MagIC researchers have significantly contributed to Information Systems, particularly in modeling abstract concepts like service quality, equity, human development, and socioeconomic status. These concepts are formative constructs and are better modeled by composites than by common factors. However, the current psychometric toolbox for scale validation, especially confirmatory factor analysis, does not apply to composites.
To address this, MagIC researchers proposed Confirmatory Composite Analysis (CCA) to assess the discrepancy between empirical and model-implied variance-covariance matrices of elementary variables. Our research shows that partial least squares and maximum likelihood can be used as estimators for CCA.
Jorg Henseler, a MagIC integrate member, comprehensively describes CCA in his textbook on composite-based structural equation modeling and introduces synthesis theory as the theoretical basis for composite models. He also develops a novel specification for composites, which was later named the "Henseler-Ogasawara" specification. A refinement of the H-O specification was developed in 2023. Tutorials demonstrate how CCA can be used in business, human development, tourism, and hospitality research.
Publication: Jörg Henseler. (2021). Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables (1st Edition). The Guilford Press.