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Social network analysis as a valuable tool for understanding tourists' multi-attraction travel behavioral intention to revisit and recommend

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number2497
JournalSustainability (Switzerland)
Volume11
Issue number9
DOIs
Publication statusPublished - 1 May 2019

Bibliographical note

Publisher Copyright:
© 2019 by the authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Behavioral intention
  • Chinese tourist
  • Degree centrality
  • Density
  • Multi-attraction travel
  • Social network analysis
  • Tourism destination image
  • Tourist behaviors

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