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The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Bridging Design and Behavioral Research With Variance-Based Structural Equation Modeling

Open access
Henseler, Jörg·2017·Journal of Advertising

Abstract

Advertising research is a scientific discipline that studies artifacts (e.g., various forms of marketing communication) as well as natural phenomena (e.g., consumer behavior). Empirical advertising research therefore requires methods that can model design constructs as well as behavioral constructs, which typically require different measurement models. This article presents variance-based structural equation modeling (SEM) as a family of techniques that can handle different types of measurement models: composites, common factors, and causal–formative measurement. It explains the differences between these types of measurement models and clears up possible ambiguity regarding formative endogenous constructs. The article proposes confirmatory composite analysis to assess the nomological validity of composites, confirmatory factor analysis (CFA) and the heterotrait-monotrait ratio of correlations (HTMT) to assess the construct validity of common factors, and the multiple indicator, multiple causes (MIMIC) model to assess the external validity of causal–formative measurement.

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Cited by

Metadata

Authors
Henseler, J.
Venue
Journal of Advertising
Published
2017-01-02
Volume
46
Issue
1
Pages
178-192
ISSN
  • 0091-3367 (ISSN-L)
  • 1557-7805
OpenAlex
W2587364646
Cited by
1,020
References
18
FWCI
56.83
Type
journal article
Language
en
Open access
bronze

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