The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
How to Specify, Estimate, and Validate Higher-Order Constructs in PLS-SEM
Open accessAbstract
Higher-order constructs, which facilitate modeling a construct on a more abstract higher-level dimension and its more concrete lower-order subdimensions, have become an increasingly visible trend in applications of partial least squares structural equation modeling (PLS-SEM). Unfortunately, researchers frequently confuse the specification, estimation, and validation of higher-order constructs, for example, when it comes to assessing their reliability and validity. Addressing this concern, this paper explains how to evaluate the results of higher-order constructs in PLS-SEM using the repeated indicators and the two-stage approaches, which feature prominently in applied social sciences research. Focusing on the reflective-reflective and reflective-formative types of higher-order constructs, we use the well-known corporate reputation model example to illustrate their specification, estimation, and validation. Thereby, we provide the guidance that scholars, marketing researchers, and practitioners need when using higher-order constructs in their studies.
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Cites
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
Self-citationModern Methods for Business Research
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Self-citationDiscriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies
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Partial least squares structural equation modeling in HRM research
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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-citationAssessing measurement model quality in PLS-SEM using confirmatory composite analysis
Hair, J. F., Howard, M. C., & Nitzl, C. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2019.11.069 · Cited by 5,446
Self-citationHair, J., & Alamer, A. (2022) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2022.100027 · Cited by 2,833
Self-citationMikalef, P., & Gupta, M. (2021) · Information & Management · doi:10.1016/j.im.2021.103434 · Cited by 1,700
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
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Metadata
- Authors
- Sarstedt, M., Hair, J. F., Cheah, J.-H., Becker, J.-M., & Ringle, C. M.
- Venue
- Australasian Marketing Journal
- Publisher
- SAGE Publications
- Published
- 2019-08
- Volume
- 27
- Issue
- 3
- Pages
- 197-211
- ISSN
- 1441-3582 (ISSN-L)
- 1839-3349
- OpenAlex
- W2950750906
- Cited by
- 3,210
- References
- 12
- FWCI
- 122.16
- Type
- journal article
- Language
- en
- Open access
- green
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