Groups Weight Outside Information Less Than Individuals Do, Although They Shouldn’t

  title={Groups Weight Outside Information Less Than Individuals Do, Although They Shouldn’t},
  author={Julia A. Minson and Jennifer S. Mueller},
  journal={Psychological Science},
  pages={1373 - 1374}
By suggesting that dyads should give less weight to outside advice than individuals should, Schultze, Mojzisch, and Schulz-Hardt (2013) raise important questions re garding whether and when collaborative judgment outperforms individual judgment. The authors argue that, normatively, the judgments of dyads should be weighted twice as heavily as those of individuals because the former are made up of two independent inputs, whereas the latter are a product of solitary contemplation. The problem… 

Why dyads heed advice less than individuals do

Following up on a recent debate, we examined advice taking in dyads compared to individuals in a set of three studies (total N = 303 dyads and 194 individuals). Our first aim was to test the

The Contingent Wisdom of Dyads: When Discussion Enhances vs. Undermines the Accuracy of Collaborative Judgments

We evaluate the effect of discussion on the accuracy of collaborative judgments. In contrast to prior research, we show that discussion can either aid or impede accuracy relative to the averaging of

The anchoring-bias in groups

Individuals vs groups: Advice-taking in decision making

: External advice is often considered as an effective approach to improve the quality of decision outcomes. However, there is a significant difference in advice-taking performance between individuals



Groups Weight Outside Information Less Than Individuals Do Because They Should

An overlooked gem is revealed in Minson and Mueller’s (2012) study, namely, an asymmetry in assessing the informational value of aggregated judgments: Whereas judges seem to be sensitive to the increased reliability of their own aggregated initial estimates, they ignore the same increased reliability when it comes to aggregated advice.

A social information processing approach to job attitudes and task design.

The social information processing perspective emphasizes the effects of context and the consequences of past choices, rather than individual predispositions and rational decision-making processes, to explain job attitudes.

The statistical analysis of data from small groups.

The authors strongly urge that the analysis model of data from small-group studies should mirror the psychological processes that generate those data.

Using Hierarchical Linear Modeling to Analyze Grouped Data

This article discusses how to use a random coefficient modeling technique known as hierarchical linear modeling to analyze data collected within groups. The article describes how to use this

Hierarchical Linear Models: Applications and Data Analysis Methods

This chapter discusses Hierarchical Linear Models in Applications, Applications in Organizational Research, and Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known.

Using hierarchical linear modeling to analyze grouped data.

The cost of collaboration: Why joint decision making exacerbates rejection

  • 2012

The cost of collaboration : Why joint decision making exacerbates rejection of outside information

  • Psychological Science
  • 2012