Analysis of spatial autocorrelation and price determinants in hotel room prices

In the lodging industry, insufficient attention has been given to how attributions affect prices. It is commonly asserted that the three most important attributes that a hotel can offer are location, location and location. This article examines how Traffic and Tourism Nodes differentially affect prices in the lodging industry in the Beijing, PRC. Spatial autocorrelation, Kriging interpolation and partial correlation are used and compared using price data of 230 hotels above in Beijing, PRC. There shows evidence of spatial autocorrelation in room prices of hotels within city of Beijing by using the Moran's I index. Furthermore, using partial correlation analysis, the research finds that the distances between hotels and the traffic nodes effect the room prices much more significantly than the distances between the hotels and the tourism node, but there are more additional attributes affecting the room prices. This article outlines a method for determining the values, or implicit prices, of a hotel attributes at market rates. If hotel managers know what attributes are determinants, or salient, amongst consumers in their choice of lodging, they can concentrate on these attributes in marketing; in particular, pricing and promotion methods can be applied to fixed both attributes such as location.