The impact of different incentive policies on new energy vehicle demand in China's gigantic cities. (September 2022)

• Record Type: Journal Article
• Authors: Xian, Yujiao; Wang, Qian; Fan, Wenrong; Da, Yabin; Fan, Jing-Li
• Is Part Of: Energy policy. Volume 168(2022)
• Publication Date: 2022-09
• Subjects: New energy vehicles -- License plate control -- Lottery -- Auction -- Queueing; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2022.113137
• Languages: English
• ISSNs: 0301-4215

Abstract

Abstract: License plate control and preferential policies are both significant for promoting New Energy Vehicles (NEVs) in China, and it is important to be aware of the impact of different policies on NEV demand. This study first conducts a survey based on questionnaires answered by 572 residents from Beijing and Shanghai. The conditional-logit model and mixed-logit model are then utilized to analyze the impact of different incentive policies (i.e., auction, lottery and queueing), vehicle attributes, and consumer attributes on China's NEV demand in gigantic cities. The results show that, i) the incentive effect of license-plate auction for purchasing NEVs is better than that of license-plate lotteries and license-plate queueing. ii) there is an evident promotion by the tax exemption policies in Beijing and Shanghai. iii) people hope that the rate of change in subsidies for battery electric vehicles (BEVs) is tied to BEV recharge mileage. iv) among those who have a high demand for purchasing a vehicle, their primary purpose is to commute to work. v) those who have BEV, live in other cities, or have urgent purchasing needs are likely not to choose NEVs. Policy implications have been proposed to promote NEVs in China's gigantic cities. Highlights: A survey based on questionnaires is proposed in impact analysis on demand. Different policies, vehicle attributes, and consumer attributes could be identified. Conditional-logit and mixed-logit model are both taken into regression. Application to the auto industry in China's gigantic cities is provided.