Timing matters: crisis severity and occupancy rate forecasts in social unrest periods
International Journal of Contemporary Hospitality Management
ISSN: 0959-6119
Article publication date: 8 June 2021
Issue publication date: 9 August 2021
Abstract
Purpose
The impact of demand fluctuation during crisis events is crucial to the dynamic pricing and revenue management tactics of the hospitality industry. The purpose of this paper is to improve the accuracy of hotel demand forecast during periods of crisis or volatility, taking the 2019 social unrest in Hong Kong as an example.
Design/methodology/approach
Crisis severity, approximated by social media data, is combined with traditional time-series models, including SARIMA, ETS and STL models. Models with and without the crisis severity intervention are evaluated to determine under which conditions a crisis severity measurement improves hotel demand forecasting accuracy.
Findings
Crisis severity is found to be an effective tool to improve the forecasting accuracy of hotel demand during crisis. When the market is volatile, the model with the severity measurement is more effective to reduce the forecasting error. When the time of the crisis lasts long enough for the time series model to capture the change, the performance of traditional time series model is much improved. The finding of this research is that the incorporating social media data does not universally improve the forecast accuracy. Hotels should select forecasting models accordingly during crises.
Originality/value
The originalities of the study are as follows. First, this is the first study to forecast hotel demand during a crisis which has valuable implications for the hospitality industry. Second, this is also the first attempt to introduce a crisis severity measurement, approximated by social media coverage, into the hotel demand forecasting practice thereby extending the application of big data in the hospitality literature.
Keywords
Acknowledgements
The authors acknowledge the financial support from Zhejiang Province Natural Science Foundation 2019 (LY19G030029), and the Start-up Research Grant of University of Macau (SRG2019-00182-FBA).
Citation
Qiu, R.T.R., Liu, A., Stienmetz, J.L. and Yu, Y. (2021), "Timing matters: crisis severity and occupancy rate forecasts in social unrest periods", International Journal of Contemporary Hospitality Management, Vol. 33 No. 6, pp. 2044-2064. https://doi.org/10.1108/IJCHM-06-2020-0629
Publisher
:Emerald Publishing Limited
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