Governance of High-Dimensional Data-Driven Intelligent Platforms

Abstract

This study proposes a unified governance framework for high-dimensional data-driven intelligent platforms by integrating insights from platform ecosystem theory, algorithmic governance, and data governance research. Rather than conceptualizing intelligent platforms as neutral technological tools, the paper positions them as decision infrastructures that structure authority, accountability, and regulation through data architectures and algorithmic control. Using tourism and healthcare platforms as comparative governance contexts, the analysis demonstrates that platforms perform equivalent institutional functions, including regulation, coordination, monitoring, accountability, and optimization, despite differences in service domains and data content. A central contribution of this research is the introduction of data efficiency as a governance performance criterion, emphasizing the capacity of platforms to transform complex, high-dimensional data into interpretable, actionable, and institutionally usable decisions. By shifting evaluation from predictive accuracy toward governance outcomes such as transparency, compliance, coordination, and trust, the study reframes intelligent platforms as socio-technical governance systems. The findings confirm that platform governance logic is institutional rather than sector-specific and that algorithms operate as operational governors within platform ecosystems. This framework advances management science by providing a transferable model for understanding how intelligent platforms govern through high-dimensional data in smart service environments.