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Forecasting hotel room demand amid COVID-19

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  • Hanyuan Zhang
  • Jiangping Lu

Abstract

The COVID-19 pandemic has hindered international travel considerably, greatly affecting the hotel industry. Hong Kong, as a well-known international tourist destination, has also been hit hard by the crisis. Recovery forecasts for hotel room demand are critical to managing this ongoing crisis. This study employs the autoregressive distributed lag error correction model to generate baseline forecasts of hotel room demand for Hong Kong followed by compound scenario analysis to optimize forecasts considering the pandemic’s impacts. The COVID-19 Travelable Index is designed to group source markets by their pandemic situations, vaccinations, policy responses, and health resilience. To capture pandemic-related uncertainty, this study presents three scenarios describing recovery patterns based on trough duration, the quarter for lifting travel restrictions, and the quarter for returning to baseline forecasts. Hotel demand forecasts geared toward each source market are analyzed, revealing strategies to help hotel businesses manage this crisis.

Suggested Citation

  • Hanyuan Zhang & Jiangping Lu, 2022. "Forecasting hotel room demand amid COVID-19," Tourism Economics, , vol. 28(1), pages 200-221, February.
    • Handle: RePEc:sae:toueco:v:28:y:2022:i:1:p:200-221
    DOI: 10.1177/13548166211035569
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    References listed on IDEAS

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    Cited by:

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    2. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).

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