Data Governance. Enablers, Inhibitors, Practices, and Outcomes

Data governance (DG) is a framework to manage data as a strategic enterprise asset. It is used to define and communicate an organization's accountability for data as well as decision rights, policies, standards, procedures, and compliance. As an emerging research topic, there is limited empirical research and theory development. Accordingly, this thesis builds upon Tallon, Ramirez, and Short's (2013) formative qualitative research that proposed the Theory of Information Governance (TIG). This thesis extends the TIG to develop the Refined Theory of Data/Information Governance, theorizes and tests hypotheses, and develops five lower-order constructs and two higher-order constructs. Exploratory factor analysis, confirmatory composite analysis, and structural equation modeling are used on survey data (N = 126, N = 227) from two separate groups of financial professionals. The findings quantitatively ascertain the composition of DG, offer a matrix of DG enablers, and identify DG as a source of competitive advantage and increased performance.