Expectation maximization algorithm cluster analysis for UK National Trust visitors

Shuang Cang*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)

    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 languageEnglish
    Pages (from-to)637-650
    Number of pages14
    JournalTourism Analysis
    Volume14
    Issue number5
    DOIs
    Publication statusPublished - 1 Dec 2009

    Keywords

    • Cluster analysis
    • Expectation maximization algorithm
    • K-means
    • Principal components analysis
    • UK National Trust

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