C88 - Data Collection and Data Estimation Methodology; Computer Programs: Other Computer SoftwareReturn

This paper empirically investigates the contribution of tourism destination competitiveness to the growth in the gross domestic product (GDP) among selected European economies. This analysis used the Travel and Tourism Competitiveness Index (TTCI) to estimate the tourism contribution of European economies. More specifically, this paper examines the variables that encourage tourism performance as defined by the TTCI rankings and the contribution of tourism to GDP. Data presented in the Travel and Tourism Competitiveness Index report by the World Economic Forum, the World Bank country database, and the World Travel and Tourism Council were used to calculate the TTCI classification and tourism performance variables. The indicators were chosen under the circumstance that they rationally suit the proposed research scheme. The results from the correlation analysis show that GDP growth depends on improved travel and tourism surroundings, higher tourism destination competitiveness, the creation of new business opportunities and the need for government support. The examination also verifies that the economic inequalities between selected countries affected the differences in the tourism competitiveness rankings. Finally, the restraints on the empirical findings are discussed and the research implications for future analyses are recommended.

The article presents and investigates new possibilities of multivariate data visualization and their analytical convenience. We demonstrate elementary principles, algorithms and graphical outputs of modern visualization methods with particular focus on Bertin matrices, RADVIZ, Projection pursuit and parallel coordinates. Illustrative examples show their practical implementation into the process of multivariate data analysis, hence providing the reader with an idea of the wide range of their application.