10,128
Views
185
CrossRef citations to date
0
Altmetric
Original Articles

Determinants of Sharing Travel Experiences in Social Media

&
Pages 93-107 | Received 01 May 2012, Accepted 03 Oct 2012, Published online: 04 Mar 2013
 

ABSTRACT

The advent of Internet-based social media technologies has enabled travelers to quickly and conveniently share their travel experiences. Shared information on social media sites is recognized as an important information source which may influence travel decision making for potential travelers. This study tests a conceptual framework which examines why travelers share their travel experiences on social media based on the social influence theory and its three conceptual foundations—identification, internalization, and compliance. Data were collected using an online survey and the research model was tested with 543 respondents who were social media users. Results showed that identification and internalization are critical determinants that positively increase actual travel-experience sharing on social media as mediated by perceived enjoyment. Our research extends prior literature on social media by identifying specific determinants that can impact travel-experience sharing. Suggestions are provided for academics, the travel industry, and those working with social media.

Acknowledgments

The authors would like to thank Mandala Research, LLC and the Center for Socioeconomic Research & Education at Texas A&M University for technical assistance.

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 309.00 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.