The industrial prospect of electric vehicles—time delay stochastic evolutionary game evidence from the U.S., China, the EU, and Japan

Yazhi Song, Yin Li, Jingjing Jiang and Bin Ye ()
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Yazhi Song: Jiangsu Normal University
Yin Li: China University of Mining and Technology
Jingjing Jiang: Harbin Institute of Technology
Bin Ye: Southern University of Science and Technology

Palgrave Communications, 2025, vol. 12, issue 1, 1-17

Abstract: Abstract The global transition to electric vehicles (EVs) represents a critical decarbonization strategy for the transportation sector, yet development pathways diverge substantially across major economies despite common climate objectives. This study addresses the knowledge gap in understanding why heterogeneous EV industrialization strategies emerge under similar technological and environmental pressures. Using a delayed stochastic evolutionary game‒theoretic model capturing policy‒market‒technology interactions, this paper analyses EV development trajectories in the U.S., China, the EU, and Japan. The results demonstrate convergent evolution in the U.S., China, and the EU, driven by coordinated policy–market dynamics, which contrasts with Japan’s unstable oscillation between government- and enterprise-led approaches because historical hydrogen vehicle prioritization dampens consumer adoption. The key mechanisms governing these pathways are as follows: information timeliness directly governs policy agility, with prolonged lags weakening regulatory efficacy. Carbon pricing nonlinearly accelerates EV adoption, quadrupling carbon prices yields no incremental time advantage over doubling them, and subsidies exhibit bounded influence, temporarily boosting consumer demand and R&D incentives but failing to shift equilibrium outcomes, underscoring the dominance of profit and market-share imperatives over subsidy-driven innovation. This work advances a unified framework explaining heterogeneous EV development pathways, offering policymakers actionable insights for aligning decarbonization goals with industrial realities through calibrated interventions.

Date: 2025
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DOI: 10.1057/s41599-025-05342-5

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