Common Method Bias: A Full Collinearity Assessment Method for PLS-SEM

Ned Kock ()
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Ned Kock: Texas A&M International University, Division of International Business and Technology Studies

Chapter Chapter 11 in Partial Least Squares Path Modeling, 2017, pp 245-257 from Springer

Abstract: Abstract In the context of structural equation modeling employing the partial least squares (PLS-SEM) method, common method bias is a phenomenon caused by common variation induced by the measurement method used and not by the network of causes and effects in the model being studied. Two datasets were created through a Monte Carlo simulation to illustrate our discussion of this phenomenon: 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. Our discussion builds on an illustrative model in the field of e-collaboration, with outputs generated by the software WarpPLS. We 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.

Keywords: Common Method Bias; Full Collinearity; Software WarpPLS; Illustrative Model; Latent Variable Increases (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-64069-3_11

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DOI: 10.1007/978-3-319-64069-3_11

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