A Multitrait-Multimethod Analysis of the End User Computing Satisfaction and Computer Self-Efficacy Instruments

Abstract

Researchers are employing confirmatory factor analysis (CFA) with multitrait-multimethod (MTMM) matrices to estimate parameters representing trait, method, and error variance, as well as parameters representing the correlations among traits (or factors). This study utilizes CFA with MTMM matrices to assess the convergent validity, discriminant validity, and the presence and effects of method variance in the end-user computing satisfaction instrument (EUCSI) and the computer self-efficacy instrument (CSE). The results of the study indicate that, in these samples, the two instruments demonstrate adequate convergent and discriminant validity, but that method variance is present and accounts for a large proportion of the variance in both models. Further, the proposed factor structure of the EUCSI appears to be unstable as a result of the effects of multiple methods, while the proposed factor structure of the CSE remains stable in the presence of the methods.