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Cited by 3,210

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 access
Sarstedt, Marko, Hair, Joseph F., Cheah, Jun-Hwa, Becker, Jan-Michael, Ringle, Christian M.·2019·Australasian Marketing Journal
DOI 10.1016/j.ausmj.2019.05.003
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Abstract

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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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
DOI
10.1016/j.ausmj.2019.05.003
OpenAlex
W2950750906
Cited by
3,210
References
12
FWCI
122.16
Type
journal article
Language
en
Open access
green

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