## 2 Literature Review
### Urban Networks  
Existing research has extensively applied network perspectives to analyze intercity relationships within urban agglomerations. Scholars have abstracted cities as nodes and their various connections as edges, constructing different types of networks based on economic flows, transportation linkages, and information exchanges. For instance, studies have used enterprise networks to capture business connections, transportation networks to reflect infrastructure connectivity, and knowledge networks to represent innovation collaborations, as shown in Table 2.  
As shown in Table 2, current research on urban networks primarily focuses on three key domains: transportation networks, social networks, and economic networks. In transportation network studies, research has predominantly addressed issues of traffic congestion, flow allocation, and sustainable transportation development [3]. Notable findings indicate an evolution in urban transportation network structure from a Beijing-centered monocentric pattern to a more complex diamond structure anchored by four national centers: Beijing, Shanghai, Guangzhou, and Chengdu. This structural transformation has facilitated more intensive intercity interactions across the network [5]. Social network analyses have revealed distinctive patterns of information dissemination and social interaction within urban agglomerations [32]. These networks typically exhibit small-world characteristics [37; 38], where key nodes serve as critical information hubs. For instance, studies of information flows in the Yangtze River Delta urban agglomeration, based on Baidu Index data, demonstrate a relatively stable hierarchical structure evolving from a \"pyramid\" to a \"spindle\" pattern [36]. Similarly, analyses of population mobility, particularly during peak migration periods such as the Spring Festival, show concentrated flows among four major urban agglomerations, with network distributions following power-law patterns and displaying small-world properties [39]. Economic network research has focused on intercity trade, investment, and cooperation relationships [10; 11]. These studies consistently reveal core-periphery patterns in urban agglomeration development. A notable example is the Yangtze River Delta's financial enterprise network, which has evolved from a Shanghai-centered monocentric structure to a polycentric network with Shanghai as the primary hub and Nanjing, Hangzhou, and Hefei as secondary centers [10]. Similar patterns have been observed in the Chengdu-Chongqing urban agglomeration, where economic development shows significant spatial concentration in core urban areas, leading to distinct regional disparities [14]. Despite significant advances in urban network research, several limitations persist in understanding intercity relationships within urban agglomerations. Current research predominantly examines either single urban agglomerations or individual types of networks, largely due to challenges in data acquisition and processing. This has constrained \begin{table}
\begin{tabular}{c c} \hline \hline
**Type** & **References** \\ \hline Airline network & [5; 25; 30] \\ High-speed rail network & [12; 25] \\ Rail network & [31] \\ Innovation network & [32; 33] \\ Investment network & [10; 34] \\ Information network & [35; 36] \\ Human mobility network & [3; 14] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Different types of urban network. our ability to conduct comprehensive analyses of multi-regional and multi-dimensional urban networks [33]. Additionally, the analytical toolkit employed in existing research tends to be relatively limited, primarily relying on basic network metrics such as centrality measures, core-periphery structures, and cohesive subgroup analysis [16; 40; 41]. While these methods have provided valuable insights, they offer insufficient explanatory power for understanding the complex mechanisms underlying the formation and evolution of urban agglomerations.