Past studies suggested that decision support systems (DSS) must be an “enabling” system aiming to enhance users’ capabilities and to leverage their skills and intelligence. This suggests that users be the center of DSS and users’ characteristics be an important factor of explaining their DSS acceptance behavior. Since DSS are aimed to work in semi-structured and unstructured task environment, perceived task complexity can be used to explain users’ willingness to accept DSS. Further, several studies also used decision models for investigating users’ DSS acceptance behavior. We argue that nature of DSS (based on their underlying decision models) and its interaction with individual differences also play important roles on users’ DSS acceptance behavior. With the conjecture that users’ DSS acceptance behavior directly affects the DSS usage and DSS success, our research question focuses on how do individual differences influence users’ DSS acceptance behavior with consideration of task characteristics and nature of the DSS. The contribution of this paper is multifold. First, we extend the existing understanding of effects of individual differences on users’ DSS acceptance behavior. Second, we extend two major measurements of cognitive styles (GEFT - Group Embedded Figures Test and MBTI - Myers-Briggs Type Indicator) for individual differences in the context of DSS. Third, we investigate multiple task complexities and multiple DSS models. Hypotheses are developed and will be tested with an experiment of 300 plus subjects.
Liu, Yucong and Chen, Andrew N.K., "The Effect of Individual Differences, Tasks, and Decision Models on User Acceptance of Decision Support Systems" (2008). AMCIS 2008 Proceedings. 357.