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知识密集型工作中多重团队成员身份与个体工作绩效之间的动态关系。

The dynamic relationship between multiple team membership and individual job performance in knowledge-intensive work.

作者信息

van de Brake Hendrik J, Walter Frank, Rink Floor A, Essens Peter J M D, van der Vegt Gerben S

机构信息

Faculty of Economics and Business University of Groningen Groningen the Netherlands.

Faculty of Economics and Business Studies Justus-Liebig-University Giessen Giessen Germany.

出版信息

J Organ Behav. 2018 Nov;39(9):1219-1231. doi: 10.1002/job.2260. Epub 2018 Jan 16.

Abstract

Many employees in modern, knowledge-based organizations are concurrently involved in more than one team at the same time. This study investigated whether a within-person change in such individual multiple team membership (MTM) may precede and may be predicted by changes in an employee's overall job performance. We examined this reciprocal relationship using longitudinal archival data from a large knowledge-intensive organization, comprising 1,875 employees and spanning 5 consecutive years. A latent change score model demonstrated that an increase in an employee's MTM was associated with a subsequent decrease in his or her overall job performance evaluations. By contrast, an increase in job performance was associated with a subsequent increase in an employee's MTM. Moreover, our results indicated that although an increase in an individual employee's MTM initially decreases his or her job performance, in the long run, this increase in MTM was associated with higher job performance. Together, these results suggest a dynamic association between an individual employee's MTM and his or her overall job performance, such that these variables are mutually connected in a highly complex manner over time.

摘要

在现代的知识型组织中,许多员工同时参与不止一个团队。本研究调查了员工个体多重团队成员身份(MTM)的个体内部变化是否可能先于员工整体工作绩效的变化并可由其预测。我们使用来自一个大型知识密集型组织的纵向档案数据来检验这种相互关系,该组织有1875名员工,数据跨度为连续5年。一个潜在变化得分模型表明,员工MTM的增加与随后其整体工作绩效评估的下降相关。相比之下,工作绩效的提高与员工MTM的随后增加相关。此外,我们的结果表明,虽然单个员工MTM的增加最初会降低其工作绩效,但从长远来看,MTM的这种增加与更高的工作绩效相关。总之,这些结果表明单个员工的MTM与其整体工作绩效之间存在动态关联,使得这些变量随着时间的推移以高度复杂的方式相互联系。

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