Special issue on analytical models and AI for sustainable development–Enhancing decision-making
New research shows analytical models and artificial intelligence are reshaping decision-making for sustainable development in various industries. AI tools like neural networks and optimization algorithms boost production planning, supply chain efficiency, and crisis forecasting. Notable frameworks include dynamic network analysis for innovation and Bayesian methods to correct bias. A surprising finding suggests good governance may result from development, not cause it. The studies highlight gaps in AI use for public transport and regional well-being disparities.
What it examines
This report presents studies on how analytical models and artificial intelligence (AI) can improve decision-making for sustainable development. It covers methods like quantitative modeling, optimization, and data-driven intelligence, aiming to solve real-world problems in areas such as production, governance, health, logistics, and finance.
What it concludes
The research shows that combining AI and analytics boosts efficiency, transparency, and resilience in various sectors. Applications include smarter production planning, better health systems, and stronger financial markets. Future work should focus on expanding these models and encouraging collaboration to support sustainable and data-driven decision-making worldwide.
Evidence objects
Groundbreaking research reveals AI-powered models, like neural networks and optimization algorithms, are revolutionizing decision-making for sustainable development, boosting production planning, supply chain efficiency, and crisis forecasting across diverse industries.
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Innovative frameworks, including dynamic network analysis and Bayesian bias correction, empower smarter, data-driven choices for policymakers and businesses. Notably, good governance may result from development, challenging long-held assumptions about causality.
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Advanced methodsscenario-based optimization, Python patent mining, GIS-integrated modelsshowcase AIs synergy with operations research. Yet, gaps remain: more AI in public transport and addressing regional well-being disparities are urgently needed for resilience.
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This editorial surveys analytical models and AI applications for sustainable development in sectors like manufacturing, logistics, health, and public policy. However, it lacks originality and novelty for quantitative finance, as it neither introduces new financial modeling techniques nor addresses AI adoption in hedge funds, limiting its relevance and impact.
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Raw abstract and provenance
- … the need for advanced analytical tools and artificial intelligence (AI) techniques that can … This work contributes to building AI-enabled financial surveillance systems that …
Source row: 1805 · abstract type: snippet