Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences
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Individuals frequently discount recommendations that contradict their prior judgment, even when those recommendations are objectively accurate.
“Individuals frequently discount recommendations that contradict their prior judgment, even when those recommendations are objectively accurate (Bonaccio and Dalal 2006).”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Bonaccio and Dalal 2006
Even when external advice is objectively accurate, decision makers frequently maintain their original judgment, especially when that advice contradicts their prior beliefs or professional intuition.
“Even when external advice is objectively accurate, decision makers frequently maintain their original judgment, especially when that advice contradicts their prior beliefs or professional intuition.”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Bonaccio and Dalal 2006
This finding differs from the expectation that experienced judges may be more resistant to advice because they can generate more internal arguments supporting their initial view.
“This finding differs from the expectation that experienced judges may be more resistant to advice because they can generate more internal arguments supporting their initial view (Yaniv 2004;Bonaccio and Dalal 2006).”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Bonaccio and Dalal 2006
Expertise may amplify discounting behavior; individuals who perceive themselves as highly competent generally show stronger resistance to external advice.
“Expertise may further amplify this discounting behavior.Individuals who perceive themselves as highly competent generally show stronger resistance to external advice (Bonaccio and Dalal 2006).”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Bonaccio and Dalal 2006
Convergent advice from multiple sources increases perceived validity and strengthens confidence in external recommendations.
“Research indicates that convergent advice from multiple sources increases perceived validity and strengthens confidence in external recommendations (Bonaccio and Dalal 2006;Soll et al. 2022).”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Bonaccio and Dalal 2006
Disagreement among advisors reduces trust and decreases the weight assigned to external inputs.
“Disagreement among advisors reduces trust and decreases the weight assigned to external inputs (Bonaccio and Dalal 2006;Wanzel et al. 2017;Yaniv et al. 2009).”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Bonaccio and Dalal 2006
When some information is missing, decision-makers must rely on estimates, and humans tend to err in these estimates, often overestimating their chance of being correct, leading to ego bias.
“Unfortunately, humans tend to err in these estimates, often overestimating their chance of being correct, leading to an implicit, unwarranted preference for their own opinions, an ego bias [52][53][54][55][56][57] .”
From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [53]
Trust was measured as CADx prediction utilization, defined as an endoscopist's willingness to follow the CADx prediction when the endoscopist initially disagreed with the CADx prediction.
“Trust was measured as CADx prediction utilization, defined as an endoscopist's willingness to follow the CADx prediction when the endoscopist initially disagreed with the CADx prediction 9,10”
From Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction (2024) · cites this paper as [10]
Unsolicited advice can be received poorly and considered intrusive, whereas explicitly solicited advice can be considered cooperative and helpful.
“Unsolicited advice can be received poorly and considered intrusive, whereas explicitly solicited advice can be considered cooperative and helpful.10”
From Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction (2024) · cites this paper as [10]
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“For example, people often give less weight to other people’s advice than they should when left to their own devices (see Bonaccio & Dalal, 2006); however, it is possible that people will commit to using another person’s advice in a constrained manner.”
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Human Decision Making and Recommender Systems
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The risk of algorithm transparency: How algorithm complexity drives the effects on the use of advice
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Social information use and social information waste
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- Authors
- Bonaccio, S., & Dalal, R. S.
- Affiliations
- Purdue University West Lafayette (US)
- Corresponding author
- Bonaccio, Silvia
- Venue
- Organizational Behavior and Human Decision Processes
- Publisher
- Elsevier BV
- Published
- 2006-11
- Volume
- 101
- Issue
- 2
- Pages
- 127-151
- ISSN
- 0749-5978 (ISSN-L)
- OpenAlex
- W2148237550
- Cited by
- 1,011
- References
- 171
- Citations by year
- 2026: 91 · 2025: 95 · 2024: 71 · 2023: 66 · 2022: 67 · 2021: 72 · 2020: 59 · 2019: 66 · 2018: 54 · 2017: 58 · 2016: 46 · 2015: 53 · 2014: 41 · 2013: 34 · 2012: 54
- FWCI
- 6.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Organizational Behavior and Human Decision Processes (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Leadership, Behavior, and Decision-Making Studies
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Keywords
- advice taking, advice-giving, decision-making, decision accuracy, confidence, organizational behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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