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How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research
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“The evaluation results were satisfactory as summarized in Tables 5 and 6.”
From Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making (2021) · cites this paper as Benitez et al., 2020
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“Discriminant validity was also further established as the scores of the heterotrait-monotrait (HTMT) ratio of correlations were below the suggested threshold of 0.85 (Benitez et al., 2020).”
From Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making (2021) · cites this paper as Benitez et al., 2020
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“Benitez et al. [114] identify two types of formative constructs, composite, and causal-formative constructs.”
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“The confirmatory composite analysis aims at examining the overall fit of the measurement (saturated) model [114].”
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“All direct values are greater than the thresholds of 0.15 and 0.35, so we can thus conclude that they have moderate to high effect sizes [114].”
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“Questionnaire records were screened sequentially for eligibility and attention.Respondents first completed a visual check to confirm that they correctly identified an AIO (Li & Aral, 2025).Records with abnormally short completion times were then removed (Benítez et al., 2020), followed by records that failed an instructional manipulation check (Oppenheimer et al., 2009).”
From From search results to generative answers: A mixed-methods study of credibility assessment and trust formation in AI Overviews (2027) · cites this paper as Benítez et al., 2020
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- G. Franke, M. Sarstedt, Heuristics versus statistics in discriminant validity testing: a comparison of four procedures, Internet Res. (in press), pp. 1-32.
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Metadata
- Authors
- Benitez, J., Henseler, J., Castillo, A., & Schuberth, F.
- Affiliations
- Universidad de Granada (ES)
- Universidade Nova de Lisboa (PT)
- Venue
- Information & Management
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 57
- Issue
- 2
- Pages
- 103168
- ISSN
- 0378-7206 (ISSN-L)
- OpenAlex
- W2945049087
- Cited by
- 1,788
- References
- 151
- Citations by year
- 2026: 240 · 2025: 327 · 2024: 346 · 2023: 351 · 2022: 287 · 2021: 169 · 2020: 60
- FWCI
- 102.19
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Information & Management (publishedVersion, other-oa)
- HAL (submittedVersion, cc-by-nc)
- University of Twente Research Information (submittedVersion, cc-by)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by-nc)
- Funders
- European Regional Development Fund
- Government of Spain
- Research Grant
- Regional Government of Andalusia
- COVIRAN-Prodware Chair of Digital Human Resource Strategy at the University of Granada
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Keywords
- partial least squares, reporting guidelines, information systems research, structural equation modeling, research methodology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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