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            Chapter Using eye-tracking to evaluate the viewing behavior on tourist landscapes

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            Author(s)
            Zammarchi, Gianpaolo
            contu, giulia
            Frigau, Luca
            Language
            English
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            Abstract
            Every tourist website employs images to attract potential tourists. In particular, destination tourism websites use environmental images, such as landscapes, to attract the attention of tourists and to address their purchase choice. Nowadays the effectiveness of these tools has been enhanced by the use of eye-tracking technology. That allows measuring the exact eye position during the visualization of images, texts, or other visual stimuli. Consequently, eye-tracking data can be processed to obtain quantitative measures of viewing behavior that can be analyzed for several purposes in many fields such as to cluster consumers, to improve the effectiveness of a website and for neuroscience studies. This work is aimed to use eye-tracking technology to investigate user behavior according to different types of images (e.g. natural landscapes, city landscapes). Specifically, we compare different statistical descriptive tools with supervised and unsupervised models. Furthermore, we discuss the effectiveness of their results and their capacity to provide satisfactory and interpretable solutions that can be used by decision-makers.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/180339
            Keywords
            Tourism; Eye-tracking; Fixations
            DOI
            10.36253/978-88-5518-304-8.28
            ISBN
            9788855183048
            Publisher
            Firenze University Press
            Publisher website
            www.fupress.com/
            Publication date and place
            Florence, 2021
            Series
            Proceedings e report,
            Pages
            6
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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