The potentials of partial least squares structural equation modeling (PLS-SEM) in leisure research

Shintaro Kono, Mikihiro Sato

Research output: Contribution to journalArticlepeer-review


Partial least squares structural equation modeling (PLS-SEM) is a multivariate statistical technique that helps examine complex relationships among a number of variables. Although its use has increased over decades, PLS-SEM remains underutilized in leisure research. The purpose of this methodological paper is to offer a primer on PLS-SEM for leisure researchers and to present a critical review of PLS-SEM’s strengths and limitations, while identifying potential applications of PLS-SEM across different sub-fields and theories in leisure research. Specifically, as to strengths, we discuss PLS-SEM’s sample size requirements, accommodation of formative and reflective measures, ability to model many variables and relationships, and statistical prediction capacity. In terms of its limitations, we review criticisms regarding PLS-SEM’s biased estimates as well as the lack of measurement error estimation and model fit assessment tools. Lastly, we provide recommendations for leisure researchers who wish to use PLS-SEM and journal editors and reviewers who assess PLS-SEM articles.

Original languageEnglish (US)
Pages (from-to)309-329
Number of pages21
JournalJournal of Leisure Research
Issue number3
StatePublished - 2023


  • Leisure research
  • measurement
  • multivariate statistics
  • partial least squares
  • structural equation modeling

ASJC Scopus subject areas

  • Environmental Science (miscellaneous)
  • Sociology and Political Science
  • Tourism, Leisure and Hospitality Management


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