HUMAN RESOURCE PRACTICES AND TALENT RETENTION IN THE NIGERIAN OIL AND GAS SECTOR

The Nigerian oil and gas sector remain the backbone of the national economy, yet it continues to
experience high employee turnover, loss of technical expertise, and declining workforce
commitment despite substantial human resource (HR) investments. This study examines the
relationship between human resource practices and talent retention in the Nigerian oil and gas
sector, with specific emphasis on recruitment and selection, training and development,
performance appraisal, compensation management, and career development. Guided by the
Resource-Based View (RBV) and Human Capital Theory, the study adopts a quantitative research
design using a stratified random sample of 210 employees drawn from five major oil and gas firms
in Lagos and Port Harcourt. Data were collected through structured questionnaires and analyzed
using multiple regression and mediation analysis. Findings reveal that training and development,
compensation, and career management significantly and positively influence talent retention,
whereas recruitment and performance appraisal show weaker effects. Moreover, organizational
culture and leadership support partially mediate the relationship between HR practices and
retention outcomes, underscoring the importance of supportive managerial behavior and a
learning-oriented culture in sustaining workforce commitment. These findings align with recent
empirical evidence from emerging economies, emphasizing that effective HR practices serve as
strategic levers for reducing turnover and enhancing operational continuity. The study contributes
to both theoretical and practical knowledge by providing context-specific insights into how
integrated HR strategies can strengthen human capital sustainability and organizational resilience
in Nigeria’s energy industry.

Funding: This research is self-funded research.

Conflict of Interest: The authors declare no conflicts of interest.

Ethics Approval: Not_applicable

Data Availability: Data will be made available upon reasonable request.

AI-Assisted Writing: No AI tools were used in the preparation of this manuscript.