Abstract
This article examines digital-nomad mobility as an emerging form of digitally enabled urban mobility. It reconstructs global city-to-city movement networks and asks how destinations differ in their attractiveness, brokerage position, reach, and dependence on particular origin markets.
Network analysis is combined with interpretable machine learning to explain city attractiveness and cross-city flows. The explanatory framework considers urban amenities, costs, institutional conditions, connectivity, labour-market characteristics, and the broader geography of remote work.
The study connects digital-nomad research with urban and economic geography by treating mobility as a relational system and by examining how digitally mobile professionals may reinforce or redirect uneven urban development.