Optimal levels of tourism for experience quality and income.

We propose to do an experimental study in which we will use 360 video and still photo simulations that portray varying levels of crowding. Simulations will be presented to 25 student participants and 25 older adult participants (65+; a lucrative tourist segment) in an experimental setting while signals of their emotional responses are recorded from their brain (EEG) and body (skin conductivity and heart rate) at our Experience Measurement Lab. A questionnaire will measure their intent to recommend and their willingness to pay for the ‘experiences’ (simulations) they have viewed. Analyses will determine optimal levels of crowding for the quality of the tourist experience, but also for income at the destination, accounting for the fact that a more crowded destination features more potential sources of income (visitors), but each a (possibly) different level of willingness to pay, including potential implications for local tourist taxes. Models will also account for possibly different processes in the two different age groups. Furthermore, modelling word-of-mouth/mouse marketing based on intent to recommend will also make it possible to predict how crowding affects demand long-term.

Partner: KU Leuven.