The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Partial least squares path modeling: Time for some serious second thoughts
Open accessAbstract
Partial least squares (PLS) path modeling is increasingly being promoted as a technique of choice for various analysis scenarios, despite the serious shortcomings of the method. The current lack of methodological justification for PLS prompted the editors of this journal to declare that research using this technique is likely to be desk‐rejected (Guide and Ketokivi, 2015). To provide clarification on the inappropriateness of PLS for applied research, we provide a non‐technical review and empirical demonstration of its inherent, intractable problems. We show that although the PLS technique is promoted as a structural equation modeling (SEM) technique, it is simply regression with scale scores and thus has very limited capabilities to handle the wide array of problems for which applied researchers use SEM. To that end, we explain why the use of PLS weights and many rules of thumb that are commonly employed with PLS are unjustifiable, followed by addressing why the touted advantages of the method are simply untenable.
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Cites
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Cited by
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-017-0517-x · Cited by 2,712
Partial least squares structural equation modeling in HRM research
Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020) · The International Journal of Human Resource Management · doi:10.1080/09585192.2017.1416655 · Cited by 1,943
Improving PLS-SEM Use for Business Marketing Research
Guenther, P., Guenther, M., Ringle, C. M., Zaefarian, G., & Cartwright, S. (2023) · Industrial Marketing Management · doi:10.1016/j.indmarman.2023.03.010 · Cited by 800
Procurement 4.0 and its implications on business process performance in a circular economy
Bag, S., Wood, L. C., Mangla, S. K., & Luthra, S. (2020) · Resources, Conservation and Recycling · doi:10.1016/j.resconrec.2019.104502 · Cited by 339
Abbasi, G. A., Jagaveeran, M., Goh, Y.-N., & Tariq, B. (2021) · Technology in Society · doi:10.1016/j.techsoc.2020.101521 · Cited by 182
Metadata
- Authors
- Rönkkö, M., McIntosh, C. N., Antonakis, J., & Edwards, J. R.
- Venue
- Journal of Operations Management
- Publisher
- Wiley
- Published
- 2016-06-22
- Volume
- 47-48
- Issue
- 1
- Pages
- 9-27
- ISSN
- 0272-6963 (ISSN-L)
- 1873-1317
- OpenAlex
- W2467386812
- Cited by
- 303
- References
- 25
- FWCI
- 30.29
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Rönkkö, M., McIntosh, C. N., Antonakis, J., & Edwards, J. R. (2016). Partial least squares path modeling: Time for some serious second thoughts. Journal of Operations Management. https://doi.org/10.1016/j.jom.2016.05.002
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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.
