Transportation Interrelation Embedded in Regional Development: The Characteristics and Drivers of Road Transportation Interrelation in Guangdong Province, China
Abstract
:1. Introduction
2. Methods and Data
2.1. Social Network Analysis
2.2. Network Structure Characteristics
2.2.1. Overall Network Characteristics
2.2.2. Analysis of Centrality
2.2.3. Block Model Analysis
2.3. Quadratic Assignment Procedure (QAP)
2.4. Data Source
3. Results and Discussion
3.1. Network Structure Features
3.1.1. Overall Network Characteristics
3.1.2. Centrality Analysis
3.1.3. Block Model Analysis
3.2. Influencing Factors of Transportation Networks
3.2.1. QAP Correlation Analysis
3.2.2. Provincial QAP Regression Analysis
3.2.3. Block QAP Regression Analysis
4. Conclusions and Policy Implications
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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City | Centrality Degree | Betweenness | ||
---|---|---|---|---|
Out Degree | In Degree | Degree | ||
Chaozhou | 2 | 2 | 15.000 | 0.000 |
Dongguan | 5 | 14 | 70.000 | 7.585 |
Foshan | 4 | 14 | 70.000 | 6.031 |
Guangzhou | 3 | 17 | 85.000 | 26.964 |
Heyuan | 5 | 2 | 30.000 | 0.614 |
Huizhou | 5 | 6 | 40.000 | 2.003 |
Jiangmen | 6 | 7 | 50.000 | 0.847 |
Jieyang | 2 | 4 | 20.000 | 0.456 |
Maoming | 4 | 2 | 20.000 | 0.175 |
Meizhou | 7 | 1 | 35.000 | 15.714 |
Qingyuan | 6 | 2 | 35.000 | 0.312 |
Shaoguan | 6 | 0 | 30.000 | 0.105 |
Shantou | 2 | 4 | 20.000 | 0.456 |
Shanwei | 6 | 0 | 30.000 | 9.549 |
Shenzhen | 5 | 12 | 65.000 | 9.687 |
Yunfu | 5 | 2 | 30.000 | 0.000 |
Yangjiang | 11 | 1 | 55.000 | 3.707 |
Zhuhai | 6 | 3 | 35.000 | 0.000 |
Zhanjiang | 2 | 2 | 15.000 | 0.000 |
Zhaoqing | 7 | 3 | 40.000 | 0.368 |
Zhongshan | 6 | 7 | 40.000 | 0.163 |
Mean | 5 | 5 | 39.524 | 4.035 |
Block | Number of Cites | Receive Relationship | Send Relationship | Expected Internal Relationship Ratio | Actual Internal Relationship Ratio | Block Attribute | ||
---|---|---|---|---|---|---|---|---|
Inside the Block | Outside the Block | Inside the Block | Outside the Block | |||||
Ⅰ | 8 | 37 | 42 | 37 | 2 | 35.00% | 94.87% | Net beneficial |
Ⅱ | 8 | 13 | 2 | 13 | 34 | 35.00% | 27.66% | Net spillover |
Ⅲ | 3 | 5 | 5 | 5 | 1 | 10.00% | 83.33% | Bidirectional spillover |
Ⅳ | 2 | 0 | 1 | 0 | 13 | 5.00% | 0.00% | Broker |
Variables | Obs Value | Significa | Average | Std Dev | Minimum | Maximum | Prop ≥ 0 | Prop ≤ 0 |
---|---|---|---|---|---|---|---|---|
Urbanization level difference | −0.024 | 0.327 | −0.001 | 0.063 | −0.244 | 0.178 | 0.674 | 0.327 |
Population density differences | 0.168 | 0.033 | −0.001 | 0.085 | −0.191 | 0.233 | 0.033 | 0.967 |
Output value of secondary industry differences | 0.200 | 0.004 | −0.001 | 0.084 | −0.254 | 0.224 | 0.004 | 0.996 |
Civil vehicle ownership differences | 0.185 | 0.004 | −0.001 | 0.078 | −0.257 | 0.224 | 0.004 | 0.996 |
Tourism income differences | 0.223 | 0.000 | −0.000 | 0.089 | −0.154 | 0.220 | 0.000 | 1.000 |
Geographical adjacency | 0.471 | 0.000 | 0.001 | 0.052 | −0.143 | 0.214 | 0.000 | 1.000 |
Independent | Unstandardized Coefficient | Standardized Coefficient | Significance | Proportion as Large | Proportion as Small |
---|---|---|---|---|---|
Intercept | 0.020 | 0.000 | - | - | - |
Population density differences | 0.091 | 0.242 | 0.002 | 0.002 | 0.098 |
Output value of secondary industry differences | −0.087 | −0.235 | 0.111 | 0.889 | 0.111 |
Civil vehicle ownership differences | 0.091 | 0.217 | 0.072 | 0.072 | 0.929 |
Tourism income differences | 0.034 | 0.140 | 0.010 | 0.010 | 0.990 |
Geographical adjacency | 0.556 | 0.494 | 0.000 | 0.000 | 1.000 |
R2 | 0.298 | Adj-R2 | 0.291 |
Independent | Block I (Net Beneficial) | Block II (Net Spillover) | Block III (Bidirectional Spillover) | |||
---|---|---|---|---|---|---|
Stdized Coefficient | Significance | Stdized Coefficient | Significance | Stdized Coefficient | Significance | |
Population density differences | 0.356 | 0.052 | 0.001 | 0.499 | 0.572 | 0.327 |
Output value of secondary industry differences | −0.274 | 0.216 | −0.036 | 0.447 | −0.022 | 0.834 |
Civil vehicle ownership differences | 0.317 | 0.108 | −0.029 | 0.409 | 0.094 | 0.662 |
Tourism income differences | 0.057 | 0.469 | 0.264 | 0.018 | 0.137 | 0.366 |
Geographical adjacency | 0.428 | 0.003 | 0.633 | 0.001 | / | / |
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Yang, L.; Wu, D.; Cao, S.; Zhang, W.; Zheng, Z.; Liu, L. Transportation Interrelation Embedded in Regional Development: The Characteristics and Drivers of Road Transportation Interrelation in Guangdong Province, China. Sustainability 2022, 14, 5925. https://doi.org/10.3390/su14105925
Yang L, Wu D, Cao S, Zhang W, Zheng Z, Liu L. Transportation Interrelation Embedded in Regional Development: The Characteristics and Drivers of Road Transportation Interrelation in Guangdong Province, China. Sustainability. 2022; 14(10):5925. https://doi.org/10.3390/su14105925
Chicago/Turabian StyleYang, Lu, Dan Wu, Shuhui Cao, Weinan Zhang, Zebin Zheng, and Li Liu. 2022. "Transportation Interrelation Embedded in Regional Development: The Characteristics and Drivers of Road Transportation Interrelation in Guangdong Province, China" Sustainability 14, no. 10: 5925. https://doi.org/10.3390/su14105925