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A dual-model EV closed-loop supply chain: Optimal strategy and policy analysis

Author

Listed:
  • Wu, Fan
  • Zheng, Gengzhao
  • Tang, Jinjun

Abstract

As the adoption of electric vehicles (EVs) accelerates to achieve climate goals, it concurrently creates a pressing challenge in managing end-of-life power batteries. This issue is significantly complicated by the coexistence of two distinct battery supply models: charging (consumer-owned) and swapping (enterprise-owned), which creates significant challenges for the closed-loop supply chain (CLSC) management of retired power batteries. To analyze their interaction and differential impacts on the reverse recycling chain, this study develops a game-theoretic model of a CLSC with a Manufacturer of Battery Charging Electric Vehicles (MCEV) and a Manufacturer of Battery Swapping Electric Vehicles (MSEV). We analyze their optimal decisions and compare the efficacy of four government subsidies: Consumer Subsidy (CS), Manufacturer Subsidy (MS), Recycler Subsidy (RS) and Producter Subsidy(PS). Key findings show: (1) The MSEV, despite higher costs, exhibits greater resilience to reverse market fluctuations. (2) A Recycler Subsidy (RS) is the optimal policy, simultaneously enhancing supply chain profits and the overall battery recycling rate. while the Producer Subsidy (PS) serves as a subordinate alternative. (3) A Consumer Subsidy (CS) is counterproductive, negatively impacting the recycler's profit and the recycling rate. (4) A Manufacturer Subsidy (MS) acts as a market balancer, fostering the swapping model's growth at the expense of the dominant MCEV. This research provides practical decision support for stakeholders and policymakers in the evolving dual-model EV market.

Suggested Citation

  • Wu, Fan & Zheng, Gengzhao & Tang, Jinjun, 2026. "A dual-model EV closed-loop supply chain: Optimal strategy and policy analysis," Socio-Economic Planning Sciences, Elsevier, vol. 105(C).
  • Handle: RePEc:eee:soceps:v:105:y:2026:i:c:s003801212600073x
    DOI: 10.1016/j.seps.2026.102486
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