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How to Specify, Estimate, and Validate Higher-Order Constructs in PLS-SEM

2019; SAGE Publishing; Volume: 27; Issue: 3 Linguagem: Inglês

10.1016/j.ausmj.2019.05.003

1839-3349

Marko Sarstedt, Joseph F. Hair, Jun‐Hwa Cheah, Jan-Michael Becker, Christian M. Ringle,

Consumer Behavior in Brand Consumption and Identification

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.