Does historical data still matter for demand forecasting in uncertain and turbulent times? An extension of the additive pickup time series method for SME hotels

Heo, Cindy Yoonjoung; Viverit, Luciano; Pereira, Luis

http://hdl.handle.net/10400.1/19809

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Authors

Heo, Cindy Yoonjoung

Viverit, Luciano

Pereira, Luis

Abstract(s)

Demand forecast accuracy is critical for hotels to operate their properties efciently and proftably. The COVID-19 pandemic is a massive challenge for hotel demand forecasting due to the relevance of historical data. Therefore, the aims of this study are twofold: to present an extension of the additive pickup method using time series and moving averages; and to test the model using the real reservation data of a hotel in Italy during the COVID-19 pandemic. This study shows that historical data are still useful for a SME hotel amid substantial demand uncertainty caused by COVID-19. Empirical results suggest that the proposed method performs better than the classical one, particularly for longer forecasting horizons and for periods when the hotel is not fully occupied.