Do Maximizers Predict Better than Satisficers
Bibliographic Data
| ID | 12166168 |
|---|---|
| Authors | Kriti Jain (0000-0002-0639-1036, INSEAD Singapore, corresponding author), J Neil Bearden (INSEAD Singapore), Allan Filipowicz (INSEAD Singapore) |
| Year | 2011 |
| Volume | 26 |
| Issue | 1 |
| Pages | 41-50 |
| Publication date | 2011-10-11 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Behavioral Decision Making (JOURNAL) |
| Journal identifiers | ISSN: 0894-3257 • E-ISSN: 1099-0771 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/bdm.763 |
| OpenAlex | W2332411514 |
| Language | EN |
| Citations received | 7 |
| References cited | 36 |
We examine the relationship between maximizing (i.e., seeking the best) versus satisficing (i.e., seeking the good enough) tendencies and forecasting ability in a real‐world prediction task: forecasting the outcomes of the 2010 FIFA World Cup. In Studies 1 and 2, participants gave probabilistic forecasts for the outcomes of the tournament and completed a measure of maximizing tendencies. We found that although maximizers expected themselves to outperform others much more than satisficers, they actually forecasted more poorly. Hence, on net, they were more overconfident about their relative performance. Decompositional analyses of overall accuracy revealed that differences in forecasting abilities were primarily driven by maximizers' tendency to give more noisy estimates. In Study 3, participants played a betting task where they could choose between safe and uncertain gambles linked to World Cup outcomes. Again, maximizers did more poorly and earned less, because of greater noise in their choice‐based responses. Copyright © 2011 John Wiley & Sons, Ltd
Econometrics · Economics · Expected utility hypothesis · Mathematical economics · Microeconomics · Probabilistic logic · Satisficing · Subjective expected utility · Task (project management · Tournament · Computer Science · Decision-Making and Behavioral Economics · Forecasting Techniques and Applications · Mathematics · Psychology · Sports Analytics and Performance · Artificial Intelligence
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| Unique citing works | 7 |
|---|---|
| Citations per year | 0.54 |
| Citation span | 2013 - 2026 (14) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |