Changes in Economic Network Patterns and Influencing Factors in the Urban Agglomeration of Guangdong–Hong Kong–Macao Greater Bay Area: A Comprehensive Study
Autor(en): |
Ruipu Li
Bo Yu Qun Wang Gang Wu Zhiyu Ma |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 27 März 2024, n. 4, v. 14 |
Seite(n): | 1093 |
DOI: | 10.3390/buildings14041093 |
Abstrakt: |
The aim of this study is to comprehensively evaluate the economic network patterns and their influencing factors of the Guangdong–Hong Kong–Macao Greater Bay Area (GHMGBA) in China, considering population scale, economic development level, and land-resource endowment. By employing a modified gravity model and a social-network method, we quantitatively analyzed urban agglomeration integrity indices, such as network density, edge–core structure, cohesive-subgroup index, and urban individual index (e.g., centrality degree) of this region, encompassing nine cities in Guangdong Province and two special administrative regions. The results revealed significant changes in the economic network patterns within the GHMGBA over time. Furthermore, the quadratic assignment procedure correlation analysis index was used to identify the various factors affecting the strength of the economic interaction. The findings demonstrated an annual increase in the strength of economic interaction between cities and regions within the GHMGBA over the past 20 years, along with the emergence of a polycentric economic development pattern. The results also suggest that the spatial location and level of economic development are key determinants influencing the strength of economic linkages in this area. This study supports the conclusion that deepening exchanges and cooperation among core cities, bolstering economic development in sub-core cities, and facilitating the construction of an integrated regional transportation network will expedite the process of economic integration. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
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Datenseite - Reference-ID
10773542 - Veröffentlicht am:
29.04.2024 - Geändert am:
05.06.2024