Data Analysis
SmartPLS Analysis in India
SmartPLS is the leading software for Partial Least Squares Structural Equation Modelling (PLS-SEM), a technique that has become one of the most widely used analytical methods in management, marketing, information systems, entrepreneurship, and tourism research globally. Its ability to handle smaller samples, non-normal data, formative constructs, and exploratory models makes it particularly well-suited to the research designs commonly used in Indian MBA and management PhD studies.
But SmartPLS is not simply a simpler alternative to AMOS. It requires its own analytical rigour — the correct distinction between reflective and formative measurement models, thorough evaluation of the measurement model before structural testing, appropriate bootstrapping for path significance, and careful use of HTMT for discriminant validity. Journals that publish PLS-SEM studies now expect this level of rigour as standard.
At E-Clearby Research Consulting Pvt. Ltd., we provide expert SmartPLS PLS-SEM analysis services for PhD scholars, MBA researchers, and faculty members across India. Our consultants apply current best practices in PLS-SEM, aligned with the Hair et al. methodological guidelines widely cited in management and marketing research, and deliver results that are technically sound and publication-ready.
Get Expert Guidance
Start your journey to a successful PhD today.
What Our SmartPLS PLS-SEM Analysis Service Includes
Our SmartPLS engagement follows the current best-practice two-stage approach: measurement model evaluation first, structural model testing second:
Reflective vs. Formative Construct Identification
We confirm whether each construct in your model is reflective (indicators caused by the construct) or formative (construct caused by its indicators) — a foundational decision that determines which validity and reliability criteria apply.
Outer Model (Measurement Model) Evaluation, Reflective Constructs
Factor loadings (outer loadings ≥ 0.70), internal consistency reliability (Cronbach's Alpha and Composite Reliability ≥ 0.70), convergent validity (AVE ≥ 0.50), and discriminant validity (HTMT ratio < 0.85 / 0.90, and Fornell-Larcker criterion).
Outer Model Evaluation, Formative Constructs
Indicator weights and significance (via bootstrapping), Variance Inflation Factor (VIF) for collinearity among indicators, and redundancy analysis for convergent validity.
Common Method Bias Assessment
We assess common method variance through the full collinearity test using VIF values across all constructs — current best practice as per Hair et al. 2022.
Structural Model (Inner Model) Evaluation
Path coefficients and their significance (via bootstrapping, 5,000 subsamples), effect sizes (f²) for each path, R² values for endogenous constructs, and predictive relevance (Q² via blindfolding).
Mediation Analysis in SmartPLS
Indirect effects tested via bootstrapping, reporting point estimates and 95% bias-corrected confidence intervals to determine whether mediation is supported.
Moderation Analysis
Interaction term creation and testing using the two-stage approach or orthogonalisation method, with slope analysis and Johnson-Neyman technique where applicable.
Multi-Group Analysis (MGA) in SmartPLS
Testing whether path coefficients differ significantly across groups, using SmartPLS MGA, permutation testing, and parametric approach as appropriate.
Full Results Write-Up
Complete written interpretation of measurement model and structural model results, formatted for your thesis chapter or target journal manuscript.
SmartPLS Project File Delivery
Full project file delivered for transparency and auditability.
Specialized Modules
Sub-Services
Module 01
Full PLS-SEM Analysis in SmartPLS
For studies requiring a complete two-stage PLS-SEM analysis — measurement model assessment followed by structural model testing — we handle the full workflow from data preparation to final write-up, delivering a results chapter that meets the methodological standards of management and marketing journals.
Module 02
Reflective and Formative Measurement Model Evaluation
Distinguishing between reflective and formative constructs is one of the most consequential decisions in PLS-SEM and one of the most commonly mishandled in student research. We assess each construct's theoretical nature, apply the appropriate validity and reliability criteria, and document the evaluation clearly for your methodology chapter.
Module 03
SmartPLS Mediation and Moderation Analysis
Testing mediating and moderating effects is a central analytical requirement in behavioural, marketing, and organisational research. We conduct bootstrapped indirect effect testing for mediation and interaction term analysis for moderation in SmartPLS, reporting confidence intervals, effect sizes, and slopes in the format required by peer-reviewed journals.
Module 04
SmartPLS Results for Journal Manuscript Submission
Translating SmartPLS output into publication-ready tables and text is a specialised task. We format your measurement model and structural model results to the exact reporting standards of your target journal, including HTMT tables, path coefficient tables, effect size tables, and model figures, ensuring the results section meets reviewer expectations in management, marketing, and IS journals.
Module 05
SmartPLS Model Review and Correction
If your SmartPLS model has been flagged by a supervisor or peer reviewer for weak discriminant validity, poor outer loadings, insignificant paths, or incorrect formative construct evaluation, we review the model, diagnose the specific issues, and re-run the analysis with corrections, delivering a revised model with a clear explanation of what was changed and why.
SmartPLS PLS-SEM Measurement Model Evaluation: Key Criteria at a Glance
See how our professional academic advisory compares to generic online alternatives.
| Feature | Generic Online Services | E-Clearby Research Consulting |
|---|---|---|
| Outer Loadings | Reflective | Factor loading ≥ 0.70 (All item loadings per construct) |
| Internal Consistency | Reflective | Cronbach's Alpha + CR ≥ 0.70 (Both indices per construct) |
| Convergent Validity | Reflective | AVE ≥ 0.50 (AVE per construct) |
| Discriminant Validity | Reflective | HTMT ratio < 0.85 or < 0.90 (HTMT matrix) |
| Indicator Weights | Formative | Bootstrapped weight significant p < 0.05 (Weights + significance) |
| Collinearity | Formative | VIF < 3.3 or < 5.0 (VIF per indicator) |
| R² (Explained Variance) | Endogenous constructs | R² value: Moderate ≥ 0.33, Substantial ≥ 0.67 (R² per endogenous construct) |
| Effect Size | All paths | f²: 0.02 = small, 0.15 = medium, 0.35 = large (f² per path) |
Frequently Asked Questions
SmartPLS Done to Publication Standard: Rigorous, Defensible, and Reviewer-Ready
PLS-SEM is one of the most scrutinised analytical techniques in management and marketing journals. Our SmartPLS consultants apply current best-practice methodology — measurement model first, structural model second, HTMT for discriminant validity, bootstrapped confidence intervals for mediation — and deliver results that stand up to peer review and examiner questioning.
Get SmartPLS Analysis Support →