Assessing measurement model quality in PLS-SEM using confirmatory composite analysis

Joe F. Hair, Matt C. Howard and Christian Nitzl

Journal of Business Research, 2020, vol. 109, issue C, 101-110

Abstract: Confirmatory factor analysis (CFA) has historically been used to develop and improve reflectively measured constructs based on the domain sampling model. Compared to CFA, confirmatory composite analysis (CCA) is a recently proposed alternative approach applied to confirm measurement models when using partial least squares structural equation modeling (PLS-SEM). CCA is a series of steps executed with PLS-SEM to confirm both reflective and formative measurement models of established measures that are being updated or adapted to a different context. CCA is also useful for developing new measures. Finally, CCA offers several advantages over other approaches for confirming measurement models consisting of linear composites.

Keywords: Confirmatory composite analysis; CCA; PLS-SEM; Confirmatory factor analysis; CFA; Measurement model confirmation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (402)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:109:y:2020:i:c:p:101-110

DOI: 10.1016/j.jbusres.2019.11.069

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