Expectation Maximization Algorithm Cluster Analysis for UK National Trust Visitors.

Cang, S., 2009. Expectation Maximization Algorithm Cluster Analysis for UK National Trust Visitors. Tourism Analysis, 14 (5), pp. 637-650.

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DOI: 10.3727/108354209X12597959359257

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.

Item Type:Article
ISSN:1083-5423
Uncontrolled Keywords:UK National Trust; cluster analysis; principal components analysis; k-means; expectation maximization algorithm
Subjects:Social Sciences > Tourism
Group:School of Tourism > International Centre for Tourism and Hospitality Research
ID Code:15443
Deposited By:Dr Shuang Cang
Deposited On:01 Jul 2010 19:25
Last Modified:07 Mar 2013 15:33
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