Digital health transformation and innovation behavior: examining the role of technological readiness and dynamic capabilities in public hospitals

Purpose This study aims to investigate the relationship between Technological Readiness (TR) and Job Performance (JP), mediated by Digital Health Transformation (DHT) and nurses’ Innovative Work Behavior (IWB). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5,000 bootstrap resamples, the authors assess direct relationships as well as two sequential mediations. The authors present standardized coefficients (β), explained variance (R²), effect sizes (f²) and mediation strength (variance accounted for [VAF]) to quantify practical significance. Design/methodology/approach A quantitative, cross-sectional design was used, with data gathered from 300 registered nurses through a structured survey. The research model was analyzed using PLS-SEM. Constructs were grounded in the Technology–Organization–Environment (TOE) framework and Social Cognitive Theory (SCT). Findings The results substantiate all eight hypothesized relationships. TR is found to significantly predict both DHT and IWB and directly influence JP. Furthermore, DHT positively affects both IWB and JP, while IWB exhibits a robust predictive relationship with JP. Mediation analysis indicates that DHT mediates the relationship between TR and IWB, and IWB mediates the relationship between DHT and JP. These findings validate the proposed integrated model and highlight the importance of behavioral mechanisms in digital transformation. Practical implications Hospital administrators and policymakers should prioritize the enhancement of technological readiness and the fostering of an innovative culture among nursing staff. Effective digital transformation requires both systemic investment and the empowerment of individual behaviors. For health systems in developing countries, infrastructure deficiencies (e.g. intermittent internet and power supply) may weaken downstream connections (DHT → IWB; IWB → JP). The authors delineate strategies for mitigation – including tiered technology readiness-based training, low-bandwidth and offline-first deployment and workflow-integrated enablement – aimed at transforming digital investments into innovative work behaviors and enhanced performance. Originality/value This study contributes a novel, empirically validated model that links technological readiness and innovative behavior to job performance within the digital health-care framework. This study examines an empirically grounded behavioral pathway that connects technological readiness, digital health transformation, innovative work behavior and job performance among nurses in public hospitals. By transcending traditional adoption-intention models, such as the Technology Acceptance Model (Davis, 1989), and enhancing implementation frameworks like the Nonadoption, Abandonment, Scale-up, Spread IT Information Technology (NASSS) framework (Greenhalgh et al., 2017), this research addresses the paucity of empirical evidence regarding the integration of digital innovations into routine practice within resource-constrained health systems (Dionisio et al., 2023).