Permanent record · RIR–2062
Theoretical Frameworks for Data-Intensive Economies and Digital Governance Policy Design
This paper proposes a theoretical model of the data economy, arguing that data sharing is essential to correct market failures in knowledge production.
How can theoretical economic models of data-intensive industries inform the design of digital governance and data-sharing policies?
Knowledge gap
What remains worth asking
Existing economic models may insufficiently account for the unique characteristics of data as a non-rivalrous input in AI-driven knowledge creation.
Potential contribution
Why it may matter
Provides a conceptual foundation for policymakers to address the societal challenges of data capitalism and AI transparency.
Academic placement
OECD fields and topic tags
Scope: Macro-level data economy and digital governance frameworks. · Method signals: Theoretical conceptualization, Economic modeling
Possible study pathways
One question, different levels
Strategic management of data assets and corporate governance in AI.
Developing new economic theories for the digital knowledge economy.
Qualification signal
90/100
- Highly theoretical approach.
- Applicable to both public policy and private sector strategy.
- Open-access scholarly source and DOI metadata verified
Provenance
Research Idea Registry curation
- DOI and bibliographic metadata independently resolved
- Open-access status verified
- The research direction is transparently marked as AI-inferred
APA 7 source
de Pedraza, P., & Vollbracht, I. (2023). General theory of data, artificial intelligence and governance. Humanities and Social Sciences Communications, 10(1), Article 607. https://doi.org/10.1057/s41599-023-02096-w
Paper abstract and discussion context; AI-inferred direction
Open source ↗