Expectation Maximization Algorithm Cluster Analysis for UK National Trust Visitors

Cang, Shuang (2009) Expectation Maximization Algorithm Cluster Analysis for UK National Trust Visitors. Tourism Analysis, 14 (5). pp. 637-650. ISSN 1083-5423

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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
Uncontrolled Keywords:	Cluster analysis, Expectation maximization algorithm, K-means, Principal components analysis, UK National Trust
Subjects:	G200 Operational Research N800 Tourism, Transport and Travel
Department:	Faculties > Business and Law > Newcastle Business School
Depositing User:	Paul Burns
Date Deposited:	14 Jan 2019 17:51
Last Modified:	19 Nov 2019 09:53
URI:	http://nrl.northumbria.ac.uk/id/eprint/37580

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