Robo-Advisor Configuration: An Investigation of User Preferences and the Performance-Control Dilemma
2020 | European Conference On Information Systems | Citations: 0
Authors: Rühr, Alexander
Abstract: Technological advancements have enabled the emergence of increasingly intellige ...
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Abstract: 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.
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Abstract: Computer-based decision support systems have been proposed as a tool to improve ...
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Abstract: Computer-based decision support systems have been proposed as a tool to improve the decision-making of less-experienced personnel by reducing the information processing demands necessary for decision-making. This study investigated the utility of three decision support system interfaces that differed in their capacity for reduced processing. The participants comprised experienced and less-experienced Fireground Incident Commanders who used the decision support system interfaces to identify the most appropriate entry point to extract a victim from a simulated burning building. The results revealed that reduced processing interfaces enabled less-experienced participants to acquire information using a process equivalent to their more experienced counterparts. However, this process did not result in improvements in the accuracy of the decision-making process. Indeed, the accuracy of experienced participants' decisions was consistently greater than the less-experienced participants, irrespective of the decision support system interface. It was concluded that the success of reduced processing decision support systems amongst less-experienced operators is significantly dependent upon their understanding of the relative value of key features associated with the decision-making process.
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