Determinant factors of Chief Data Officer adoption in government: A topic model and structural equation modelling approach - Hui Zhang; Huiying Ding; Jianying Xiao (PLoS ONE, 2025)
With the generation of massive amounts of data, the Chief Data Officer (CDO) has been introduced in governments worldwide. Existing research on CDO is quite limited and primarily focuses on general descriptions of CDO. However, there is little research exploring the underlying reasons for the establishment of the CDO in government. To address this gap, this paper employs topic modeling to analyze government documents, identify factors influencing the adoption of CDO, and construct a research model. Data were collected from 277 employees within Chinese government organizations through a questionnaire survey and a quantitative analysis was performed to evaluate five hypotheses using structural equation modeling (SEM). The findings suggest that (1) data exploitation, data sharing and data management significantly influence data dividends, and (2) both data dividends and institutional pressures are key predictors of the intention to adopt the CDO, with digital dividends exerting a greater effect than institutional pressures.