Hotel occupancy rate volatility and its determinants

In the hotel industry, the occupancy rate, which is the number of rooms occupied by inbound tourists in proportion to the total number of rooms available for occupation, is an indicator of a hotel’s availability. For planning purposes, it is useful for hotel management to know well in advance the expected occupancy rates. However, since the hotel industry is among the most volatile and is influenced by local and international economic and political factors, it is difficult to predict exact occupancy rates. To manage risks associated with this volatility and uncertainty, the hotel industry considers it sufficient to be able to know in advance the turning points in occupancy rates, which are the periods in time when increasing occupancy rates change to decreasing occupancy rates and, subsequently, decreasing occupancy rates change to increasing occupancy rates. The present study aims to develop models that could predict the turning points of the upward and downward trends in hotel occupancy rates so that hoteliers would know in advance when the current trend would change for the better or worse. These models are developed not for individual hotels but for groups of hotels that have similar tariffs or pricing levels, as occupancy rates vary according to prices charged. Given that there is no evidence of past research using non-linear models for predicting occupancy rates in the hotel industry, the present study predicts the turning points that indicate the directional change in the hotel occupancy rate by estimating logistic and probit regression models with a composite leading indicator and hotel demand determinants