In the context of sustainable transition, the factors that impact the decision to purchase electric vehicles (EVs) have garnered significant interest. However, existing research predominantly concentrates on the promotional factors while disregarding an examination of the resistance effects. Drawing on the innovation resistance theory (IRT), this study aims to investigate the influence of three functional barriers (usage, value, and risk) and two psychological barriers (tradition and image) on consumers’ intention to purchase EVs. Additionally, we also analyze the moderating effect of environmental concern and incentive policy. Based on a survey of 297 respondents in China, we used SPSS 26.0 and AMOS 24.0 to verify our hypothesis. Our findings indicate that usage, value, risk, and tradition barriers negatively affect EV purchase intentions. Moreover, the negative relationship between functional barriers and EV purchase intentions is weaker for a strong incentive policy. Furthermore, we found that Gen Y and households with private car consumers are more willing to purchase EVs. These findings contribute to extending the applicability of IRT to the sustainable transportation field. They also offer practical guidance for EV enterprises with regard to marketing strategies that effectively mitigate the functional and psychological barriers to enhance profits, and for policymakers to better stimulate the development of the EV market.

Electric Vehicles (EVs) are considered to be a potential viable technology to address the persistent unsustainable problems in transport sector. In this paper, we focus on analyzing the transition processes of EVs in China because the sustainability of developing countries is essential for the worldwide sustainability. The two-round demonstration programs of EVs in China were analyzed by adopting the strategic niche management (SNM) approach so as to find out what niche protection has been provided and which obstacles hamper the further development of EVs. The results show that the financial subsidy is the most important protective measure. However, the diffusion results of EVs in different pilot cities are greatly different. The main reason lies in the uneven geographical landscape. In addition, some obstacles were exposed during the niche internal processes including low quality of expectations and poor alignment within the network. Based on the analysis results, we develop a list of suggestions that are important to consider when developing EVs.

Comprehensively understanding how the policy influences the sustainability transition of the automotive industry is a critical focus in recent years. This paper focuses on the dual-credit policy, an underexplored but critical policy in China, and examines how it would influence the transition of automotive industry. To achieve this goal, an SD model is developed to simulate the effect of policy parameters on the policy objectives by considering the interaction of production, technology and market. The findings reveal that this policy can in general promote the sustainable development of the automotive industry by greatly decreasing its overall energy consumption. However, its impact on the market share of new energy vehicles is limited. Based on the results, some policy suggestions are proposed so as to improve the effectiveness of the dual-credit policy.

The combination of car-sharing and electric vehicles can increase the acceptance of electric vehicles and facilitate car-sharing to be a more sustainable means of transport. However, this also poses more challenges for the good planning of electric car-sharing systems. To assist car-sharing companies in improving the planning decisions, this paper developed an evaluation framework from a comprehensive view. In the first step, four evaluation criteria were identified according to the planning process: construction of stations; routine inspection; vehicle usability and relocation management; and the maintenance and replacement of stations. Then, a combinatorial method based on analytic hierarchy process (AHP), cost-benefit analysis (CBA), and Voronoi diagram (VD) is developed to determine the relative weight of the four criteria and evaluate the alternative. Finally, the evaluation framework was applied in a realistic case of EVCARD, which is the most influential electric car-sharing company in China. The performance of two different operational districts of EVCARD—Jingan and Changning—were compared. The results showed that vehicle usability and relocation management is the greatest criterion influencing the planning performance of the electric car-sharing system in China, and that routine inspection is a negligible but important factor. According to the relative scores, Jiagan District performed better than Changning district.

The Yangtze River Delta (YRD) is China’s largest urban agglomeration with a rapid urbanization process. This paper analyzes the dynamic relationship between urbanization rate, energy intensity, GDP per capita, and population with CO₂ emissions in YRD over 1990–2011 based on the extended STIRPAT model, impulse response function, and variance decomposition. A support vector machine model was constructed to further predict the scenarios of YRD’s CO₂ emissions from 2015–2020. The results show that YRD’s CO₂ emissions continuously increased during the sample period and are predicted to increase over 2015–2020. Energy intensity is the most influential factor, both in the short and long term, and the total population contributes the least. However, the influencing magnitude of energy intensity tends to decrease in the long term. The increase of urbanization rate is still accompanied by the increase of CO₂ emissions in YRD, but an inverted-U shape relationship between them may exist in the long term. The contribution of GDP per capita to CO₂ emissions is higher than the population and urbanization rate, and its contribution rate for CO₂ emissions is growing. The Kuznets curve does not exist in the current YRD.