In recent years, more and more attention has been paid to the behavior of tourists and their intention to travel after certain natural disasters or social unrest. The aim of the research was to establish the influence of psychological profiles of tourists on their decision to choose a tourist destination, using three psychographic techniques BFI-10 (Big Five Inventory), AIO (Activities, Interests, Opinions), and VALS 2 (Values and lifestyle), and a freely determined six-level scale of risk and tourist attractiveness of the imagined destinations. By analyzing the results through structural modeling-path analysis, it was determined that almost all psychographic orientations derived from lifestyles negatively perceive destinations with a high degree of risk and attractiveness, while with the VALS 2 technique, only members of the action orientation tend to accept the risk and challenge of visiting high-risk destinations. The results of the research have a degree of innovation in the application of the combination of the mentioned models, as well as in the theoretical and applied aspects in supplementing the building and strategic planning of the future business.

This paper focuses on the data-driven evaluation ski resorts, employing the attractiveness index. Unlike similar studies, this research concentrates on smaller resorts essential for local economies. Input data acquired through meta-analysis offers insights into skier preferences, combining information from various sources, including volunteered geographic information (VGI). Employing a geographic information system (GIS), the study addresses pertinent questions regarding over-tourism, regional resort ratings, and spatial patterns, providing a foundation for sustainable development in alpine regions. As the case study, the evaluation of 40 regional ski resorts in Austria is introduced.