Improved Design of SOR Model Based on Virtual Tourism User-generated Content and Destination Attachment

This study enhances the Stimulus-Organism-Response (SOR) model to form the Stimulus-Organism-ResponsePlace (SOR-P) model, tailored for virtual tourism. By integrating user-generated content and analyzing data from Ctrip mobile application reviews, we examine how virtual tourism influences destination attachment. Our methodology involves theoretical model analysis, quantitative data mining, and associative word analysis, focusing on the emotional and cognitive trajectories of tourists. The results highlight that virtual tourism stimuli significantly enhance emotional attachment and destination recognition. Comparative analysis shows the optimized SOR-P model provides a more comprehensive understanding of tourists’ experiences and their impacts on destination branding. This model not only deepens insights into the man-land relationship in a virtual context but also offers strategic guidance for developing effective virtual tourism experiences that promote long-term visitor loyalty and destination competitiveness.

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Publication Details

Published
2024-08-25
DOI
https://doi.org/10.1109/cost64302.2024.00044
Citations
1
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
0.68
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article

Improved Design of SOR Model Based on Virtual Tourism User-generated Content and Destination Attachment

Bowen Guan
1 citations
E-commerce and Technology Innovations
0.68
article

Improved Design of SOR Model Based on Virtual Tourism User-generated Content and Destination Attachment

Bowen Guan
article en
1 citations

Abstract

This study enhances the Stimulus-Organism-Response (SOR) model to form the Stimulus-Organism-ResponsePlace (SOR-P) model, tailored for virtual tourism. By integrating user-generated content and analyzing data from Ctrip mobile application reviews, we examine how virtual tourism influences destination attachment. Our methodology involves theoretical model analysis, quantitative data mining, and associative word analysis, focusing on the emotional and cognitive trajectories of tourists. The results highlight that virtual tourism stimuli significantly enhance emotional attachment and destination recognition. Comparative analysis shows the optimized SOR-P model provides a more comprehensive understanding of tourists’ experiences and their impacts on destination branding. This model not only deepens insights into the man-land relationship in a virtual context but also offers strategic guidance for developing effective virtual tourism experiences that promote long-term visitor loyalty and destination competitiveness.

Sichuan University (CN)
Decent work and economic growth
Openalex Percentile: Top 27%
E-commerce and Technology Innovations
0.68
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