Electrification decisions of traditional automakers under the dual-credit policy regime

被引:48
|
作者
He, Haonan [1 ]
Li, Shiqiang [1 ]
Wang, Shanyong [2 ]
Chen, Zhuru [1 ]
Zhang, Jinxi [3 ]
Zhao, Jie [1 ]
Ma, Fei [1 ]
机构
[1] Changan Univ, Sch Econ & Management, Xian 710064, Shaanxi, Peoples R China
[2] Univ Sci & Technol China, 96 Jinzhai Rd, Hefei 230026, Anhui, Peoples R China
[3] Changan Univ, Coll Transportat Engn, Xian 710064, Shaanxi, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Dual-credit policy regime; Traditional automaker; Electric vehicles; Electrification decision; Genetic algorithm; FLEET REPLACEMENT; GENETIC ALGORITHM; ELECTRIC VEHICLE; CARBON CAPTURE; COST; TECHNOLOGY; PROGRAM; IMPACT; SALES;
D O I
10.1016/j.trd.2021.102956
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The newly introduced dual-credit policy has made electrification inevitable for traditional automakers. This study considers stochastic credit prices and time-dependent electric vehicle (EV) investment costs to present a novel optimal decision model with three indicators: investment timing, research and development intensity, and product line allocation. This combinatorial optimization problem is solved by developing a genetic algorithm. The simulation result shows that the high profitability of EVs can accelerate electrification, while rapid credit price increases may instead d[1]elay it. Meanwhile, the Corporate Average Fuel Consumption (CFAC) credit rules outperform the New Energy Vehicle (NEV) credit rules in facilitating electrification and driving long-term cumulative EV productions. Interestingly, despite the pressure these rules bring, tightening them is not necessarily beneficial for boosting electrification. Overall, introducing credit ceiling and floor prices, or coordinating policy parameters by steadily tightening CAFC rules while appropriately moderating NEV rules, would effectively accelerate electrification and promote EV productions.
引用
收藏
页数:18
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