# Network Structure and Synergy Characteristics in the Guangdong-Hong Kong-Macao Greater Bay Area
## 4 Results Analysis
### The City Nodes Variability in Logistics and Capital Flow Linkages  
The logistics and capital flow networks in the Greater Bay Area exhibit distinct characteristics in spatial distribution and functional roles. The logistics network emphasizes extensive intercity coverage, while the capital flow network demonstrates centralized development around core cities. As shown in Figure 2, the logistics network reveals that Shenzhen and Hong Kong possess higher weighted degrees, underscoring their dominant roles in logistics output. Hong Kong, in particular, functions as an international logistics center, characterized by a significant outflow of logistics resources. Conversely, Guangdong, Foshan, and Dongguan exhibit higher weighted inwardness, indicating strong demand for logistics inputs. These regions, as manufacturing hubs, are increasingly reliant on efficient logistics systems. In the capital flow network, Hong Kong and Shenzhen are prominent in capital exports, with Hong Kong's capital outflow reflecting its status as an international financial center. Guangzhou's exceptionally high weighted inwardness highlights its central role in absorbing capital within the region, closely linked to the degree of industrial agglomeration and the vibrancy of business activities in the city. There exists a spatial overlap between core cities in the logistics network and the capital flow network, indicating a differentiated division of roles among these cities. In the logistics network, core cities are geographically and logistically concentrated in hub locations. In contrast, core cities within the capital flow network are closely linked to regional economic centers and capital hubs. Regarding the division of roles, Hong Kong and Shenzhen serve as output nodes for logistics resources, while Zhuhai and Zhongshan \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Network Indicator**} & \multicolumn{2}{c}{**2016**} & \multicolumn{2}{c}{**2019**} & \multicolumn{2}{c}{**2021**} \\ \cline{2-7}  & **Logistics** & **Capital Flow** & **Logistics** & **Capital Flow** & **Logistics** & **Capital Flow** \\ \hline Clustering factor & 0.869 & 0.785 & 0.819 & 0.807 & 0.853 & 0.819 \\ Efficiency & 0.903 & 0.845 & 0.918 & 0.9 & 0.864 & 0.918 \\ Density & 0.75 & 0.555 & 0.691 & 0.645 & 0.645 & 0.682 \\ Caliber & 2 & 2 & 2 & 2 & 3 & 2 \\ \multirow{2}{*}{Center potential} & Degree & 1.500 & 1.109 & 1.382 & 1.290 & 1.291 & 1.364 \\  & Intermediary & 0.036 & 0.051 & 0.034 & 0.040 & 0.033 & 0.036 \\ \multirow{2}{*}{potential} & Tightness & 0.821 & 0.712 & 0.799 & 0.750 & 0.715 & 0.770 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Network topology statistics. function as input nodes, effectively complementing regional cargo flow. Conversely, capital primarily flows from Hong Kong and Shenzhen to Guangzhou, subsequently radiating to other cities. This pattern reflects a cascading distribution of capital flows, highlighting the interconnectedness of logistics and capital networks in the region. Outgoing centrality indicates the influence a city exerts on others within the network. Cities with high outgoing centrality in logistics or capital flow networks are more likely to function as output and distribution centers. Conversely, incoming centrality measures a node's capacity to receive information and capital, with cities exhibiting high incoming centrality serving as primary recipients. As illustrated in Figure 3, the outgoing and incoming centrality of Greater Bay Area cities in the logistics and capital flow networks reveals characteristics such as spatial imbalance, the dual role of core nodes, and strong synergy of factor flows. Specifically, the incoming centrality of each city indicates a clear core-edge structure. Cities with both high out-degree and high in-degree centrality not only generate significant resources and funds but also act as major recipients, embodying the dual function of core nodes within the network. The synergy between logistics and capital flow elements is significant.