Supplementary file 2_When readiness fails: a TOE–TAM mixed-methods analysis of AI-enabled HR digitalization in a resource-constrained small island context.xlsx

<p>This study examines barriers to adopting artificial intelligence (AI) in human resource management (HRM)—hereafter AI-enabled human resources (AI-HR)—across Zanzibar’s public and private sectors and asks whether the standard predictors of an integrated Technology–Organization–Environment and Technology Acceptance Model (TOE–TAM) framework behave as theorized under mandatory, resource-constrained conditions. An explanatory sequential mixed-methods design combined a survey of HR professionals, information technology (IT) managers, and administrators (N = 137), analyzed with partial least squares structural equation modelling (PLS-SEM), with nine semi-structured key-informant interviews used to explain the quantitative results.

The organizational readiness (OR) scale failed internal consistency (Cronbach’s α = −0.105) and was therefore excluded before structural testing. Of the six structurally interpretable paths, perceived ease of use strongly predicted perceived usefulness (β = 0.552, p < 0.001), while technological readiness predicted AI-HR adoption readiness only marginally (β = 0.216, p = 0.044; bias-corrected and accelerated [BCa] confidence interval that included zero).