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Production Channel Strategies of an Automotive Supply Chain Under Government Intervention

In: Liss 2022

Author

Listed:
  • Li Shen

    (Beijing Wuzi University)

  • Luhong Chang

    (Beijing Wuzi University)

  • Xiaohui Yu

    (Beijing Wuzi University)

Abstract

International auto supply chain can be influenced by various policies, among which the tariff and dual-credit policies (DCP) play key roles. In order to explore the production channel in four cases under the two policies, a game-theoretical model consisting of a two-echelon auto supply chain and the government is proposed. The government pursues social welfare maximization, while the automakers and dealers are profit-driven. In the four cases, the optimal tariffs and pricing decisions are calculated. Threshold policies to ensure profitability for automakers and dealers are also introduced. Finally, the influence of different channel structures on the optimal solutions and the optimal channel strategy are obtained with numerical analysis. The results show that the optimal tariff with only new energy vehicles (NEV) production at home (case E) is always smaller than that with NEV and fuel vehicle (FV) production abroad (case T). Only when the production cost gap between NEV and FV exceeds a certain threshold, will the optimal tariff with only FV production at home (case F) be the smallest. Furthermore, there exists a certain threshold of credit ratio to influence the trend of profits and social welfare respectively. The market environment with higher environmental awareness can decrease the negative effect of DCP. The numerical analysis further indicates that the social-welfare-maximizing government does not impose tariffs that exceed the optimal tariff, and the government can receive sub-optimal social welfare when case E reaches equilibrium.

Suggested Citation

  • Li Shen & Luhong Chang & Xiaohui Yu, 2023. "Production Channel Strategies of an Automotive Supply Chain Under Government Intervention," Lecture Notes in Operations Research, in: Xiaopu Shang & Xiaowen Fu & Yixuan Ma & Daqing Gong & Juliang Zhang (ed.), Liss 2022, pages 513-541, Springer.
  • Handle: RePEc:spr:lnopch:978-981-99-2625-1_40
    DOI: 10.1007/978-981-99-2625-1_40
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