Tourism Network Attention Variation of Chinese Cities under the COVID-19 Pandemic

Xinshuo Hou
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Xinshuo Hou: Business School, Xiangtan University, Xiangtan 411105, China
Authors registered in the RePEc Author Service: 侯新烁 ()

Sustainability, 2022, vol. 14, issue 9, 1-15

Abstract: At the end of 2019, the COVID-19 pandemic broke out globally and had a tremendous impact on tourism development in countries around the world. The rapid shift of tourism from “over-tourism” to “under-tourism”, threatening the future of the global economy and society, has generated considerable interest from academia and the policy community, but the impact of COVID-19 on tourism variation remains untested by empirical evidence. Based on the daily Baidu Index of 247 prefecture-level cities in China from 2018 to 2021, this study assessed the treatment effect of COVID-19 on tourism and analyzed its dynamic characteristics using the regression-discontinuity-design (RDD) method combined with tourism network attention ( TNA ) data. The results show that after the outbreak of the COVID-19 pandemic, the level value of TNA dropped significantly by 2.12 ( p < 0.10), and the difference value of TNA ( TNA _diff ) dropped significantly by 10.77 ( p < 0.01), indicating that COVID-19 has a negative causal effect on tourism development, and its impact is more pronounced in major tourist source cities, with a coefficient of −14.91 ( p < 0.01) corresponding to −4.57 ( p < 0.01) for non-major tourist source cities when the dependent variable TNA_diff . The identification of dynamic effects further confirms that the negative impact of the pandemic on tourism network attention is fluctuating and persistent during the study period, with the two major “golden weeks” and peak season being the most severe. Compared to 2020, the TNA has generally shown an upward trend since 2021, indicating signs of a rebound in the vitality of resident tourism, which is conducive to the healthy development of the tourism market.

Keywords: COVID-19 pandemic; tourism development; the Baidu index; RDD; dynamic effects (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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