AI‐Powered Sustainable Tourism: Unlocking Circular Economies and Overcoming Resistance to Change
研究了泰国旅游业中人工智能与循环经济原则的结合，发现AI增强的预测性废物分析能改善资源管理，但员工对变革的抵制会削弱AI效果，并提出了克服阻力的策略。
ABSTRACT This study examines the integration of artificial intelligence (AI) with circular economy (CE) principles in Thailand's tourism industry. It explores the interactions between AI‐Enhanced Predictive Waste Analytics (AI‐PWA), Regenerative Resource Integration (RRI), Dynamic Material Flow Optimization (DMFO), and AI‐Induced Resistance to Change (AIRC). Using a mixed‐methods approach, qualitative insights from industry stakeholders are combined with quantitative analysis via Partial Least Squares Structural Equation Modeling (PLS‐SEM). Findings reveal that AI‐PWA improves real‐time resource management, driving DMFO and supporting regenerative practices through RRI. However, AIRC moderates AI's effectiveness in sustainability transitions, with concerns such as job displacement, mistrust, and complexity hindering adoption. This study provides actionable strategies to mitigate resistance, enhance stakeholder collaboration, and scale AI adoption in resource‐constrained settings, contributing to SDG 12 and SDG 13. The findings offer practical insights for aligning AI innovations with sustainable development in high‐variability industries.