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Main Authors: Liu, Bing, Liao, Yuan, Yeh, Sonia, Cats, Oded, Nielsen, Kristian S., Dong, Zhenning, Wang, Yong, Li, Yi, Liu, Yanli, Ni, Zirui, Ma, Xiaolei
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.09237
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author Liu, Bing
Liao, Yuan
Yeh, Sonia
Cats, Oded
Nielsen, Kristian S.
Dong, Zhenning
Wang, Yong
Li, Yi
Liu, Yanli
Ni, Zirui
Ma, Xiaolei
author_facet Liu, Bing
Liao, Yuan
Yeh, Sonia
Cats, Oded
Nielsen, Kristian S.
Dong, Zhenning
Wang, Yong
Li, Yi
Liu, Yanli
Ni, Zirui
Ma, Xiaolei
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2511_09237
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Scaling behavioral incentives for low-carbon mobility through digital platforms
Liu, Bing
Liao, Yuan
Yeh, Sonia
Cats, Oded
Nielsen, Kristian S.
Dong, Zhenning
Wang, Yong
Li, Yi
Liu, Yanli
Ni, Zirui
Ma, Xiaolei
Applications
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.
title Scaling behavioral incentives for low-carbon mobility through digital platforms
topic Applications
url https://arxiv.org/abs/2511.09237