Purpose: This study examines the influence of Human Resource Development (HRD) and compensation on village apparatus performance to address persistent governance gaps in Indonesia’s decentralized rural public administration system, with an empirical focus on Malaka Regency, East Nusa Tenggara Province. Method/approach: A quantitative census design was employed to collect data from the entire population of 70 village officials in Manulea Village, Sasitamean District, Malaka Regency, during June–July 2025. Data were analyzed using multiple linear regression with robust assumption testing, supplemented by exploratory factor analysis and common method bias assessment. Findings: The results confirm that both constructs are critical predictors. HRD significantly enhances performance ( = 0.64, p < .001, = .413), while compensation demonstrates a slightly stronger individual effect ( = 0.69, p < .001, = .475). In the simultaneous model, these predictors jointly explain 55.8% of the variance in performance (F (2, 67) = 42.22, p < .001). All effect sizes exceed Cohen’s (1988) thresholds for large magnitude, confirming strong practical significance. Limitations: The cross-sectional, single-district design limits causal inference and generalizability. Future research should employ longitudinal, multi-site designs incorporating objective performance indicators to explore boundary conditions across diverse Indonesian contexts. Implications: The study recommends that local governments institutionalize mandatory HRD budget allocations (e.g., a minimum of 5% of village funds) and standardize comprehensive compensation packages. Crucially, this includes ensuring adequate work facilities such as computers, internet connectivity, and office infrastructure to enhance the capacity of frontline public servants in delivering rural development programs. Contribution: This study extends Human Capital Theory and Expectancy Theory to the resource-constrained context of village governance in an emerging market. It provides precise effect size estimates to guide evidence-based policy prioritization for Indonesia’s 74,954 villages and contributes methodologically through rigorous measurement validation.
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