Complex network analysis of China's domestic air cargo network based on actual flight data

Abstract

Driven by the rapid development of China's e-commerce and logistics industries, the demand for air cargo has been steadily increasing. This study aims to analyze the spatiotemporal evolution and robustness of China's Air Cargo Network (CACN) using monthly operational data. The research employs complex network theory to examine spatial and temporal dynamics, integrates multiple central indicators for evaluating node importance, and assesses network robustness under various attack scenarios. Our study demonstrates that China's air cargo network faces challenges such as low route execution rates, an unstable structure, and significant cargo flow imbalances—particularly in low-traffic areas. Strategic hubs, such as Urumqi (URC), Kunming (KMG), Hangzhou (HGH), Shenzhen (SZX), and Nanjing (NKG) play vital roles., while the rise of Ezhou Huahu Airport (EHU) alleviates network pressure on major hubs. Moreover, our analysis reveals a distinct differentiation in hub airport roles, with the network exhibiting scale-free and small-world characteristics. The robustness of the network is shown to vary depending on the type of attack strategy employed, underscoring the need for targeted interventions to enhance overall network efficiency and resilience. Key findings reveal that CACN has a low route execution rate and an unstable structure, with significant cargo flow imbalances, especially in low-traffic regions. Additionally, CACN shows scale-free and small-world characteristics, with network robustness varying under different attack strategies. These insights provide a foundation for optimizing the network's efficiency and robustness.