The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling
Abstract
Partial least squares path modeling (PLS) was developed in the 1960s and 1970s as a method for predictive modeling. In the succeeding years, applied disciplines, including organizational and management research, have developed beliefs about the capabilities of PLS and its suitability for different applications. On close examination, some of these beliefs prove to be unfounded and to bear little correspondence to the actual capabilities of PLS. In this article, we critically examine several of these commonly held beliefs. We describe their origins, and, using simple examples, we demonstrate that many of these beliefs are not true. We conclude that the method is widely misunderstood, and our results cast strong doubts on its effectiveness for building and testing theory in organizational research.
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Cites
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
lavaan : An R Package for Structural Equation Modeling
Rosseel, Y. (2012) · Journal of Statistical Software · doi:10.18637/jss.v048.i02 · Cited by 27,955
To parcel or not to parcel: Exploring the question, weighing the merits
Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem0902_1 · Cited by 6,552
Modern Methods for Business Research
(1998) · doi:10.4324/9781410604385 · Cited by 6,534
Predicting unit performance by assessing transformational and transactional leadership.
Bass, B. M., Avolio, B. J., Jung, D. I., & Berson, Y. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.2.207 · Cited by 3,026
An empirical comparison of the efficacy of covariance-based and variance-based SEM
Reinartz, W., Haenlein, M., & Henseler, J. (2009) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2009.08.001 · Cited by 2,906
On making causal claims: A review and recommendations
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010) · The Leadership Quarterly · doi:10.1016/j.leaqua.2010.10.010 · Cited by 2,441
The fit between product market strategy and business model: implications for firm performance
Zott, C., & Amit, R. (2008) · Strategic Management Journal · doi:10.1002/smj.642 · Cited by 1,731
Peng, D. X., & Lai, F. (2012) · Journal of Operations Management · doi:10.1016/j.jom.2012.06.002 · Cited by 1,532
Gender differences in work-family conflict
Duxbury, L. E., & Higgins, C. A. (1991) · Journal of Applied Psychology · doi:10.1037/0021-9010.76.1.60 · Cited by 782
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
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
An updated and expanded assessment of PLS-SEM in information systems research
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017) · Industrial Management & Data Systems · doi:10.1108/imds-04-2016-0130 · Cited by 4,043
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
Metadata
- Authors
- Rönkkö, M., & Evermann, J.
- Venue
- Organizational Research Methods
- Publisher
- SAGE Publications
- Published
- 2013-03-07
- Volume
- 16
- Issue
- 3
- Pages
- 425-448
- ISSN
- 1094-4281 (ISSN-L)
- 1552-7425
- OpenAlex
- W2326958296
- Cited by
- 434
- References
- 12
- FWCI
- 31.73
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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