A new criterion for assessing discriminant validity in variance-based structural equation modeling

Jörg Henseler, Christian M. Ringle, Marko Sarstedt

Research output: Contribution to journalArticlepeer-review

6418 Citations (Scopus)
200 Downloads (Pure)


Discriminant 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.

Original languageEnglish
Pages (from-to)115-135
Number of pages21
JournalJournal Of The Academy Of Marketing Science
Issue number1
Publication statusPublished - 1 Jan 2014


  • Cross-loadings
  • Discriminant validity
  • Fornell-Larcker criterion
  • Heterotrait-monotrait (HTMT) ratio of correlations
  • Measurement model assessment
  • Multitrait-multimethod (MTMM) matrix
  • Partial least squares (PLS)
  • Results evaluation
  • Structural equation modeling (SEM)


Dive into the research topics of 'A new criterion for assessing discriminant validity in variance-based structural equation modeling'. Together they form a unique fingerprint.

Cite this