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Ambiguity and Conflict Aversion When Uncertainty Is in the Outcomes
Michael Smithson1, Daniel Priest1, Yiyun Shou1
1Research School of Psychology, The Australian National University, Canberra, ACT, Australia.
Frontiers in Psychology
|April 16, 2019
Summary
Ambiguity aversion persists even when outcomes are unclear, challenging prior research. This study reveals that judges exhibit similar aversion to ambiguity and conflict, driven by pessimistic forecasts rather than information neglect.
Area of Science:
- Decision-making research
- Cognitive psychology
- Behavioral economics
Background:
- Prior research on ambiguity effects often overlooks ambiguity in outcomes.
- Existing operationalizations may not fully capture real-world decision-making complexities.
Purpose of the Study:
- To investigate ambiguity aversion when judges encounter ambiguity in sampled outcomes.
- To examine the impact of outcome ambiguity and conflicting information on decision-making.
- To explore the psychological mechanisms underlying ambiguity and conflict aversion.
Main Methods:
- Two studies were conducted using hypothetical scenarios without participant incentives.
- Judges were presented with sampled outcomes, either all at once or sequentially.
- Ambiguity aversion and conflict aversion were measured and compared across different conditions.
Main Results:
- Ambiguity aversion was found to be significant, even when outcome ambiguity was present.
- Conflict aversion also remained robust, unaffected by the presentation format (simultaneous vs. sequential).
- Pessimistic outcome forecasts, stemming from uncertainty about comparative desirability, partially explained ambiguity and conflict aversion.
Conclusions:
- The operationalization of ambiguity in decision-making research needs to account for outcome ambiguity.
- Ambiguity and conflict aversion are not simply due to ignoring uncertain information but are influenced by cognitive biases like pessimism.
- Understanding judges' uncertainty in comparing ambiguous versus risky alternatives is crucial for future research.
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