Context (archaeology)

Biology

Identification (biology)

Statistics

Data mining

Computer science

Botany

Paleontology

Collinearity

Mathematics

Partial least squares regression

Econometrics

Artificial intelligence

Monte Carlo method

Machine learning

International Journal of e-Collaboration

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 nevertheless passes standard convergent and discriminant validity assessment criteria based on a confirmation factor analysis.

Common Method Bias in PLS-SEM