Henseler, JörgJörgHenselerRingle, Christian M.Christian M.RingleSarstedt, MarkoMarkoSarstedt2019-12-122019-12-122014-08-22Journal of the Academy of Marketing Science 43 (1): 115-135 (2014-08-22)http://hdl.handle.net/11420/4026Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these approaches do not reliably detect the lack of discriminant validity in common research situations. We therefore propose an alternative approach, based on the multitrait-multimethod matrix, to assess discriminant validity: the heterotrait-monotrait ratio of correlations. We demonstrate its superior performance by means of a Monte Carlo simulation study, in which we compare the new approach to the Fornell-Larcker criterion and the assessment of (partial) cross-loadings. Finally, we provide guidelines on how to handle discriminant validity issues in variance-based structural equation modeling.en0092-070320141115135Cross-loadingsDiscriminant validityFornell-Larcker criterionHeterotrait-monotrait (HTMT) ratio of correlationsMeasurement model assessmentMultitrait-multimethod (MTMM) matrixPartial least squares (PLS)Results evaluationStructural equation modeling (SEM)Allgemeines, WissenschaftJournal Article10.1007/s11747-014-0403-8Journal Article