# Network Structure and Synergy Characteristics in the Guangdong-Hong Kong-Macao Greater Bay Area
## 3 Research Data and Methods
### Data Source  
The underlying logic of transport networks is rooted in interregional trade relations, particularly those driven by factor flows, with a focus on capital. Inter-enterprise investment reflects the movement of resources, capital, technology, and markets, which are central to regional economic linkages [34]. This encompasses not only capital flow paths but also insights into industrial partnerships, technology transfer, and market expansion. Furthermore, inter-enterprise investment relationships elucidate the synergies among industries, revealing the division of labor and cooperative dynamics across various links in the industrial chain. This enhances the comprehension of industrial synergies and resource-sharing mechanisms among the economies within the Greater Bay Area. The study selects 2016, 2019, and 2021 as key temporal nodes based on two principal considerations. First, these years reflect critical shifts in policy and macro-level conditions. Specifically, 2016 marks the prelude to the formal release of the Outline Development Plan for the Greater Bay Area, serving as a baseline for regional economic linkage analysis prior to policy implementation. The year 2019 represents the initial phase of policy execution, enabling observation of the early impact on regional factor flows. In contrast, 2021 coincides with the onset of the 14 th Five-Year Plan and is characterized by the dual context of epidemic disruption and deepened policy advancement, providing a robust basis for examining network evolution. Second, data for all three years derive from a consistent platform with standardized collection protocols and indicator definitions. This ensures temporal continuity, enhances data comparability, and strengthens the foundation for longitudinal network analysis.  
Therefore, utilizing inter-enterprise investment data to construct a capital flow network effectively captures the complexity and multidimensionality of economic interactions within and beyond the region [35]. This analysis is based on inter-regional investment data from 2016, 2019, and 2021, provided by Qixinbao (Qixinbao is a complete database containing samples from 110 million Chinese enterprises extracted from 100 websites, including the National Enterprise Credit Information Public Disclosure System, the China Court Judgment Network, and the China Enforcement Information Public Network ([[https://www.qixin.com/group-buy](https://www.qixin.com/group-buy)]([https://www.qixin.com/group-buy](https://www.qixin.com/group-buy)), accessed on 1 June 2025)). The data undergoes manual verification and correction through random sampling and cross-checking to ensure completeness and scientific integrity. Applying principles of representativeness, quantifiability, and comparability, the \"enterprise-enterprise\" network is transformed into a \"city-city\" network. This process filters the investment linkage data between enterprises across cities in the Greater Bay Area. Ultimately, a capital flow network is constructed, using city economic data sourced from the China City Yearbook.  
Considering the geographical specificity of the city cluster in the Greater Bay, transport flow data is sourced from container liner AIS data provided by global port, shipping, and  
Figure 1: Geographic location of the Guangdong-Hong Kong-Macao Greater Bay Area.  
logistics companies, particularly Alphhainer. This data includes detailed information such as shipping companies, origin ports, destination ports, call ports, route operation ship sizes (measured by container capacity), and schedules (frequency of calls at each port per week). A global shipping database is constructed for the years 2016, 2019, and 2021. From this database, ship schedule information between ports in the Greater Bay Area, including transshipment ports, is screened and analyzed. Based on these insights, a comprehensive transportation and logistics network is developed. Additionally, port cargo throughput and port container throughput data are obtained from the China Port Yearbook.