SmartSustain Recommender System: Navigating Sustainability Trade-offs in Personalized City Trip Planning

2025-10-20

AI Summary

Tourism significantly contributes to global carbon emissions and overtourism, necessitating sustainable recommendation systems that balance informational utility with behavioral guidance. This paper proposes a personalized urban travel recommendation system that innovatively integrates CO₂-equivalent (CO₂e) emissions, destination popularity, and seasonality. It employs interactive city cards, dynamic banner notifications, and real-time animated environmental metrics to visualize multidimensional trade-offs—namely environmental impact, cost, convenience, and user interest. The system leverages an interest-matching algorithm, a responsive frontend, and a real-time data feedback loop to enable dynamic comparison of alternatives and promote low-carbon options. A preliminary user study (N=21) demonstrates high usability and perceived effectiveness, revealing statistically significant improvements in users’ awareness of and willingness to adopt sustainable travel decisions.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Humans and AI: Intelligent User Interfaces
• Data Mining & Knowledge Management: Recommender Systems

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Tourism is a major contributor to global carbon emissions and over-tourism, creating an urgent need for recommender systems that not only inform but also gently steer users toward more sustainable travel decisions. Such choices, however, often require balancing complex trade-offs between environmental impact, cost, convenience, and personal interests. To address this, we present the SmartSustain Recommender, a web application designed to nudge users toward eco-friendlier options through an interactive, user-centric interface. The system visualizes the broader consequences of travel decisions by combining CO2e emissions, destination popularity, and seasonality with personalized interest matching. It employs mechanisms such as interactive city cards for quick comparisons, dynamic banners that surface sustainable alternatives in specific trade-off scenarios, and real-time impact feedback using animated environmental indicators. A preliminary user study with 21 participants indicated strong usability and perceived effectiveness. The system is accessible at https://smartsustainrecommender.web.app.

Problem

• Balancing environmental impact with personal travel preferences
• Addressing tourism's carbon emissions through sustainable recommendations
• Navigating trade-offs between sustainability, cost and convenience

Innovation

• Interactive city cards for quick travel comparisons
• Dynamic banners surface sustainable alternative options
• Real-time feedback with animated environmental indicators