Ali Zeb, Majed Bin Othayman, Gerald Guan Gan Goh, Syed Asad Ali Shah
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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.
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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