The Task Space: An Integrative Framework for Team Research

任务(项目管理) 空格(标点符号) 计算机科学 群(周期表) 人工智能 任务分析 团队效能 知识管理 工作(物理) 数据科学 认知心理学 人机交互 知识空间 机器学习 团队构成 多样性(控制论) 工作组 基线(sea)
作者
Xinlan Emily Hu,Mark E. Whiting,Linnea Gandhi,Duncan J. Watts,Abdullah Almaatouq
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
标识
DOI:10.1287/mnsc.2023.03544
摘要

Research on teams spans many contexts, but integrating knowledge from heterogeneous sources is challenging because studies typically examine different tasks that cannot be directly compared. Most investigations involve teams working on just one or a handful of tasks, and researchers lack principled ways to quantify how similar or different these tasks are from one another. We address this challenge by introducing the “Task Space,” a multidimensional space in which tasks—and the distances between them—can be represented formally, and use it to create a “Task Map” of 102 crowd-annotated tasks from the published experimental literature. We then demonstrate the Task Space’s utility by performing an integrative experiment that addresses a fundamental question in team research: when do interacting groups outperform individuals? Our experiment samples 20 diverse tasks from the Task Map at three complexity levels and recruits 1,231 participants to work either individually or in groups of three or six (180 experimental conditions). We find striking heterogeneity in group advantage, with groups performing anywhere from three times worse to 60% better than the best individual working alone, depending on the task context. Critically, the Task Space makes this heterogeneity predictable: it significantly outperforms traditional typologies in predicting group advantage on unseen tasks. Our models also reveal theoretically meaningful interactions between task features; for example, group advantage on creative tasks depends on whether the answers are objectively verifiable. We conclude by arguing that the Task Space enables researchers to integrate findings across different experiments, thereby building cumulative knowledge about team performance. This paper was accepted by Sameer Srivastava, organizations. Funding: The authors thank the Alfred P. Sloan Foundation [Grant #202-13924] and the MIT Wade Fund for their generous support of this research. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03544 .
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Lucas应助内向的小懒猪采纳,获得10
刚刚
乐乐应助Menand采纳,获得10
刚刚
LH0925完成签到 ,获得积分10
1秒前
Jasper应助Cy采纳,获得10
1秒前
1秒前
1秒前
祥瑞发布了新的文献求助10
1秒前
科研通AI6.4应助deng采纳,获得10
1秒前
辰辰发布了新的文献求助10
2秒前
2秒前
3秒前
科研通AI6.4应助迷之糜采纳,获得10
3秒前
4秒前
正直的紫安完成签到,获得积分20
4秒前
困困酱完成签到,获得积分10
4秒前
蓝天应助安纳采纳,获得10
5秒前
JIN0发布了新的文献求助10
5秒前
Ten发布了新的文献求助20
6秒前
7秒前
7秒前
7秒前
成就映秋发布了新的文献求助10
7秒前
纯洁的彦祖完成签到,获得积分10
8秒前
8秒前
呆呆完成签到,获得积分10
9秒前
cdercder应助正直的紫安采纳,获得10
9秒前
顾矜应助wangdave采纳,获得10
10秒前
12秒前
呆呆发布了新的文献求助20
12秒前
飓风发布了新的文献求助10
12秒前
红尘意三分完成签到,获得积分10
13秒前
fhp完成签到,获得积分10
13秒前
13秒前
18859805972完成签到 ,获得积分10
13秒前
13秒前
14秒前
在水一方应助阿赵采纳,获得10
14秒前
15秒前
15秒前
饭遇碟完成签到 ,获得积分10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The anomeric effect 1314
Principles of town planning: translating concepts to applications 1000
Navigating Normative Orders. Interdisciplinary Perspectives 800
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7737585
求助须知:如何正确求助?哪些是违规求助? 9286831
关于积分的说明 20180358
捐赠科研通 7315420
什么是DOI,文献DOI怎么找? 3305617
关于科研通互助平台的介绍 2457870
邀请新用户注册赠送积分活动 2315256