TY - JOUR
T1 - Stay or travel? Spatial heterogeneity impact of air pollution on travel intention
AU - Cao, Xianting
AU - Zhang, Honglei
AU - Wang, Mengqing
AU - Xiao, Xiao
AU - Yang, Yang
N1 - Publisher Copyright:
© 2023 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Air quality
KW - Baidu index
KW - geographically weighted negative binomial regression
KW - spatial heterogeneity
KW - travel intention
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U2 - 10.1080/13683500.2023.2197199
DO - 10.1080/13683500.2023.2197199
M3 - Article
AN - SCOPUS:85152412822
SN - 1368-3500
JO - Current Issues in Tourism
JF - Current Issues in Tourism
ER -