The paper aims to clarify the relationship between data governance, data quality, and data-driven culture within organizations. It proposes a model to quantify these relationships and examines their role in fostering a data-driven culture, extending the Resource-Based View (RBV) by positioning these constructs as strategic resources.
The paper employs a quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate relationships between data governance, data quality, and data-driven culture.
The paper provides empirical evidence of a positive relationship between data governance and data-driven culture, with data quality as a mediator. It suggests that effective data governance enhances data quality and fosters a data-driven culture, positioning both as strategic resources within the Resource-Based View (RBV) framework.
The use of a non-probabilistic convenience sample may limit the generalizability of the findings.
The paper suggests that effective data governance practices enhance data quality and foster a data-driven culture. By viewing data governance and quality as strategic resources, companies can better align their operations with data-driven goals.
This paper empirically examines the relationships between data governance, data quality and data-driven culture, offering quantitative analysis within the Resource-Based View (RBV) framework. It provides valuable insights for academics and practitioners in effective data management.
