Characteristics and attitudes of actual electric vehicle adopters from different classes of cities

被引:6
作者
Wang, Pinxi [1 ,2 ]
Guan, Chengyi [1 ]
Zhuge, Chengxiang [3 ,4 ]
Sun, Mingdong [5 ]
机构
[1] Beijing Transport Inst, 9 Liuliqiao South lane, Fengtai Dist, Beijing 100073, Peoples R China
[2] Beijing Key Lab Transport Energy Conservat & Emiss, 9 Liuliqiao South lane, Fengtai Dist, Beijing 100073, Peoples R China
[3] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hung Hom, Hong Kong, Peoples R China
[4] Hong Kong Polytech Univ Shenzhen Res Inst, Shenzhen, Peoples R China
[5] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol Co, 3 Shangyuancun, Xizhimenwai, Beijing 100044, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicle; Early adopters; Class of a city; Vehicle Price; Charging infrastructure; Financial incentives; INCENTIVES; INTENTIONS; BARRIERS; MOBILITY; ADOPTION; IMPACTS; BUYERS; MARKET;
D O I
10.1016/j.rtbm.2021.100728
中图分类号
F [经济];
学科分类号
02 ;
摘要
The pathways to the uptake of Electric Vehicles (EVs) may vary across cities and regions. This paper investigated characteristics and attitudes of early EV adopters from three different classes of Chinese cities, namely Beijing, Wuhan and Shijiazhuang, which were defined as the upper, middle and lower classes of cities, respectively. A questionnaire survey was conducted in 2017 in the three study areas separately, targeting at actual EV adopters. In total, 1119 samples were collected. Discrete choice models were developed to relate decisions and attitudes of EV adopters to their sociodemographic characteristics and the class of a city which they were from. The results suggested that the class of a city was a statistically significant factor to several of the decisions and attitudes, including the reason for choosing EVs, actual payment made for EVs owned, preferences towards EVs and demand for public charging infrastructure. Specifically, the early adopters from the lower class of city tended to pay less for purchasing EVs. Also, they tended to agree on that EVs were generally better than Conventional Vehicles (CVs) given that their purchase costs were the same. As a result, over 80% of them would still purchase an EV given that no financial incentives were provided. Furthemore, those early EV adopters from the lower class of city tended to accept a lower density of charging stations. Finally, the potential applications of the empirical findings in policy making and infrastructure planning were discussed.
引用
收藏
页数:12
相关论文
共 41 条
[21]   Identifying and characterizing potential electric vehicle adopters in Canada: A two-stage modelling approach [J].
Mohamed, Moataz ;
Higgins, Chris ;
Ferguson, Mark ;
Kanaroglou, Pavlos .
TRANSPORT POLICY, 2016, 52 :100-112
[22]   Future standard and fast charging infrastructure planning: An analysis of electric vehicle charging behaviour [J].
Morrissey, Patrick ;
Weldon, Peter ;
O'Mahony, Margaret .
ENERGY POLICY, 2016, 89 :257-270
[23]   How large is the effect of financial incentives on electric vehicle sales? - A global review and European analysis [J].
Muenzel, Christiane ;
Ploetz, Patrick ;
Sprei, Frances ;
Gnann, Till .
ENERGY ECONOMICS, 2019, 84
[24]   Factors influencing early battery electric vehicle adoption in Ireland [J].
Mukherjee, Sanghamitra Chattopadhyay ;
Ryan, Lisa .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2020, 118
[25]   Spatial planning of public charging points using multi-dimensional analysis of early adopters of electric vehicles for a city region [J].
Namdeo, A. ;
Tiwary, A. ;
Dziurla, R. .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2014, 89 :188-200
[26]   Who will buy electric vehicles? Identifying early adopters in Germany [J].
Ploetz, Patrick ;
Schneider, Uta ;
Globisch, Joachim ;
Duetschke, Elisabeth .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2014, 67 :96-109
[27]   Spatiotemporal model for estimating electric vehicles adopters [J].
Rodrigues, Joao L. ;
Bolognesi, Hugo M. ;
Melo, Joel D. ;
Heymann, Fabian ;
Soares, F. J. .
ENERGY, 2019, 183 :788-802
[28]  
Rolim CC, 2014, EUR J TRANSP INFRAST, V14, P229
[29]   Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption [J].
Saarenpaa, Jukka ;
Kolehmainen, Mikko ;
Niska, Harri .
APPLIED ENERGY, 2013, 107 :456-464
[30]   The influence of financial incentives and other socio-economic factors on electric vehicle adoption [J].
Sierzchula, William ;
Bakker, Sjoerd ;
Maat, Kees ;
van Wee, Bert .
ENERGY POLICY, 2014, 68 :183-194