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

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.

Keywords

Affiliated Institutions

• Universität Hamburg DE
• Hamburg University of Technology DE
• University of Waikato NZ
• Otto-von-Guericke University Magdeburg DE
• University of South Alabama US
• Universiti Putra Malaysia MY
• University of Cologne DE
• Monash University Malaysia MY

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