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Article

Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend

1
International Center for Hospitality Research & Development, Dedman School of Hospitality, Florida State University, Tallahassee, FL 32306, USA
2
College of Hotel and Tourism, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea
3
Center for Converging Humanities, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea
*
Author to whom correspondence should be addressed.
This paper is excerpted from the doctor’s thesis of the first author (2015).
Sustainability 2019, 11(9), 2497; https://doi.org/10.3390/su11092497
Received: 15 February 2019 / Revised: 9 April 2019 / Accepted: 18 April 2019 / Published: 29 April 2019
(This article belongs to the Special Issue Marketing for Sustainable Tourism)
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. View Full-Text
Keywords: multi-attraction travel; social network analysis; degree centrality; density; tourist behaviors; tourism destination image; behavioral intention; Chinese tourist multi-attraction travel; social network analysis; degree centrality; density; tourist behaviors; tourism destination image; behavioral intention; Chinese tourist
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MDPI and ACS Style

Park, D.; Lee, G.; Kim, W.G.; Kim, T.T. Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend. Sustainability 2019, 11, 2497. https://doi.org/10.3390/su11092497

AMA Style

Park D, Lee G, Kim WG, Kim TT. Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend. Sustainability. 2019; 11(9):2497. https://doi.org/10.3390/su11092497

Chicago/Turabian Style

Park, Deukhee, Gyehee Lee, Woo G. Kim, and Taegoo T. Kim 2019. "Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend" Sustainability 11, no. 9: 2497. https://doi.org/10.3390/su11092497

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