Predicting the direction of dynamic price adjustment in the Hong Kong hotel industry

Abstract

This study analysed dynamic pricing data of Hong Kong hotels within the last-minute 1-week booking window to determine patterns and direction of room rate changes and their association with hotel characteristics regarding tangible attributes, reputational variables and contextual factors. Findings show that room rates are more likely to increase than decrease or stay constant, and that, holding demand and market conditions constant, the likelihood of price increases (decreases), based on standard binomial probit regression, is positively (negatively) associated with size (tangible attribute), chain affiliation and star rating (reputational attributes), and seller density and location accessibility (contextual factors). These results confirm the importance of differentiation in pricing hotel rooms and indicate how hotel customers and revenue managers can combine these characteristics with predicted demand to anticipate the direction of room rate change in the last-minute booking window as the booking horizon approaches check-in.