Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to transportation, energy utilization, and resource consumption collectively precipitating substantial ecological impacts. Recommender systems, which generate personalized suggestions based on user preferences and historical interaction data, exert considerable influence on individual behavioral trajectories. However, conventional recommender systems predominantly optimize for user engagement and economic metrics, inadvertently neglecting the environmental and societal ramifications of their recommendations, potentially catalyzing over-consumption and reinforcing unsustainable behavioral patterns. Given their instrumental role in shaping user decisions, there exists an imperative need for sustainable recommender systems that incorporate sustainability principles to foster eco-conscious and socially responsible choices. This comprehensive survey addresses this critical research gap by presenting a systematic analysis of sustainable recommender systems. As these systems can simultaneously advance multiple sustainability objectives--including resource conservation, sustainable consumer behavior, and social impact enhancement--examining their implementations across distinct application domains provides a more rigorous analytical framework. Through a methodological analysis of domain-specific implementations encompassing transportation, food, buildings, and auxiliary sectors, we can better elucidate how these systems holistically advance sustainability objectives while addressing sector-specific constraints and opportunities. Moreover, we delineate future research directions for evolving recommender systems beyond sustainability advocacy toward fostering environmental resilience and social consciousness in society.

翻译：人类行为模式与消费范式已成为环境退化与气候变化的关键决定因素，涉及交通、能源利用及资源消耗的日常决策共同引发了显著的生态影响。推荐系统基于用户偏好和历史交互数据生成个性化建议，对个体行为轨迹产生重要影响。然而，传统推荐系统主要优化用户参与度和经济指标，无意中忽视了推荐行为的环境与社会效应，可能助长过度消费并强化不可持续的行为模式。鉴于推荐系统在塑造用户决策中的关键作用，亟需构建融入可持续性原则的推荐系统，以促进生态友好型和社会责任型选择。本综述通过系统分析可持续推荐系统来填补这一关键研究空白。由于此类系统能同时推进多重可持续性目标——包括资源保护、可持续消费行为和社会影响提升——考察其在不同应用领域中的实施可为分析提供更严谨的框架。通过对交通、食品、建筑及辅助领域的具体实施方案进行方法论分析，我们能更清晰地阐释这些系统如何整体推进可持续性目标，同时应对特定领域的约束与机遇。此外，本文还界定了未来研究方向，推动推荐系统从可持续性倡导向培育社会环境韧性与社会意识演进。