已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Too much of a good thing: Examining the curvilinear relationship between team‐level proactive personality and team performance

心理学 人格 社会心理学 心理安全 凝聚力(化学) 曲线坐标 团队效能 应用心理学 知识管理 计算机科学 化学 几何学 数学 有机化学
作者
Ruixue Zhang,Anran Li,Yaping Gong
出处
期刊:Personnel Psychology [Wiley]
卷期号:74 (2): 295-321 被引量:38
标识
DOI:10.1111/peps.12413
摘要

Abstract Research has largely shown a positive linear relationship between proactive personality and job performance at the individual level. However, it remains unknown whether the same relationship holds at the team level. In this research, we propose and test a curvilinear relationship between team mean level of proactive personality and team performance. We also examine team potency and team cohesion as the explanatory mechanisms and the dispersion of proactive personality as a boundary condition for the relationship. We conducted two studies to test these ideas. In Study 1, we collected data from 93 teams in four companies from different industries. In Study 2, we collected data from 101 nursing teams in three hospitals. We found a curvilinear relationship between team mean level of proactive personality and team performance in Study 1 and replicated it in Study 2. We further demonstrated in Study 2 the moderating role of dispersion of proactive personality and the mediating role of team potency and team cohesion, respectively, in this curvilinear relationship. The positive trend of the curvilinear relationship is strengthened (weakened) when the dispersion of proactive personality is high (low). The negative trend is mitigated under high dispersion of proactive personality but is not significant under low dispersion of proactive personality. Practically, managers must be aware that team mean level of proactive personality benefits team performance only up to a certain point.
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
chy发布了新的文献求助10
1秒前
2秒前
3秒前
3秒前
3秒前
4秒前
4秒前
LIANGMEIHAO发布了新的文献求助20
5秒前
5秒前
我是老大应助刘昊宇采纳,获得10
7秒前
w_发布了新的文献求助10
8秒前
冷静伟诚发布了新的文献求助10
8秒前
9秒前
liuu完成签到,获得积分10
9秒前
10秒前
传奇3应助科研通管家采纳,获得10
10秒前
meihui完成签到 ,获得积分10
10秒前
dream完成签到 ,获得积分10
12秒前
2515424504完成签到,获得积分20
14秒前
xionggege完成签到,获得积分10
16秒前
标致小甜瓜完成签到,获得积分10
16秒前
ooj完成签到,获得积分10
17秒前
18秒前
Jasper应助舒适的秋尽采纳,获得30
19秒前
19秒前
Richard完成签到,获得积分10
20秒前
21秒前
可爱的函函应助冷静伟诚采纳,获得10
22秒前
义气的妙彤完成签到 ,获得积分10
23秒前
小蘑菇应助chy采纳,获得10
24秒前
ooj发布了新的文献求助10
25秒前
YJ888发布了新的文献求助10
25秒前
蔡江琦发布了新的文献求助20
28秒前
28秒前
orixero应助坦率的薯片采纳,获得10
29秒前
29秒前
30秒前
34秒前
菜根谭发布了新的文献求助10
34秒前
坦率的薯片完成签到,获得积分20
36秒前
高分求助中
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6495054
求助须知:如何正确求助?哪些是违规求助? 8291966
关于积分的说明 17694375
捐赠科研通 5588405
什么是DOI,文献DOI怎么找? 2916410
邀请新用户注册赠送积分活动 1893297
关于科研通互助平台的介绍 1752303