Open government data has drawn increasing attention from both governments and academic researchers around the world in recent years. Innovation on the basis of such data can be termed data-driven innovation, and it has been considered a critical mechanism that can create social and economic value. Understanding the driving factors for the adoption of these data among user innovators has become a significant issue for associated initiatives. Accordingly, this study examines the factors influencing the adoption of open government data from the perspective of individual user innovators to fill the existing knowledge gap. Based on the social cognitive theory, this study developed a research model that integrates the following factors that are central to individuals' adoption decisions: computer self-efficacy, tool experience, government support, and social influence. This study examined this model by using survey data from individual users with experience in the adoption of open government data for innovation in Taiwan. The study utilized structural equation modelling to examine the research framework and hypotheses. The results show a significant positive relationship among computer self-efficacy, social influence, and adoption of open government data. This study serves as a first attempt to advance knowledge on the adoption of open government data from the perspectives of individual user innovators by empirically testing a research model that integrates factors within personal and environmental contexts. This study contributes by offering significant theoretical and managerial implications for researchers of open government data and government policy practitioners.
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