Technological advancements have enabled the emergence of increasingly intelligent and autonomous support of private decision-making. Automated financial investing by robo-advisors is exemplary of this development. For the user to benefit from digital investment management, robo-advisors must reflect user preferences. Important robo-advisor characteristics are their level of automation, the degree of control they allow customers, and their transparency. However, suitable configurations along the characteristics have not yet been determined. Specifically, users value high financial performance while desiring control over investments, partly caused by cognitive bias. In case of algorithmic superiority to human decisions in this context, a performance-control dilemma occurs. In this study, we conduct a choice-based conjoint analysis to derive user preferences of robo-advisor configurations and investigate the potential of transparency to alleviate the performance-control dilemma. Results suggest that users prefer hybrid automation and high levels of control and transparency, supporting the dilemma’s occurrence. Transparency is confirmed to be a potential mitigator of the dilemma only for some attribute levels tested. These findings enhance our understanding of user preferences in highly autonomous decision support in the presence of cognitive bias. We provide implications for theory and practice by identifying the performance-control dilemma and suggesting transparency as a mitigator.
Rühr, Alexander, "Robo-Advisor Configuration: An Investigation of User Preferences and the Performance-Control Dilemma" (2020). In Proceedings of the 28th European Conference on Information Systems (ECIS), An Online AIS Conference, June 15-17, 2020.
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