Abstract
This article aims to investigate the segmenting of UK National Trust (NT) visitors based on behavior and motivation for the visit. The main focus of the article is to apply the more powerful, robust, and stable expectation maximization (EM) algorithm cluster analysis method together with PCA (without varimax rotation), which is rarely used in a tourism context, to the NT data set. This study identifies four clusters of NT visitors, and also identifies the most important items (questions) in the classification of NT visitors, which is the satisfaction with the NT service. The intracluster inequality, which means the diversity of the cluster, is also analyzed. Each cluster has its own characteristics and the results of cluster analysis will be useful for future NT marketing management to maximize the benefit to the NT. The diversity of each cluster is also discussed.
Original language | English |
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Pages (from-to) | 637-650 |
Number of pages | 14 |
Journal | Tourism Analysis |
Volume | 14 |
Issue number | 5 |
DOIs | |
Publication status | Published - 1 Dec 2009 |
Keywords
- Cluster analysis
- Expectation maximization algorithm
- K-means
- Principal components analysis
- UK National Trust