Understanding the dynamics of users belief in software application adoption
Research has identified numerous factors that influence initial technology adoption decisions. However, extant studies consider beliefs to be static rather than dynamic over the adoption time-span. Various models have been employed to identify adoption behavior, pre- and post-adoption, however, there is little research on the dynamics of users belief structures over time and the inter-relationships among them. This study aims to investigate the dynamic nature of users beliefs and the relationships among their dynamics, i.e., rates of change. We test our research model based on data obtained at three time-windows using a parallel-growth process model. The results reveal that self-efficacy, usefulness and intention to use are likely to be dynamic, and increase with time. The rate of change in self-efficacy influences the rate of change in usefulness, which in turn affects the rate of change in intention to use. This study theoretically contributes to expanding the extant cross-sectional TAM research to include time-phased TAM studies, and highlights the role of self-efficacy as an important determinant of the dynamics.
parallel-growth process model technology acceptance model latent growth curve modeling intention to adopt a technology