Stay or travel? Spatial heterogeneity impact of air pollution on travel intention

ABSTRACT

Air pollution help shape people's travel preferences and behaviour, and when facing air pollution, individuals may consider travelling out for a short or long time as a coping strategy. We apply a Geographically Weighted Negative Binomial Regression (GWNBR) to analyze the effects of air pollution on people's travel intentions from origins. Our research covers 332 prefecture-level cities across China and collects daily air quality index (AQI), the Baidu indexes of ‘tourism’, and weather data from 2015 and 2018. The results show that AQI is positively associated with people's willingness to travel, and the long-term threat of air deterioration will strengthen people's willingness to flee. We estimate a series of GWNBR models with different air pollutants and cities with varying levels of air quality. The distribution of GWNBR regression results shows a more obvious strip characteristic, with coefficients of AQI in most cities are positive. Residents in cities with better air quality are more sensitive to air deterioration, compared with the residents in heavily polluted cities, who demonstrate a higher tolerance to air pollution. Finally, we provide the theoretical and practical implications of these effects on tourism.

KEYWORDS:

• Air quality
• Baidu index
• travel intention
• geographically weighted negative binomial regression
• spatial heterogeneity

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [Grant Number 41771153].