The role of agent autonomy in using decision support systems at work

Abstract Digitalization of work leads to ever-increasing information processing requirements for employees. Agent-based decision support systems (DSS) can assist employees in information processing tasks and decrease processing requirements. With increasing system capabilities, agency between the user and the system shifts, with high autonomy DSS being able to take over complete information processing tasks. In the present study, we distinguish degrees of DSS autonomy, operationalized by levels of automation (LOA), the delegation of task processing stages, and user control. In two vignette studies, we investigate the effects of DSS autonomy on perceptions of information load reduction, technostress, and user intention as well as the moderating role of technology and job experience. With high DSS autonomy, participants reported higher levels of information load reduction and technostress as well as lower levels of user intention. Job experience was a significant moderator. For high autonomy DSS, participants in the high job experience condition indicated greater information load reducation, lower technostress, and higher user intentions. Results suggest, that while being beneficial for decreasing information load, high DSS autonomy may negatively impact technostress and user intentions. It is suggested that technology and job training may improve user reactions.