Evaluating the effects of taskindividualtechnology fit in multi-DSS models context: A two-phase view
We investigate the effects of individual difference with the framework of taskindividualtechnology fit under a multi-DSS models context using a two-phase view. Our research question is: in addition to tasktechnology fit, does individualtechnology fit or individualtask fit matter in users' attitude and performance in the multi-tasks and multi-DSS models context? We first divide the concept of taskindividualtechnology fit into three dimensions  tasktechnology fit (TTF), individualtechnology fit (ITeF), and taskindividual fit (TaIF)  so that we can explore mechanisms and effects of interaction among these factors (i.e., task, individual difference, and technology). We then propose a two-phase view of taskindividualtechnology fit (i.e., pre-paradigm phase and paradigm phase) based on Kuhn's concept of revolutionary science. We conducted a controlled laboratory experiment with multiple DSS models and decision-making tasks to test our hypotheses. Results confirmed our arguments that in the paradigm phase, the effects of individual differences on user attitudes toward DSS models can be ignored and that in the pre-paradigm phases individual differences play an important role. In addition, we found that effects of individual difference can be a two-blade sword: ITeF can enhance but TaIF can diminish users' attitude to DSS model (i.e., technology). Our results also suggested that different dimensions of fit may affect performance directly or indirectly.
taskindividualtechnology fit dss dss models two-phase view cognitive style task structuredness