driving mechanisms include network density and node isolation, structural dependence effects, and temporal dependence effects, while exogenous driving mechanisms include urban development level and multidimensional proximity. 3) Inter-district and district-county network linkages in Northeast China are driven by different mechanisms. Network connections between municipal districts are more influenced by structural dependence effects and are less constrained by institutional proximity mechanisms, making them more likely to form long-distance connections. Network relations between municipal districts and county-level cities are more influenced by the isolate effect and temporal dependence mechanism, and urban areas with higher levels of economic and population development are more likely to establish network connections. This study contributes to the literature by providing a county-level perspective on urban network evolution and identifying the distinct mechanisms driving different types of network connections in Northeast China.