Research Interests and Areas of Expertise

This figure shows a schematic overview of my research identity and agenda. It centers on behavioral experimentation (see the examples below) and on developing and applying advanced quantitative methods (e.g., Rebholz, Biella, et al., 2024) to investigate human judgment and decision-making (JDM) processes and belief updating. The specific phenomena that interest me most cluster into four pillars: informational and social influence from others (e.g., advice taking; Rebholz & Hütter, 2022); the sequential sampling and utilization of external evidence (e.g., Bayesian updating; Rebholz et al., 2023); people’s adaptiveness or rationality of belief updating in these contexts (e.g., heuristics and biases; Rebholz, Groß, et al., 2025; but also science communication; Schreiner et al., 2025, in press); and the implications of these phenomena for human-computer interaction (e.g., algorithm aversion vs. appreciation; Rebholz, conditionally recommended; Rebholz, Koop, et al., 2024; Rebholz, Uphoff, et al., 2025). This last pillar primarily concerns augmented JDM settings, where human decision-makers retain responsibility for the final decision but receive input from AI and other decision-support systems before or during the judgment process.