SmartPLS is the most widely used software for Partial Least Squares Structural Equation Modelling (PLS-SEM) — a technique that lets you test a whole network of relationships between latent constructs (things you measure with multiple questionnaire items) in one model. If your thesis has a conceptual framework with arrows between constructs like trust, satisfaction and loyalty, PLS-SEM is very likely the technique you'll be asked about.
PLS-SEM vs CB-SEM in one paragraph
Covariance-based SEM (AMOS, LISREL) asks: does my whole theorised model fit the data? — best for confirming established theory with larger, roughly normal samples. PLS-SEM asks: how well does my model explain and predict the outcomes? — best for prediction, theory building, complex models, smaller or non-normal samples, and formative constructs. The full comparison is in SPSS vs AMOS vs SmartPLS.
The PLS-SEM workflow
1. Assess the measurement model
- Indicator reliability — outer loadings ≥ 0.708 (items below 0.40 are removed; 0.40–0.708 removed only if it improves reliability/validity).
- Internal consistency — Cronbach's alpha and composite reliability (rho_c) ≥ 0.70.
- Convergent validity — Average Variance Extracted (AVE) ≥ 0.50.
- Discriminant validity — HTMT below 0.85 (0.90 for conceptually similar constructs).
2. Assess the structural model
- Collinearity — inner VIF values below 3–5.
- Path coefficients — size, sign and significance via bootstrapping (5,000+ resamples).
- Explanatory power — R² of endogenous constructs; effect sizes f².
- Predictive relevance — Q² (blindfolding) or PLSpredict.
3. Extensions when your model needs them
SmartPLS handles mediation and moderation analysis, multi-group analysis (does the model differ for men vs women?), higher-order constructs, and importance–performance maps — which is why it dominates management, marketing and IS research.
Sample size — the honest version
PLS-SEM tolerates smaller samples than CB-SEM, but the old '10 times rule' is a floor, not a defence. Reviewers now expect a power-based justification — start with our sample size calculator and the guidance in how to determine your sample size.
Journals expect the full chain: measurement model results (loadings, alpha, CR, AVE, HTMT), then structural results (VIF, paths with bootstrapped confidence intervals, R², f², Q²). Missing links in this chain are the most common reason PLS-SEM papers bounce.
If you're deciding between tools or need your model reviewed before you collect data, our SmartPLS mentoring coaches you to run and defend the analysis yourself — or book a free consult.
Frequently asked
Is SmartPLS free?+
SmartPLS 4 offers a free tier with limited features alongside paid licences; universities often hold licences. The free student options are typically sufficient to learn the workflow before your main analysis.
What sample size does PLS-SEM need?+
Enough for the statistical power your model requires — commonly 100–300+ in practice. The '10 times the maximum arrows' rule is only a minimum bound; use power analysis for a defensible number.
Can I use SmartPLS for exploratory research?+
Yes — that's one of its core strengths. PLS-SEM suits theory building and prediction-oriented studies, whereas CB-SEM (AMOS) suits strict confirmation of established theory.
phdguide's mentors are senior academics, former supervisors, statisticians and publication specialists with 25+ years of combined experience guiding MBA, MPhil and PhD scholars from topic to viva.
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