Deakin University
Browse

Modelling dimensionality of cultural experience attitudes for international tourists

Download (175.36 kB)
conference contribution
posted on 2006-01-01, 00:00 authored by Pandora Kay
This empirical research of tourists’ cultural experiences aims to advance theory by developing a measurement model of attitudes towards attending cultural experiences for a sample of international tourists visiting Melbourne, Australia. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to cross-validate the underlying dimensionality structure of cultural experience attitudes in the model. A five-factor model was extracted from the EFA and some further modifications were required to establish discriminant validity. A four-factor model was retained in the CFA, which included three factors based on a liking for different types of cultural experiences and one factor indicating that social interaction was the most liked socio-psychological attitude towards attending cultural experiences. Although the sample were all English-speaking international tourists, cross-cultural validation of the model was also examined for factor configural and metric invariance of the measurement model as there were three different groups of international tourists within the sample: North Americans; New Zealanders; and tourists from United Kingdom and Ireland. This measurement structure was found to be relatively invariant for the factor loadings across the three groups of international tourists.

History

Pagination

1 - 21

Location

Sydney, N.S.W.

Open access

  • Yes

Start date

2006-12-10

End date

2006-12-13

ISBN-13

9780980318814

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2006, The Author

Title of proceedings

ACSPRI : Proceedings of the Social Science Methodology Conference

Usage metrics

    Research Publications

    Categories

    No categories selected

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC