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October 1, 2013European Journal of Tourism ResearchOpen Access

Hair, J. F. Jr., Hult, G. T. M., Ringle, C. M., Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications. ISBN: 978-1-4522-1744-4. 307 pp.

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Authors

LFLawrence Hoc Nang FongRLRob Law

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Overview

Methodological guide demonstrates the utility of partial least squares structural equation modeling in social sciences, highlighting its flexibility for complex models.

Key Points

  • To introduce the theoretical fundamentals, methodological steps, and software applications of partial least squares structural equation modeling (PLS-SEM) for empirical research.
  • Comparative methodological analysis contrasting variance-based PLS-SEM with covariance-based SEM (CB-SEM).
  • Systematic breakdown of model specification covering mediation, moderation, higher-order structures, and formative versus reflective constructs.
  • Step-by-step evaluation protocol for measurement and structural models using SmartPLS software and bootstrapping estimation.
  • Identifies key methodological advantages of PLS-SEM, including robust performance with small sample sizes, complex model structures, and single-item measures.
  • Defines standardized evaluation metrics for reflective models (internal consistency, convergent validity, discriminant validity) and formative models (convergent validity, collinearity, indicator significance).

Cite This Study

Fong et al. (2013) studied this question.

synapsesocial.com/papers/6a00bd5be92f4a033c8550e4https://doi.org/10.54055/ejtr.v6i2.134
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