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Tourism Destination Competitiveness: Second Thoughts on the World Economic Forum Reports

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  • Josef A. Mazanec

    (Institute for Tourism and Leisure Studies, Vienna University of Economics and Business, Augasse 2–6, A-1090 Vienna, Austria)

  • Amata Ring

    (BWZ, University of Vienna, Bruenner Strasse 72, A-1210 Vienna, Austria)

Abstract

The Travel and Tourism Competitiveness Reports of the World Economic Forum elaborate the Travel and Tourism Competitiveness Index (TTCI) as an overall measure of destination competitiveness for 130 economies worldwide. From a tourism management point of view, a measure such as the TTCI is expected to be instrumental in explaining and predicting the tourism performance of receiving countries. This study explores several ways to transform the TTCI into a formative structural model. Partial least squares path modelling, PLS regression, mixture modelling and non-linear covariance-based structural equation modelling are applied to examine the TTCI's predictive power. The analysis probes possible measures for improvement. The destination countries may be subject to unobserved heterogeneity with regard to how the various constituents of competitiveness act on tourism performance. Interaction phenomena seem to prohibit a simple cause–effect pattern and non-linear relationships show encouraging results.

Suggested Citation

  • Josef A. Mazanec & Amata Ring, 2011. "Tourism Destination Competitiveness: Second Thoughts on the World Economic Forum Reports," Tourism Economics, , vol. 17(4), pages 725-751, August.
    • Handle: RePEc:sae:toueco:v:17:y:2011:i:4:p:725-751
    DOI: 10.5367/te.2011.0065
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    References listed on IDEAS

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    1. Esposito Vinzi, Vincenzo & Ringle, Christian M. & Squillacciotti, Silvia & Trinchera, Laura, 2007. "Capturing and Treating Unobserved Heterogeneity by Response Based Segmentation in PLS Path Modeling. A Comparison of Alternative Methods by Computational Experiments," ESSEC Working Papers DR 07019, ESSEC Research Center, ESSEC Business School.
    2. Carsten Hahn & Michael D. Johnson & Andreas Herrmann & Frank Huber, 2002. "Capturing Customer Heterogeneity Using A Finite Mixture Pls Approach," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 54(3), pages 243-269, July.
    3. Sarstedt, Marko & Salcher, André, 2007. "Modellselektion in Finite Mixture PLS-Modellen," Discussion Papers in Business Administration 1394, University of Munich, Munich School of Management.
    4. Hildebrandt, Lutz & Temme, Dirk, 2006. "Formative measurement models in covariance structure analysis: Specification and identification," SFB 649 Discussion Papers 2006-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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