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Tourism Arrival Prediction

In: Tourism Analytics Before and After COVID-19

Author

Listed:
  • Cao Wenfei

    (Nanyang Technological University)

  • Gu Yichao

    (Nanyang Technological University)

  • Wang Jingyi

    (Nanyang Technological University)

  • Wang Yanan

    (Nanyang Technological University)

  • Zhao Yifan

    (Nanyang Technological University)

  • Zhu Haoxiang

    (Nanyang Technological University)

Abstract

COVID-19 led to various economic and social impacts on various stakeholders from hotel industry. In this study, we analyzed the performance of hotel industry influenced by the number of confirmed COVID-19 cases in the global scale. The analysis shows that, in the face of the pandemic, high-class hotel is the most severely affected hotel type; on the other hand, luxury hotels can recover much faster than the relatively lower tiered ones due to their high premium and eligibility of functioning as quarantine stays. After running the predictive model, we are optimistic that the hotel industry and tourism industry will recover soon when vaccination rates improve. To obtain a faster recovery, we believe both policy makers and companies from tourism industry should work hard in times of crisis.

Suggested Citation

  • Cao Wenfei & Gu Yichao & Wang Jingyi & Wang Yanan & Zhao Yifan & Zhu Haoxiang, 2023. "Tourism Arrival Prediction," Springer Books, in: Yok Yen Nguwi (ed.), Tourism Analytics Before and After COVID-19, pages 231-246, Springer.
    • Handle: RePEc:spr:sprchp:978-981-19-9369-5_14
    DOI: 10.1007/978-981-19-9369-5_14
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