A Bayesian analysis of determinants of open science utilization among Gen Z students in Vietnamese universities challenges digital native assumptions

Open science adoption among Generation Z students in developing contexts presents a critical test of technology acceptance frameworks developed in Western settings. This study examines factors predicting open science resource utilization among 1,422 Vietnamese undergraduate students using Bayesian regression analysis. We tested a theoretical framework integrating Self-Efficacy Theory, Theory of Planned Behavior, Institutional Theory, and Mindsponge Theory through progressive model building. Model comparison via WAIC identified the main effects model as optimal. Results revealed Technical Self-efficacy (β = 0.25) and Open Science Self-efficacy (β = 0.21) as the strongest predictors, with Institutional Support showing moderate effects (β = 0.12). All three predictors demonstrated highly credible positive effects with narrow uncertainty intervals. Contrary to Western technology acceptance models, Perceived Benefits showed minimal direct influence, and Value Alignment demonstrated no credible effect on Utilization. Hypothesized interaction effects between Technical Self-efficacy and Perceived Benefits were not supported by model comparison, suggesting additive rather than synergistic adoption mechanisms. These findings challenge the digital native assumption and reveal that Vietnamese students adopt open science for practical reasons, relying on skills and support rather than ideology. Interventions in resource-constrained settings should therefore prioritize technical skill development and institutional support. This pragmatic approach has implications for advancing open science in the age of AI.