Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (11): 2607-2617.doi: 10.13229/j.cnki.jdxbgxb20210388

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Urban residents' low⁃carbon travel intention after implementation of driving restriction policy

Zhuang-lin MA1(),Shan-shan CUI2,Da-wei HU1   

  1. 1.College of Transportation Engineering，Chang'an University，Xi'an 710064，China
    2.Shandong Provincial Communications Planning and Design Institute Group Co. ，Ltd. ，Jinan 250031，China
  • Received:2021-04-30 Online:2022-11-01 Published:2022-11-16

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Abstract:

To explore the influencing factors and interaction mechanism of urban residents' low-carbon travel intention after implementing the driving restriction policy， the multiple indicators multiple cause （MIMIC） model is developed to construct urban residents' low-carbon travel intention model under the driving restriction policy， concerning the theory of planned behavior and technology acceptance model. The revealed preference（RP） survey was used to design the questionnaire， and 637 valid samples was obtained through network survey and field survey. Finally， the empirical test was conducted by the MIMIC model. The results show that policy attitude， policy effect perception and problem perception have a direct and significant impact on travel intention. Policy attitude and policy effect perception are mediating variables， and policy effect perception and subjective norms could indirectly affect travel intention through policy attitude， and problem perception could indirectly affect travel intention through policy effect perception. The total effect value of potential variables on urban residents' low-carbon travel intention after implementing the driving restriction policy rank from large to small as policy effect perception， policy attitude， problem perception， and subjective norms. Socio-economic attributes are moderating variables， which can indirectly affect travel intention by adjusting travelers' psychological perception factors. The research conclusions could provide the theoretical support for traffic management authorities to improve the efficiency of driving restriction policy and guide residents to low-carbon travel.

Key words: engineering of communications and transportation system, driving restriction policy, multiple indicators multiple cause model, travel intention, theory of planned behavior, technology acceptance model

CLC Number: 

  • U491

Fig.1

Framework of TPB"

Fig.2

Framework of TAM"

Fig.3

Framework of hypothesis model"

Fig.4

MIMIC model of urban residents' travel intention after implementation of driving restriction policy"

Table 1

Description of variable"

类别变量代码定义
问题感知对空气污染问题的感知PS1

非常不严重=1，较不严重=2，一般=3，

较严重=4，非常严重=5

对交通拥堵问题的感知PS2
政策效果感知对限行在缓解交通拥堵方面的效果感知PE1

没有效果=1，效果不明显=2，一般=3，

略有效果=4，效果显著=5

对限行在缓解空气污染方面的效果感知PE2
对限行在未来缓解交通拥堵方面的效果感知PE3
对限行在未来缓解空气污染方面的效果感知PE4
对限行收益损失比的感知PE5

损失非常多=1，损失多=2，中立=3

收益多=4，收益非常多=5

主观规范身边的家人和朋友对限行政策的接受度SN1

非常不支持=1，比较不支持=2，中立=3，

比较支持=4，非常支持=5

身边的家人和朋友是否支持你接受限行政策SN2
政策认知对限行政策的了解情况PK

非常不了解=1，不了解=2，

一般=3，了解=4，非常了解=5

政策态度对限行政策的接受度PA

非常不支持=1，比较不支持=2，中立=3，

比较支持=4，非常支持=5

出行意向日常出行中更倾向于选择低碳环保的出行方式TI一定不=1，几乎不=2，偶尔=3，经常=4，一定=5
社会经济属性性别xsex女性=1，男性=0
年龄（＜25岁）xage1＜25岁=1，否则=0
年龄（25~35岁）*xage225~35岁=1，否则=0
年龄（36~45岁）xage336~45岁=1，否则=0
年龄（45岁以上）xage445岁以上=1，否则=0
学历xedu高中及以下=1，本科及以上=0
职业xjob固定职业=1，自由职业=0
低收入（＜5000元）xinc1＜5000元=1，否则=0
中收入（5000~15 000元）xinc25000~15 000元=1，否则=0
高收入（＞15 000元）*xinc3＞15 000元=1，否则=0
是否接送孩子xpic是=1，否=0
私家车拥有量xcar2辆及以上=1，不多于1辆=0

Fig.5

Sample characteristics of the respondents"

Table 2

Results of reliability and validity test"

潜在变量题项KMO检验Bartlett球形度检验Cronbach's αAVECR
问题感知PS10.747<0.0010.6580.5100.661
PS2
效果感知EP10.747<0.0010.7820.5300.796
EP2
EP3
EP4
EP5
主观规范SN10.747<0.0010.7240.6880.763
SN2
政策认知PK0.747<0.0011.0001.0001.000
政策态度PA1.0001.0001.000
出行意图TI1.0001.0001.000

Table 3

Test of goodness-of-fit"

拟合指标χ2/dfRMSEAGFITLI
拟合结果值2.4800.0480.9110.918
拟合成功建议值2~5之间，越小越好<0.08>0.90>0.90

Fig.6

Path relationships between latent variables"

Table 4

Effect values between the latent variables"

项目直接效应间接效应总效应
政策态度→出行意向0.535-0.535
问题感知→政策态度--0.288-0.288
问题感知→出行意向0.655-0.3150.340
政策效果感知→政策态度0.502-0.502
政策效果感知→出行意向0.2810.2690.550
主观规范→政策态度0.195-0.195
主观规范→出行意向-0.1040.104
问题感知→政策效果感知-0.573--0.573

Fig.7

Path relationship of latent factors and causal variable"

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