探索心理因素在上司支持与工作绩效关系中的中介作用

IF 1.8 Q3 MANAGEMENT Journal of Modelling in Management Pub Date : 2024-07-19 DOI:10.1108/jm2-07-2023-0137
Ali Zeb, Majed Bin Othayman, Gerald Guan Gan Goh, Syed Asad Ali Shah
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引用次数: 0

摘要

目的社会交换和社会学习理论在许多学科中得到了广泛应用,但有关发展中环境下主管支持与工作绩效之间关系的研究却很少。因此,本研究旨在通过心理因素(授权和自信)的中介作用,研究主管支持与工作绩效之间的联系。 设计/方法/途径本研究的数据收集自巴基斯坦电信有限公司的 364 名员工。研究结果表明,上司的支持对工作绩效有促进作用。本研究通过心理因素的中介作用,深入探讨了感知到的上司支持对工作绩效的影响,从而为现有的文献体系增添了新的内容。 原创性/价值 据作者所知,这是极少数探讨发展中环境下上司支持与工作绩效之间关系的研究之一,尤其侧重于赋权和自信的中介机制。
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Exploring the mediating role of psychological factors in the relationship between supervisor support and job performance

Purpose

Social exchange and social learning theories are widely used in many disciplines, but there is little research on the relationships between supervisor support and job performance in a developing context. Therefore this study aims to examine the links between supervisor support and job performance with the mediating role of psychological factors; empowerment and self-confidence.

Design/methodology/approach

Data for this study were collected from 364 employees working at Pakistan Telecommunication Company Limited. Partial least square structural equation modeling was used for the analysis.

Findings

The results revealed that supervisor support stimulates job performance. Empowerment and self-confidence both partially mediate the relationships between supervisor support and job performance.

Practical implications

This study adds to the current body of literature by providing insight into the influence of perceived supervisor support on job performance through the mediating role of psychological factors.

Originality/value

To the best of the authors’ knowledge, this is one of the very few studies exploring the relationships between supervisor support and job performance in developing contexts, particularly focusing on the mediating mechanisms of empowerment and self-confidence.

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来源期刊
CiteScore
5.50
自引率
12.50%
发文量
52
期刊介绍: Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.
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