Description

Human Resources Management and Services (HRMS) is an international open access journal on theoretical and practical research in the field of human resource management. HRMS adopts a double-blind peer review model and publishes high-quality articles. It is committed to disseminating unique and insightful insights and promoting the development, innovation and understanding of human resource management. Potential readers of HRMS include scholars, practice managers, and policy makers in the field.

HRMS welcomes articles based on original research, reviews, case reports, perspectives, etc. HRMS also publishes editorials reflecting the official opinions of the journal's editorial office. Submissions to HRMS can be interdisciplinary around the topic of human resource management. Examples of some related topics are as follows:

  • Human resource planning;
  • Human resource services;
  • Organizational management;
  • Human capital;
  • Training and development;
  • Sustainable human resource practices;
  • Employee efficiency and performance management;
  • Labor relations;
  • Employee well-being;
  • Policy formulation;
  • Job satisfaction;
  • Psychological issues;
  • Social issues;
  • Fairness in employment.

Latest Articles

  • Open Access

    Review

    Article ID: 4595

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

    by Kawthar Bouzerda, Selimane Hani, Hasnae Rahmani, Ali Hebaz, Abdessamad Dibi, Hasna Mharzi

    Human Resources Management and Services , Vol.7, No.4, 2025; 14 Views

    DOI: https://doi.org/10.18282/hrms4595

    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. Implicat ions:  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.

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Announcements

2025 Volume 7 Issue 1 has been released online!

2025-04-15

We are delighted to announce that Vol.7, No.1 has been released, focusing on cutting-edge research in Human Resource Management and Organizational Behavior. This issue collects 10 articles authored by 10 countries, and aims to provide a platform for scholars and practitioners to share their latest findings and insights on a wide range of topics related to human resources management and organizational dynamics.

More details, please discovery here.

Read more about 2025 Volume 7 Issue 1 has been released online!