Abstract
Partial least squares structural equation modeling (PLS-SEM), as an alternative technique to traditional covariance-based structural equation modeling (CB-SEM), offers greater flexibility with regard to data assumptions and could be better harnessed by tourism researchers as a research tool. This article reviews four selected tourism articles using PLS-SEM to highlight the key methodological issues of applying the technique. In so doing, the article provides guidelines for researchers adopting PLS-SEM as a data analysis tool in tourism research, especially when data are multivariate nonnormal and the model includes formative and reflective constructs.
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