Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2016.1156554
Determinants of tourism industry in selected European countries: a smooth partial least squares approach
Lukáš Malec
orcid.org/0000-0002-5564-9611
Josef Abrhám
Sažetak
Various events, such as the global economic crisis, have seriously
hampered long-term stable tourism processes with a particular
relevance to international visits. In this study, we use the smooth
paths of partial least squares (PLS; more specifically its PLS-SVD
algorithm) and principal component analysis (PCA) dependent on a time parameter to descriptively examine the multivariate connections of tourism and economic growth during the periods close to the crisis. A novel approach regarding the paths of leading singular values and corresponding singular vectors and describing the maximum covariance strength reveals many practical outputs as time lags and mutual connections between sets of data. From the base of Central European countries analysed here, only Switzerland shows a significant tourism lagged situation, where the results provide relative perceptive conditions to non-residents with stable conditions for domestic tourism. Our findings show great evidence of similar behaviour in the Austria, Slovenia and Poland group as well as the
Czech Republic and Slovakia group. Also the Czech Republic and
Slovakia are potentially very sensitive to non-resident visits. Germany reveals its strong interconnection to the European economy. On the other hand, in the case of Hungary, simultaneous changes in income and consumer prices form ideal conditions for tourism.
Ključne riječi
European countries tourism; partial least squares (PLS); principal component analysis (PCA ); singular values path
Hrčak ID:
171711
URI
Datum izdavanja:
22.12.2016.
Posjeta: 1.592 *