School of Resources and Planning, Guangzhou Xinhua University, Guangzhou, China.
Faculty of Innovation and Design, City University of Macau, Macau, China.
Front Public Health. 2022 Oct 25;10:973843. doi: 10.3389/fpubh.2022.973843. eCollection 2022.
The COVID-19 pandemic has seriously affected China's macroeconomy, industrial transformation, and high-quality development. Research on economic patterns and urban network systems can provide a reference for healthy development of the regional economic system. The evolution of the economic pattern and urban network system of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2010 to 2020 is investigated using methods (e.g., the gravity center model, the gravitational force model, social network analysis, and geographic information system). (1) The gravity center of gross domestic product (GDP) of the GBA is located in Nansha district, Guangzhou, with a skewing direction northwest-east-northwest and a movement rate of "large-small-large." The center of import and export and the center of consumption show a "zigzagging migration" in which the center of investment shows an "irregular (random) migration". (2) The economic connection degree of cities in the GBA exhibits a high ascending velocity, and the whole area tends to be mature, with a significant effect of spatial proximity. With the steady increase in network density, there is significant polarization of network centrality in the region. The four major cohesive subgroups have been relatively stable and consistent with the degree of geographic proximity of the cities. The center-periphery structure is more significant, in which the core area is extended to the cities on the east coast of the Pearl River Estuary, thus forming the core cluster of "Hong Kong-Shenzhen-Guangzhou-Dongguan." In this study, the evolution of economic patterns and urban network systems in the GBA over the past decade is analyzed using multiple methods (i.e., gravity model, urban network system analysis, and geographic information system) based on urban socioeconomic data by starting from various spatial elements (e.g., "points, lines, and networks") to gain insights into and optimize research on regional economic development after the COVID-19 pandemic.
新冠疫情对中国宏观经济、产业转型和高质量发展产生了严重影响。研究经济格局和城市网络系统可以为区域经济系统的健康发展提供参考。本文采用重心模型、万有引力模型、社会网络分析和地理信息系统等方法，研究了 2010-2020 年粤港澳大湾区（GBA）经济格局和城市网络系统的演变。（1）GBA 地区生产总值（GDP）重心位于广州市南沙区，呈西北-东南-西北偏斜方向，移动速度为“大-小-大”。进出口重心和消费重心呈“曲折迁移”，投资重心呈“不规则（随机）迁移”。（2）GBA 城市经济联系程度呈高速上升趋势，整体趋于成熟，空间邻近效应显著。随着网络密度的稳步增加，区域内网络中心度的极化现象显著。四大凝聚子群相对稳定，与城市地理邻近程度一致。中心-边缘结构更加明显，核心区域向珠江口东岸城市延伸，形成“港深广莞”核心集聚。本研究基于城市社会经济数据，从多个空间要素（如“点、线、网”）出发，运用多种方法（重力模型、城市网络系统分析和地理信息系统），分析了过去十年粤港澳大湾区经济格局和城市网络系统的演变，为后疫情时代区域经济发展研究提供了思路和优化。
