CLC number:
On-line Access: 2023-11-13
Received: 2023-02-01
Revision Accepted: 2023-03-19
Crosschecked: 2023-11-14
Cited: 0
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Citations: Bibtex RefMan EndNote GB/T7714
Yilin SUN, Yinan DONG, Dianhai WANG, E. Owen D. WAYGOOD, Hamed NASERI, Kazuo NISHII. Correlation between travel experiences and post-COVID outbound tourism intention: a case study from China[J]. Journal of Zhejiang University Science A, 2023, 24(11): 1003-1016.
@article{title="Correlation between travel experiences and post-COVID outbound tourism intention: a case study from China",
author="Yilin SUN, Yinan DONG, Dianhai WANG, E. Owen D. WAYGOOD, Hamed NASERI, Kazuo NISHII",
journal="Journal of Zhejiang University Science A",
volume="24",
number="11",
pages="1003-1016",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2300057"
}
%0 Journal Article
%T Correlation between travel experiences and post-COVID outbound tourism intention: a case study from China
%A Yilin SUN
%A Yinan DONG
%A Dianhai WANG
%A E. Owen D. WAYGOOD
%A Hamed NASERI
%A Kazuo NISHII
%J Journal of Zhejiang University SCIENCE A
%V 24
%N 11
%P 1003-1016
%@ 1673-565X
%D 2023
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2300057
TY - JOUR
T1 - Correlation between travel experiences and post-COVID outbound tourism intention: a case study from China
A1 - Yilin SUN
A1 - Yinan DONG
A1 - Dianhai WANG
A1 - E. Owen D. WAYGOOD
A1 - Hamed NASERI
A1 - Kazuo NISHII
J0 - Journal of Zhejiang University Science A
VL - 24
IS - 11
SP - 1003
EP - 1016
%@ 1673-565X
Y1 - 2023
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2300057
Abstract: The COVID-19 pandemic has devastated global tourism and recovery is proceeding very slowly. For many countries, tourism served as a major economic sector, so investigating how to recover is essential. As China was the largest source of outbound travelers before the outbreak, study of the factors influencing Chinese intentions to travel overseas in the post-COVID era is revealing. In Apr. 2022, among seven provinces (or cities) with the most outbound tourists from 2019 to 2021, 2450 individuals responded to a questionnaire on daily mobility, tourism experiences, and the shifts due to the pandemic. Light gradient boosting machine (LightGBM), a robust ensemble learning method, was adopted to quantify and visualize the impact of explanatory factors on outbound travel intention. In addition, the Optuna mechanism and Shapley additive explanation (SHAP) instruments were employed for tuning hyperparameters and interpreting results, respectively. Findings suggest neither one-day nor multi-day tours have resumed to pre-COVID levels. Higher frequency of multi-day tours with further destinations, less car utilization in daily shopping trips, and moderate pandemic restrictions can boost the intention to travel abroad. The concerns and desires of different age groups for overseas travel need different responses. This study reveals the factors affecting Chinese outbound travel intentions and provides suggestions for the recovery of tourism in the post-COVID period.
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