*3.3. Statistical Analyses*

The proposed model and hypotheses were tested by performing a partial least squares (PLS) analysis using SmartPLS3 software [85]. PLS was selected because of its suitability to the exploratory nature of this study, in which some of the hypothesised relationships amongs<sup>t</sup> the variables had not been previously examined. Moreover, PLS is suitable when a research model is in its infancy, and it avoids the limitations of covariance-based SEM, such as sample size and restrictions, because of modelling complexity [74]. Nonparametric bootstrapping was utilized to assess the significance of the path coefficients amongs<sup>t</sup> the latent variables, and between the latent and evident variables.
