Abstract:Public data is recognized as a powerful source of innovation. Currently, most studies on the effect of open public data on innovation are conducted at the organizational level, with only a few studies focusing on the impact of individual adoption of public data on innovation. To fill this gap, this article proposes a moderated mediation model based on the human-data interaction theory, which includes features of open public data, individual characteristics, external environmental factors, and academic innovation, and uses scholars as the survey object to investigate the mechanism of the effect of open public data on academic innovation by adopting structural equation model. The empirical results show that: data richness and access restriction significantly positively affect academic innovation. Data literacy and social interaction play a full mediating role in open public data-driven innovation. The impact of access restrictions on academic innovation is bolstered by the disciplinary climate, while the relationship between the two is weakened by technological conditions. The indirect effect of data richness on academic creativity via data literacy is negatively moderated by disciplinary climate, i.e., the weaker the disciplinary climate, the more significant the influence of indirect effect with data literacy. The indirect effect of access restrictions on academic creativity via data literacy is negatively moderated by technology conditions, and the lower the technological conditions, the greater the indirect effect.