The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods
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Cites
A Paradigm for Developing Better Measures of Marketing Constructs
Churchill, G. A. (1979) · Journal of Marketing Research · doi:10.1177/002224377901600110 · Cited by 16,549
Construct validity in psychological tests.
Cronbach, L. J., & Meehl, P. E. (1955) · Psychological Bulletin · doi:10.1037/h0040957 · Cited by 11,195
Modern Methods for Business Research
(1998) · doi:10.4324/9781410604385 · Cited by 6,534
Specification, evaluation, and interpretation of structural equation models
Bagozzi, R. P., & Yi, Y. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0278-x · Cited by 3,735
Representing and Testing Organizational Theories: A Holistic Construal
Bagozzi, R. P., & Phillips, L. W. (1982) · Administrative Science Quarterly · doi:10.2307/2392322 · Cited by 2,064
Unit weighting schemes for decision making
Einhorn, H. J., & Hogarth, R. M. (1975) · Organizational Behavior and Human Performance · doi:10.1016/0030-5073(75)90044-6 · Cited by 673
The superiority of simple alternatives to regression for social science predictions
Dana, J., & Dawes, R. M. (2004) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986029003317 · Cited by 131
Cited by
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
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
Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research
F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014) · European Business Review · doi:10.1108/ebr-10-2013-0128 · Cited by 11,728
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
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
Metadata
- Authors
- Rigdon, E. E.
- Venue
- Long Range Planning
- Publisher
- Elsevier BV
- Published
- 2012-10
- Volume
- 45
- Issue
- 5-6
- Pages
- 341-358
- ISSN
- 0024-6301 (ISSN-L)
- OpenAlex
- W2072964722
- Cited by
- 877
- References
- 7
- FWCI
- 17.51
- Type
- journal article
- Language
- en
- Open access
- closed
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- Rigdon, E. E. (2012). Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods. Long Range Planning. https://doi.org/10.1016/j.lrp.2012.09.010
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
