Data Equivalence in Cross-Cultural Research: A Comparison of Classical Test Theory and Latent Trait Theory Based Approaches

Abstract

Given the increasing importance of international business, cross-cultural research becomes more and more relevant to marketing academics and practitioners. This paper illustrates the difficulties in achieving equivalence when conducting marketing research across borders. It opens with a general typology of equivalence issues in cross-cultural research and, subsequently, focuses specifically on data equivalence. Recent studies either disregard data equivalence at all or they predominantly suggest the use of simultaneous confirmatory factor analysis (CFA) for establishing data equivalence. The Latent Trait Theory (LTT), based on a different measurement paradigm, offers an alternative which promises to overcome many of the problems inherent in CFA. This paper contrasts the advantages and disadvantages of both approaches and illustrates their application by means of a simulated data set. In conclusion, a call is made for the incorporation of equivalence issues in scale development by quantitative as well as qualitative analyses.