Acta Univ. Agric. Silvic. Mendelianae Brun. 2016, 64, 677-682

https://doi.org/10.11118/actaun201664020677
Published online 2016-05-04

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

Ida Vajčnerová1, Jakub Šácha2, Kateřina Ryglová3, Pavel Žiaran1

1Department of Management, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic
2Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic
3Department of Marketing and Trade, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

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.

Funding

This paper stems from the research realized in the frame of the project GAČR- the Quality Evaluation of Tourism Destination N.15-21179S

References

18 live references