Investigating the Effects of Eco-Friendly Service Options on Rebound Behavior in Ride-Hailing

2026-02-10

AI Summary

This study investigates how eco-friendly service options (EFSOs), despite their intent to reduce emissions, may inadvertently trigger rebound effects by leading users to justify higher-carbon transportation choices through their “green” labeling. Through a within-subjects online experiment (N=75) in the ride-hailing context, the research compares five EFSO designs—no option, minimal presentation, CO₂-equivalent display, gamification, and social framing—on users’ decisions between walking and taking a ride. Complemented by qualitative interviews, the findings reveal that EFSOs lacking explicit ecological feedback significantly increase ride-hailing uptake, as users leverage the environmental label to rationalize convenience-driven choices. This work is the first in human-computer interaction to systematically demonstrate this behavioral paradox and proposes a novel design perspective that accounts for moral licensing, underscoring the critical role of clear ecological feedback in mitigating rebound effects.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Multiagent Systems: Mechanism Design
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Eco-friendly service options (EFSOs) aim to reduce personal carbon emissions, yet their eco-friendly framing may permit increased consumption, weakening their intended impact. Such rebound effects remain underexamined in HCI, including how common eco-feedback approaches shape them. We investigate this in an online within-subjects experiment (N=75) in a ride-hailing context. Participants completed 10 trials for five conditions (No EFSO, EFSO - Minimal, EFSO - CO2 Equivalency, EFSO - Gamified, EFSO - Social), yielding 50 choices between walking and ride-hailing for trips ranging from 0.5mi - 2.0mi (0.80km - 3.22km). We measured how different EFSO variants affected ride-hailing uptake relative to a No EFSO baseline. EFSOs lacking explicit eco-feedback metrics increased ride-hailing uptake, and qualitative responses indicate that EFSOs can make convenience-driven choices more permissible. We conclude with implications for designing EFSOs that begin to take rebound effects into account.

Problem

• rebound effect
• eco-friendly service options
• ride-hailing
• carbon emissions
• eco-feedback

Innovation

• rebound effect
• eco-friendly service options
• eco-feedback
• sustainable HCI
• ride-hailing