Scaling behavioral incentives for low-carbon mobility through digital platforms

TL;DR

This study provides large-scale empirical evidence that digital platform-based carbon incentives significantly increase green travel modes and reduce car use, demonstrating their potential for scalable low-carbon mobility solutions.

Contribution

First large-scale empirical evaluation of carbon incentives embedded in a MaaS platform, showing their effectiveness and persistence in promoting low-carbon travel behaviors.

Findings

20.3% monthly increase in public transport and bike trips

1.8% daily reduction in gasoline car use

Approx. 94,000 tons annual carbon reduction

Abstract

Meeting global carbon reduction targets requires large-scale behavioral shifts in everyday travel. Yet, real-world evidence on how to motivate such large-scale behavioral change remains scarce. We evaluate a carbon incentive program embedded in a MaaS platform in Beijing, China, using data from 3.9 million participants and 4.8 billion multimodal trips over 395 days. The program increased reported public transport and bike travel by 20.3% per month and reduced gasoline car use by 1.8% per day, yielding an annual carbon reduction of ~94,000 tons, or 5.7% of certified reductions in Beijing's carbon market. Although effects diminished over time, participants still made 12.8% more green trips per month after eight months, indicating persistence. These results provide the first large-scale empirical evidence of carbon incentives in MaaS and highlight their potential to inform targeted, city-specific interventions that can scale to support global low-carbon mobility transitions.