The mediating role of perceived organizational support in the relationship between university teachers’ competence and job performance: A comprehensive analysis

Qianqian Mo, Siti Nisrin Mohd Anis — Sat, 06 Dec 2025 08:49:55 +0000

This study aims to explore the mediating role of perceived organizational support(POS) in the relationship between university teachers' competence and job performance. Through a questionnaire survey of 968 undergraduate university teachers in China, 879 valid questionnaires were collected. The study employed quantitative methods, constructing a university teacher competence scale comprising foundational competence, teaching competence, research competence, and innovation competence, as well as a job performance scale encompassing task performance, relationship performance, and adaptive performance. Structural equation modeling and SOBEL tests were used for data analysis. The results showed that POS exhibited different mediating effect patterns between various competence dimensions and job performance dimensions: no significant mediating effect was found in task performance; partial mediating effects were observed in relational performance and adaptive performance; and a complete mediating effect was identified between foundational competence and adaptive performance. The study provides theoretical support and practical guidance for university teachers management, emphasizing the importance of establishing a competence-based human resources management system, strengthening teachers perceptions of organizational support, and establishing diverse evaluation standards. Future research could further explore the impact of different cultural backgrounds and organizational types on mediating effects.

The rise of AI in human resource management: A systematic review of task automation through PRISMA

Fri, 14 Nov 2025 09:29:15 +0000

Objective: This study synthesizes current evidence on the role of Artificial Intelligence (AI) and, where relevant, Open Science (OS) practices in enhancing Human Resource Management (HRM) performance. It focuses on recruitment processes, ethical considerations, and employee participation. Methodology: A systematic literature review was conducted in Scopus covering the period 2019–2024, following PRISMA guidelines. The initial search yielded 1486 records. After de-duplication and screening using Rayyan, 66 studies (≈ 4.4%) met the inclusion criteria, which targeted peer-reviewed works addressing AI-supported HR decision-making. A combined content and bibliometric analysis was performed in R (Bibliometrix) to identify thematic patterns and conceptual structures. Results: Analysis revealed four thematic clusters: 1) Implementation and employee participation emphasizing human-in-the-loop approaches and effective change management; 2) ethical challenges including algorithmic bias, transparency gaps, and data privacy risks; 3) data-driven decision-making delivering higher accuracy, fewer errors, and personalized recruitment and performance assessment; 4) operational efficiency enabling faster workflows and reduced administrative workloads. AI tools consistently improved selection quality, while OS practices promoted transparency and knowledge sharing. Implications: The successful adoption of AI in HRM requires employee engagement, strong ethical safeguards, and transparent data governance. Future research should address the long-term cultural, organizational, and well-being impacts of AI integration, as well as its sustainability.

Human Resources Management and Services

The mediating role of perceived organizational support in the relationship between university teachers’ competence and job performance: A comprehensive analysis

The rise of AI in human resource management: A systematic review of task automation through PRISMA