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A Tourist Segmentation Based on Motivation, Satisfaction and Prior Knowledge with a Socio-Economic Profiling: A Clustering Approach with Mixed Information
Authors
L. De Giovanni
Marta Disegna
+3 more
P. D’Urso
R. Massari
V. Vitale
Publication date
1 January 2021
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
Abstract
© 2020, The Author(s). The popularity of the cluster analysis in the tourism field has massively grown in the last decades. However, accordingly to our review, researchers are often not aware of the characteristics and limitations of the clustering algorithms adopted. An important gap in the literature emerged from our review regards the adoption of an adequate clustering algorithm for mixed data. The main purpose of this article is to overcome this gap describing, both theoretically and empirically, a suitable clustering algorithm for mixed data. Furthermore, this article contributes to the literature presenting a method to include the “Don’t know” answers in the cluster analysis. Concluding, the main issues related to cluster analysis are highlighted offering some suggestions and recommendations for future analysis
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Archivio della ricerca- Università di Roma La Sapienza
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oai:iris.uniroma1.it:11573/163...
Last time updated on 07/10/2022
Archivio della ricerca- LUISS Libera Università Internazionale degli Studi Sociali Guido Carli di Roma
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oai:iris.luiss.it:11385/202270
Last time updated on 24/02/2022
Archivio istituzionale della ricerca - Università di Padova
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oai:www.research.unipd.it:1157...
Last time updated on 23/08/2022
Bournemouth University Research Online
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Last time updated on 03/12/2020