A practical guide to factorial validity using PLS-graph: tutorial and annotated example
Open accessAbstract
This tutorial explains in detail what factorial validity is and how to run its various aspects in PLS. The tutorial is written as a teaching aid for doctoral seminars that may cover PLS and for researchers interested in learning PLS. An annotated example with data is provided as an additional tool to assist the reader in reconstructing the detailed example.
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Indicators AUTH5, PSR5, and PGE4 with loadings below 0.50 were removed for both overall and country-specific data.
“By following these rules and using (Gefen and Straub, 2005) decision logic, the model was cleaned up by getting rid of AUTH5, PSR5, and PGE4 (loadings <0.50) for both overall and country-specific data.”
From Cross-national evidence on influencer-driven green choice: a moderated-mediation model of authenticity, parasocial ties, and greenwashing exposure (2026) · cites this paper as Gefen and Straub, 2005
The discussion of PCA and EFA says that items that do not load properly may be dropped to purify an instrument, which supports the general decision to remove weak indicators. But the PLS Factorial Validity section says there is no established loading threshold and does not prescribe removal below 0.50. The named indicators and the overall and country-specific analyses are the citing authors’ own results, not findings attributed to Gefen and Straub. (LLM, conf=0.85)
Experimental — accuracy not yet measuredComposite reliability values for all focal constructs met or came close to the 0.70 benchmark, indicating satisfactory internal consistency.
“The CR values for all focal constructs (AUTH, INTENT, PGE, PGR, PSR, TRUST) met or came close to the 0.70 benchmark, which indicates that the internal consistency was satisfactory (Gefen and Straub, 2005;Henseler et al., 2015).”
From Cross-national evidence on influencer-driven green choice: a moderated-mediation model of authenticity, parasocial ties, and greenwashing exposure (2026) · cites this paper as Gefen and Straub, 2005
Figure 5 in “Discriminant Validity: Procedure 1” reports composite reliability for the tutorial’s own constructs (Buy Tick, PU, and PEOU), not the six focal constructs in the citing sentence. Searches for a 0.70 composite-reliability benchmark and internal consistency found no passage in our copy establishing that benchmark or the claimed assessment. (LLM, conf=0.73)
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- Authors
- Gefen, D., & Straub, D.
- Affiliations
- Drexel University (US)
- Georgia State University (US)
- Venue
- Communications of the Association for Information Systems
- Publisher
- Association for Information Systems
- Published
- 2005
- Volume
- 16
- ISSN
- 1529-3181 (ISSN-L)
- OpenAlex
- W1496783311
- Cited by
- 3,280
- References
- 7
- Citations by year
- 2026: 57 · 2025: 167 · 2024: 176 · 2023: 216 · 2022: 235 · 2021: 231 · 2020: 219 · 2019: 208 · 2018: 182 · 2017: 184 · 2016: 182 · 2015: 207 · 2014: 224 · 2013: 182 · 2012: 163
- FWCI
- 60.90
- Type
- journal article
- Language
- en
- Open access
- green
- aisel.aisnet.org
- Locations
- Communications of the Association for Information Systems (publishedVersion)
- Journal of the Association for Information Systems (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Decision Sciences › Management Science and Operations Research › Business Strategies and Management Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- factorial validity, partial least squares, construct validity, structural equation modeling, PLS-SEM
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