Abstract
Binary survey data from the Austrian National Guest Survey conducted in the summer season of 1997 were used to identify behavioural market segments on the basis of vacation activity information. Bagged clustering overcomes a number of diffculties typically encountered when partitioning large binary data sets: The partitions have greater structural stability over repetitions of the algorithm and the question of the "correct" number of clusters is less important because of the hierarchical step of the cluster analysis. Finally, the bootstrap part of the algorithm provides means for assessing and visualizing segment stability for each input variable.
Publication Details
This book chapter was originally published as Dolnicar, S & Leisch, F, Behavioral Market Segmentation of Binary Guest Survey Data with Bagged Clustering, in Dorffner, G, Bischof, H & Hornik, K (eds), Artificial Neural Networks – ICANN 2001, volume 2130 of Lecture Notes in Computer Science, Springer, Berlin, 2001, 111-118.