Tourism seasonality, online user rating and hotel price: A quantitative approach based on the hedonic price model [Summary]

Abstract

The paper aims to investigate the relationship between tourism seasonality, online user ratings and the determinants of hotel prices based on the hedonic price model using the online dataset of hotels in Sanya, China. The empirical results of ordinary least squares (OLS) and quantile regressions both show that hotel prices are highly related to tourism seasonality. Compared to the low season, hotel prices increase by 23.1% in the high season and by 159.9% during Chinese New Year. Online user ratings demonstrate heterogeneous impacts on both location and time dimensions in hotel pricing. The quantile regressions further indicate that hotels with higher prices are less sensitive to seasonality and that the online user rating plays a more important role for mid- and low-priced hotels by mitigating the negative seasonal effects on hotel prices. Our findings provide new evidence supporting the current literature and offer useful implications for hospitality management.