## 4 Results  
### Coupling Coordination Analysis  
This study employs the entropy-weighted TOPSIS method to derive the comprehensive scores for the two subsystems of supply and demand. Building on this foundation, this study utilizes a modified coupling coordination degree model to assess the coupling coordination degree between these two subsystems. The temporal trend of the coupling coordination degree of supply-demand of civil aviation passenger transport from 2004 to 2019 is shown in Figure 2. Overall, the coupling coordination degree of China's civil aviation passenger transport supply and demand has demonstrated a steady annual increase. The coupling coordination value was 0.19 in 2004 and increased to 0.34 in 2019, achieving a transition from extreme imbalance to low coordination. The supply and demand subsystems also show a steady upward trend. 1.1 Time Characteristics Analysis of Supply-Demand Coupling Coordination Degree of Civil Aviation Passenger Transport  
Taking 2004, 2009, 2014 and 2019 as representative years, the coupling coordination degree of civil aviation passenger transport supply-demand in 31 province-level administrative divisions (excluding Hong Kong, Macao, and Taiwan) in China is shown in Figure 3. In 2004, Shanghai, Beijing, Guangdong, Hainan and Fujian ranked as the top five in terms of the provincial coupling coordination degree. The supply-demand coupling coordination  
Figure 2: Time series changes in supply–demand coupling coordination degree and subsystem evaluation index of China’s civil aviation passenger transport from 2004 to 2019.  
of the above province-level administrative divisions was relatively good, and the matching relationship between the supply subsystem and the demand subsystem was relatively appropriate. The last five were Jiangxi, Jilin, Gansu, Anhui and Hebei. The matching relationship between the supply and demand of civil aviation passenger transport in the above province-level administrative divisions was relatively imbalanced. The lag of one party or the advanced development of the other party led to the incomplete release of the interaction effect between the two. In 2019, Shanghai, Beijing, Guangdong, Hainan and Zhejiang ranked as the top five in terms of the coupling coordination degree of provincial supply-demand while Gansu, Jilin, Hebei, Jiangxi and Anhui ranked as the bottom five. The top province-level administrative divisions have superior natural conditions, developed economies, perfect transportation networks, rich tourism resources and strong residential consumption ability. The province-level administrative divisions ranked in the bottom have poor natural conditions, backward economic foundations, weak traffic accessibility and insufficient consumer potential. The reason may be that the supply and demand coupling level of civil aviation passenger transport is affected by regional economic development. Taking 2004, 2009, 2014 and 2019 as representative years, the kernel density map is drawn in Figure 4, based on the coupling coordination degree of civil aviation passenger transport supply and demand in 31 province-level administrative divisions (excluding Hong Kong, Macao, and Taiwan) in China. From the perspective of the time dimension, the kernel density curve of the coupling coordination degree of civil aviation passenger supply and demand moves to the right, indicating that the coupling coordination level of civil aviation passenger supply and demand is constantly improving. The shape of the  
Figure 3: Coupling coordination degree of supply–demand of civil aviation passenger transport in 31 province-level administrative divisions (excluding Hong Kong, Macao, and Taiwan) in China in 2004, 2009, 2014 and 2019.  
nuclear density curve gradually becomes flat and there is a right tail, indicating that there are differences in the coupling coordination degree between province-level administrative divisions during the investigation period.