Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Do low-carbon rewards incentivize people to ridesplitting? Evidence from structural analysis
https://orcid.org/0000-0002-2387-8030
https://orcid.org/0000-0002-1919-0794
Abstract Ridesplitting is a pooled version of a ridesourcing service that can reduce emissions per trip compared with exclusive ridehailing. However, it only takes a small share of the ridesourcing market currently. Fiscal and social incentives are potential leverage tools to attract passengers from solo hailed rides. This study aims to quantitatively identify the effects of carbon credits (CC) and monetary rewards (MR) on people's willingness to adopt ridesplitting. The theory of planned behavior realized by structural equation modeling decomposes the factors which affect passengers' intention and actual action on choosing ridesplitting. Confirmatory factor analysis suggests that pro-environmental attitudes do not directly force people to ridesplitting. Path effect analysis shows that subjective norms and perceived behavioral control significantly affect ridesplitting intentions. Immediate effect regression reveals that CC has greater direct effects on ridesplitting intention than MR (4.5 times more effective). Moderating effect analysis shows the MR effect reduces while the CC effect enhances when increasing the incentive value. The results encourage policymakers and operation designers to consider better marketing schemes combining monetary and social incentives to promote ridesplitting and to gain better fiscal and environmental benefits from ridesourcing systems.
Do low-carbon rewards incentivize people to ridesplitting? Evidence from structural analysis
https://orcid.org/0000-0002-2387-8030
https://orcid.org/0000-0002-1919-0794
Abstract Ridesplitting is a pooled version of a ridesourcing service that can reduce emissions per trip compared with exclusive ridehailing. However, it only takes a small share of the ridesourcing market currently. Fiscal and social incentives are potential leverage tools to attract passengers from solo hailed rides. This study aims to quantitatively identify the effects of carbon credits (CC) and monetary rewards (MR) on people's willingness to adopt ridesplitting. The theory of planned behavior realized by structural equation modeling decomposes the factors which affect passengers' intention and actual action on choosing ridesplitting. Confirmatory factor analysis suggests that pro-environmental attitudes do not directly force people to ridesplitting. Path effect analysis shows that subjective norms and perceived behavioral control significantly affect ridesplitting intentions. Immediate effect regression reveals that CC has greater direct effects on ridesplitting intention than MR (4.5 times more effective). Moderating effect analysis shows the MR effect reduces while the CC effect enhances when increasing the incentive value. The results encourage policymakers and operation designers to consider better marketing schemes combining monetary and social incentives to promote ridesplitting and to gain better fiscal and environmental benefits from ridesourcing systems.
Do low-carbon rewards incentivize people to ridesplitting? Evidence from structural analysis
https://orcid.org/0000-0002-2387-8030
https://orcid.org/0000-0002-1919-0794
Abstract Ridesplitting is a pooled version of a ridesourcing service that can reduce emissions per trip compared with exclusive ridehailing. However, it only takes a small share of the ridesourcing market currently. Fiscal and social incentives are potential leverage tools to attract passengers from solo hailed rides. This study aims to quantitatively identify the effects of carbon credits (CC) and monetary rewards (MR) on people's willingness to adopt ridesplitting. The theory of planned behavior realized by structural equation modeling decomposes the factors which affect passengers' intention and actual action on choosing ridesplitting. Confirmatory factor analysis suggests that pro-environmental attitudes do not directly force people to ridesplitting. Path effect analysis shows that subjective norms and perceived behavioral control significantly affect ridesplitting intentions. Immediate effect regression reveals that CC has greater direct effects on ridesplitting intention than MR (4.5 times more effective). Moderating effect analysis shows the MR effect reduces while the CC effect enhances when increasing the incentive value. The results encourage policymakers and operation designers to consider better marketing schemes combining monetary and social incentives to promote ridesplitting and to gain better fiscal and environmental benefits from ridesourcing systems.
Do low-carbon rewards incentivize people to ridesplitting? Evidence from structural analysis
Wang, Lei (Autor:in) / Li, Wenxiang (Autor:in) / Weng, Jinxian (Autor:in) / Zhang, Dong (Autor:in) / Ma, Wanjing (Autor:in)
Transportation ; 50
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
BKL:
55.80$jVerkehrswesen$jTransportwesen: Allgemeines
/
55.80
Verkehrswesen, Transportwesen: Allgemeines
/
74.75$jVerkehrsplanung$jVerkehrspolitik
/
74.75
Verkehrsplanung, Verkehrspolitik
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