Data-Driven Management and Governance

Summary

Despite the rapid spread of “data-driven” approaches, scholarship on data management and data governance remains fragmented. Studies often examine these areas in isolation and within narrow domains, overlooking their interdependence as parallel constructs in sociotechnical systems. This fragmentation is largely due to the absence of a shared conceptual framework. To address this issue, this article starts with a review of 2,234 Social Sciences Citation Index–indexed publications, which combines bibliometric mapping with targeted qualitative synthesis. The review clarifies conceptual distinctions and complementarities between data-driven management and data-driven governance, while showing how definitions and applications are embedded in varied political, social, managerial, and technological contexts. These contextual dimensions form a recognizable landscape that recurs across domains but is weighted differently in practice. Rather than treating these aspects as external conditions, they are positioned as constitutive foundations that shape both management-oriented and governance-oriented data practices. Building on this review, a sociotechnical synthesis is proposed that aligns fragmented insights through a comparative lens. Rather than prescribing a definitive model, the synthesis points toward integrative frameworks better suited for analyzing cross-sector and cross-level data-driven systems.