Designing tourist experiences amidst air pollution: A spatial analytical approach using social media

Zhang, Xiaowei; Yang, Yang; Yi, Zhang; Zhang, Zili

doi:10.1016/j.annals.2020.102999

Cited by 49 publications

(33 citation statements)

References 50 publications

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“…In Dianping's "tour around" module, users are expected to share their own travel experience, and their comments are mostly tourismrelated; By using Weibo, users can share their lives, and their posts are diverse in themes, including travel experience, personal feeling, residents' daily activities, etc. (Zhang, Yang, Zhang, & Zhang, 2020). Therefore, the themes extracted by Dianping should be more concentrated on tourism.…”

Section: Data Collection and Preprocessingmentioning

confidence: 99%

Culture vs. distance: comparing the effects of geographic segmentation variables on tourists’ destination images based on social media data

Jiang

Zhang

et al. 2021

Comput.Urban Sci.

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Culture and distance are two major factors for geographically segmenting tourists in tourism marketing and advertising. Previous empirical studies on the destination image, however, have examined extensively the effect of the culture while inadequately the effect of the distance, let alone comparing the effects of the two variables. Using social media data, this study compares the effect of distance-based segments of tourists with that of culture-based segments in producing diverse perceived images of a destination. From Sina Weibo data, 282,532 Chinese mainland tourists who visited Suzhou, China during 2012–2016 and their perceived destination images are extracted and analyzed. The main results include: 1) for distance-based segments, the image differences increased with distance and the short-haul tourists perceived a more comprehensive image than the long-haul tourists; 2) for culture-based segments, the image differences were clear and relatively complex, while tourists from Wuyue cultural region had similar image perceptions with the local visitors; 3) the q-statistic of the Geodetector method shows that the culture-based segmentation can explain 65.8% of image variations while the distance-based segmentation can explain 46.6% of image variations, suggesting that culture is a more appropriate variable to segment the tourism market.

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Section: Data Collection and Preprocessingmentioning

confidence: 99%

Culture vs. distance: comparing the effects of geographic segmentation variables on tourists’ destination images based on social media data

Jiang

Zhang

et al. 2021

Comput.Urban Sci.

Self Cite

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“…The study found that haze pollution had a significant impact on the image of Beijing, and potential tourists were constantly decreasing. Others proposed a spatial analytical framework to explore tourist experiences from geotagged social media data in Beijing in 2013 [40]. They investigated tourists who reported fewer positive sentiments and more health issues due to increasing air pollution.…”

Section: Literature Reviewmentioning

confidence: 99%

Machine Learning Aided Tracking Analysis of Haze Pollution and Regional Heterogeneity

2021

KSII TIIS

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Not only can air pollution reduce the overall competitiveness of tourist destinations, but also changes tourists' travel decisions, thereby affecting the tourism flows. The study presents a machine learning method to analyze how the haze pollution puts spatial effect on tourism flows in China from 2001 to 2018, and reveals the regional differences in heterogeneity among eastern, central, and western China. Our investigation reveals three interesting observations. First, the Environmental Kuznets Curve of the impact of haze pollution on tourism flows is not significant. In the eastern and western regions, the interaction between haze pollution and domestic tourism flows as well as inbound tourism flows shows an inverted U-shaped curve respectively. Second, there is an significantly positive spillover effect of tourism flows in all of the eastern, central, and western regions. As to the intensity of spillover, domestic tourism flows is higher than that of the inbound tourism flows. Both of the above figures are greatest in the eastern. Third, the Chinese haze pollution mainly reduces the inbound tourism flows, and only imposes significantly negative direct effects on the domestic tourism flows in the central region. In the central and eastern regions, significantly negative direct effects and spillover effects are exerted on inbound tourism.

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“…Tasci and Boylu [ 49 ] confirmed that disaster events could change individuals’ perception of tourism destinations and directly influence the tourism decisions of tourists, and this impact is continuous. Zhang, Yang, Zhang, and Zhang [ 54 ] reported that tourists in Beijing showed fewer positive emotions and more health concerns due to severe smog pollution. Specifically, tourists showed more sensitively to air pollution compared to residents.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Understanding Tourist Behavioural Intention When Faced with Smog Pollution: Focus on International Tourists to Beijing

Ruan

Lee

Song

2021

IJERPH

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This study examines the behavioural intentions of international tourists travelling to Beijing when faced with smog pollution. An extended MGB (model of goal-directed behaviour) was employed as the theoretical framework by integrating mass-media effect and perception of smog. The role of mass-media effect and perception of smog were considered as new variables in the international tourist’s decision-making process for travel to Beijing. Structural equation modelling (SEM) was employed to identify the structural relationships among research variables. Our research results showed a strong correlation between positive anticipated emotion and desire. The mass-media effect is a significant (direct) predictor of both the perception of smog and behavioural intention. The Chinese government could attach great importance to the mass-media effect to reduce the negative impact caused by smog pollution on inbound tourism.

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Designing tourist experiences amidst air pollution: A spatial analytical approach using social media

Cited by 49 publications

References 50 publications

Culture vs. distance: comparing the effects of geographic segmentation variables on tourists’ destination images based on social media data

Culture vs. distance: comparing the effects of geographic segmentation variables on tourists’ destination images based on social media data

Machine Learning Aided Tracking Analysis of Haze Pollution and Regional Heterogeneity

Understanding Tourist Behavioural Intention When Faced with Smog Pollution: Focus on International Tourists to Beijing

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