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dc.contributor.authorBassi, Francesca
dc.contributor.authorVera Vera, José Fernando 
dc.contributor.authorMarmolejo Martín, Juan Antonio
dc.identifier.citationBassi, F., Vera, J.F. & Marmolejo Martín, J.A. Profile-based latent class distance association analyses for sparse tables:application to the attitude of European citizens towards sustainable tourism. Adv Data Anal Classif (2023). []es_ES
dc.description.abstractSocial and behavioural sciences often deal with the analysis of associations for cross-classified data. This paper focuses on the study of the patterns observed on European citizens regarding their attitude towards sustainable tourism, specifically their willingness to change travel and tourism habits to be more sustainable. The data collected the intention to comply with nine sustainable actions; answers to these questions generated individual profiles; moreover, European country belonging is reported. Therefore, unlike a variable-oriented approach, here we are interested in a person-oriented approach through profiles. Some traditional methods are limited in their performance when using profiles, for example, by sparseness of the contingency table. We removed many of these limitations by using a latent class distance association model, clustering the row profiles into classes and representing these together with the categories of the response variable in a low-dimensional space. We showed, furthermore, that an easy interpretation of associations between clusters’ centres and categories of a response variable can be incorporated in this framework in an intuitive way using unfolding. Results of the analyses outlined that citizens mostly committed to an environmentally friendly behavior live in Sweden and Romania; citizens less willing to change their habits towards a more sustainable behavior live in Belgium, Cyprus, France, Lithuania and the Netherlands. Citizens preparedness to change habits however depends also on their socio-demographic characteristics such as gender, age, occupation, type of community where living, household size, and the frequency of travelling before the Covid-19 pandemic.es_ES
dc.description.sponsorshipUniversidad de Granada/CBUAes_ES
dc.rightsAtribución 4.0 Internacional*
dc.subjectPerson-based analysises_ES
dc.subjectCircular economyes_ES
dc.titleProfile-based latent class distance association analyses for sparse tables:application to the attitude of European citizens towards sustainable tourismes_ES

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Atribución 4.0 Internacional
Except where otherwise noted, this item's license is described as Atribución 4.0 Internacional