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A dataset of human decision-making in teamwork management

Overview of attention for article published in Scientific Data, January 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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43 X users

Citations

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15 Dimensions

Readers on

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61 Mendeley
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Title
A dataset of human decision-making in teamwork management
Published in
Scientific Data, January 2017
DOI 10.1038/sdata.2016.127
Pubmed ID
Authors

Han Yu, Zhiqi Shen, Chunyan Miao, Cyril Leung, Yiqiang Chen, Simon Fauvel, Jun Lin, Lizhen Cui, Zhengxiang Pan, Qiang Yang

Abstract

Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

X Demographics

X Demographics

The data shown below were collected from the profiles of 43 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 18%
Student > Master 11 18%
Student > Bachelor 5 8%
Professor 4 7%
Student > Doctoral Student 3 5%
Other 7 11%
Unknown 20 33%
Readers by discipline Count As %
Engineering 8 13%
Computer Science 8 13%
Business, Management and Accounting 7 11%
Agricultural and Biological Sciences 2 3%
Sports and Recreations 2 3%
Other 12 20%
Unknown 22 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 February 2017.
All research outputs
#1,070,789
of 24,853,509 outputs
Outputs from Scientific Data
#452
of 3,086 outputs
Outputs of similar age
#23,068
of 428,444 outputs
Outputs of similar age from Scientific Data
#14
of 47 outputs
Altmetric has tracked 24,853,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,086 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.0. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 428,444 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.