The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Do right PLS and do PLS right: A critical review of the application of PLS-SEM in construction management research
Open accessAbstract
Partial least squares structural equation modeling (PLS-SEM) is a modern multivariate analysis technique with a demonstrated ability to estimate theoretically established cause-effect relationship models. This technique has been increasingly adopted in construction management research over the last two decades. Accordingly, a critical review of studies adopting PLS-SEM appears to be a timely and valuable endeavor. This paper offers a critical review of 139 articles that applied PLS-SEM from 2002 to 2019. Results show that the misuse of PLS-SEM can be avoided. Critical issues related to the application of PLS-SEM, research design, model development, and model evaluation are discussed in detail. This paper is the first to highlight the use and misuse of PLS-SEM in the construction management area and provides recommendations to facilitate the future application of PLS-SEM in this field.
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Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Statistical Power Analysis for the Behavioral Sciences
Muller, K. (1989) · Technometrics · doi:10.1080/00401706.1989.10488618 · Cited by 99,167
Statistical power analysis for the behavioral sciences
(1990) · Computers, Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,269
Coefficient Alpha and the Internal Structure of Tests
Cronbach, L. J. (1951) · Psychometrika · doi:10.1007/bf02310555 · Cited by 43,931
Statistical Power Analysis for the Behavioral Sciences (2nd ed.).
Lachenbruch, P. A., & Cohen, J. (1989) · Journal of the American Statistical Association · doi:10.2307/2290095 · Cited by 37,395
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163
Pls-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
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
A typology of reviews: an analysis of 14 review types and associated methodologies
Grant, M. J., & Booth, A. (2009) · Health Information & Libraries Journal · doi:10.1111/j.1471-1842.2009.00848.x · Cited by 10,817
PLS-regression: a basic tool of chemometrics
Wold, S., Sjöström, M., & Eriksson, L. (2001) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(01)00155-1 · Cited by 10,084
Cited by
Partial 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
Partial Least Squares Structural Equation Modeling
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021) · Handbook of Market Research · doi:10.1007/978-3-319-05542-8_15-2 · Cited by 876
A perspective on using partial least squares structural equation modelling in data articles
Ringle, C. M., Sarstedt, M., Sinkovics, N., & Sinkovics, R. R. (2023) · Data in Brief · doi:10.1016/j.dib.2023.109074 · Cited by 767
Khan, M. T., Idrees, M. D., Rauf, M., Sami, A., Ansari, A., & Jamil, A. (2022) · Sustainability · doi:10.3390/su14063362 · Cited by 118
“The PLS-structural equation modeling method was used to test the hypotheses, as the PLS-SEM method is used to test and evaluate complex statistical models [90,91].”
Metadata
- Authors
- Zeng, N., Liu, Y., Gong, P., Hertogh, M., & König, M.
- Venue
- Frontiers of Engineering Management
- Published
- 2021-03-27
- Volume
- 8
- Issue
- 3
- Pages
- 356-369
- ISSN
- 2095-7513 (ISSN-L)
- 2096-0255
- OpenAlex
- W3151173194
- Cited by
- 300
- References
- 66
- FWCI
- 25.29
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Zeng, N., Liu, Y., Gong, P., Hertogh, M., & König, M. (2021). Do right PLS and do PLS right: A critical review of the application of PLS-SEM in construction management research. Frontiers of Engineering Management. https://doi.org/10.1007/s42524-021-0153-5
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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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