Interpretation of Formative Measurement in Information Systems Research

By Ronald T. Cenfetelli, Geneviève Bassellier. MIS Q., 2009

1,293 citations recorded by the source corpus.

Subfields: Computer Science Applications

View Paper: https://www.semanticscholar.org/paper/d7c0ac3d633de5c7548ae70ca3246052a357903b

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In Computer Science Applications

1. Raquel Benbunan-Fich
2. Gregory Moody
3. John D'Arcy
4. Ned Kock
5. V. Venkatesh
6. Chuang Wang
7. Adamantios Diamantopoulos
8. John D. Wells

Citations in the corpus

• Formative Vs. Reflective Measurement Model: Guidelines for Structural Equation Modeling Research (2020, methodology): “Different to the reflective indicator by which moderate multicollinearity between construct indicators is desirable, the balance of the model can be triggered by the high multicollinearity present in the formative construct ([15]; [32]; [33]).”
• Characteristics of organizational structure relating to hybrid competitive strategy: Implications for performance (2012, background): “…multicollinearity between formative indicators, since multicollinearity would indicate that a conceptual redundancy between the indicators of the construct exists (Cenfetelli and Bassellier, 2009), that is to say, that some of the indicators would be measuring a same facet of the latent construct.”
• How University Entrepreneurship Support Affects College Students’ Entrepreneurial Intentions: An Empirical Analysis from China (2021, background): “When the weight and loading are not significant, there is no empirical evidence to support retaining the indicator, and its theoretical relevance should be questioned [113].”
• Does gamification affect brand engagement and equity? A study in online brand communities (2020, positive): “Even though some of the indicators had low weights that were statistically non-significant, all of the indicators had high loadings (above 0.573), indicating that the external validity is acceptable (Cenfetelli & Bassellier, 2009).”
• How perceptions of intelligence and anthropomorphism affect adoption of personal intelligent agents (2020, methodology): “The evaluation of the formative measurement model shows that the guidelines of Cenfetelli and Bassellier (2009) are fulfilled.”
• When to use and how to report the results of PLS-SEM (2019, background): “Formative measurement models are, therefore, inherently limited in the number of indicator weights that can be statistically significant (Cenfetelli and Bassellier, 2009).”
• How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research (2020, background): “Assessment of the composite model The composite model requires an evaluation sui generis – an examination of the composite model with respect to multicollinearity, weights, composite loadings, and their significances [43,76,77,83,122].”
• Why Do Adults Engage in Cyberbullying on Social Media? An Integration of Online Disinhibition and Deindividuation Effects with the Social Structure and Social Learning Model (2016, methodology): “…assessing factorial validity is to determine which constructs are formative and which are reflective (Diamantopoulos and Winklhofer 2001).i We used (Cenfetelli and Bassellier 2009; Diamantopoulos and Winklhofer 2001; Petter et al. 2007) as the basis for determining which constructs were formative…”