Abstract
AbstractThe 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.
Funder
Università degli Studi di Roma La Sapienza
Publisher
Springer Science and Business Media LLC
Subject
General Social Sciences,Sociology and Political Science,Arts and Humanities (miscellaneous),Developmental and Educational Psychology
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