<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Global Mobility | Junyao He | Academic Portfolio</title><link>https://junyaohe001.github.io/tags/global-mobility/</link><atom:link href="https://junyaohe001.github.io/tags/global-mobility/index.xml" rel="self" type="application/rss+xml"/><description>Global Mobility</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sun, 04 Jan 2026 00:00:00 +0000</lastBuildDate><image><url>https://junyaohe001.github.io/media/icon_hu14599980757415029838.png</url><title>Global Mobility</title><link>https://junyaohe001.github.io/tags/global-mobility/</link></image><item><title>Revealing the Global Mobility and Driving Forces of Digital Nomads through Network Analysis and Interpretable Machine Learning</title><link>https://junyaohe001.github.io/working-papers/digital-nomad-mobility/</link><pubDate>Sun, 04 Jan 2026 00:00:00 +0000</pubDate><guid>https://junyaohe001.github.io/working-papers/digital-nomad-mobility/</guid><description>&lt;p>&lt;strong>Status:&lt;/strong> Finalizing&lt;/p>
&lt;p>This article conceptualises digital-nomad mobility as an emerging form of digitally enabled urban mobility. It combines network analysis and interpretable machine learning to explain city attractiveness, cross-city flows, and the uneven geography of mobile remote work.&lt;/p></description></item></channel></rss>