Determinants of open government data continuance usage and value creation: A self-regulation framework analysis

Abstract

In the era of the digital economy, open government data (OGD) has emerged as a pivotal driver of socio-economic innovations. Despite its transformative potential value, research remains scarce on the antecedents and value creation of OGD usage in the post-adoption stage, where sustained engagement determines long-term success. To address this gap, our study investigates the determinants of users' continuance usage of OGD and its cascading impact on value creation. Leveraging Bagozzi's self-regulation framework, we integrate the DeLone and McLean's model (D&M model) and the democratic e-governance website evaluation model (DEWEM) to develop a comprehensive theoretical lens that disentangles the roles of website functionality (e.g., transparency, citizen engagement) and data quality (e.g., accessibility, completeness). Empirical data was collected from 267 skilled OGD users in China and analyzed via PLS-SEM. The results show that user satisfaction and perceived value jointly drive continuance usage, with user satisfaction predominantly shaped by information suitability, transparency, security, and citizen engagement. Notably, data accessibility plays a foundational role in enhancing perceived value, whereas data completeness and timeliness show unexpected non-significant effects. Crucially, continuance usage of OGD directly amplifies users' net benefits and trust in governments, underscoring OGD's dual value proposition. These findings contribute to the theoretical understanding of post-adoption behavior in OGD and provide practical insights for policymakers to optimize platform design, prioritize high-impact data features, and foster sustainable OGD ecosystems.