Network Structure and Synergy Characteristics in the Guangdong-Hong Kong-Macao Greater Bay Area
Source abstract
Abstract
In regions where transportation and the economy are closely integrated, optimizing network structure and enhancing synergy are vital for regional integration. This paper constructs a dual-factor linkage network using enterprise investment and liner shipping data to analyze linkage strength and synergy effects among cities in the Greater Bay Area. The findings reveal that (1) a core-periphery structure exists, with core cities dominating resource flows while secondary cities remain weak. The logistics network is led by Hong Kong and Shenzhen, while the capital flow network showcases the dominance of Hong Kong, Shenzhen, and Guangzhou. (2) From 2016 to 2021, interactions between transportation and the economy deepened, showing strong correlations in logistics and capital flows among core cities and between core and edge cities, but weaker correlations with sub-core and edge cities. Core cities stabilize regional transportation and economy, fostering agglomeration, while sub-core cities are more reliant on them, indicating a need for better resource balance. (3) The spatio-temporal coupling analysis reveals significant heterogeneity in flows among cities, with many exhibiting antagonistic couplings outside core areas. This study enhances understanding of synergy mechanisms in transportation and economic networks, offering insights for optimizing layouts and improving capital flow efficiency.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Global Urban Networks and Dynamics · Transportation Planning and Optimization · Complex Network Analysis Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Guangzhou 510663, China
School of Economics, Lanzhou University, Lanzhou 730000, China
Department of Economics and Management, Dalian University of Technology, Dalian 116081, China
Surveying and Mapping Institute, Lands and Resource Department of Guangdong Province, Guangzhou 510663, China
Funding
Ministry of Natural Resources
References (47)
Show source-provided references
1. Implications of International Bay Area Practices for Building the Guangdong-Hong Kong-Macau Greater Bay Area
2. How does transportation facilitate regional economic development? A heuristic mapping of the literature
3. Major Progress and Future Development Direction of China’s Urban Agglomeration Research
4. Progress and Perspectives of City Cluster Research
5. A Digital Twin for Intelligent Transportation Systems in Interurban Scenarios10.3390/app15137454 ↗
6. The Spatial Pattern and Influencing Factors of China’s Nighttime Economy Utilizing POI and Remote Sensing Data10.3390/app14010400 ↗
7. Henri, L., and Donald, N.-S. (1991). The Production of Space, Wiley.
8. The backbone structure and influence mechanism of urban information networks in China
9. Multidimensional Measurement of the Network Structure of the Guangdong-Hong Kong-Macao Greater Bay Area from the Spatial Perspective of Traffic Flow
10. Research on the Evolution and Spatial Expansion Model of the Digital Economy Network in the Yangtze River Delta Based on Enterprise Equity Correlation
11. The Spatial evolution of China’s Transnational Intercity Technology Corridors and its influencing factors
12. Loder, A., Ambühl, L., Menendez, M., and Axhausen, K.W. (2019). Understanding traffic capacity of urban networks. Sci. Rep., 9.10.1038/s41598-019-51539-5 ↗
13. Correlation analysis of day-to-day origin-destination flows and traffic volumes in urban networks10.1016/j.jtrangeo.2020.102899 ↗
14. Emergence of Scaling in Random Networks10.1126/science.286.5439.509 ↗
15. Destruction Resistance of Marine Freight Transportation Networks Based on Multilayer Complex Network Theory
16. Assessing the role of network topology in transportation network resilience10.1016/j.jtrangeo.2015.05.006 ↗
17. Study on the structural characteristics of transportation network and spatial correlation of cities and towns in Inner Mongolia
18. Spatial Identification and Structural Characterization of Chinese City Clusters Based on Transportation Big Data Networks
19. Network capital and urban development: An inter-urban capital flow network analysis10.1080/00343404.2021.1955098 ↗
20. Research on the Impact of New Trade Corridors on the Economic Linkages of Cities Along the Route—A Quasi-Natural Experiment Based on the Opening of the China-Europe Liner Train
21. Technology spillovers accompanying capital flows—The impact of shareholders’ technology level on innovation in high-tech firms
22. The Influence of Enterprise Investment Behavior on the Cyberspace Connection of Coastal Cities: Empirical Evidence from China10.1061/(ASCE)UP.1943-5444.0000904 ↗
23. Spatial Matching of Land Transportation and Tourism Economy in the Central Triangle Region
24. Air transport and economic growth: A review of the impact mechanism and causal relationships10.1080/01441647.2020.1738587 ↗
25. Comparing China’s city transportation and economic networks10.1016/j.cities.2016.01.006 ↗
26. Spatial Impacts of High Speed Rail on Accessibility and Economic Linkages in Less Developed Regions—Taking Lanzhou-Xinjiang High Speed Rail as an Example
27. Research on the Coupled Coordination Relationship between Transportation Advantage Degree and Economic Development—Taking Guangdong Province as an Example
28. Study on the Dynamic Development of Wuhan City Circle Based on the Degree of City Connectivity
29. The effects of information voids on capital flows in emerging markets10.1057/s41267-016-0056-6 ↗
30. Spatial Network Patterns of Guangdong, Hong Kong and Macao Greater Bay Area under the Flow Spatial Perspective: A Comparative Analysis Based on Information Flow and Traffic Flow
31. Deciphering the spatial structure of China’s megacity region: A new bay area—The Guangdong-Hong Kong-Macao Greater Bay Area in the making10.1016/j.cities.2018.10.011 ↗
32. Does regional cooperation constrain urban sprawl? Evidence from the Guangdong-Hong Kong-Macao Greater Bay Area10.1016/j.landurbplan.2023.104742 ↗
33. Transport Accessibility and Spatial Connections of Cities in the Guangdong-Hong Kong-Macao Greater Bay Area10.1007/s11769-019-1034-2 ↗
34. Economic development, flow of funds, and the equilibrium interaction of financial frictions10.1073/pnas.1707055114 ↗
35. Coupling characteristics of coastal ports and urban network systems based on flow space theory: Empirical evidence from China10.1016/j.habitatint.2022.102624 ↗
36. Cyberspatial linkages of coastal port city systems from the perspective of different flow elements
37. Characteristics and Network Structure of Urban Linkage in Northwest China from the Perspective
38. Evolution characteristics of the spatial network structure of tourism efficiency in China: A province-level analysis
39. Scale structure and coupling type of coastal port city system bit sequence from multifunctional perspective
40. Specification of the World City Network10.1111/j.1538-4632.2001.tb00443.x ↗
41. Urban Networks and Regional Integration: Theory and Chinese Experience
42. Study on the Synergistic Relationship between Spatial Structure and Logistics-Economic Network of the Yangtze River Delta City Cluster
43. Pain, K. (2012). The Polycentric Metropolis: Learning from Mega-City Regions in Europe, Routledge.
44. Exploring the influence of transportation on urban spatial structure using the spatial Durbin model: Evidence from 265 prefecture-level cities in China10.1007/s43762-024-00118-0 ↗
45. Study on Spatial Linkages within Urban Agglomerations and Coordinated Regional Development
46. Spatial structure and productivity in European regions10.1080/00343404.2021.1950912 ↗
47. Spatial structure and productivity in US metropolitan areas10.1068/a42151 ↗