Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence

In cross-national marketing research, the question whether measurement accu racy reliability, and validity are achieved across samples traditionally ha s hampered research efforts. Measurement equivalence across samples has par ticularly perplexed researchers in their efforts to evaluate responses rega rding latent variables. Recently, multiple-group structural equations model ing has been suggested as a reliable method for determining measurement equ ivalence. To date, however, the use of this approach has remained limited. In this study, the authors apply multiple-group structural equations modeli ng to assess measurement equivalence in three distinct constructs across U. S. and Korean samples on data derived from cross-cultural advertising resea rch. The authors propose an extension of this method using the measurement error covariance matrices, which will enable researchers to evaluate measur ement reliability across samples better and to attempt to disentangle cultu ral differences in instrument usage from measurement-related differences. T he authors evaluate the results and discuss the findings, as well as outlin e the implications and limitations of this method for further research.