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

Hair, Joe F., Howard, Matt C., Nitzl, Christian·2020·Journal of Business Research

DOI 10.1016/j.jbusres.2019.11.069

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Authors: Hair, J. F., Howard, M. C., & Nitzl, C.
Affiliations: University of South Alabama (US)
Universität der Bundeswehr München (DE)
Corresponding author: Hair, Joe F.
ORCID: Hair, Joe F.
Howard, Matt C.
Nitzl, Christian
Venue: Journal of Business Research
Publisher: Elsevier BV
Published: 2020-03
Volume: 109
Pages: 101-110
ISSN: 0148-2963 (ISSN-L)
DOI: 10.1016/j.jbusres.2019.11.069
OpenAlex: W2995576379
Cited by: 5,446
References: 88
Citations by year: 2026: 1102 · 2025: 1296 · 2024: 1180 · 2023: 841 · 2022: 592 · 2021: 348 · 2020: 84
FWCI: 183.37
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Journal of Business Research (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Management Research
Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords: measurement model validation, PLS-SEM, formative constructs, reflective constructs, construct measurement, scale development

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