Abstract
An enduring debate in decision-making and social cognition concerns the algorithm governing the formation of intuitive preferences and attitudes. Here we contrast 2 principles that are considered central to such judgments: averaging versus summation. Participants in 4 experiments were prompted to rely on their intuition when rating the Hall of Fame eligibility of basketball players, or their liking of athletes, lecturers or slot-machines, on the basis of rapid numerical sequences that represent performances, class feedback, or rewards. Experiment 1 showed that participants are sensitive to the sequences' averages, and prefer alternatives with high averages over those with high sums. Experiment 2 replicated these findings, and further showed that in a comparison between several models such as averaging, summation and the Peak-End heuristic, averaging type models account best for participants' preferences. Experiment 3 indicated that these evaluations are mediated by automatic/intuitive processes. Based on computational considerations we propose that the critical variable, determining whether preferences are more sensitive to sums or to averages, is the presentation and evaluation format: one by one versus grouped. This prediction is confirmed in Experiment 4.
Original language | English |
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Journal | Decision |
DOIs | |
State | Published - 2019 |
Keywords
- Averaging
- Evaluation format
- Intuitive preferences
- Peak-End heuristic
- Summation
All Science Journal Classification (ASJC) codes
- Social Psychology
- Neuropsychology and Physiological Psychology
- Applied Psychology
- Statistics, Probability and Uncertainty