The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.
Assessing measurement model quality in PLS-SEM using confirmatory composite analysis
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Additionally, both the composite reliability (CR) and Cronbach's alpha (α) values for each of the four constructs used in this study exceeded the suggested threshold of 0.70, indicating that the measures exhibit internal consistency, reliability and credibility (Fornell and Larcker, 1981;Hair et al., 2020).”
From Promoting transparency and accountability towards anti-corruption in pharmaceutical procurement system: does e-procurement play a significant role? (2024) · cites this paper as Hair et al., 2020
In the citing paper
“The results presented in Figure 2 and Table 1 provide sufficient evidence for the unidimensionality of the measurement scales in this study, with all observed items demonstrating factor loadings (λ) greater than 0.7 (Hair et al., 2020).”
From Promoting transparency and accountability towards anti-corruption in pharmaceutical procurement system: does e-procurement play a significant role? (2024) · cites this paper as Hair et al., 2020
In the citing paper
“PLS is proficient in handling multicollinearity issues as it can provide reliable findings even in cases of high multicollinearity (Hair et al., 2017, 2020).”
From Sustainable entrepreneurship and knowledge management: Role of green information technology in building sustainable entrepreneurial ecosystems (2025) · cites this paper as Hair et al., 2020
Citations
Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
Principles and Practice of Structural Equation Modeling
Tabri, N., & Elliott, C. M. (2012) · Canadian Graduate Journal of Sociology and Criminology · doi:10.15353/cgjsc.v1i1.3787 · Cited by 39,094
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459
(1998) · Cited by 36,049
Herne, H., Cooley, W. W., & Lohnes, P. R. (1973) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344428 · Cited by 35,801
When to Use and How to Report the Results of PLS-SEM
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019) · European Business Review · doi:10.1108/ebr-11-2018-0203 · Cited by 27,541
Self-citationPls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631
Self-citationA primer on partial least squares structural equation modeling (PLS-SEM)
Leguina, A. (2015) · International Journal of Research & Method in Education · doi:10.1080/1743727x.2015.1005806 · Cited by 18,921
Confirmatory factor analysis for applied research
Brown, T. A. (2007) · Choice Reviews Online · doi:10.5860/choice.44-2769 · Cited by 15,621
(2014) · DigitalCommons - Kennesaw State University (Kennesaw State University) · Cited by 12,785
Self-citation(1998) · Cited by 12,725
Construct validity in psychological tests.
Cronbach, L. J., & Meehl, P. E. (1955) · Psychological Bulletin · doi:10.1037/h0040957 · Cited by 11,195
Cross validatory choice and assessment of statistical predictions
Stone, M. (1974) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1974.tb00994.x · Cited by 10,881
Applied Multivariate Statistics for the Social Sciences
Stevens, J. P. (2012) · Routledge eBooks · doi:10.4324/9780203843130 · Cited by 10,652
Evaluating the use of exploratory factor analysis in psychological research.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999) · Psychological Methods · doi:10.1037/1082-989x.4.3.272 · Cited by 9,587
An assessment of the use of partial least squares structural equation modeling in marketing research
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0261-6 · Cited by 8,088
Self-citationVandenberg, R. J., & Lance, C. E. (2000) · Organizational Research Methods · doi:10.1177/109442810031002 · Cited by 7,997
Using pls path modeling in new technology research: updated guidelines
Henseler, J., Hubona, G., & Ray, P. A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-09-2015-0382 · Cited by 7,173
Modern Methods for Business Research
(1998) · doi:10.4324/9781410604385 · Cited by 6,534
"General Intelligence," Objectively Determined and Measured
Spearman, C. (1904) · The American Journal of Psychology · doi:10.2307/1412107 · Cited by 6,207
PLS-SEM or CB-SEM: updated guidelines on which method to use
Jr., J. F. H., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017) · International Journal of Multivariate Data Analysis · doi:10.1504/ijmda.2017.087624 · Cited by 5,441
Self-citationIntroduction to Classical and Modern Test Theory
Crocker, L. M., & Algina, J. J. (1986) · Cited by 5,090
Predictive model assessment in PLS-SEM: guidelines for using PLSpredict
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019) · European Journal of Marketing · doi:10.1108/ejm-02-2019-0189 · Cited by 4,618
Self-citationAn Introduction to the Theory of Statistics
(1911) · Nature · doi:10.1038/087345a0 · Cited by 4,430
Cohen, J. (1994) · American Psychologist · doi:10.1037/0003-066x.49.12.997 · Cited by 4,003
How to Specify, Estimate, and Validate Higher-Order Constructs in PLS-SEM
Sarstedt, M., Hair, J. F., Cheah, J., Becker, J.-M., & Ringle, C. M. (2019) · Australasian Marketing Journal (AMJ) · doi:10.1016/j.ausmj.2019.05.003 · Cited by 3,990
Self-citationKlemelä, J. (2018) · Wiley series in probability and statistics · doi:10.1002/9781119409137.ch4 · Cited by 3,817
Exploratory and confirmatory factor analysis: Understanding concepts and applications.
Thompson, B. (2004) · doi:10.1037/10694-000 · Cited by 3,469
Fundamentals of item response theory
(1992) · Choice Reviews Online · doi:10.5860/choice.29-4185 · Cited by 3,420
An Easy Guide to Factor Analysis
Kline, P. (2014) · Routledge eBooks · doi:10.4324/9781315788135 · Cited by 3,380
Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014) · Organizational Research Methods · doi:10.1177/1094428114526928 · Cited by 3,332
Self-citationA Predictive Approach to the Random Effect Model
Geisser, S. (1974) · Biometrika · doi:10.1093/biomet/61.1.101 · Cited by 3,101
Testing measurement invariance of composites using partial least squares
Henseler, J., Ringle, C. M., & Sarstedt, M. (2016) · International Marketing Review · doi:10.1108/imr-09-2014-0304 · Cited by 2,964
Mediation analysis in partial least squares path modeling
Nitzl, C., Roldán, J. L., & Cepeda‐Carrión, G. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-07-2015-0302 · Cited by 2,818
Self-citationAdvanced Issues in Partial Least Squares Structural Equation Modeling
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017) · Cited by 2,503
Self-citationHeuristics versus statistics in discriminant validity testing: a comparison of four procedures
Franke, G. R., & Sarstedt, M. (2019) · Internet Research · doi:10.1108/intr-12-2017-0515 · Cited by 2,355
Methods of multivariate analysis
(1995) · Choice Reviews Online · doi:10.5860/choice.33-1586 · Cited by 2,292
Becker, J.-M., Klein, K., & Wetzels, M. (2012) · Long Range Planning · doi:10.1016/j.lrp.2012.10.001 · Cited by 2,279
Reading and understanding multivariate statistics
Grimm, L. G., & Yarnold, P. R. (1995) · Cited by 2,235
Latent Variable Path Modeling with Partial Least Squares
Lohmöller, J.-B. (1989) · Physica-Verlag eBooks · doi:10.1007/978-3-642-52512-4 · Cited by 2,197
Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012) · MIS Quarterly · doi:10.2307/41410402 · Cited by 2,184
Estimation issues with PLS and CBSEM: Where the bias lies!
Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2016.06.007 · Cited by 1,991
Self-citationGalit Shmueli, A., Ray, S., Estrada, J. M. V., & Chatla, S. B. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2016.03.049 · Cited by 1,904
Rethinking some of the rethinking of partial least squares
Hair, J. F., Sarstedt, M., & Ringle, C. M. (2019) · European Journal of Marketing · doi:10.1108/ejm-10-2018-0665 · Cited by 1,839
Self-citationBenitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020) · Information & Management · doi:10.1016/j.im.2019.05.003 · Cited by 1,788
PLS-SEM or CB-SEM: updated guidelines on which method to use
Hair, J. F., Matthews, L. M., Matthews, R. L., et al. (2017) · International Journal of Multivariate Data Analysis · doi:10.1504/ijmda.2017.10008574 · Cited by 1,489
Self-citationAdvancing formative measurement models
Diamantopoulos, A., Riefler, P., & Zeugner‐Roth, K. P. (2008) · Journal of Business Research · doi:10.1016/j.jbusres.2008.01.009 · Cited by 1,469
Howard, M. C. (2016) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2015.1087664 · Cited by 1,349
Self-citationConsistent and asymptotically normal PLS estimators for linear structural equations
Dijkstra, T. K., & Henseler, J. (2014) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2014.07.008 · Cited by 1,344
Soft modelling: The Basic Design and Some Extensions
Wold, H. (1982) · Medical Entomology and Zoology · Cited by 1,314
Structural model robustness checks in PLS-SEM
Sarstedt, M., Ringle, C. M., Cheah, J.-H., Ting, H., Moisescu, O. I., & Radomir, L. (2020) · Tourism Economics · doi:10.1177/1354816618823921 · Cited by 1,271
Essentials of Business Research Methods
Hair, J., Wolfinbarger, M. F., Money, A. H., Samouel, P., & Page, M. J. (2015) · Routledge eBooks · doi:10.4324/9781315704562 · Cited by 1,221
Self-citationInterpretation of Formative Measurement in Information Systems Research1
Cenfetelli, R. T., & Bassellier, G. (2009) · MIS Quarterly · doi:10.2307/20650323 · Cited by 1,051
Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods
Rigdon, E. E. (2012) · Long Range Planning · doi:10.1016/j.lrp.2012.09.010 · Cited by 915
Repairing Tom Swift's Electric Factor Analysis Machine
Preacher, K. J., & MacCallum, R. C. (2003) · Understanding Statistics · doi:10.1207/s15328031us0201_02 · Cited by 860
Partial Least Squares: The Better Approach to Structural Equation Modeling?
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012) · Long Range Planning · doi:10.1016/j.lrp.2012.09.011 · Cited by 855
Self-citationMethods of Multivariate Analysis
Rencher, A. C., & Christensen, W. F. (2012) · Wiley series in probability and statistics · doi:10.1002/9781118391686 · Cited by 767
On the emancipation of PLS-SEM: a commentary on Rigdon (2012)
Sarstedt, M., Ringle, C. M., Henseler, J., & Hair, J. F. (2014) · Long Range Planning · doi:10.1016/j.lrp.2014.02.007 · Cited by 758
Self-citationEssentials of Business Research Methods
Hair, J. F., Page, M., & Brunsveld, N. (2019) · doi:10.4324/9780429203374 · Cited by 732
Self-citationInterpretation of formative measurement in information systems research
Cenfetelli, R. T., & Bassellier, G. (2009) · Journal of the Association for Information Systems · doi:10.5555/2017434.2017440 · Cited by 706
Nitzl, C. (2016) · Journal of Accounting Literature · doi:10.1016/j.acclit.2016.09.003 · Cited by 580
Self-citationCheah, J.-H., Sarstedt, M., Ringle, C. M., Ramayah, T., & Ting, H. (2018) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-10-2017-0649 · Cited by 566
The ML and PLS techniques for modeling with latent variables : Historical and comparative aspects
Jöreskog, K. G. (1982) · Cited by 472
Factors versus Composites: Guidelines for Choosing the Right Structural Equation Modeling Method
Hair, J. F., & Sarstedt, M. (2019) · Project Management Journal · doi:10.1177/8756972819882132 · Cited by 412
Self-citationGeneralized Structured Component Analysis
Hwang, H., & Takane, Y. (2004) · Psychometrika · doi:10.1007/bf02295841 · Cited by 337
Prediction‐Oriented Model Selection in Partial Least Squares Path Modeling
Sharma, P. N., Galit Shmueli, A., Sarstedt, M., Danks, N. P., & Ray, S. (2018) · Decision Sciences · doi:10.1111/deci.12329 · Cited by 314
Partial Least Squares (PLS) Methods: Origins, Evolution, and Application to Social Sciences
Mateos-Aparicio, G. (2011) · Communication in Statistics- Theory and Methods · doi:10.1080/03610921003778225 · Cited by 286
An Introduction to the Theory of Statistics.
Allen, R. G. D., Yule, G. U., & Kendall, M. G. (1937) · The Economic Journal · doi:10.2307/2225339 · Cited by 254
Assessing the predictive performance of structural equation model estimators
Evermann, J., & Tate, M. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2016.03.050 · Cited by 252
Rethinking Partial Least Squares Path Modeling: Breaking Chains and Forging Ahead
Rigdon, E. E. (2014) · Long Range Planning · doi:10.1016/j.lrp.2014.02.003 · Cited by 229
Confirmatory Composite Analysis
Schuberth, F., Henseler, J., & Dijkstra, T. K. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.02541 · Cited by 225
PLS-Based Model Selection: The Role of Alternative Explanations in Information Systems Research
Sharma, P. N., Sarstedt, M., Galit Shmueli, A., Kim, K. H., & Thiele, K. O. (2019) · Journal of the Association for Information Systems · doi:10.17705/1jais.00538 · Cited by 220
On the Equivalence of Factors and Components
Bentler, P. M., & Kano, Y. (1990) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2501_8 · Cited by 206
Bootstrapped Confidence Intervals as an Approach to Statistical Inference
Wood, M. C. (2005) · Organizational Research Methods · doi:10.1177/1094428105280059 · Cited by 184
Goetz, C., Coste, J., Lemétayer, F., Rat, A., Montel, S., Recchia, S., Debouverie, M., Pouchot, J., Spitz, É., & Guillemin, F. (2013) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2012.12.015 · Cited by 175
The case of partial least squares (PLS) path modeling in managerial accounting research
Nitzl, C., & Chin, W. W. (2017) · Journal of Management Control · doi:10.1007/s00187-017-0249-6 · Cited by 170
Self-citationPredictions from Partial Least Squares Models
Danks, N. P., & Ray, S. (2018) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-78756-699-620181003 · Cited by 139
On the theory of correlation for any number of variables, treated by a new system of notation
Yule, G. U. (1907) · Proceedings of the Royal Society of London Series A Containing Papers of a Mathematical and Physical Character · doi:10.1098/rspa.1907.0028 · Cited by 128
"Haters Gonna Hate": PLS and Information Systems Research
Petter, S. (2018) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/3229335.3229337 · Cited by 118
PLS-Based Model Selection: The Role of Alternative Explanations in Information Systems Research
Sharma, P. N., Sarstedt, M., Galit Shmueli, A., Kim, K. H., & Thiele, K. O. (2019) · tub.dok (Hamburg University of Technology) · doi:10.17005/1.jais.00538 · Cited by 98
Applying Partial Least Squares in Tourism and Hospitality Research
Ali, F., Rasoolimanesh, S. M., & Cobanoglu, C. (2018) · Emerald Group Publishing Limited eBooks · doi:10.1108/9781787566996 · Cited by 94
Rigdon, E. E., Becker, J.-M., & Sarstedt, M. (2019) · Multivariate Behavioral Research · doi:10.1080/00273171.2018.1535420 · Cited by 93
Applying the future time perspective scale to advertising research
Kuppelwieser, V. G., & Sarstedt, M. (2014) · International Journal of Advertising · doi:10.2501/ija-33-1-113-136 · Cited by 67
Matt, G. E. (2001) · Elsevier eBooks · doi:10.1016/b0-08-043076-7/00723-3 · Cited by 67
Nitzl, C., Roldán, J. L., & Cepeda‐Carrión, G. (2017) · Developments in marketing science: proceedings of the Academy of Marketing Science · doi:10.1007/978-3-319-47331-4_130 · Cited by 46
Self-citationDR. G. FREDERIC KUDER 1903‐2000
Hakel, M. D. (2000) · Personnel Psychology · doi:10.1111/j.1744-6570.2000.tb00201.x · Cited by 2
Marion Webster Richardson (1896–1965)
Lorr, M., & Heiser, R. B. (1965) · Psychometrika · doi:10.1007/bf02289489 · Cited by 1
Research works printed but not linked: 3
- Fassott, 2015, Vol. 9
- Howard, 2018, Scale pretesting, Practical Assessment, Research & Evaluation, 23
- Stouffer, 1950, Vol. 4
Cited by
Sorted by citations
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021) · Classroom Companion: Business · doi:10.1007/978-3-030-80519-7 · Cited by 10,343
Self-citationCB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting
Dash, G., & Paul, J. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121092 · Cited by 2,836
An Introduction to Structural Equation Modeling
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021) · Classroom companion: business · doi:10.1007/978-3-030-80519-7_1 · Cited by 1,932
Self-citationSarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., & Ringle, C. M. (2022) · Psychology and Marketing · doi:10.1002/mar.21640 · Cited by 1,844
Self-citationPartial Least Squares Structural Equation Modeling
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2022) · Handbook of Market Research · doi:10.1007/978-3-319-57413-4_15 · Cited by 1,483
Self-citation
Metadata
- Authors
- Hair, J. F., Howard, M. C., & Nitzl, C.
- Affiliations
- University of South Alabama (US)
- Universität der Bundeswehr München (DE)
- Corresponding author
- Hair, Joe F.
- Venue
- Journal of Business Research
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 109
- Pages
- 101-110
- ISSN
- 0148-2963 (ISSN-L)
- OpenAlex
- W2995576379
- Cited by
- 5,446
- References
- 88
- Citations by year
- 2026: 1102 · 2025: 1296 · 2024: 1180 · 2023: 841 · 2022: 592 · 2021: 348 · 2020: 84
- FWCI
- 183.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Business Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Management Research
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- measurement model validation, PLS-SEM, formative constructs, reflective constructs, construct measurement, scale development
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 ›
Are you an author, or do you see a problem with this page? Request a review
