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How to specify, estimate, and validate higher-order constructs in PLS-SEM


Citation

Sarstedt, Marko and Hair, Joseph F. and Cheah, Jun Hwa and Becker, Jan Michael and Ringle, Christian M. (2019) How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal, 27 (3). pp. 197-211. ISSN 1441-3582; ESSN: 1839-3349

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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Additional Metadata

Item Type: Article
Divisions: Faculty of Economics and Management
DOI Number: https://doi.org/10.1016/j.ausmj.2019.05.003
Publisher: Elsevier
Keywords: Hierarchical component models; Higher-order constructs; Partial least squares; Path modelling; PLS-SEM; Second-order constructs
Depositing User: Azhar Abdul Rahman
Date Deposited: 21 Sep 2020 08:22
Last Modified: 21 Sep 2020 08:22
Altmetrics: http://altmetrics.com-details.php?domain=psair.upm.edu.my&doi= 10.1016/j.ausmj.2019.05.003
URI: http://psasir.upm.edu.my/id/eprint/80089
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