Photographs as cognitive sources might have an impact on the development of a tourist destination image (TDI). When we look at pictures of places to visit, we imagine being in the represented place, “as if” we would be physically present exploring that place. This mechanism is grounded on the match between perception and action advocated by the embodied cognition account. Besides, it has been demonstrated that the aesthetic appearance of the place has a significant impact on the TDI. Since images can influence TDI, we aimed to test the role of embodied and aesthetic components in the choice of tourism destinations. In an online study, we presented 50 photographs of tourist places. Participants (N=121) provided ratings to evaluate three embodied components (bodily engagement, sense of exploration and the will to explore behind the scene) and symmetry. They also indicated how much they like each photograph and how much they would visit the place. All ratings were provided on a 0-100mm visual analogue scale. In addition, image aesthetics (symmetry, self-similarity and variance) were extracted with a Convolutional Neural Network (CNN) deep learning algorithm. We found that bodily engagement and sense of exploration predicted both liking and tourist judgments, whereas the intention to explore further predicted only the tourist judgment. None of the CNN components accounted for liking and tourism judgments. Interestingly, left-right mirror symmetry predicted subjective symmetry, reflecting a left-right exploration strategy through the images. Taken together these results lend support to the involvement of embodied processing in TDI.

Embodied and Aesthetic Processes in the Evaluation of Tourist Destination Image

Sonia Malvica
Primo
;
2021-01-01

Abstract

Photographs as cognitive sources might have an impact on the development of a tourist destination image (TDI). When we look at pictures of places to visit, we imagine being in the represented place, “as if” we would be physically present exploring that place. This mechanism is grounded on the match between perception and action advocated by the embodied cognition account. Besides, it has been demonstrated that the aesthetic appearance of the place has a significant impact on the TDI. Since images can influence TDI, we aimed to test the role of embodied and aesthetic components in the choice of tourism destinations. In an online study, we presented 50 photographs of tourist places. Participants (N=121) provided ratings to evaluate three embodied components (bodily engagement, sense of exploration and the will to explore behind the scene) and symmetry. They also indicated how much they like each photograph and how much they would visit the place. All ratings were provided on a 0-100mm visual analogue scale. In addition, image aesthetics (symmetry, self-similarity and variance) were extracted with a Convolutional Neural Network (CNN) deep learning algorithm. We found that bodily engagement and sense of exploration predicted both liking and tourist judgments, whereas the intention to explore further predicted only the tourist judgment. None of the CNN components accounted for liking and tourism judgments. Interestingly, left-right mirror symmetry predicted subjective symmetry, reflecting a left-right exploration strategy through the images. Taken together these results lend support to the involvement of embodied processing in TDI.
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3217796
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