公共数据开放对学术创新的作用机制——基于人-数交互理论

The Mechanism of the Effect of Open Public Data on Academic Innovation:From the Perspective of Human-Data Interaction

研究基于人-数交互理论,构建含公共数据开放的数据属性、个体特征、环境因素以及学术创新的有调节的中介模型,以科研人员为研究对象,采用结构方程模型来探究公共数据开放对学术创新的作用机制。结果表明:数据丰富性与获取限制性对学术创新具有显著的正向作用;科研人员的数据素养以及社会互动在公共数据开放驱动创新中起着完全中介的作用;学科氛围强化了获取限制性对学术创新的影响,技术条件则弱化了二者之间的关系;学科氛围负向调节数据丰富性对学术创新经由数据素养的间接效应,即学科氛围越弱,间接效应越强;技术条件负向调节获取限制性对学术创新经由数据素养的间接效应,且在技术条件越低的情况下间接效应越显著。

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.