Journal
CITIES
Volume 103, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.cities.2020.102738
Keywords
City network; Guangdong-Hong Kong-Macao Greater Bay Area; Exponential random graph model (ERGM); Interlocking networks model
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Funding
- Guangdong Science and Technology Department [2019A101002064]
- Humanities and Social Science Fund of Ministry of Education of China [20YJC790189]
- National Statistical Science Research Program [2019510]
- Social Science Planning Project of Guangdong Province [GD19YGL17]
- Shantou University Scientific Research Foundation Project [STF18010]
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As one of the fast-developing mega-city regions in the world, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is in the process of construction. Drawing on the idea of cities as strategic places, our analysis describes the city network in the GBA and contributes to the quantitative analysis of the formation of city network, as we: (1) identify the network structure through the lens of APS firms' locational strategies within the GBA; (2) take a step further in exploring the influential factors affecting the formation of the city network using the exponential random graph model (ERGM), compared with the previous studies only focusing on the description of the city networks. Major findings include: (1) the connectivity among cities has enhanced in the GBA since 2014, indicating that there are closer relationships among the cities; (2) from the perspective of the node cities, polycentric structure has emerged, whereby the status of Guangzhou and Shenzhen in the city network has improved and they are gradually becoming the core cities in the GBA; (3) a hierarchical structure is detected in the city network in the GBA, including the core cities (Hong Kong, Guangzhou and Shenzhen), the semi-peripheral cities (Macao, Foshan, Dongguan and Zhongshan), and the peripheral cities (Zhuhai, Jiangmen, Huizhou and Zhaoqing); (4) according to the results of ERGM, the city network in the GBA has significant path dependence characteristics, the existing city network, city's per capita GDP, innovative environment and international reputation are the main factors affecting the formation of the city network.
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