Group performance as a function of group type and group composition

1976 ◽  
Vol 6 (3) ◽  
pp. 381-385 ◽  
Author(s):  
Suresh Kanekar ◽  
Priya Neelakantan
Keyword(s):  
Group Composition ◽  
Group Performance ◽  
Group Type

scholarly journals Multi-trait diversity of online groups improves geo-political forecasting accuracy as a function of group size

2020 ◽  
Author(s):  
Niccolo Pescetelli ◽  
Alexis Rutherford ◽  
Iyad Rahwan
Keyword(s):  
Group Size ◽  
Group Composition ◽  
Time Pressure ◽  
Group Performance ◽  
Causal Link ◽  
Online Groups ◽  
Consensus Forecasts ◽  
Political Events ◽  
Digital Environments ◽  
And Performance

Many modern interactions happen in a digital space, where automated recommendations and homophily can shape the composition of groups interacting together and the knowledge that groups are able to tap into when operating online. Digital interactions are also characterized by different scales, from small interest groups to large online communities. Here, we manipulate the composition of online groups based on a large multi-trait profiling space to explore the causal link between group composition and performance as a function of group size. We asked volunteers to search information online under time pressure and measured individual and group performance in forecasting real geo-political events. Our manipulation affected the correlation of forecasts made by people after online searches. Group composition interacts with group size so that diversity benefits individual and group performance proportionally to group size. Aggregating opinions of modular crowds composed of small independent groups achieved better results than using non-modular ones. Finally, we show differences existing among groups in terms of disagreement, speed to convergence to consensus forecasts and within-group variability in performance. The present work sheds light on the mechanisms underlying effective collaboration in digital environments.

Actual and Perceived Group Performance as a Function of Group Composition: The Moderating Role of the Type A and B Behavior Patterns1

1989 ◽  
Vol 19 (2) ◽  
pp. 140-158 ◽  
Author(s):  
Michael J Strube ◽  
N. Rand Keller ◽  
Julie Oxenberg ◽  
Daphna Lapidot
Keyword(s):  
Group Composition ◽  
Group Performance ◽  
Type A ◽  
Moderating Role

NOMINAL AND REAL GROUP PERFORMANCE IN RELATION TO MANIFEST ANXIETY AND INDUCED STRESS

1975 ◽  
Vol 3 (2) ◽  
pp. 197-204 ◽  
Author(s):  
Suresh Kanekar ◽  
Priya Neelakantan ◽  
Pareen K. Lalkaka
Keyword(s):  
College Students ◽  
Group Performance ◽  
Multiple Solution ◽  
Female College Students ◽  
Female College ◽  
Group Type ◽  
Induced Stress ◽  
Real Group ◽  
Nominal Groups ◽  
Manifest Anxiety

Female college students were selected on the basis of their scores on the Manifest Anxiety Scale. The subjects worked either alone or in pairs on a multiple-solution anagrams task. The experiment had a 2 × 2 × 2 design, with group type (nominal versus real), manifest anxiety (low versus high), and induced stress (low versus high) as the three variables. The results indicated that increased anxiety and stress were relatively more detrimental to the performance of real groups as compared with nominal groups.

Group performance as a function of group type, task condition and scholastic level

1978 ◽  
Vol 8 (4) ◽  
pp. 439-451 ◽  
Author(s):  
Suresh Kanekar ◽  
Cynthia Libby ◽  
Jeff Engels ◽  
Gretchen Jahn
Keyword(s):  
Group Performance ◽  
Task Condition ◽  
Group Type

scholarly journals Modularity and composite diversity affect the collective gathering of information online

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Niccolò Pescetelli ◽  
Alex Rutherford ◽  
Iyad Rahwan
Keyword(s):  
Group Size ◽  
Group Composition ◽  
Time Pressure ◽  
Group Performance ◽  
Causal Link ◽  
Online Information ◽  
Consensus Forecasts ◽  
Political Events ◽  
Digital Environments ◽  
And Performance

AbstractMany modern interactions happen in a digital space, where automated recommendations and homophily can shape the composition of groups interacting together and the knowledge that groups are able to tap into when operating online. Digital interactions are also characterized by different scales, from small interest groups to large online communities. Here, we manipulate the composition of groups based on a large multi-trait profiling space (including demographic, professional, psychological and relational variables) to explore the causal link between group composition and performance as a function of group size. We asked volunteers to search news online under time pressure and measured individual and group performance in forecasting real geo-political events. Our manipulation affected the correlation of forecasts made by people after online searches. Group composition interacted with group size so that composite diversity benefited individual and group performance proportionally to group size. Aggregating opinions of modular crowds composed of small independent groups achieved better forecasts than aggregating a similar number of forecasts from non-modular ones. Finally, we show differences existing among groups in terms of disagreement, speed of convergence to consensus forecasts and within-group variability in performance. The present work sheds light on the mechanisms underlying effective online information gathering in digital environments.

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