Tourism is deeply intertwined with environmental conditions and vulnerable to external shocks. Climate factors, particularly air pollution, act as both a push and pull factor: pollution at the origin “pushes” tourists to flee, while pollution at the destination degrades the experience. Understanding these dynamics is crucial for destination management. Furthermore, resilience—the ability to withstand and recover from shocks like COVID-19—is paramount. Developing quantifiable indices for resilience (e.g., for restaurants or heritage sites) allows stakeholders to identify vulnerable sectors and target interventions. Finally, investigating risk perception at the tourist level helps predict travel avoidance and behavioral changes during crises, which is essential for crisis communication.

 

Our work has extensively covered air pollution and climate. Our team utilized big data to show that pollution in origin cities increases residents’ travel intention (the “fleeing” effect). We also linked relative air quality to the “restorative quality” of destinations, finding that cleaner air relative to the tourist’s home enhances the feeling of being “physically away”. Regarding resilience and COVID-19, we developed a “Restaurant Resilience Index” for U.S. counties, identifying that areas with higher dining-in habits and specific political ideologies were less resilient to stay-at-home orders. We also examined hotel survival, finding that inter-organizational imitation (following peers’ closure decisions) exacerbated market exits during the pandemic. For cultural heritage sites, our team constructed a resilience evaluation index, identifying cultural inheritance and protection values as key drivers of system resilience. At the tourist level regarding risk perception, we conducted a meta-analysis confirming a significant negative link between perceived risk and travel intention, identifying that cognitive and affective risk perceptions work in parallel. Our team also introduced the concept of “cognitive inconsistency” using behavioral economics, showing that individuals hold conflicting risk perceptions depending on whether they identify as a “tourist” or a “resident” during a pandemic, which leads to modifications in travel plans.