Global Mobility Networks of Smart City Researchers: Spatiotemporal and Multi-Scale Perspectives, 2000–2020

This study examines the global mobility of researchers in the smart city domain from 2000 to 2020, using inter-country and intercity affiliation data from the Web of Science. Employing network analysis and spatial econometric models, the paper maps the structural reconfiguration of scientific labor circulation. The results show that the international mobility network is dense yet asymmetric, dominated by a small set of high-frequency corridors such as China–United States, which intensified markedly over the two decades. While early networks were fragmented and polycentric, the later period reveals a multipolar configuration with significant growth in South–South and intra-European exchanges. At the city level, Beijing, Shanghai, Wuhan, and Nanjing emerged as central nodes, reflecting the consolidation of East Asian hubs within the global knowledge system. Mesoscale community detection highlights the coexistence of territorially embedded ecosystems and transregional corridors sustained by thematic and reputational affinities. Growth decomposition indicates that high-income countries benefit from both talent retention and international inflows, while upper-middle-income countries rely heavily on inbound mobility. Spatial regression and quantile models confirm that economic growth and baseline scientific visibility remain robust drivers of urban smart city performance. In contrast, mobility effects are context-dependent and heterogeneous across city positions. Together, these findings demonstrate that researcher mobility is not only a vector of knowledge exchange but also a mechanism that reinforces spatial hierarchies and reshapes the geography of global smart city innovation.