Elaborating or Aggregating? The Joint Effects of Group Decision-Making Structure and Systematic Errors on the Value of Group Interactions

2018 ◽  
Author(s):  
Steffen Keck ◽  
Wenjie Tang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Systematic Errors ◽  
Group Interactions ◽  
Joint Effects

Facilitating Idea Generation and Decision-Making with Concept Maps

2004 ◽  
Vol 03 (02) ◽  
pp. 179-192
Author(s):  
John W. Coffey
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Concept Mapping ◽  
Group Decision Making ◽  
Concept Maps ◽  
Group Decision ◽  
Idea Generation ◽  
Methodological Issues ◽  
Group Interactions ◽  
The Creation

This paper contains a description of the creation of Concept Maps in facilitated sessions to promote idea generation and group decision-making. A number of issues pertain to facilitated Concept Mapping, including the number of facilitators, the optimal or manageable size of groups, the sorts of group interactions that are encountered and their impacts on the proceedings, and the sorts of outcomes that can be expected. This article describes these basic issues as well as attributes, concerns, and skills required of facilitators. It presents two case studies illustrating methodological issues pertaining to the facilitation process and the sorts of outcomes that can be achieved.

scholarly journals Modeling other minds: Bayesian inference explains human choices in group decision-making

2019 ◽  
Vol 5 (11) ◽  
pp. eaax8783 ◽  
Author(s):  
Koosha Khalvati ◽  
Seongmin A. Park ◽  
Saghar Mirbagheri ◽  
Remi Philippe ◽  
Mariateresa Sestito ◽  
...  
Keyword(s):  
Decision Making ◽  
Bayesian Inference ◽  
Group Decision Making ◽  
Group Decision ◽  
Other Minds ◽  
Group Interactions ◽  
Markov Decision ◽  
The Mind ◽  
Partially Observable ◽  
Large Groups

To make decisions in a social context, humans have to predict the behavior of others, an ability that is thought to rely on having a model of other minds known as “theory of mind.” Such a model becomes especially complex when the number of people one simultaneously interacts with is large and actions are anonymous. Here, we present results from a group decision-making task known as the volunteer’s dilemma and demonstrate that a Bayesian model based on partially observable Markov decision processes outperforms existing models in quantitatively predicting human behavior and outcomes of group interactions. Our results suggest that in decision-making tasks involving large groups with anonymous members, humans use Bayesian inference to model the “mind of the group,” making predictions of others’ decisions while also simulating the effects of their own actions on the group’s dynamics in the future.

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