Integrative Electric Vehicle Pricing—Battery Recycling Mechanisms for Battery Swapping and Charging Modes
Si-Rui Hong & Jiuh‐Biing Sheu
Abstract
The battery-swapping electric vehicle (SEV) is an example of a circular economy (CE) business model, which has been increasingly urged by governments. To facilitate battery circularity, governments offer incentive schemes, such as the reward-penalty mechanism (RPM) aimed at encouraging battery recycling, and special purchase (SP) subsidies for SEVs aimed at promoting CE business models. However, which incentive is more conducive to environmental and social welfare remains unclear. To address this issue, we construct a game-theoretic model to explore the impacts of these incentive schemes on different stakeholders (i.e., the charging EV (CEV) manufacturer, the SEV manufacturer, the government, and consumers). We derive several findings. First, under the RPM scheme, CEV manufacturers tend to lower EV prices and achieve higher profits when the recycling target is relatively low. In contrast, SEV manufacturers benefit from the spillover effects of SP subsidies, achieving higher profits by raising EV prices. Second, at high subsidy levels, the SP subsidy outperforms the RPM scheme in improving environmental performance. Third, under certain conditions, the SP subsidy yields higher social welfare than the RPM scheme. Notably, when the reward-penalty (RP) intensity exceeds a certain threshold, a “danger zone” emerges, leading to a decline in social welfare. Finally, we conduct two extensions: considering endogenous government incentives and exploring a combined policy. We find that the main results remain robust. Overall, these findings provide valuable insights for managers and policymakers, accelerating the transition of the EV industry towards CE.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.