Determinants and the Moderating Effects of Individual Characteristics on Autonomous Vehicle Adoption in China

被引:6
|
作者
Tang, Tianpei [1 ]
Wang, Xiwei [1 ]
Wu, Jianbing [2 ]
Yuan, Meining [1 ]
Guo, Yuntao [3 ]
Xu, Xunqian [1 ]
机构
[1] Nantong Univ, Sch Transportat & Civil Engn, Nantong 226019, Peoples R China
[2] Nantong Municipal Engn Design Inst Co Ltd, Nantong 226000, Peoples R China
[3] Tongji Univ, Dept Traff Engn, Minist Educ, Key Lab Rd & Traff Engn, Shanghai 201804, Peoples R China
基金
中国国家自然科学基金;
关键词
autonomous mobility; modified technology acceptance model; policy measure; moderating effects; TECHNOLOGY ACCEPTANCE MODEL; USER ACCEPTANCE; ELECTRIC VEHICLES; WIDESPREAD ADOPTION; POLICY; INTENTION; IMPACT; PREFERENCES; ATTITUDES; BARRIERS;
D O I
10.3390/ijerph20010043
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Along with the increasing popularity of autonomous vehicles (AVs), urban livability and public health will be enhanced due to ecofriendly issues: alleviated traffic congestion, lower car ownership, and reduced transport emissions. However, some emerging issues, including public safety, trust, privacy, reliability, underdeveloped legislation, and liability, may deter user intentions to adopt an AV. This study introduces an extensive factor, playfulness, into the technology acceptance model (TAM) to quantify the impacts of psychological factors (perceived usefulness, perceived ease of use, and perceived playfulness) on AV adoption intention. This study proposes four AV-related policy measures (financial incentivization, information dissemination, convenience, and legal normalization) and examines how policy measures motivate users to adopt an AV to facilitate public safety. Furthermore, this study investigated the moderating effects of demographic factors on the relationships between independent variables and AV adoption intention. Two models were proposed and estimated using a total of 1831 survey responses in China. The psychology-related and policy-related models explained 62.2% and 33.6% of the variance in AV adoption intention, respectively. The results suggest that perceived playfulness (beta = 0.524, p < 0.001) and information dissemination (beta = 0.348, p < 0.001) are the most important influencing factors of AV adoption intention. In addition, demographic factors (gender, education, income, the number of private cars owned by a family, and types of cities) can moderate the effects of psychological factors and policy measures on user intentions to adopt an AV. These insights can be employed to design more cost-effective policies and strategies for subgroups of the population to maximize the AV adoption intention.
引用
收藏
页数:17
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