A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend
In order to better understand tourists’ multi-attraction travel behavior, the present study developed a research model by combining the social network analysis technique with the structural equation model. The object of this study was to examine the structural relationships among destination image, tourists’ multi-attraction travel behavior patterns, tourists’ satisfaction, and their behavioral intentions. The data were gathered via an online survey using the China panel system. A total of 468 respondents who visited multiple attractions while in Seoul, Korea, were used for actual analysis. The results showed that all hypotheses are supported. Specifically, destination image was an important antecedent to multi-attraction travel behavior indicated by density and degree indices. In addition, the present study confirmed that density and degree centrality, the indicators of tourists’ multi-attraction travel behavior, were positively related to tourist satisfaction. The current study represented theoretical and practical implications and suggested avenues for future research.
Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend
In order to better understand tourists’ multi-attraction travel behavior, the present study developed a research model by combining the social network analysis technique with the structural equation model. The object of this study was to examine the structural relationships among destination image, tourists’ multi-attraction travel behavior patterns, tourists’ satisfaction, and their behavioral intentions. The data were gathered via an online survey using the China panel system. A total of 468 respondents who visited multiple attractions while in Seoul, Korea, were used for actual analysis. The results showed that all hypotheses are supported. Specifically, destination image was an important antecedent to multi-attraction travel behavior indicated by density and degree indices. In addition, the present study confirmed that density and degree centrality, the indicators of tourists’ multi-attraction travel behavior, were positively related to tourist satisfaction. The current study represented theoretical and practical implications and suggested avenues for future research.
Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend
Deukhee Park (author) / Gyehee Lee (author) / Woo Gon Kim (author) / Taegoo Terry Kim (author)
2019
Article (Journal)
Electronic Resource
Unknown
multi-attraction travel , social network analysis , degree centrality , density , tourist behaviors , tourism destination image , behavioral intention , Chinese tourist , Environmental effects of industries and plants , TD194-195 , Renewable energy sources , TJ807-830 , Environmental sciences , GE1-350
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