Consistent Partial Least Squares Path Modeling

Author List: Dijkstra, Theo K.; Henseler, Jorg;

MIS Quarterly, 2015, Volume 39, Issue 2, Page 297-316.

This paper resumes the discussion in information systems research on the use of partial least squares (PLS) path modeling and shows that the inconsistency of PLS path coefficient estimates in the case of reflective measurement can have adverse consequences for hypothesis testing. To remedy this, the study introduces a vital extension of PLS: consistent PLS (PLSc). PLSc provides a correction for estimates when PLS is applied to reflective constructs: The path coefficients, inter-construct correlations, and indicator loadings become consistent. The outcome of a Monte Carlo simulation reveals that the bias of PLSc parameter estimates is comparable to that of covariance-based structural equation modeling. Moreover, the outcome shows that PLSc has advantages when using non-normally distributed data. We discuss the implications for IS research and provide guidelines for choosing among structural equation modeling techniques.

Keywords: PLS; consistent partial least squares; SEM; variance-based structural equation modeling; Monte Carlo simulation

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#11	0.769	structural pls measurement modeling equation research formative squares partial using indicators constructs construct statistical models researchers latent analysis results sem
#209	0.084	results study research information studies relationship size variables previous variable examining dependent increases empirical variance accounting independent demonstrate important addition
#77	0.052	information systems paper use design case important used context provide presented authors concepts order number various underlying implementation framework nature