Appealing to the Elusive Tourist: An Attribute Cluster Strategy

The development of a technique to identify tourist-attracting features for use in market segmentation was the primary focus of this article. For purposes of segmentation, 10 tourist attracting attributes were used as the basis of a linear-compensatory, multi attribute attitude model. A unidimensional attitude score representative of a bundle of attributes was used as a basis for the BMDP K-means clustering procedure, which was used to divide heterogeneous tourist markets into homogeneous subsegments. Within the resort test area, three viable tourist clusters were identified as differing significantly (p < .001) for each attribute. Demographic differences between the clusters were examined. However, no significant differences were revealed. In other words, the clusters or market segments differed with respect to benefits sought but did not differ demographi cally. The use of attribute bundles and demographic information for the development of promotional campaign strategies is discussed.