Corporate Image Management using Structural Equation Modeling (SEM)
Tokuhisa Suzuki
Abstract
Open-access reader
Tokuhisa Suzuki
Abstract
Open-access reader
The purpose of this paper is to show a method of describing a corporate image fluctuation using factor scores derived from simultaneous analysis in multiple populations with structured means. A confirmatory factor analysis (CFA) model was applied to the independent, random samples collected in survey research conducted once a year since 1988. As a result, a multiple population CFA model, which constrained the model form, the values of factor loadings and the variances-covariance matrix of exogenous variables to be the same in all groups (1988-1997), fitted to the data well.In traditional exploratory factor analysis (EFA) models, it has been difficult to compare factor scores in different years owing to the lack of a fixed factor pattern across groups. However, structural equation modeling (SEM) settled this problem.
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The purpose of this paper is to show a method of describing a corporate image fluctuation using factor scores derived from simultaneous analysis in multiple populations with structured means. A confirmatory factor analysis (CFA) model was applied to the independent, random samples collected in survey research conducted once a year since 1988. As a result, a multiple population CFA model, which constrained the model form, the values of factor loadings and the variances-covariance matrix of exogenous variables to be the same in all groups (1988-1997), fitted to the data well.In traditional exploratory factor analysis (EFA) models, it has been difficult to compare factor scores in different years owing to the lack of a fixed factor pattern across groups. However, structural equation modeling (SEM) settled this problem.
Key concepts: Structural equation modeling, Confirmatory factor analysis, Factor analysis, Exploratory factor analysis, Covariance, Factor (programming language), Econometrics, Mathematics