Abstract
The author discusses common method bias in the context of structural equation modeling employing the partial least squares method (PLS-SEM). Two datasets were created through a Monte Carlo simulation to illustrate the discussion: one contaminated by common method bias, and the other not contaminated. A practical approach is presented for the identification of common method bias based on variance inflation factors generated via a full collinearity test. The author's discussion builds on an illustrative model in the field of e-collaboration, with outputs generated by the software WarpPLS. They demonstrate that the full collinearity test is successful in the identification of common method bias with a model that…
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8,093
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- FWCI
- 95.41
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Authors
1Topics & keywords
Keywords
- Collinearity
- Computer science
- Identification (biology)
- Context (archaeology)
- Monte Carlo method
- Statistics
- Partial least squares regression
- Data mining
UN Sustainable Development Goals
- Reduced inequalities
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