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Influence of Tourism Safety Perception on Destination Image: A Case Study of Xinjiang, China

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  • Guijin Ding

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China)

  • Jinfeng Wu

    (School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China)

Abstract

Tourism safety perception is one of the factors influencing destination image, but there is a lack of systematic research on the multidimensional influence of tourism safety perception on destination image. In this paper, based on the survey data collected from 623 tourists traveling in Xinjiang, China, we classified the respondents into three types of high, medium, and low levels of tourism safety perception by cluster analysis, and studied the influence of tourism safety perception on destination image in multiple dimensions by means of content analysis, diversity index, one-way ANOVA, and factor analysis. We found that tourism safety perception significantly affects the cognitive image, affective image, and conative image of the destination. Tourists with a high safety perception evaluate and affectively experience destination attributes more positively with higher satisfaction and stronger willingness to revisit and recommend. Tourism safety perception affects the stereotype image of the destination to a certain extent. Tourists in general produce a broadly homogeneous stereotype image, but there are differences in diversity and emotions. Tourists with a high safety perception have a richer and more positive stereotype image. This study enriches and deepens the theory regarding the influence of tourism safety perception on destination image, and also provides a richer theoretical basis for destination image construction and precision marketing.

Suggested Citation

  • Guijin Ding & Jinfeng Wu, 2022. "Influence of Tourism Safety Perception on Destination Image: A Case Study of Xinjiang, China," Sustainability, MDPI, vol. 14(3), pages 1-21, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1663-:d:739508
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    Cited by:

    1. Ying Zhang & Jiehang Song & Angelo Sciacca & Jin Chan & Xiaoguang Qi, 2022. "Novel Sentiment Lexica Derived from User Generating Content by Chinese Tourists in Pacific Islands," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
    2. Mihai F. Băcilă & Raluca Ciornea & Luiza M. Souca & Alexandra M. Drule, 2022. "Content Analysis on Sustainability Dimensions in DMOs’ Social Media Videos Advertising the World’s Most Visited Cities," Sustainability, MDPI, vol. 14(19), pages 1-25, September.

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