# Network Structure and Synergy Characteristics in the Guangdong-Hong Kong-Macao Greater Bay Area
## 4 Results Analysis
### The Potential of Logistics and Capital Flow Networks in the Greater Bay Area  
Table 2 illustrates the evolution of the logistics and capital flow networks in the Greater Bay Area from 2016 to 2021. The logistics network emphasizes balanced development, while the capital flow network increasingly centralizes, indicating differentiated resource flow and allocation patterns. First, regarding collaboration intensity among local cities, the agglomeration coefficient of the logistics network shows fluctuation; it is 0.869 in 2016, 0.819 in 2019, and 0.853 in 2021, which indicates that the regional collaboration capacity of the logistics network tends to stabilize after experiencing a certain decline in the short term. In contrast, the agglomeration coefficient of the capital flow network rises consistently, from 0.785 in 2016 to 0.819 in 2021, reflecting enhanced cooperation among cities. Second, concerning the transmission speed and cost of information and resources, the efficiency of the logistics network peaks at 0.918 in 2019 before declining, likely due to diminishing marginal efficiency from expanded logistics resource distribution. Conversely, the capital flow network's efficiency shows continuous improvement, indicating ongoing optimization and increasing mobility in resource allocation. Third, in terms of physical connectivity, the logistics network's density decreases annually, correlating with broader distribution and diversification within the Greater Bay Area. The capital flow network, however, becomes more cohesive, signifying heightened economic activity. This is evidenced by an increase in the logistics network's diameter and a stable diameter in the capital flow network, indicating structural complexity in logistics and compact connectivity in capital flows. Finally, examining network centrality potential, the degree centrality of the logistics network declines from 1.5 in 2016 to 1.291 in 2021, reflecting a balance in the importance of regional cities. The capital flow network improves from 1.109 to 1.364, highlighting increased control by core cities. Regarding intermediary centrality, the logistics network remains lower than the capital flow network, which plays a more significant role for key cities, suggesting that certain cities serve as crucial intermediaries in capital flows. In terms \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Coupling** & **Relative** & & & **Relative** & **Overall** & **Development** \\
**Coordination** & **Development** & **Type** & & **Development Stage** & **Development Stage** & **Stage** \\ \hline \multirow{3}{*}{\(0\leq C-D\leq 0.45\)} & \(0<R\leq 0.8\) & I & Logistic delay & Logistics Imbalance & \multirow{3}{*}{Antagonistic phase} \\  & \(0.8<R<1.2\) & II & Relative synchronization & Relative disorder & \\  & \(1.2\leq R\) & III & Funding delay & Capital Imbalance & \\ \hline \multirow{3}{*}{\(0.45<C-D<0.65\)} & \(0<R\leq 0.8\) & IV & Logistic delay & Logistic delay & \multirow{3}{*}{Break-in phase} \\  & \(0.8<R<1.2\) & V & Relative synchronization & Relative disorder & \\ \cline{1-1}  & \(1.2\leq R\) & VI & Funding delay & Funding delay & \\ \hline \multirow{3}{*}{\(0.65\leq C-D\leq 1\)} & \(0<R\leq 0.8\) & VII & Logistic delay & Funding Overruns & \multirow{3}{*}{Coordination} \\  & \(0.8<R<1.2\) & VIII & Relative synchronization & Balanced coordination & \\ \cline{1-1}  & \(1.2\leq R\) & IX & Funding delay & Logistic overruns & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Status of coupled and coordinated development between logistics and capital flow. of tight centrality, the logistics network declines annually, while the capital flow network increases to 0.770 in 2021, indicating greater efficiency in resource flow and diffusion. Overall, the logistics network exhibits a downward trend, while the capital flow network remains relatively balanced, with core cities maintaining a stable position.