Abstract
Effective Human Resource Management (HRM) is widely acknowledged as a critical determinant of institutional performance in public sector organizations. In sub-Saharan Africa (SSA), however, the relationship between HRM practices and measurable institutional performance outcomes remains fragmented across disciplinary silos, dominated by evidence from anglophone countries, and almost entirely absent for lusophone contexts including Mozambique. This systematic literature review synthesizes empirical evidence from 48 peer-reviewed studies published between 2010 and 2025, following PRISMA 2020 guidelines, to examine how five core HRM practices merit-based recruitment and selection, performance appraisal, training and development, compensation and payroll management, and digital HRM systems influence institutional performance outcomes in SSA public sector organizations. Performance is operationalized across five dimensions: service delivery quality, employee productivity, institutional accountability, staff retention, and public trust. Findings reveal that merit-based recruitment is the single most consistently impactful HRM practice, with strong positive effects across all five performance dimensions, while patronage-based recruitment shows correspondingly strong negative effects. Performance appraisal demonstrates a striking design-dependence: well-designed, participatory systems enhance performance, while poorly designed, compliance-oriented systems actively harm it. Training and development consistently improve service delivery quality and staff retention. Transparent payroll management is the strongest predictor of institutional accountability and public trust. Digital HRM systems show promising accountability effects but face sócio-technical implementation constraints. Critical gaps include the near-absence of lusophone SSA evidence, neglect of military and uniformed services, and dominance of cross-sectional designs. The review proposes a contextualized HRM-Performance framework for SSA and identifies eight priority directions for future research.