TY - JOUR
T1 - The role of agent autonomy in using decision support systems at work
AU - Ulfert, Anna Sophie
AU - Antoni, Conny H.
AU - Ellwart, Thomas
N1 - Funding Information:
We thank Katharina Schimek and Laura Schout for their contributions to the development of the vignette scenarios and the data collection as part of their master's theses at the University of Trier.
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
KW - Autonomy
KW - Decision support system
KW - Information load
KW - Technology acceptance
KW - Technostress
UR - http://www.scopus.com/inward/record.url?scp=85113372219&partnerID=8YFLogxK
U2 - 10.1016/j.chb.2021.106987
DO - 10.1016/j.chb.2021.106987
M3 - Article
AN - SCOPUS:85113372219
VL - 126
JO - Computers in Human Behavior
JF - Computers in Human Behavior
SN - 0747-5632
M1 - 106987
ER -