A meta-analysis of the weight of advice in decision-making

Abstract

The degree to which people take advice, and the factors that influence advice-taking, are of broad interest to laypersons, professionals, and policy-makers. This meta-analysis on 346 effect sizes from 129 independent datasets (N = 17, 296) assessed the weight of advice in the judge-advisor system paradigm, as well as the influence of sample and task characteristics. Information about the advisor(s) that is suggestive of advice quality was the only unique predictor of the overall pooled weight of advice. Individuals adjusted estimates by 32%, 37%, and 48% in response to advisors described in ways that suggest low, neutral, or high quality advice, respectively. This indicates that the benefits of compromise and averaging may be lost if accurate advice is perceived to be low quality, or too much weight is given to inaccurate advice that is perceived to be high quality. When examining the three levels of perceived quality separately, advice-taking was greater for subjective and uncertain estimates, relative to objective estimates, when information about the advisor was neutral in terms of advice quality. Sample characteristics had no effect on advice-taking, thus providing no evidence that age, gender, or individualism influence the weight of advice. The findings contribute to current theoretical debates and provide direction for future research.

Mixed-Effects Regression Weights for Advice Taking and Related Phenomena of Information Sampling and Utilization

“…We will focus on advice taking here but argue that most claims, formulas, and findings can be transferred to other cognitive phenomena with similar structure such as anchoring, hindsight, or persuasion (e.g., Bochner & Insko, 1966; see also Yaniv, 2004a;Yaniv & Milyavsky, 2007) due to conceptual and paradigmatic similarities. Harvey and Fischer's (1997) advice taking index dominated the recent literature (e.g., Hütter & Ache, 2016;Schultze et al, 2015;Soll & Larrick, 2009; see Bailey et al, 2022, for a review). Their index, as formally introduced below, reflects how strongly people adapted their judgment (i.e., the endogenous component) in units of the distance between the initial judgment and the advice (i.e., exogenous components).…”

Conspiracy Believers Underuse Social Information (Like Everyone Else)

“…These percentages are lower than the average meta-analytical evidence regarding how much people update their estimate when exposed to the advice of another participant (i.e., 37%; Bailey et al, 2022).…”

“…Weight of Advice. We measured advice use with the following formula "(Final estimate -initial estimate) / (advice -initial estimate)" (Bailey et al, 2022;Harvey & Fisher, 1997). The measure ranges from 0 (ignoring the advice and sticking to one's first estimate) to 1 (ignoring one's initial estimate and endorsing the advice).…”

“…To test whether conspiracy believers display a generally distrustful mindset, we relied on two behavioral tasks of social information use (by contrast with previous research mostly relying on self-reported measures). In particular, we used the judge-advisor system (JAS) paradigm to measure how much weight conspiracy believers put on their intuitions compared to social information provided in the form of advice (Bailey, 2022). The literature on advice taking has shown that people tend to put more weight on their estimate than on advice, a phenomenon known as 'egocentric discounting' (Bailey, 2022;Morin et al, 2021).…”

“…In particular, we used the judge-advisor system (JAS) paradigm to measure how much weight conspiracy believers put on their intuitions compared to social information provided in the form of advice (Bailey, 2022). The literature on advice taking has shown that people tend to put more weight on their estimate than on advice, a phenomenon known as 'egocentric discounting' (Bailey, 2022;Morin et al, 2021).…”