Sustainable Development in Industry and Society: Insights from AI, Energy, and Market Dynamics
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Abstract
This review examines sustainable development in industry and society through the lens of artificial intelligence, market dynamics, organizational behavior, digital platforms, and urban mobility. Sequential behavior modeling and context-aware personalization enable more efficient digital ecosystems while reducing resource waste and enhancing user engagement. Market-oriented development, capacity sharing, and behavioral incentives promote resource-efficient industrial growth and resilient labor systems. Data-driven analytics improve platform sustainability by optimizing user retention and minimizing operational inefficiencies. Mobility modeling and integrated urban planning further support environmental and social sustainability in cities. By synthesizing these interdisciplinary insights, the review highlights strategies for aligning technological, economic, and behavioral systems with long-term sustainability goals, and outlines future directions involving multi-modal AI, cross-domain integration, and responsible data governance.
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