This paper addresses the issue of discriminant validity assessment in variance-based structural equation modeling (SEM), particularly in the context of partial least squares (PLS). Traditional approaches, such as the Fornell-Larcker criterion and cross-loadings, are found to be insufficiently sensitive in detecting lack of discriminant validity. To overcome this limitation, the authors propose the heterotrait-monotrait ratio of correlations (HTMT) as an alternative method. The HTMT is derived from the multitrait-multimethod matrix and is designed to assess the empirical uniqueness of constructs. The paper demonstrates the superior performance of HTMT through a Monte Carlo simulation study, which compares its sensitivity and specificity with traditional methods. The results show that HTMT, especially with a lower threshold (HTMT85), is highly effective in identifying lack of discriminant validity. The paper also provides guidelines for researchers on how to apply HTMT and handle discriminant validity issues in their studies.This paper addresses the issue of discriminant validity assessment in variance-based structural equation modeling (SEM), particularly in the context of partial least squares (PLS). Traditional approaches, such as the Fornell-Larcker criterion and cross-loadings, are found to be insufficiently sensitive in detecting lack of discriminant validity. To overcome this limitation, the authors propose the heterotrait-monotrait ratio of correlations (HTMT) as an alternative method. The HTMT is derived from the multitrait-multimethod matrix and is designed to assess the empirical uniqueness of constructs. The paper demonstrates the superior performance of HTMT through a Monte Carlo simulation study, which compares its sensitivity and specificity with traditional methods. The results show that HTMT, especially with a lower threshold (HTMT85), is highly effective in identifying lack of discriminant validity. The paper also provides guidelines for researchers on how to apply HTMT and handle discriminant validity issues in their studies.