真实领导与员工工作绩效:员工积极健康的中介作用

IF 3.6 2区 管理学 Q2 BUSINESS Journal of Management Analytics Pub Date : 2023-06-06 DOI:10.1080/23270012.2023.2219993
Yang Liu, Bryan Fuller, K. Hester, Hong Chen
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引用次数: 0

摘要

在全球竞争和2019冠状病毒病大流行的背景下,组织面临着越来越具有挑战性和不可预测的环境。因此,员工正在经历更高程度的工作压力。本研究旨在探讨组织内各种组织机制对促进员工积极健康,最终影响员工工作绩效的影响。本研究发现,真实的领导和组织政治的缺失是正向员工健康的显著预测因子。此外,积极的员工健康通过对工作投入的影响,对主管评价的工作绩效有积极的影响。这项研究为组织提供了宝贵的资源,揭示了促进员工健康的基本因素。它还提高了管理者对培养和维持员工的情绪和身体健康以保持市场竞争力的重要性的认识。©2023上海交通大学安泰经济与管理学院
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Authentic leadership and employees’ job performance: mediation effect of positive employee health
In light of global competition and the COVID-19 pandemic, organizations are encountering an increasingly challenging and unpredictable environment. Consequently, employees are experiencing heightened levels of job strain. This study aims to explore the impact of various organizational mechanisms on promoting positive employee health within the organization, ultimately affecting employees' job performance. The findings of this study indicate that authentic leadership and the absence of organizational politics are significant predictors of positive employee health. Moreover, positive employee health has a positive influence on supervisor-rated job performance through its effect on job engagement. This study serves as a valuable resource for organizations, shedding light on the fundamental factors that contribute to positive employee health. It also raises managers' awareness of the importance of nurturing and sustaining employees' emotional and physical well-being to maintain competitiveness in the market. © 2023 Antai College of Economics and Management, Shanghai Jiao Tong University.
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来源期刊
Journal of Management Analytics
Journal of Management Analytics SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
13.30
自引率
3.40%
发文量
14
期刊介绍: The Journal of Management Analytics (JMA) is dedicated to advancing the theory and application of data analytics in traditional business fields. It focuses on the intersection of data analytics with key disciplines such as accounting, finance, management, marketing, production/operations management, and supply chain management. JMA is particularly interested in research that explores the interface between data analytics and these business areas. The journal welcomes studies employing a range of research methods, including empirical research, big data analytics, data science, operations research, management science, decision science, and simulation modeling.
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