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.

This study investigates the competitive and cooperative relationships within urban agglomerations, specifically focusing on the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Using the Lotka–Volterra model from ecology, the research aims to analyse and predict the dynamic relationships among cities in this area. The purpose is to understand how competition and cooperation influence regional integration, and their complex economic connections. This paper employs both qualitative and quantitative methods, including time-series analysis and the application of the Lotka–Volterra model, to evaluate economic interactions and the roles of various cities or regions within the GBA. The study reveals that mutualistic, competitive, predatory, commensal, and parasitic relationships coexist among them, with core cities such as Shenzhen, Guangzhou, Hong Kong, and Macao assuming pivotal roles in shaping the overall dynamics. The findings highlight the importance of functional division, regional cooperation, and innovative collaboration to enhance sustainable development. Policy recommendations are provided to foster a balanced and integrated growth model, emphasizing inter-city cooperation, resource sharing, and avoidance of industrial homogeneity.