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A platform for research: civil engineering, architecture and urbanism
Clustering Travelers’ Lifestyle Destination Image from Five Asian Traveler-Generated Content
This study examines the destination image and lifestyle experience via traveler-generated comments. To understand the travelers’ behavior, we first established a crawler, which helps us to gather the travelers’ comments from tourism social media. After conducting a content analysis, text mining, and factor analysis of a sampling of 23,019 travelers’ comments, this study found that travelers based on their activities and experiences constructed their image. Additionally, we also found that the travelers’ emotions and impressions showed up with their images. From the result of factor analysis, we extract the 13 clustering results and perform the one-way ANOVA with Scheffe’s method to compare the difference among each group. Finally, we used the related sentences to draw a relation map to explain the inner difference between travelers. This study’s results suggest that traveler-generated comments can be especially useful for destination image analysis and market segments in tourism marketing and management. This study also highlights the importance of understanding destination image and marketing segment from the travelers’ comments and challenges for those in tourism marketing to narrow the gap.
Clustering Travelers’ Lifestyle Destination Image from Five Asian Traveler-Generated Content
This study examines the destination image and lifestyle experience via traveler-generated comments. To understand the travelers’ behavior, we first established a crawler, which helps us to gather the travelers’ comments from tourism social media. After conducting a content analysis, text mining, and factor analysis of a sampling of 23,019 travelers’ comments, this study found that travelers based on their activities and experiences constructed their image. Additionally, we also found that the travelers’ emotions and impressions showed up with their images. From the result of factor analysis, we extract the 13 clustering results and perform the one-way ANOVA with Scheffe’s method to compare the difference among each group. Finally, we used the related sentences to draw a relation map to explain the inner difference between travelers. This study’s results suggest that traveler-generated comments can be especially useful for destination image analysis and market segments in tourism marketing and management. This study also highlights the importance of understanding destination image and marketing segment from the travelers’ comments and challenges for those in tourism marketing to narrow the gap.
Clustering Travelers’ Lifestyle Destination Image from Five Asian Traveler-Generated Content
Ping-Heng Tsai (author) / Chia-Chi Hsaio (author) / Yan-Ru Li (author) / Chun-Chieh Lin (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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