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Profile-based latent class distance association analyses for sparse tables:application to the attitude of European citizens towards sustainable tourism

Author

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  • Francesca Bassi

    (University of Padova)

  • José Fernando Vera

    (Faculty of Sciences, University of Granada)

  • Juan Antonio Marmolejo Martín

    (Faculty of Social and Legal Sciences, University of Granada)

Abstract

Social 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.

Suggested Citation

  • Francesca Bassi & José Fernando Vera & Juan Antonio Marmolejo Martín, 2024. "Profile-based latent class distance association analyses for sparse tables:application to the attitude of European citizens towards sustainable tourism," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(4), pages 953-980, December.
    • Handle: RePEc:spr:advdac:v:18:y:2024:i:4:d:10.1007_s11634-023-00559-1
    DOI: 10.1007/s11634-023-00559-1
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    References listed on IDEAS

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    1. Mark Rooij & Willem Heiser, 2005. "Graphical representations and odds ratios in a distance-association model for the analysis of cross-classified data," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 99-122, March.
    2. Francesca Bassi & Mariangela Guidolin, 2021. "Resource Efficiency and Circular Economy in European SMEs: Investigating the Role of Green Jobs and Skills," Sustainability, MDPI, vol. 13(21), pages 1-21, November.
    3. Chris Roberts & Joel Reynolds & Mary Jo Dolasinski, 2022. "Meta-Analysis of Tourism Sustainability Research: 2019–2021," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
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