Save A Tree or 6 kg of CO2? Understanding Effective Carbon Footprint Interventions for Eco-Friendly Vehicular Choices

TL;DR

The paper investigates how different carbon-emission representations influence eco-friendly vehicle choices in ride-hailing and car rentals. Across multiple studies, raw CO2 figures outperform many equivalencies and social cues in nudging participants toward greener options, though framing, context, and temporality modulate effectiveness. The authors find substantial heterogeneity in responses, suggesting potential for personalized carbon messaging and embeddable eco-feedback designs. They also demonstrate that concepts like collective impact and negative framing can boost green choices, while explicit explanations about equivalencies do not consistently help. The work informs the design of eco-feedback interfaces and advocates broader efforts to raise carbon literacy through diverse, context-aware interventions.

Abstract

From ride-hailing to car rentals, consumers are often presented with eco-friendly options. Beyond highlighting a "green" vehicle and CO2 emissions, CO2 equivalencies have been designed to provide understandable amounts; we ask which equivalencies will lead to eco-friendly decisions. We conducted five ride-hailing scenario surveys where participants picked between regular and eco-friendly options, testing equivalencies, social features, and valence-based interventions. Further, we tested a car-rental embodiment to gauge how an individual (needing a car for several days) might behave versus the immediate ride-hailing context. We find that participants are more likely to choose green rides when presented with additional information about emissions; CO2 by weight was found to be the most effective. Further, we found that information framing - be it individual or collective footprint, positive or negative valence - had an impact on participants' choices. Finally, we discuss how our findings inform the design of effective interventions for reducing car-based carbon-emissions.

Figures (18)

• Figure 1: Equivalencies in the wild. (a) While booking a flight, carbon equivalencies are shown to the buyer. (b) A spool of 3D printer filament with a sticker denoting "This product plants one tree."
• Figure 2: Sub-categories and dimensions of eco-feedback information (reprinted from Sanguinetti et al. sanguinetti2018information with permission from Elsevier).
• Figure 3: An example "Pick your Rideshare" survey question showing information about CO$_2$ emissions in equivalent terms (coal here) for two ridesharing options---a standard ("Ride") and an eco-friendly alternative ("Ride Green").
• Figure 4: Study \ref{['study:1']} (a) Influence of different intervention types on probability that participants chose the Ride Green option for different price differences. Colored dots indicate average probabilities across subjects, error bars indicate 95% confidence intervals, and trend lines indicates the best fitting exponential decay curve. (b) Logistic mixed-effects contrast coefficients comparing the influence of individual intervention types compared to the Baseline condition (dashed line). Error bars indicate 95% confidence intervals.
• Figure 5: MaxDiff responses for the (a) relatability and (b) usefulness of different equivalencies.