Abstract:
A taxonomy of tourists visiting Austria during the summer season is constructed using Kohonen’s self organising feature maps and conventional k-means cluster analysis. 8000 tourists visiting Austria in the summer season of 1994 indicated the importance they attach to 22 vacation aspects that are used as active clustering variables. The resulting market segments from both methodological approaches are described. Comparisons are made between self organising feature maps and k-means clustering concerning the final results, and the variability of final results. Self organising feature maps turn out to be an interesting alternative to conventional k-means clustering and furthermore bear the potential of unveiling additional precious information for market segmentation studies.