Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/337794 
Year of Publication: 
2024
Citation: 
[Journal:] Annals of Tourism Research Empirical Insights [ISSN:] 2666-9579 [Volume:] 5 [Issue:] 2 [Article No.:] 100131 [Year:] 2024 [Pages:] 1-14
Publisher: 
Elsevier, Amsterdam
Abstract: 
The study aims to develop a novel approach to assess Tourism Capital in resort areas, specifically Zermatt-Matterhorn, between 2014 and 2021. This approach integrates a two-tiered empirical model, where the first tier involves CNN-based image analysis, and the second tier employs mathematical techniques and time-series social media data to evaluate stakeholder engagement. The research emphasizes how fluctuations in tourism capital are influenced by stakeholder interactions and external events, highlighting the significance of empirical and quantitative approaches in understanding tourism dynamics. The findings underscore the substantial role of stakeholder engagement in shaping overall tourism capital, offering a practical and dynamic tool for tourism analysis and urban planning. This study innovatively assesses Tourism Capital by analyzing Instagram images, offering a more in-depth, data-driven view of tourism development in resorts.
Subjects: 
Deep learning
Instagram
Time series
Tourism capital
Visual methods
Zermatt
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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