Big data hedonic pricing: Econometric insights into room rates' determinants by hotel category

This research uses a big dataset of online prices published on Booking.com by three-, four- and five-star hotels located in Madrid (Spain). Data is broadened by other sources, resulting in a rich set of context-, hotel- and offerbased variables. This research aims to determine the impact of these variables on the online room prices set by one representative sample, featuring the total pricing behaviour as well as per hotel categories. The variables considered, their extent and the insight per category represent a novelty and complement the literature on demand forecasting and hedonic pricing, enabling the improvement of optimisation techniques. The models, based on regression analysis with random effects, reveal a significant impact of the variables on room prices and a clearly distinct behaviour for five-star hotels. This research contributes to the scientific community and practitioners by showing the pricing dynamics behaviour of an important urban destination by star rating.

Automated summary

This research analyzes the pricing behavior of three-, four- and five-star hotels in Madrid using a large dataset of online prices, uncovering the impact of various variables on room prices and identifying distinct behavior for five-star hotels. The study contributes to the scientific community by providing insights into pricing dynamics in a major urban destination based on star ratings.