Managing Complexity through Consensus Mapping: Technology for the Structuring of Group Decisions

1985 ◽  
Vol 10 (3) ◽  
pp. 587 ◽  
Author(s):  
Stuart Hart ◽  
Mark Boroush ◽  
Gordon Enk ◽  
William Hornick
Keyword(s):  
Group Decisions ◽  
Mapping Technology ◽  
Consensus Mapping ◽  
Managing Complexity

Managing Complexity Through Consensus Mapping: Technology for the Structuring of Group Decisions

1985 ◽  
Vol 10 (3) ◽  
pp. 587-600 ◽  
Author(s):  
Stuart Hart ◽  
Mark Boroush ◽  
Gordon Enk ◽  
William Hornick
Keyword(s):  
Group Decisions ◽  
Mapping Technology ◽  
Consensus Mapping ◽  
Managing Complexity

Frames in Context: Comparing Technology-Mediated and Face-to-Face Group Decisions

2008 ◽  
Author(s):  
Michel Handgraaf ◽  
Philip Schuette ◽  
Nicole Yoskowitz ◽  
Elke Weber ◽  
Kerry Milch ◽  
...  
Keyword(s):  
Group Decisions ◽  
Face To Face

Millennials, learning, and development: Managing complexity avoidance and narcissism.

2017 ◽  
Vol 20 (3) ◽  
pp. 176-193 ◽  
Author(s):  
Robert C. Giambatista ◽  
J. Duane Hoover ◽  
Lori Tribble
Keyword(s):  
Learning And Development ◽  
Managing Complexity

scholarly journals Managing complexity and uncertainty in agricultural innovation through adaptive project design and implementation

2020 ◽  
pp. 1-16
Author(s):  
Jeffery W. Bentley ◽  
Diego Naziri ◽  
Gordon Prain ◽  
Enoch Kikulwe ◽  
Sarah Mayanja ◽  
...  
Keyword(s):  
Project Design ◽  
Agricultural Innovation ◽  
Design And Implementation ◽  
Managing Complexity

scholarly journals Group decisions based on confidence weighted majority voting

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Sascha Meyen ◽  
Dorothee M. B. Sigg ◽  
Ulrike von Luxburg ◽  
Volker H. Franz
Keyword(s):  
Cognitive Modeling ◽  
Group Discussion ◽  
Group Processes ◽  
Majority Voting ◽  
Group Decisions ◽  
Optimal Method ◽  
Weighted Majority ◽  
Real Group ◽  
Lower Accuracy ◽  
Weighted Majority Voting

Abstract Background It has repeatedly been reported that, when making decisions under uncertainty, groups outperform individuals. Real groups are often replaced by simulated groups: Instead of performing an actual group discussion, individual responses are aggregated by a numerical computation. While studies have typically used unweighted majority voting (MV) for this aggregation, the theoretically optimal method is confidence weighted majority voting (CWMV)—if independent and accurate confidence ratings from the individual group members are available. To determine which simulations (MV vs. CWMV) reflect real group processes better, we applied formal cognitive modeling and compared simulated group responses to real group responses. Results Simulated group decisions based on CWMV matched the accuracy of real group decisions, while simulated group decisions based on MV showed lower accuracy. CWMV predicted the confidence that groups put into their group decisions well. However, real groups treated individual votes to some extent more equally weighted than suggested by CWMV. Additionally, real groups tend to put lower confidence into their decisions compared to CWMV simulations. Conclusion Our results highlight the importance of taking individual confidences into account when simulating group decisions: We found that real groups can aggregate individual confidences in a way that matches statistical aggregations given by CWMV to some extent. This implies that research using simulated group decisions should use CWMV instead of MV as a benchmark to compare real groups to.

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