This study uses intercity travel data and Internet search data to measure physical and virtual flows among 296 cities in China. To avoid the effects of the pandemic (as China has implemented strict lockdown policies), the main analysis is based on 2019. We first analyse the correlation between the two flows and compare their directional symmetry and hierarchical structures at the national level and within six major urban agglomerations. To explain intercity virtual flows, we apply the extended gravity model to proxy the “virtual mass” of cities. At the national level, the correlation of physical and virtual flows is 0.551. A decomposition analysis suggests that the two flows decouple at higher intensity of intercity physical flows. In particular, the correlations are the weakest at the two largest urban agglomerations of the Greater Bay Area (GBA) and the Beijing-Tianjin-Hebei Region (BTH). The gravity model framework applies well in the virtual space, and the total Internet use time is a good proxy in representing the virtual mass of a city. Compared to virtual flows, physical flows tend to concentrate more at top ranked city pairs, suggesting a more hierarchical city network. On the contrary, the Zipf curve for virtual flows is generally flatter, suggesting a more decentralised city network with more comparable virtual flows across cities at different ranks. Geographical distance generally still matters but is no longer significant for virtual flows in well-integrated urban agglomerations like GBA and BTH. • Compare physical and virtual flows among 296 cities in China. • Apply the extended gravity model framework to intercity virtual flows. • Internet time is an effective proxy for city “mass” in virtual space. • Distance decay is not significant in some well-integrated urban agglomerations. • Spatial scale matters in understanding multi-dimensional intercity connectivity.
Li et al. (Sat,) studied this question.