Using the Cluster Analysis and the Principal Component Analysis in Evaluating the Quality of a Destination

The objective of the paper is to explore possibilities of evaluating the quality of a tourist destination by means of the principal components analysis (PCA) and the cluster analysis. In the paper both types of analysis are compared on the basis of the results they provide. The aim is to identify ad...

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Bibliographic Details
Main Authors: Ida Vajčnerová, Jakub Šácha, Kateřina Ryglová, Pavel Žiaran
Format: Article
Language:English
Published: Mendel University Press 2016-01-01
Series:Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
Subjects:
Online Access:https://acta.mendelu.cz/64/2/0677/
Description
Summary:The objective of the paper is to explore possibilities of evaluating the quality of a tourist destination by means of the principal components analysis (PCA) and the cluster analysis. In the paper both types of analysis are compared on the basis of the results they provide. The aim is to identify advantage and limits of both methods and provide methodological suggestion for their further use in the tourism research. The analyses is based on the primary data from the customers’ satisfaction survey with the key quality factors of a destination. As output of the two statistical methods is creation of groups or cluster of quality factors that are similar in terms of respondents’ evaluations, in order to facilitate the evaluation of the quality of tourist destinations. Results shows the possibility to use both tested methods. The paper is elaborated in the frame of wider research project aimed to develop a methodology for the quality evaluation of tourist destinations, especially in the context of customer satisfaction and loyalty.
ISSN:1211-8516
2464-8310