نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسنده English
Purpose: This article examines the adaptive-governance mechanisms required to transform a national vision from a primarily directional document into a monitorable, learning-oriented, and revisable framework. It also investigates the supporting role of big data and artificial intelligence in analysis, monitoring, scenario development, and policy decision support during the transition from Iran’s 1404 Vision Document to the 1430 horizon.
Design/ methodology/ approach: The study adopts an applied qualitative design and employs directed document analysis and a structured comparison of Finland, Estonia, Singapore, South Korea, the United Arab Emirates, and Malaysia. The evidence was examined through six dimensions: operational definition of goals, indicators, and baselines; data governance and interoperability; analytical capacity, foresight, and scenario development; institutional coordination and accountability; policy review and learning; and legal, ethical, and public-trust requirements.
Research Findings: The findings indicate that, despite its important role in setting broad national directions, the 1404 Vision Document had limitations in establishing clear, traceable links among goals, indicators, data, institutional responsibilities, implementation arrangements, reporting, and periodic review. Evidence from economic performance, science and technology, welfare, and regional standing also shows uneven performance and difficulty tracing the chain from goal-setting to policy feedback. The comparative analysis shows that the effectiveness of big data and artificial intelligence depends less on technology alone than on data quality and interoperability, institutional coordination, human oversight, transparency, and accountability. The study develops three exploratory scenarios for the 1430 horizon: continued fragmented governance, dispersed digitalization, and adaptive data-driven governance.
Limitations & Consequences: The study relies on documents and secondary evidence and does not test causal relationships between individual factors and the achievement of vision objectives. The scenarios are exploratory and require further validation through expert-based research, administrative data, and sector-specific evaluations.
Practical Consequences: The 1430 Vision should link every broad objective to measurable indicators, baselines, data sources, responsible institutions, implementation arrangements, financing sources, periodic reporting, and midterm review mechanisms. Big data and artificial intelligence should be deployed gradually and problem-specifically, alongside human oversight and clear rules for data protection and accountability.
Innovation or value of the Article: The article develops an adaptive-governance framework for national visions by connecting vision evaluation with data governance, foresight, and artificial intelligence. Rather than treating technology as an independent objective, it conceptualizes big data and artificial intelligence as tools to strengthen analysis, monitoring, learning, and policy adjustment.
Paper Type: Original Paper
کلیدواژهها English
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