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Advancing Sustainability via Recommender Systems: A Survey

Xin Zhou, Lei Zhang, Honglei Zhang, Yixin Zhang, Xiaoxiong Zhang, Jie Zhang, Zhiqi Shen

TL;DR

This comprehensive survey addresses this critical research gap by presenting a systematic analysis of sustainable recommender systems and delineates future research directions for evolving recommender systems beyond sustainability advocacy toward fostering environmental resilience and social consciousness in society.

Abstract

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.

Advancing Sustainability via Recommender Systems: A Survey

TL;DR

This comprehensive survey addresses this critical research gap by presenting a systematic analysis of sustainable recommender systems and delineates future research directions for evolving recommender systems beyond sustainability advocacy toward fostering environmental resilience and social consciousness in society.

Abstract

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.

Paper Structure

This paper contains 30 sections, 10 figures.

Table of Contents

  1. Introduction
  2. Background
  3. Sustainability
  4. Recommender Systems
  5. Sustainable Travel Recommendation
  6. POI Recommendation
  7. Route Recommendation
  8. Transportation Recommendation
  9. Sustainable Food Recommendation
  10. Healthy-awareness Food Recommendation
  11. Environmental-friendly Food Recommendation
  12. Sustainable Building Recommendation
  13. Recommender Systems in Residential Buildings
  14. Recommender Systems in Commercial and Large Buildings
  15. Broader applications of sustainable recommendations
  16. ...and 15 more sections

Figures (10)

  • Figure 1: Global $\textrm{CO}_\textrm{2}$ emissions trends (1960-2023) and a comparative analysis of Microsoft and Google's carbon footprints.
  • Figure 2: Hierarchical taxonomy of recommender system categories and their applications in advancing sustainability initiatives.
  • Figure 3: An example of the sustainable POI recommendation.
  • Figure 4: Illustration of sustainable route and transportation recommendations.
  • Figure 5: Illustration of the sustainable food recommendation.
  • ...and 5 more figures