1,704
Views
3
CrossRef citations to date
0
Altmetric
Articles

Determinants of tourists’ intention to share travel experience on social media: an fsQCA application

, & ORCID Icon
Pages 2595-2612 | Received 09 Feb 2022, Accepted 14 Jun 2022, Published online: 23 Jun 2022
 

ABSTRACT

Sharing travel experience on social media has gained substantial popularity in the Internet era. However, existing knowledge about tourists’ determinants for sharing remains inconsistent and scattered. This study seeks to propose an innovative direction to analyze the determinants of tourists’ intention to share travel experience on social media. Building upon the complexity theory, this study implemented an asymmetrical analysis by applying the fuzzy-set qualitative comparative analysis (fsQCA) approach on a sample of 383 valid questionnaires. A structural equation modeling analysis and cross-tabulation analysis were also performed. The results revealed five causal configurations of determinants that lead to Chinese tourists’ high sharing intention on WeChat. The finding fills the gap in research on determinants to share travel experiences on strong-tie social media platforms and offers practical insights and marketing advice about how to encourage tourists to share their travel experiences on mainstream social media.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 273.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.