ORGANIZATIONAL BEHAVIOR AND HUMAN DECISION PROCESSES www.elsevier.com/locate/obhdp Receiving other peopleÕs advice: Influence and benefit q
By Ilan Yaniv
632 citations recorded by the source corpus.
Subfields: Economics and Econometrics, General Decision Sciences, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Francesca Gino
- Jack B. Soll
- Ben Green
- Yiling Chen
- Richard P. Larrick
- Reeshad S. Dalal
- Silvia Bonaccio
- Maxim Milyavsky
In General Decision Sciences
- Francesca Gino
- Richard P. Larrick
- Jack B. Soll
- L. Tost
- Naomi B Rothman
- E. W. Morrison
- Albert E. Mannes
- Kelly E. See
In Management Science and Operations Research
- Francesca Gino
- Jack B. Soll
- Richard P. Larrick
- Albert E. Mannes
- Ben Green
- Yiling Chen
- Reeshad S. Dalal
- Silvia Bonaccio
Citations in the corpus
- Asking for Help: Survey and Experimental Evidence on Financial Advice and Behavior Change (2010, background): “Indeed, a robust finding is that individuals who receive advice by default tend to significantly discount it (Bonaccio and Dalal, 2006; Yaniv, 2004a; Yaniv, 2004b; Yaniv and Kleinberger, 2000).”
- Too arrogant for their own good? Why and when narcissists dismiss advice (2015, methodology): “After making an initial estimate and receiving advice, individuals tend to favor their own judgments (Bonaccio & Dalal, 2006; Gino & Moore, 2007; Harvey & Fischer, 1997; Yaniv, 2004).”
- The social psychology of the wisdom of crowds. (2012, background): “Yaniv and his colleagues (Yaniv, 2004; Yaniv & Kleinberger, 2000) proposed that people weight their own answers more highly because they know the reasons for their own judgments but not those behind the judgments of others.”
- The Principles and Limits of Algorithm-in-the-Loop Decision Making (2019, background): “This is akin to the “weight of advice” metric that has been used in other contexts to measure how much people alter their decisions when presented with advice [57, 75].”
- Power, competitiveness, and advice taking: Why the powerful don’t listen (2012, methodology): “Individuals commonly weigh advice received from experienced and knowledgeable advisors more heavily than advice received from advisors with less experience or expertise (Feng & MacGeorge, 2006; Goldsmith & Fitch, 1997; Harvey & Fischer, 1997; Sniezek et al., 2004; Yaniv, 2004; Yaniv & Kleinberger, 2”
- Intuitions About Combining Opinions: Misappreciation of the Averaging Principle (2006, background): “by 10% with their intuitive revision strategies (see also Harvey & Fischer, 1997; Yaniv, 2004 ), they”
- The ambivalent mind can be a wise mind: Emotional ambivalence increases judgment accuracy (2013, background): “Ignoring or heavily discounting estimatesmade by others, however, reduces this fundamental benefit of averaging, resulting in lower accuracy (Mannes, 2009; Soll & Larrick, 2009; Yaniv, 2004).”
- Decision Difficulty in the Age of Consumer Empowerment (2014, background): “When consumers are less knowledgeable, they place greater weight on advice (Yaniv, 2004) and utilize more simplifying heuristics when faced with difficult decisions (Chernev, 2008).”
- Blind in one eye: How psychological ownership of ideas affects the types of suggestions people adopt (2012, background): “Thus, being invested in one’s opinions or judgments may cause people to shun others’ advice (Yaniv, 2004), especially in cases in which advice runs counter to one’s initial inclinations and therefore has the potential to trigger negative affective responses such as anger.”
- Disparate Interactions: An Algorithm-in-the-Loop Analysis of Fairness in Risk Assessments (2019, methodology): “4 This measure of in � uence is similar to the “weight of advice” metric that has been used to measure how much people alter their decisions when presented with advice [48, 65].”
- Using advice from multiple sources to revise and improve judgments (2007, methodology): “For example, in a study involving estimation, participants reduced their initial error by about 20% by considering just one opinion of a fellow student drawn at random from a pool (Yaniv, 2004b).”
- The impact of information from similar or different advisors on judgment (2009, methodology): “In our study , this was rare ( 80 out of 1104 , about 7% of the cases ) ; following previous research these observations were dropped ( Yaniv , 2004a ; Yaniv , 2004b ; Gino & Moore , 2007 ) .”