Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/330731 
Erscheinungsjahr: 
2025
Quellenangabe: 
[Journal:] Journal of Marketing Analytics [ISSN:] 2050-3326 [Volume:] 13 [Issue:] 3 [Publisher:] Palgrave Macmillan [Place:] London [Year:] 2025 [Pages:] 709-724
Verlag: 
Palgrave Macmillan, London
Zusammenfassung: 
Covariance-based structural equation modeling (CB-SEM) enables researchers to estimate models with hypothesized cause-effect relationships between latent variables (i.e., constructs), each of which is operationalized by several items (i.e., indicators). To conduct CB-SEM analyses, researchers can rely on a range of software applications. However, many of these applications require researchers to engage in sometimes complicated and error-prone programming tasks. While IBM SPSS AMOS provides a graphical user interface (GUI), it does not fully meet the expectations of contemporary software. In order to address these challenges, the statistical SmartPLS 4 software has recently introduced a new CB-SEM module, which improves the user experience through a modern and intuitive graphical interface and comprehensive result reports. This tutorial describes the key CB-SEM analysis steps (i.e., model setup, estimation, and results evaluation) using the SmartPLS software.
Schlagwörter: 
CB-SEM
CFA
Confirmatory factor analysis
Covariance-based structural equation modeling
SEM
SmartPLS
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