Publication Cover
Leisure Sciences
An Interdisciplinary Journal
Volume 40, 2018 - Issue 5
383
Views
10
CrossRef citations to date
0
Altmetric
Articles

Predictors of Templestay Satisfaction: A Comparison Between Korean and International Participants

, , &
Pages 423-441 | Received 07 Jan 2016, Accepted 02 Jan 2017, Published online: 29 Mar 2017
 

ABSTRACT

The present study aims to determine the underlying factors critical to the overall satisfaction (Templestay satisfaction) of local and foreign participants in South Korean Buddhist temple stay programs (hereafter, Templestay). A two-step multivariate procedure was performed where the data were first subjected to a factor analysis followed by structural equation model. The findings are congruent with three out of five research hypotheses. Moreover, the empirical evidence showed that there are no differences in reporting of Templestay satisfaction between Korean and international participants. Nevertheless, being with nature, self-growth, and relaxation are underlying factors that define satisfaction for Koreans. For international participants, being with nature and relaxation are significant. The study reveals that learning experience is a poor predictor of Templestay satisfaction. The practical implication of this research is that Templestay managers should focus on the factors that have the highest importance for obtaining Templestay satisfaction for both Korean and international visitors.

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 242.00 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.