Purpose and applicability
How do perceived quality, value, and trust shape satisfaction and customer loyalty?
No completed-result prerequisite is required for the first run.
Do not use it merely because it is available
Use PLS-SEM Algorithm only when its estimand, data roles and assumptions answer the stated research question. Choose a related estimator or diagnostic when the intended outcome is not among the documented outputs below.
Study preparation
- Teaching data
- customer-experience-pls.csv
- Observations
- 400
- Study type
- Deterministic synthetic teaching study
- Calculate route
- Calculate → PLS-SEM Algorithm
Open the data dictionary and variable-role reference
Model
Quality (quality_1–quality_4), Value (value_1–value_3), Trust (trust_1–trust_4), Satisfaction (satisfaction_1–satisfaction_4), and Loyalty (loyalty_1–loyalty_4), all reflective
Quality, Value, and Trust → Satisfaction; Quality, Value, and Trust → Loyalty. This direct-effects teaching model deliberately leaves indirect-path analysis to the separate Mediation tutorial
Exact workflow
Download customer-experience-pls.csv and the prepared customer-experience-pls.qpls project. Keep both files in a writable study folder.
Start QuickPLS, choose Open Project, and open the prepared project. Its saved model is already arranged and fitted.
Open Data and confirm that the study contains 400 observations. Return to the model or calculation workspace.
Confirm the saved model specification: Quality (quality_1–quality_4), Value (value_1–value_3), Trust (trust_1–trust_4), Satisfaction (satisfaction_1–satisfaction_4), and Loyalty (loyalty_1–loyalty_4), all reflective. Structural specification: Quality, Value, and Trust → Satisfaction; Quality, Value, and Trust → Loyalty. This direct-effects teaching model deliberately leaves indirect-path analysis to the separate Mediation tutorial.
Confirm that construct labels, indicators, and arrows are readable. The supplied project is saved after Arrange and Fit; do not rearrange it before the tutorial run.
Choose Calculate, then use Calculate → PLS-SEM Algorithm.
Review the essential settings listed below. Open Advanced settings only when the design requires a non-default option.
Resolve actionable blockers, review applicability warnings, and leave Open Results when finished selected.
Choose Start calculation. Wait for Completed, then confirm that Results opens for this method.
Inspect the named outputs below in order. Use Save Report, table Copy, or Export as required, then save and reopen the project to confirm the result remains available.
Essential and advanced settings
- Keep the path-weighting scheme and default convergence settings for the first run
- Leave Open Results when finished selected
Keep other advanced controls at their documented defaults unless the study design requires a justified change. Record every non-default value in the research log.
Results to inspect
- Graphical Output
- Path coefficients
- Outer loadings
- R-square
- Construct reliability and validity
- Model fit — descriptive
Interpretation guidance
For PLS-SEM Algorithm, interpret the listed outputs together with the prerequisite result, the selected settings, model assumptions and data quality. The supplied values are instructional; they are not validation against an external paper or another software package.
Reporting guidance
Report the QuickPLS version, PLS-SEM Algorithm route, sample size, model or variable roles, preprocessing, essential settings, non-default advanced settings, and the named primary outputs. Retain the project, data checksum and exported table used in the manuscript.
Common mistakes and recovery
- Running the method before completing its prerequisite calculation.
- Changing the data, model or variable roles after the prerequisite result was saved.
- Treating an unavailable or not-applicable value as zero.
- Reporting an estimate without its method-appropriate uncertainty or diagnostic context.
Screen-by-screen evidence
Images shown here are mapped to this tutorial’s required installed-application evidence. Missing captures are labelled explicitly and are not replaced with generic screenshots.