The Impact on Bed and Breakfast Prices: Evidence from Airbnb in China

Abstract

As a new type of accommodation and a new way of life, it is of great significance for the spatial optimization and price management of the tourist accommodation market to explore the spatial differentiation characteristics of and influencing factors on bed and breakfast (B&B) house prices. Taking Shandong B&B merchants on the Airbnb website as the research object, this paper discusses the spatial characteristics of and influencing factors on B&B prices in the Shandong province, combining spatial autocorrelation analysis and interpolation analysis to identify the B&B cluster region. Quantile regression was used to reveal the main influencing factors. The results show that: (1) the spatial agglomeration effect of B&B prices in the Shandong province is obvious, and the high value areas form a new pattern between the provincial economic circle and the Jiaodong Economic Circle; (2) the influence of different factors on B&B house prices is very uneven in space. From the regional point of view, there are “sub-regional effects” on the spatial distribution of the influences of various factors on B&B house prices. The results of the study provide references for reasonable pricing, scientific site selection, and spatial optimization of B&Bs.