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Various policies on electric vehicles (EVs) have been implemented in Beijing to promote EV diffusion, but previous research has rarely considered the indirect network effects between EVs and EV charging infrastructures (EVCIs), and has not explored the impact of EVCI-related incentives on EV diffusion. This study aims to enrich the literature by incorporating EVCI development and indirect network effects in EV diffusion. A system dynamic model is proposed to systematically analyse the interactions among consumer, EV manufacturer and EVCI operator and simulate EV diffusion and ECVI investment in Beijing. Multiple scenarios are adopted to investigate the joint effects of the policy mix on EV diffusion. The results indicate that the oil-to-electricity subsidy promoted EVs and EVCIs to a greater extent than the license plate control policy. The EVCI maintenance policy outperformed EVCI construction and production subsidies on EV diffusion. Synergistic effects exist when the oil-to-electricity subsidy is mixed with EVCI-related incentives. This study provides implications for policymakers to promote EV diffusion with innovative and efficient policy instruments. [ABSTRACT FROM AUTHOR]

To reduce traffic congestion and protect the environment, license plate control (LPC) policy has been implemented in Beijing since 2011. In 2019, 100,000 vehicle license plates were distributed, including 60,000 for electric vehicles (EVs) and 40,000 for gasoline vehicle (GVs). However, whether the current license plate allocation is optimal from a social welfare maximization perspective remains unclear. This paper proposes a two-level Stackelberg game, which portrays the interaction between vehicle applicants and the government to quantify the optimal number of EV license plates under the LPC policy in Beijing. The equilibrium number of EV license plates derived from the Stackelberg model is 58,800, which could increase the social welfare by 0.38%. Sensitivity analysis is conducted to illustrate the impact of important influential factors — total license plate quota, vehicle rental fee, and energy price — on EV adoption. The LPC policy under COVID-19 is also studied through a scenario analysis. If the government additionally increases the total quota by 20,000, 24% could be allocated to GV and 76% to EV. One third reduction of the current vehicle rental fee could increase EV license plates by 10.5%. In terms of energy prices, when gasoline price is low, reducing electricity prices could contribute to EV adoption significantly, while that effect tapers off as gasoline prices increase. • The optimal license plate allocation between EVs and GVs in Beijing is analyzed. • A Stackelberg game is proposed to model stakeholders' interaction under LPC policy. • The optimal license plate allocation policy under COVID-19 is also studied. • One third reduction of vehicle rental fee could increase EV adoption by 10.5%. [ABSTRACT FROM AUTHOR]