The determinants of tourism destination competitiveness in 2006 – 2016: a partial least squares path modelling approach

Authors

  • Alessandro Magrini Department Statistics, Computer Science, Applications, University of Florence, Florence, Italy
  • Laura Grassini Department Statistics, Computer Science, Applications, University of Florence, Florence, Italy

DOI:

https://doi.org/10.26398/IJAS.0031-014

Keywords:

country-level, formative constructs, PLS, structural equation models, time series

Abstract

In this paper, we analyze the relationship between tourism destination competitiveness and its determinants at national level in the period 2006–2016, by applying partial least squares path models to biannual panel data. Our research is innovative because a long period (11 years) is considered, changes over time are assessed, and an overall evaluation is performed. Indicators, data sources and model specification are coherent with the ones in current applied researches on the topic, thus comparison with other recent empirical findings is possible. Results show that competitiveness does not significantly depend on demand conditions; the formative constructs have a constant composition throughout the considered period; the most important competitiveness determinants are infrastructures, followed by core resources and attractiveness and by communication technologies; the effect of competitiveness determinants is stable throughout the considered period. Our ranking indicates that Iceland, Austria, Cyprus and Qatar are

the most competitive destinations.

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Published

2020-02-14

How to Cite

Magrini, A. ., & Grassini, L. . (2020). The determinants of tourism destination competitiveness in 2006 – 2016: a partial least squares path modelling approach. Statistica Applicata - Italian Journal of Applied Statistics, 31(2), 251–269. https://doi.org/10.26398/IJAS.0031-014

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