Using accommodation price determinants to segment tourist areas

Accommodation services oriented to different tourist segments usually have price determinants. Thus, in multi-facet destinations such as large regions or cities, it should be possible find and describe the underlying types of tourism destination by using a determinant analysis. In this paper, methodology based on stepwise geographically weighted regression (GWR) is developed, k-means clustering algorithm determine existing geographical area. The method applied island Gran Canaria (Canary Islands, Spain), database more than 2000 peer-to-peer accommodation units spread over geography island. As result, was identify classify eight clusters within This can used other areas developed them.