The potentials of partial least squares structural equation modeling (PLS-SEM) in leisure research. (27th May 2023)

• Record Type: Journal Article
• Authors: Kono, Shintaro; Sato, Mikihiro
• Is Part Of: Journal of leisure research. Volume 54:Number 3(2023)
• Page Start: 309
• Page End: 329
• Publication Date: 2023-05-27
• Subjects: Leisure research -- measurement -- multivariate statistics -- partial least squares -- structural equation modeling; Leisure -- Periodicals; Leisure; Periodicals; 790.05
• DOI: 10.1080/00222216.2022.2066492
• Languages: English
• ISSNs: 0022-2216

Abstract

Abstract: 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.