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Research on the production decisions of vehicle enterprises regarding intelligent transformation under the dual credit and cap-and-trade policies

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  • Zhu, Chaoping
  • Wang, Xinhao
  • Fan, Ruguo

Abstract

Electrification and intelligent transformation are emerging trends in China's automobile manufacturing industry. Although advancements in electrification have been witnessed, the intelligent transformation is nascent, and its implications for production decisions remain unclear. This study employs a Stackelberg game-theoretic model to examine the optimal production strategies of fuel vehicle (FV) and new energy vehicle (NEV) enterprises regarding intelligent transformation under the dual credit and cap-and-trade policies. It compares the differences in pre- and post-intelligent transformation and evaluates the impact of consumers' preference, automotive technology, and governmental policies. The findings reveal that: (1) Whether FV enterprises can benefit from intelligent transformation depends on transformation timing, whereas the benefits for NEV enterprises depend on production scale; (2) As with the dual credit policy, the cap-and-trade mechanism encourages the electrification of vehicle enterprises; (3) The influence of intelligence level, consumers' green preference, and environmental protection coefficient on profits is associated with production scale; (4) An increase in consumers' sensitivity to fuel economy and fuel improvement positively impacts the optimal production decisions of FV enterprises but not those of NEV enterprises. This research deepens the comprehension of production decision-making in vehicle enterprises and offers theoretical underpinnings for the intelligent transformation within automobile manufacturing industry.

Suggested Citation

  • Zhu, Chaoping & Wang, Xinhao & Fan, Ruguo, 2025. "Research on the production decisions of vehicle enterprises regarding intelligent transformation under the dual credit and cap-and-trade policies," Energy, Elsevier, vol. 320(C).
  • Handle: RePEc:eee:energy:v:320:y:2025:i:c:s0360544225009223
    DOI: 10.1016/j.energy.2025.135280
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