Modeling low-carbon travel mode choice by incorporating carbon incentive latent variable

doi:10.3785/j.issn.1008-973X.2024.08.010

Journal of ZheJiang University (Engineering Science)

2024, Vol. 58

Issue (8): 1628-1635 DOI: 10.3785/j.issn.1008-973X.2024.08.010

Modeling low-carbon travel mode choice by incorporating carbon incentive latent variable

Yan HE1,2(

),Yilin SUN1,3,4,*(

),Zhijian ZHAO4,Yang SHU1

1. College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
2. Center for Balanced Architecture, Zhejiang University, Hangzhou 310000, China
3. The Architectural Design and Research Institute of Zhejiang University Limited Company, Hangzhou 310013, China
4. Polytechnic Institute, Zhejiang University, Hangzhou 310058, China

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Abstract

The latent variables affecting travelers’ intention to low-carbon travel were comprehensively considered based on the theory of planned behavior and the theory of value-belief-norm in order to analyze travelers’ low-carbon travel behaviors and internal mechanisms. A multi-cause and multi-indicator model was constructed by using the empirical data of Hangzhou, and the values of latent variables were calibrated. A hybrid choice model and a Logit model without latent variables were constructed to compare and analyze travelers’ weekday mode choice behavior. A binary hybrid choice model was constructed to analyze the travel behavior shift of high carbon people under carbon incentives. Results show that the latent variables such as attitude, perceived behavioral control, and view of incentive significantly affect the travelers' willingness to travel in a low-carbon way and the choice of travel modes. The hybrid choice model has a better goodness-of-fit than the Logit model without latent variables, and the prediction accuracy improves by 4.6%. 64.4% of the high-carbon individuals tends to choose low-carbon modes under carbon incentives, showing that the carbon incentives can effectively promote travel modes shift behavior. There is some heterogeneity of the variables attitude and travel time in travel mode shift behavior.

Key words： transportation engineering low-carbon travel mode choice carbon incentive hybrid choice model

Received: 19 July 2023 Published: 23 July 2024

CLC:

U 491

Fund: 浙江省“尖兵”“领雁”研发攻关计划资助项目（2023C01240）;国家自然科学基金资助项目（52131202）.

Corresponding Authors: Yilin SUN E-mail: yanhe@zju.edu.cn;yilinsun@zju.edu.cn

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Cite this article:

Yan HE,Yilin SUN,Zhijian ZHAO,Yang SHU. Modeling low-carbon travel mode choice by incorporating carbon incentive latent variable. Journal of ZheJiang University (Engineering Science), 2024, 58(8): 1628-1635.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2024.08.010 OR https://www.zjujournals.com/eng/Y2024/V58/I8/1628

融合碳激励潜变量的低碳出行方式选择模型

以计划行为理论与价值-信念-规范理论为理论基础，综合考虑影响出行者低碳出行意愿的潜变量，以分析出行者低碳出行行为及内在机理. 基于杭州市实证数据，建立多原因多指标模型，标定潜变量适配值. 构建混合选择模型与无潜变量的Logit模型，对比分析出行者工作日方式的选择行为. 建立二元混合选择模型，分析碳激励下高碳人群的出行行为转变. 结果表明，态度、知觉感知控制、激励态度等潜变量显著影响出行者的低碳出行意愿与出行方式选择，混合选择模型比无潜变量的Logit模型具有更好的拟合优度，预测精度提升了4.6%，碳激励下64.4%的高碳人群倾向于选择低碳出行，碳激励可以有效促进公众的出行方式转变，变量态度、出行时间在公众出行方式转变上存在一定的异质性.

关键词： 交通工程, 低碳出行, 方式选择, 碳激励, 混合选择模型

Fig.1 Framework of hybrid choice model

Tab.1 Latent variables scale

Fig.2 Distribution of socio-economic attributes

Tab.2 Sample reliability and convergent validity tests

Fig.3 Sample convergent validity test

Tab.3 Goodness-of-fit indicator for MIMIC

Fig.4 Result of MIMIC model for car

Fig.5 Result of MIMIC model for public transit

Fig.6 Result of MIMIC model for non-motorized transport

Tab.4 Parameter estimation result of mode choice model

Fig.7 Travel mode shifts under carbon incentives

Tab.5 Estimation results of binary hybrid choice model


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