09:00 - 10:30
Parallel sessions 1
09:00 - 10:30
Room: HSZ - N9
Chair/s:
Maren Mayer, Tobias Rebholz
When making decisions or providing a judgment, individuals often seek and receive advice from others. They may ask a friend whether or not they should spend their holidays in Japan and how much they should plan to budget for such a stay. Advice taking is typically investigated in a judge-advisor system. The judge provides an initial judgment before being introduced to the advice of the advisor. Afterward, the judge provides their final judgment. In this symposium, we combine advances in advice-taking research, outlining new perspectives for the field.

The first contribution demonstrates that individual differences can affect whether and how individuals take advice, and how much these influences have been overlooked. The second contribution presents a meta-analysis on how advice taking varies across different study contexts and designs using a dual hurdle model. The third contribution compares advice taking based on aggregated versus non-aggregated advice from multiple advisors, investigating why aggregated advice is heeded more by judges. The last two contributions focus on advice taking from algorithms. The fourth contribution investigates algorithmic advice demonstrating that without explicit communication advice can shape competition and collaboration among individuals. Finally, the fifth contribution examines algorithmic and hybrid advice combining human and algorithmic advice, demonstrating no algorithm aversion but instead algorithm appreciation.
Submission 420
To Aggregate or Not to Aggregate: Why Judges Heed Aggregated Advice from Multiple Advisors More
SymposiumTalk-03
Presented by: Julia Bengelsdorf
Julia BengelsdorfChristian TreffenstädtStefan Schulz-Hardt
University of Göttingen, Germany
When receiving advice from multiple advisors, judges tend to rely more on aggregated advice (e.g., the mean of several estimates) than on non-aggregated advice (e.g., multiple individual estimates). The present work investigates why aggregated advice is heeded more strongly in judgment processes. Study 1 (N = 280) aimed to replicate the effect of advice presentation format and tested a proposed explanatory mechanism. We hypothesized that judges underestimate the diversity of advisors' opinions when receiving aggregated advice, which leads them to perceive aggregated advice as a stronger signal for adjustment. In a between-subjects design, participants received either aggregated or non-aggregated advice and, orthogonally, information about the actual range of advisors' estimates. Results replicated the higher utilization of aggregated advice and confirmed that the effect was attenuated when the range of opinions was explicitly displayed. Study 2 (N = 284) examined this proposed mechanism directly by testing whether the underestimation of advisors' range of opinions mediates the increased use of aggregated advice. In a within-subjects design, participants received both aggregated and non-aggregated advice across several numerical judgment tasks. They additionally estimated the range of advisors' opinions after aggregated trials. Analyses confirmed higher advice taking and a significant underestimation of the actual range for aggregated advice. Together, these studies advance our understanding of cognitive processes in advice utilization and highlight how the perceived diversity of advisors' opinions shapes the integration of multiple social inputs in judgment and decision-making.