A multisession comparative study of group size and group performance in an electronic meeting system environment

Simulated virtual realities offer a promising but currently underutilized source of data in studying cultural and demographic aspects of dynamic decision-making (DDM) in small groups. This study focuses on one simulated reality, a clock-driven business simulation game, which is used to teach operations management. The purpose of our study is to analyze the characteristics of the decision-making groups, such as cultural orientation, education, gender and group size, and their relationship to group performance in a real-time processed simulation game. Our study examines decision-making in small groups of two or three employees from a global manufacturing and service operations company. We aim at shedding new light on how such groups with diverse background profiles perform as decision-making units. Our results reveal that the profile of the decision-making group influences the outcome of decision-making, the final business result of the simulation game. In particular, the cultural and gender diversity, as well as group size seem to have intertwined effects on team performance.

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Group Performance Related to Size and Initial Ability of Group Members

Psychological Reports ◽

10.2466/pr0.1971.28.2.551 ◽

1971 ◽

Vol 28 (2) ◽

pp. 551-557 ◽

Cited By ~ 3

Author(s):

Morton Goldman

Keyword(s):

Group Size ◽

Group Performance ◽

Test Results ◽

Ability Levels ◽

Group Members ◽

Paper And Pencil ◽

Relationship Of ◽

The Relationship ◽

Different Levels

This study examined the relationship of group performance as a function of group size, where members within each group are of similar initial ability levels, but members in different groups are of different levels. 5 wk. later on the basis of a paper-and-pencil test, Ss were formed into groups composed of all high Ss, all medium Ss, and all low Ss, with size varying from 2 to 5 persons. Ss working as a group retook the same test. Results showed that groups with different initial levels have their own unique patterns of improvement as the size of the group increases.

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Comparative Study of Feature Selection Techniques Respecting Novelty Detection in the Industrial Control System Environment

Proceedings of the 29th International DAAAM Symposium 2018 - DAAAM Proceedings ◽

10.2507/29th.daaam.proceedings.155 ◽

2018 ◽

pp. 1084-1091

Author(s):

Jan Vavra ◽

Martin Hromada

Keyword(s):

Feature Selection ◽

Control System ◽

Comparative Study ◽

Novelty Detection ◽

Industrial Control System ◽

Industrial Control ◽

System Environment ◽

Feature Selection Techniques

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

10.31234/osf.io/b8q2c ◽

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.

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