Toward 2035: exploring a transition plan of the CAFC-NEV credits policy for NEV in China

Abstract

As the penetration rate of new energy vehicles in China continues to rise, the incentive effect of the CAFC-NEV credits policy has gradually weakened. The Ministry of Industry and Information Technology therefore proposes to transform the CAFC-NEV credits policy into carbon emission management policy. Focusing on the transition plan for CAFC-NEV credits of automotive industry in China, this paper constructs a differential game model of the supply chain that simultaneously manufactures and sells internal combustion engine vehicle (ICEV) and new energy vehicle (NEV), so as to examine the transitional effect of carbon credit on CAFC-NEV credits. The results show that: (1) Implementing carbon credit for NEV on the basis of the current CAFC-NEV credits does not affect capital stock or goodwill. (2) Within a specific range of NEV standard type credit and proportional requirement, the optimal equilibrium solutions for manufacturer and retailer are higher under the carbon credit compared to the CAFC-NEV credits scenario. (3) Neither the single-channel nor the dual-channel sales model affects the basic conclusions of the research. (4) The abolition of CAFC-NEV credits exerts a greater impact on manufacturer’s profit than on retailer’s. Empirical analysis reveals that the profit margins for manufacturer and retailer under the CAFC-NEV credits and carbon credit differ by less than 7% and 1% respectively. This study provides a theoretical basis for promoting the transformation of automotive industry policy from CAFC-NEV credits to carbon emission management in China.

1 Introduction

Achieving carbon peaking and carbon neutrality is a solemn commitment made by the Chinese government to the world, and it is the route one must take for humanity to achieve sustainable development in the future. Developing NEV is a strategic initiative for China to implement carbon peaking and carbon neutrality goals. Chinese government has introduced a series of policies to support the development of NEV industry since 2001, which can be divided into three phases (Shi and Ming, 2023). NEV is included in the National High-tech R&D Program (863 Program) during the 10th 5-year plan period, marking the commencement of policy support for NEV industry. Since 2009, China has granted subsidy for the promotion of NEV (Zhu et al., 2026). However, the unprecedented high subsidies coupled with lax supervision have fueled widespread subsidy fraud (Li et al., 2019). Subsequently, the subsidy policy for NEV underwent a phased withdrawal. In 2017, the Chinese government has issued the Measures for the Parallel Administration of the Average Fuel Consumption and New Energy Vehicle Points of Passenger Vehicle Enterprises, which placed corporate average fuel consumption (CAFC) credit and new energy vehicle (NEV) credit under unified management and established the CAFC-NEV credits system, which signifies that the NEV market is transitioning from policy-driven to market-driven growth (Yu et al., 2021). Driven by the constraints of credit assessment and revenue incentive, automakers generally increase investment in NEV products, leading to a steady improvement in the performance and quality (Li et al., 2023; Shi and Lin, 2023).

With the implementation of CAFC-NEV credits, a surge of relevant studies has emerged. Earlier qualitative research focuses on the layout strategies of NEV for automotive enterprises (Wang et al., 2018; Teece, 2019). Subsequently, some scholars analyze the implementation effects of CAFC-NEV credits. Among the early quantitative studies, the relevant literature mainly concentrate on policy effect evaluation. Among the early quantitative studies, relevant literature mainly focus on policy effect evaluation, which indicates that CAFC-NEV credits have promoted innovation, enhanced corporate competitiveness, and effectively advanced the adoption of NEV (Wang et al., 2020; Yang et al., 2022; Wang et al., 2023). With the adjustment of CAFC-NEV credits, scholars explore the optimization of the automotive supply chain, mainly investigating the optimal decisions for ICEV and NEV through static analysis of game models (Peng et al., 2021; Jiao et al., 2022; Ding et al., 2023; Jia et al., 2024). Among the limited dynamic studies, He et al. (2022) discuss the price change of CAFC-NEV credits and optimal electrification timing of manufacturer. Yi et al. (2026) analyze the production strategies for ICEV and NEV. Jin et al. (2023) propose a dynamic CAFC-NEV credits policy. As a crucial non-subsidy policy instrument, CAFC-NEV credits play a vital role in promoting the scaled development of NEV industry (Peng and Li, 2022; Dong and Zheng, 2022). However, with the gradual increase in NEV penetration, the incentive effect of CAFC-NEV credits is diminishing, leading to significant fluctuations in credit price and a decline in market regulation efficiency. Against this backdrop, the Ministry of Industry and Information Technology has proposed transforming CAFC-NEV credits into a carbon emission management policy.

Driven by carbon emission reduction targets, the automotive industry continues to witness a constant stream of innovations, with the ongoing competition between ICEV and NEV persisting. At present, academia has proposed three primary approaches to carbon emissions management within the automotive industry, namely carbon tax, carbon quota, and carbon credit (Li et al., 2018; Liu et al., 2024; Liu and Kong, 2024). Carbon tax is a tax on carbon dioxide emitted during the use of ICEV (Ding et al., 2019), it is widely recognized that carbon tax is an effective measure to reduce carbon emissions (Sibdari and Asayesh, 2024; Liu et al., 2024). Through computable general equilibrium (CGE) and other professional models, scholars have calculated the optimal tax rate and evaluated the impact of carbon tax. However, existing research remains at the macro level and there is no detailed institutional design around the elements of carbon tax (Zhou et al., 2018; Cao et al., 2021; Wang et al., 2025). Carbon quota refers to the emission cap for enterprises participating in carbon market (Jia and Lin, 2020). Based on the practices and simulation analyses of the international transportation sector participating in carbon market, some scholars explore the implementation pathways of carbon trading (Han et al., 2017; Li et al., 2018; Liao et al., 2019). Game analysis is employed to examine the promotion strategies of NEV that introduce carbon quotas in some studies. However, the CAFC-NEV credits and carbon quota are market instruments, it is almost impossible for them to appear simultaneously in the production process in reality (Liu et al., 2023; Li et al., 2018; Liao et al., 2019). Research on carbon credit remains limited, with the concept first proposed by Academician Fengchun Sun of Beijing Institute of Technology. Carbon credit is a carbon emission reduction incentive designed to encourage the use of NEV, which quantifies the contribution of NEV travel as carbon emission reduction relative to ICEV, NEV owners earn income by trading carbon credit (Zhang, 2021). The findings indicate that carbon credit can promote the adoption of NEV, addressing the limitation that CAFC-NEV credits apply solely to the production phase (Liu and Kong, 2024).

In conclusion, scholars have long been concerned with the static supply chain decision under the CAFC-NEV credits scenario. However, research regarding the dynamic decision and policy coordination at the usage stage is limited. We therefore explore dynamic optimal decision in automotive supply chain under CAFC-NEV credits and carbon credit scenarios, evaluating the substitution effect of carbon credit on CAFC-NEV credits. The marginal contribution of this paper may lie in the following aspects. First, using differential game, this paper contributes to literature on the dynamic optimal decisions of the automotive supply chain under different policy scenarios. Previous studies focus on the static analyse of CAFC-NEV credits. Second, regarding research design, existing literature focus on a single policy, with few studies examining the effects of policy combinations. By comparing different scenarios involving CAFC-NEV credits, carbon credit, and their combination, we further analyze the potential impacts of abolishing the CAFC-NEV credits. Third, model derivation and data simulation reveal that carbon credit can achieve the same incentive effect on the development of NEV as the CAFC-NEV credits, which provides a theoretical basis for the transition from the CAFC-NEV credits to carbon emission management policy.

2 Problem assumptions and notations

On the basis of the observations from current practice, we consider a single-channel supply chain model. Manufacturer determines the R&D effort for NEV, while retailer determines retail price and marketing efforts. The following conditions are assumed in this paper.

3 Model solutions

In the decentralized scenario, the manufacturer and retailer make their own decisions to maximize their profits. Under the CAFC-NEV credits scenario, the optimization problems for manufacturer and retailer are expressed as Equations 14, 15.

By solving the above optimization problem jointly, we obtain the Proposition 1. The proof of Proposition 1 is shown in the Appendix.

4 Comparative analysis

5 Numerical experiments

This section analyzes the model results with data examples, aiming to test the above conclusions and further extend the analysis results. We refer to the relevant literature to assign values to parameters with economic significance to ensure the validity of the results in reflecting reality (Zhou and Ye, 2018; Liu et al., 2022; Liu and Kong, 2024; Lu et al., 2025; Yi et al., 2026). The conclusions are rigorously demonstrated in Sections 3, 4 as well as in the appendix. Therefore, the values assigned to certain parameters in the numerical simulations do not affect the validity of the conclusions. Parameter assignments and their bases are listed in the Appendix. We substitute the parameter values into the optimal equilibrium results and perform data analysis using Matlab, yielding the simulation analysis in Figures 1–5.

FIGURE 1

5.1 Policy parameters of CAFC-NEV credits and carbon credit

Figures 1a–d shows that within the variation range of parameters set in this paper, NEV demand and the profits of manufacturer and retailer decrease as the price of CAFC-NEV credits declines. In a horizontal comparison, when the price of the CAFC-NEV credits falls below a certain threshold, the NEV demand and the profits of manufacturer and retailer under the carbon credit scenario exceed those under the CAFC-NEV credits scenario. Figures 1e–h shows that if NEV proportional requirement in CAFC-NEV credits policy is higher than a certain level, the demand and profits of manufacturer and retailer may be lower than that in carbon credit scenario.

Figures 2a–d indicates that under the carbon credit scenario, as the price of carbon credit increases, the NEV demand and the profits of manufacturer and retailer rise accordingly. Figures 2e–h shows that as NEV carbon emission increases, NEV demand and the profits of manufacturer and retailer will decline. Based on Figure 2, no significant direct impact of the carbon credit policy on ICEV demand is observed, thus indicating that the introduction of additional carbon credit exerts no significant intervention effect on changes in ICEV demand under the existing CAFC-NEV credit. Corollary 4, Corollary 5, and Corollary 6 are verified. Figures 1, 2 demonstrate that reasonable regulation of carbon credit price in the carbon market and reduction of life cycle carbon emission for NEV can effectively stimulate the NEV demand.

FIGURE 2

Tables 4, 5 present the member strategies, steady-state capital stock, goodwill and demand, profits, and comparisons for CAFC-NEV credits under different credit prices and proportional requirements of NEV. As shown in Table 4, within the parameter test range selected in this paper, R&D effort, together with NEV demand, capital stock, goodwill and profits, increase with the increase in CAFC-NEV credits price. Rising credit prices can increase the marginal revenue of manufacturer and encourage R&D investment, which is conducive to the accumulation of capital and goodwill, improve NEV demand, and expand the profit space of manufacturer and retailer. Table 5 shows that R&D effort and NEV demand, capital stock, goodwill, and profit increase with the proportional requirement of NEV. The higher the proportional requirement of NEV, the more the costs for manufacturer to purchase NEV credit, which may inhibit the manufacturer’s R&D effort. According to Equation 16, the retailer’s equilibrium strategy is independent of ψ and α₂, so the marketing effort remains constant as the CAFC-NEV credits price and the proportional requirement of NEV change. The appendix also includes a sensitivity analysis of NEV standard type credit, showing that R&D effort, NEV demand, capital stock, goodwill, and profits increase with NEV standard type credit. Higher NEV standard type credit is more beneficial to manufacturer.

Tables 6, 7 present the member strategies, steady-state capital stock, goodwill and demand, profits, and comparisons for carbon credit under different credit prices and NEV carbon emission. The appendix also includes a sensitivity analysis of transaction cost. According to Equation 20, the optimal equilibrium strategy is independent of p_c, CE₁, and τ. Numerical analysis consistently shows that the effort level of supply chain members does not change with the change of these parameters within the test range set in this paper. Considering the linear relationship between p_c, CE₁, τ and NEV demand, NEV demand increases with a rise in the carbon credit price and decreases with an increase in NEV carbon emission and transaction cost. Rising credit price generates additional income for NEV owners, which essentially reduces the actual purchase price for consumers, thereby stimulating the NEV demand and expanding the profit margin within the supply chain. Higher carbon emission of NEV undermines the low-carbon advantages and economics, affecting consumer demand and the profitability of supply chain members. Transaction cost is negatively correlated with NEV demand and profits of manufacturer and retailer. In a mature carbon market, NEV owners can reduce the costs of finding trading partners and negotiating. Conversely, in an underdeveloped carbon market, exorbitant transaction costs may weaken the incentive effect of the carbon credit policy. Other parameters remain consistent with the CAFC-NEV credits scenario. Therefore, policymakers should dynamically regulate the carbon credit price, reduce transaction cost, strengthen carbon emission accounting and other measures to enhance the effect of policy incentives. As the carbon market matures in the future, carbon credit is expected to be an important policy instrument for popularizing NEV and achieving the carbon peaking and carbon neutrality goals.

5.2 The trajectory of capital accumulation

Figure 3 illustrates variation in capital stock with respect to various parameters. First, within the observation timeframe (t∈[0,100]), the capital stock naturally accumulates and converges to a steady state over time across all policy scenarios. This means that once the capital stock reaches a steady state (as shown in Figure 3 after t = 30), eliminating the CAFC-NEV credits policy will not affect the capital stock. Second, at a fixed time point (t = 10), the capital stock under the CAFC-NEV credits or combination scenario generally exceeds that under the carbon credit scenario. However, when NEV proportional requirement is higher than a certain threshold, the capital stock under the carbon credit scenario surpasses that under the CAFC-NEV credits and combination scenario. Finally, in parameter test area, the capital accumulation trajectory shows some effects consistent with expectations as the parameters variation. For example, an increase in goodwill and capital depreciation rates leads to a reduction in capital stock. Carbon credit price does not affect capital stock. The NEV proportional requirement and wholesale prices exhibit decreasing and increasing trends with capital stock, respectively.

FIGURE 3

5.3 The trajectory of goodwill

Figure 4 illustrates the variation in goodwill with respect to various parameters within the parameter range defined in this paper. We observe that the carbon credit price does not affect goodwill. The implementation of carbon credit leads to an increase in goodwill, which shows rapid growth at first and then leveling off. Therefore, whether stimulating production from the production link or boosting consumption from the use link, both approaches exert a long-term positive impact on goodwill. In addition, an increase in goodwill and capital depreciation coefficients will also lead to a reduction in goodwill. The NEV proportional requirement and wholesale price exhibit a decreasing and increasing trend with goodwill respectively, consistent with expectations. Figures 3, 4 validate Corollary 3.

FIGURE 4

5.4 Profit as a function of parameter variation

Figures 5a–d illustrates the variation in profit among manufacturer with respect to various parameters under various policy scenarios. Within the set parameter range, it reveals that, first, manufacturer profit is positively correlated with carbon credit price, CAFC-NEV credit price, and the goodwill marginal coefficient of ICEV and NEV demand, while negatively correlated with NEV retail price and production cost. In particular, the price variation of CAFC-NEV credits and carbon credit affect manufacturer’s profit under different scenarios. Manufacturer should seek the optimal way to maximize their own interests according to specific circumstances. Second, the manufacturer’s profit under the CAFC-NEV credits scenario is higher than that under the carbon credit scenario in most areas. When the CAFC-NEV credits price falls below a certain threshold, manufacturer’s profit under the carbon credit scenario surpass those under the CAFC-NEV credits scenario. On the current parameter configuration plane (excluding the bottom-left subgraph), the average difference in manufacturer profit under the two policy scenarios is 6.523%, 6.512%, and 6.508%. If CAFC-NEV credits is subsequently eliminated based on the combination scenario, manufacturer’s profit will decrease by 6.557%, 6.556%, and 6.542%.

FIGURE 5

Figures 5e–h indicates that retailer profit is positively correlated with carbon credit price, CAFC-NEV credit price, and goodwill diffusion coefficients, while negatively correlated with NEV production cost within the set parameter range. Different from Figures 5a–d, retailer profit is positively correlated with retail price, because rising retail price increases retailer’s marginal revenue, and coupled with the goodwill reference effect, retailer’s profit is elevated. In addition, when the price of CAFC-NEV credits falls below a certain threshold or the price of carbon credit rises above a specific level, the manufacturer’s profit will be higher under carbon credit scenario than under CAFC-NEV credits scenario. On the current parameter configuration plane, the average differences of retailer’s profit across two policy scenarios are 0.053%, 0.034%, 0.020%, and 0.026%, respectively. Eliminating CAFC-NEV credits on the basis of combination scenario reduces retailer’s profit by 0.053%, 0.074%, 0.050%, and 0.057%, respectively. Figure 5 provides strong validation for the conclusions of Corollary 5 and Corollary 6.

6 Discussion

The above analysis examines the optimal strategies for manufacturer and retailer in a single-channel supply chain, neglecting direct sales channel. For instance, manufacturer such as BYD not only operate their own direct sales channel, but also maintain an extensive retail network, and outsource a variety of service cooperation businesses to retailer or third-party provider. Consequently, we further explore optimal strategies within a dual-channel supply chain.

Considering a dual-channel automotive supply chain composed of a manufacturer, a retailer, and a third-party provider, consumers can purchase NEV or ICEV through direct (manufacturer) and indirect sales channel (retailer). During the sales phase, the manufacturer determines the direct sales prices p_1d and p_2d for NEV and ICEV in the direct sales channel, and sells NEV and ICEV to retailer at wholesale prices w₁ and w₂. Retailer determines the indirect prices p_1i and p_2i for NEV and ICEV in the indirect channel. During the usage phase, whether NEV or ICEV, regular maintenance and inspection are required to ensure proper vehicle operation and extend service life. Manufacturer usually outsources warranty services to retailer or third-party provider in a licensing model, charging them fixed licensing fees L_1i, L_2i, L_1p and L_2p for NEV and ICEV. Retailer or third-party provider earn a service premium that exceeds operating cost by professional services. When consumers purchase NEV or ICEV through indirect channel, they can only seek after-sales service from the retailer. Third-party provider only offers after-sales service to consumers who purchase NEV or ICEV from direct sales channel.

In a dual-channel supply chain, the manufacturer sells NEV or ICEV through indirect and direct channels. Following Zhou and Ye (2018), the demand for NEV and ICEV of indirect and direct sales channels are expressed as Equations 26–28.where μ₁ and μ₂ represent the retail proportions of NEV and ICEV, p_1i, p_1d, p_2i, and p_2d denote the indirect and direct sales prices of NEV and ICEV, b₁ and b₂ indicate the price sensitivity of NEV indirect and direct sales channels, b₃ and b₄ denote the price sensitivities of ICEV indirect and direct sales channels, ξ₁ represents the cross-price sensitivity of NEV, with b₁ > ξ₁ and b₂ > ξ₁; ξ₂ denotes the cross-price sensitivity of ICEV, with b₃ > ξ₂ and b₄ > ξ₂.

Under the carbon credit scenario, NEV demand under indirect and direct sales models are expressed as Equations 30, 31.

In a dual-channel supply chain, the objective functions for manufacturer and retailer under the CAFC-NEV credits scenario are expressed as Equations 32, 33.where subscripts 1 and 2 denote NEV and ICEV, D_1i and D_2i represent the indirect sales of NEV and ICEV, D_1d and D_2d denote the direct sales, w₁ and w₂ are the wholesale prices, c_1p and c_2p are the production costs, R_1i and R_2i represent the after-sales service fees charged by retailers to consumers, L_1i and L_1p denote the NEV after-sales service licensing fees paid by retailer and third-party provider to manufacturer, while L_2i and L_2p represent the ICEV after-sales service licensing fees.

The objective functions for manufacturer and retailer under the carbon credit scenario are expressed as Equations 34, 35.

The objective functions for manufacturer and retailer under the combination scenario are expressed as Equations 36, 37.

Under the CAFC-NEV credits scenario, the optimization problems for manufacturer and retailer are expressed as follows.

Simultaneous solution Equations 38, 39, we obtain Proposition 4.

FIGURE 6

7 Conclusion

This paper has made some progress on the basis of existing research, but there may still be some imperfections. For instance, this paper only considers single-period decision and ignore the carry-over of credit across years, which thus has certain limitation. In addition, there are some factors affecting demand that are not included in the model. Subsequent research may consider these issues for further expansion.

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