The Quarterly Journal of Intelligent Management of Human Capital is an open-access, peer-reviewed academic publication that adopts an interdisciplinary and forward-looking approach to advancing knowledge in the field of intelligent human capital management. The journal aims to publish original research and theoretical developments focused on the application of data-driven strategies and convergent technologies—particularly information technology, cognitive science, and biotechnology—in managing human capital processes across diverse organizational contexts.
The journal welcomes high-quality contributions that investigate intelligent systems, models, frameworks, roadmaps, strategic programs, and big data applications to improve decision-making in the monitoring, recruitment, performance management, development, retention, and sustainability of human capital at national and international levels.
The mission of the Quarterly Journal of Intelligent Management of Human Capital is to foster the dissemination and exchange of innovative knowledge and scientific achievements in the domain of human capital intelligence. The journal aims to support the localization, integration, and sharing of expertise and experience from academics, practitioners, and policymakers to advance intelligent human capital management.
To achieve this, the journal provides a platform for publishing scholarly work by faculty members, students, and researchers—both domestic and international—who explore the intelligent automation of human capital systems. This includes research on recruitment and selection, performance evaluation, organizational development, strategic sustainability, and other core HR processes, with a strong emphasis on data-oriented approaches and convergent technologies such as AI, machine learning, cognitive sciences, and bio-technologies.
The journal aspires to become a leading scientific resource in the field of intelligent human capital management at national, regional, and global levels. It aims to be recognized for its commitment to academic rigor, technological innovation, and real-world applicability. By facilitating the exchange of cutting-edge research on the integration of convergent technologies in HRM, the journal seeks to enhance its scientific credibility and become the preferred venue for researchers seeking to publish novel, impactful work that contributes to the advancement of knowledge and practice in human capital intelligence.
Advancing Knowledge: To promote the development and dissemination of innovative research on the intelligent automation of human resource management (HRM) processes.
Technological Integration: To support and share new findings on the application of convergent technologies—particularly in IT, cognitive science, and biotechnology—in managing human capital.
Data-Driven Insights: To publish research that emphasizes data-oriented approaches to automating and optimizing core HR processes such as recruitment, performance evaluation, development, retention, and sustainability.
Localization and Synergy: To encourage the contextualization and synthesis of knowledge and managerial experiences in intelligent HRM across various sectors and institutions.
Convergence Awareness: To promote understanding of technological convergence and its implications for human capital management.
Research Needs Alignment: To respond to the research demands of executive and public sector organizations by publishing practical and policy-relevant scientific work.
Knowledge Exchange: To facilitate the exchange of knowledge and best practices on intelligent human capital management at national, regional, and international levels.
National Capacity Building: To address the academic and scientific needs of the country by contributing to solutions for human capital management challenges.
The journal covers a wide range of topics related to intelligent human capital management, including but not limited to:
Intelligent automation of HRM processes: monitoring, recruitment, selection, performance management, development, retention, and sustainability using data-driven approaches.
Application of convergent technologies in human capital management, including artificial intelligence, machine learning, data analytics, cloud computing, and virtual/augmented reality.
Technological convergence of IT, cognitive sciences, and biological sciences in advancing intelligent HR systems.
Design and implementation of smart HR systems such as talent acquisition platforms, assessment and development centers, employee sentiment analysis tools, performance appraisal systems, feedback mechanisms, and reward systems.
Strategic planning: development of roadmaps, strategies, and action plans for intelligent HRM practices.
Value creation through intelligent human capital strategies: ROI on Human Capital (ROIHC), cost efficiency, and intelligent auditing.
Knowledge management systems for capturing and disseminating organizational human capital insights.
Screening and evaluation techniques using intelligent systems in candidate selection and assessment.
Futures studies and scenario planning in intelligent human capital management.
Competency-based intelligent testing: designing recruitment tools aligned with job-specific competencies.
Talent monitoring systems for identifying and attracting top talent to key organizational roles.
Smart mentoring and coaching programs for talent development and leadership pipelines.
Development of cognitive and interpersonal skills such as communication, teamwork, and neuro-cognitive capabilities.
Intelligent personal development: integration of strategic, analytical, emotional, spiritual, cultural, and verbal intelligences into human capital growth strategies.
Career path intelligence: facilitating strategic career planning and development opportunities using smart tools and analytics.
Other emerging topics related to the future of human capital intelligence and its governance.