From intuition to evidence: the influence of environmental forces, technology and organizational competence on HR analytics adoption in organizations

Human Resource Analytics (HRA) has emerged as a strategic lever for evidence-based workforce management, yet its adoption remains theoretically contested and empirically uneven across institutional contexts. While existing literature predominantly draws on developed-economy settings, the mechanisms through which environmental pressures, technological readiness, and organizational competence jointly shape HRA adoption in emerging economies remain insufficiently understood. This study examines how environmental forces, technological availability, and organizational competence influence HRA adoption within Nepalese organizations, where weak enforcement structures, informality, and nascent digital infrastructure create distinct boundary conditions for established theoretical frameworks. A descriptive and explanatory research design was adopted using a quantitative approach. Data were collected through a structured survey administered to 210 human resource professionals across diverse organizations in Nepal. Validated measurement scales assessed HRA adoption and its antecedents. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized relationships, given the exploratory nature of the model and the non-normal distribution of the data. Environmental forces and technological availability exert a significant positive influential relationship to HRA adoption, while organizational competence does not demonstrate a statistically significant direct positive influential relationship, a finding that diverges from prior literature and warrants further theoretical attention. The results also reveal moderate access to analytics tools and data systems, alongside strong normative and mimetic institutional pressures that drive organizations toward HRA adoption. This study extends institutional theory and technology adoption perspectives to an under-researched emerging economy context, offering one of the first empirical examinations of HRA adoption in Nepal. Rather than treating geography as the primary contribution, the study identifies how institutional voids and infrastructural constraints moderate the explanatory power of established frameworks, producing differential factor effects not anticipated by existing models. These findings offer actionable insights for organizational leaders and policymakers seeking to advance analytics-driven workforce management in contexts where structural conditions diverge significantly from those assumed in mainstream HRA literature.