Research on the Influence Mechanism of New Energy Vehicle Promotion Policy

Abstract

In recent years, China has actively advanced the new energy vehicle industry to achieve its “dual carbon” objectives via a green revolution. The growth of green technical innovation by new energy vehicle enterprises has emerged as a significant national support project, and it has implemented a number of new energy vehicle promotion policies. Therefore, it is essential to investigate if promotional policies encourage the development of green technologies in businesses. China’s 2016 “New Energy Vehicle Promotion Catalogue” serves as the policy’s temporal shock point, and data from Chinese-listed new energy vehicle companies from 2011 to 2022 are used in this study. The effect and mechanism of the new energy vehicle promotion strategy on developing green technologies in businesses are investigated using a double difference model. As per the research, the promotion policy substantially enhances the green technological innovation of new energy vehicle firms. It can augment the level of R&D investment and alleviate financing constraints for enterprises, and enterprises’ social responsibility can act as a positive moderator for the promotion policy and enterprise green technological innovation. Finally, it has a more apparent positive impact on the green technological innovation of major companies and non-state-owned enterprises compared to state-owned firms. Additionally, it is more evident that enterprises are raising green technology innovation in the eastern and central regions.

1. Introduction

A major challenge to environmentally sustainable development is the production and use of conventional high-energy, high-emission vehicles, which are associated with significant fossil fuel consumption [1]. This not only accelerates the overconsumption of global resources but also causes a significant pollution problem. To foster the growth of the new energy vehicle sector, governments have implemented various legislative measures and have promoted new energy as a significant national strategic direction. For example, the European Union implemented the Green Deal program, which aims to outlaw the sale of fuel-powered vehicles entirely by 2035 while increasing support for the production of new energy vehicles and the establishment of basic charging infrastructure [2]. Through the Inflation Reduction Act, the United States established a subsidy system for new energy manufacturing businesses, actively encouraging the domestic production of new energy vehicles and batteries while lowering their reliance on international supply chains for electric vehicles [3]. China, the world’s largest producer and consumer of automobiles, accounted for 50% of the global 14 million new energy vehicles sold in 2023 [4]. Of the 30.161 million vehicles produced in China that year, approximately 20.574 million were fuel-powered, while nearly 30% were new energy vehicles [5]. Therefore, the government significantly encouraged the development of green technology innovation among new energy automobile enterprises in order to accelerate the achievement of the “dual-carbon” strategic target. China officially designated the new energy automotive sector as an emerging industry in 2009 and started to incorporate new energy vehicles into its broader automobile industry development strategy [6]. The “Made in China 2025” manifesto further strengthened this push, which resulted in the widespread use of new energy vehicles in China. China’s green transition was aided by advancements in green technology for new energy vehicles, which were sparked by the “Made in China 2025” whitepaper. To improve China’s environmental sustainability, a comprehensive plan for resource conservation and emission reduction must be implemented.

Green technology innovation depends on external support due to high risks and uncertainties [7]. The government aims to alleviate the risks linked to green technology innovation by accelerating the advancement of new energy vehicle enterprises through economic and administrative strategies, consequently fostering mutually beneficial outcomes for both the economy and the environment. Currently, the state has implemented various policy initiatives to advocate for the advancement of the new energy automobile sector, including the Catalogue of Recommended Models for the Promotion and the Notice on the Financial Subsidy Policy for the Promotion and Application of New Energy Vehicles. These measures encompass the reduction of purchase tax on new energy vehicles, lowering corporate personal income tax, distributing consumption vouchers, and increasing subsidies for the disposal of fuel-powered cars [8]. Such policies can stimulate companies to enhance their R&D investment and drive green technological innovation; in addition, they can also elevate consumers’ purchasing inclination and expedite the expansion of the new energy vehicle industry [9]. Nonetheless, there are still deficiencies in the investigation of promotion policies and green technology innovation within enterprises. Firstly, there is a deficiency of research investigating the effects of new energy promotion initiatives; secondly, research on the green technological innovations of new energy enterprises is limited, and there is insufficient granularity in classifying the scale and region of new energy automobile firms.

To address the above issues, this paper selected A-share-listed new energy automobile enterprises in China from 2011 to 2022 as investigative subjects. A difference-in-difference (DID) model, based on theoretical analysis, was developed to investigate the impact and mechanisms of promotional policies on the green technology innovation of these firms. Additionally, this study investigated the heterogeneous effects of promotional policies, considering the characteristics of the firms, geographical locations, and scales, aiming to offer valuable suggestions for developing future promotion policies. This paper’s marginal contribution is twofold. First, it introduces enterprise micro-variable indicators, including financing constraints, R&D investment, and corporate social responsibility. It shows a comprehensive analysis of the direct and indirect effects of promotional policies on enterprises’ green technological innovation, thereby enhancing the theoretical discourse on new energy promotional policies. Secondly, the majority of the existing research on green technology innovation emphasizes the province and national macro levels, but this study analyzes it from the perspective of new energy vehicles, thereby enhancing the discourse on green technology innovation. Furthermore, by categorizing firms based on scale, nature, and magnitude, this study will increase the diversity of research on promotion policies and their effects on green technology innovation within enterprises.

2. Literature Review

2.1. The Concept of Green Technological Innovation

The concept of technological innovation originated from the economist Schumpeter [10]. Green technological innovation, a subset of this broader concept, was first proposed by Braun and Wield. They believed that the essence of green technology lies in the strict control of pollution production and the continuous innovation of technology, with the main purpose of reducing pollution emissions [11,12]. Scholars mainly elaborate on the concept of green technology innovation from three perspectives. Firstly, based on the entire process of production, green technology innovation involves the integration of energy saving, emission reduction, and the sustainable use of resources across the process of product research, design, production, testing, etc. [13,14]. Secondly, based on the perspective of the type of innovation, green technology innovation refers to the application of modern science and technology to reduce environmental damage, innovate green processes and products, and promote the development of green transformation [15]. Green product innovation includes product materials, product packaging, and recycling of old products. Green process innovation includes the implementation of technological innovation in the entire production process, minimizing product production costs and reducing pollution, facilitating the market entry of green technologies [16,17]. Thirdly, from the perspective of sustainable development, some scholars believe that green technological innovation is a collective term for technological and product innovations aimed at energy conservation, emission reduction, and the optimization of the allocation of resources; the purpose is to maximize economic and environmental benefits, ultimately achieving a compatible economy and sustainable development [18,19].

2.2. The Concept of New Energy Vehicle Promotion Policy

The new energy vehicle (NEV) promotion policy includes the government facilitation of the NEV industry by regulatory constraints and incentive subsidies, aiming to achieve carbon emission reduction and technological innovation. Researchers have conducted a variety of investigations on the industrial policy of new energy automobiles, categorizing China’s policy into the following three stages: first, the planning stage, which encompasses technology access [20], the strategic formulation of transportation policy [12], and pilot programs in developed cities [21]; the second step focuses on policy promotion, encompassing government subsidies and tax incentives [22,23]. These measures can offer financial assistance to firms and enhance consumer purchasing motivation [24]. Additionally, the government has undertaken extensive infrastructure development, including installing charging stations [25], establishing a robust foundation for advancing the new energy vehicle industry. The third stage involves enhancing and standardizing the industry’s policies. In recent years, the administration has refined these policies, signifying that the industry has entered a mature phase. Currently, the government’s new direction for policy development focuses on optimizing resource allocation and reducing financial subsidies [26].

2.3. Influence of Promotion Policy on Corporate Technological Innovation

Concerning the correlation between the new energy vehicle policy and corporate technological innovation, scholars have yet to reach a consensus, with the research findings categorized into three types. Firstly, some scholars use difference in differences (DID) and propensity score matching (PSM) for empirical analyses [27], concluding that the new energy promotion policy enhances patent application volumes for enterprises through financial subsidies and tax reductions, thereby significantly augmenting innovation efficiency [28,29]. Some scholars employ data envelopment analysis and random effect model analysis to validate that the subsidy impact of the promotional policy enhances the efficiency of technological innovation within organizations [30]. Furthermore, a non-linear relationship exists between these two variables. Ren.Y. validated a dual threshold effect of government policy on corporate technological innovation through a panel threshold model [31]. The government’s initial policy support for enterprises can enhance technological innovation; however, as subsidies increase, this may conversely inhibit technological advancement, exhibiting an inverted U-shaped relationship [32]. Furthermore, some studies assert that government-implemented preferential subsidies, analyzed through industrial panel data, can foster dependency among enterprises, resulting in diminished productivity and reluctance to invest significantly in innovation, thereby impairing their technological capabilities [33], particularly for enterprises with weak financial constraints [34].

In summary, while numerous studies exist on the promotion policies for new energy vehicles and enterprise green technology innovation, several gaps still remain. Firstly, the current literature predominantly emphasizes government subsidy policies or new energy industrial policies, with limited attention given to how specific new energy promotion policies influence enterprise green technology innovation. Secondly, the heterogeneity analysis between the two areas needs more detail in classifying new energy automobile enterprises, failing to address the heterogeneity related to factors such as enterprise location and scale, which could provide targeted recommendations for future research.

3. Theoretical Analysis and Research Hypotheses

3.1. The Impact of Promotion Policy on Enterprise Technology Innovation

China’s new energy vehicle industry has been developing rapidly in recent years, with intense competition among enterprises [35]. To enhance their competitiveness and pursue sustainable development, they rely significantly on external environmental support, particularly the regulatory framework established by the government, which is crucial for facilitating green technological innovation [36]. The new energy vehicle promotion policy offers financial assistance to firms for green technology innovation, channeling additional R&D resources into the new energy sector [37]. Enterprises can create technical barriers in the market by developing green processes and products that constitute their core competitiveness [38]. This success in exploring new markets enables enterprises to secure more significant economic benefits and acquire additional resources for new product development, creating a virtuous cycle [39,40]. Simultaneously, firms can integrate green innovation technologies and information, enhancing resource and information sharing, which further enhances their innovation capacity [41]. In addition, the new energy vehicle promotion policy sets standards for enterprise support that compels companies to pursue green technological innovation in order to meet government criteria [42], thereby boosting their innovation capacity. Consequently, this study posits the following hypothesis:

Hypotheses 1 (H1).

Policies Promoting New Energy Vehicles Can Enhance Enterprises’ Green Technology Innovation.

3.2. The Mechanisms Effect of Financial Constraints

Organizations that engage in green technology innovation frequently face significant risks, as substantial initial capital investments may yield no returns for extended durations, resulting in heightened financing constraints [43,44]. The new energy promotion policy establishes screening requirements for new energy vehicle firms included in the promotion catalog, necessitating that companies meet product quality and user assessment standards. According to signal theory, enterprises selected in the promotion catalog convey positive signals to external investors, highlighting their R&D capabilities and robust overall strength [45]. This mitigates the enterprise’s financing constraints, thereby attracting more investor support and facilitating resource allocation for future green technology innovation activities [46]. The government offers a financial subsidy for firms listed in the new energy promotion catalog, which mitigates some financial constrain, allowing these enterprises to allocate more funding towards green technology research initiatives. Thus the new energy industrial strategy can assist firms in mitigating financing constraints to pursue green transformation. Consequently, this paper proposes the following hypothesis:

Hypotheses 2 (H2).

The new energy industrial policy enhances firms’ green technological innovation capacity by mitigating corporate financing constraints.

3.3. The Mechanisms Effect of R&D Investment

Investment in research and development (R&D) is the crucial driver and essential resource for firms to transform their development model and implement green innovation initiatives [47]. Green technology innovation requires substantial resources and entails uncertainty, thus requiring a specific level of R&D investment funding as assurance [48]. In the highly competitive NEV sector, enterprises enhance technological innovation through increased R&D investment, establish technological barriers, and reduce homogeneity in market competition to sustain their market leadership [49]. The new energy vehicle promotion policy enables the government to provide substantial monetary assistance to enterprises through preferential taxation, grants, and other subsidies, thereby alleviating financial burdens and innovation risks, which in turn encourages increased R&D investment to foster the enterprise’s green development [50,51]. Consequently, this study posits the following hypothesis:

Hypotheses 3 (H3).

Promotion policies for new energy vehicles enhance corporate green technology innovation via increased R&D investment.

3.4. The Moderating Effects of Corporate Social Responsibility

According to hypothesis H1, this article posits that moderating variables may exist in the link between promotional policies and enterprises’ green technological innovation. During the execution of the promotion policy, firms may recognize that delivering high-quality green innovation products and services is essential for augmenting their competitive advantages and meeting the technological standards established by the promotion policy [52]. Signaling theory posits that proactive engagement in corporate social responsibility (CSR) can signal a positive corporate reputation to pertinent stakeholders [53], enhancing the connection between the companies and these stakeholders. The government’s newly implemented energy promotion policy aligns with CSR objectives, aiming to foster sustainable societal development. Moreover, investors consider not only the stock return of the firm but also the effectiveness of its corporate social responsibility efforts in protecting their interests [54]. Investors often prefer to invest in companies with strong social responsibility performance [55]. Additionally, investors’ capital allocation to companies demonstrating strong social responsibility would bolster the company image within the sector, attracting greater investor confidence and facilitating access to resources that support green technological innovation capabilities [56]. Consequently, the following hypothesis is formulated:

Hypotheses 4 (H4).

Corporate social responsibility fulfillment moderates the association between new energy vehicle promotion policies and the magnitude of firms’ innovation in green technology.

The research structure of this paper is shown in Figure 1:

4. Research Design

4.1. Model Specification

The difference-in-differences model evaluates the effect of a specific policy on its target by categorizing the sample into experimental and control groups and by measuring the policy’s effect through the variations in estimated coefficients of these groups before and after the policy’s implementation. This study examines the effects of new energy promotion policies on corporate green technology innovation for hypothesis H1. This research utilizes the new energy promotion policy as a quasi-natural experiment and employs a two-way fixed difference-in-differences model to examine its effect on the green technology innovation of new energy vehicle companies. The precise formula is shown as follows:

$${\mathrm{G}\mathrm{P}}_{\mathrm{i}\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\alpha }}_1{\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{t}}_{\mathrm{i}}\times {\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{e}}_{\mathrm{t}}+{\mathsf{\alpha }}_2{\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\mu }}_{\mathrm{i}}+{\mathsf{\delta }}_{\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$$

(1)

where ${\mathrm{G}\mathrm{P}}_{\mathrm{i}\mathrm{t}}$ denotes the level of green technology innovation of enterprise i in year t; ${\mathsf{\alpha }}_0$ denotes a constant term; ${\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{t}}_{\mathrm{i}}\times {\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{e}}_{\mathrm{t}}$ indicates whether enterprise i is affected by policy intervention after 2016, with “1” indicating intervention and “0” indicating no intervention. ${\mathsf{\alpha }}_1$ reflectingreflects the effects of the new energy promotion policy and the extent of the effect on the green technology innovation of new energy automotive companies. ${\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}_{\mathrm{i}\mathrm{t}}$ is the control variable of the paper, ${\mathsf{\mu }}_{\mathrm{i}}$ is an individual fixed effect, ${\mathsf{\delta }}_{\mathrm{t}}$ is a time fixed effect, and ${\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$ is a randomized disturbance term.

To verify that the parallel trend test is valid, the following model is set up:

$${GP}_{it}={\alpha }_0+\sum _{\tau =1}^m{\alpha }_{-\tau }{treat}_i\times {time}_{t-\tau }+{\alpha }_1{treat}_i\times {time}_t+\sum _{\tau =1}^n{\alpha }_{+\tau }{treat}_i\times {time}_{t+\tau }+{\alpha }_2{Control}_{it}+{\mu }_i+{\delta }_t+{\epsilon }_{it}$$

(2)

where ${\mathsf{\alpha }}_{-\mathsf{\tau }}$ is the impact produced in the $\mathsf{\tau }$ period before the implementation of the policy, and the ${\mathsf{\alpha }}_{+\mathsf{\tau }}$ is the impact of the policy after the implementation of the $\mathsf{\tau }$ period. The year 2016 is the year of policy shocks; the enterprises subject to policy intervention after 2016 take “1”, and vice versa take “0”; if the results before 2016 are not significant, then the parallel trend test hypothesis holds.

To examine the mediating mechanism of new energy promotion policies on the green technology innovation of enterprises, this research employs Jiang T’s mechanism analysis methods, proposing Equation (3) based on Equation (1), where the mediator indicates financial constraints and R&D investment, and this is shown as follows:

$${Mediator}_{it}={\gamma }_0+{\gamma }_1{did}_{it}+{\gamma }_2{Control}_{it}+{\epsilon }_{it}$$

(3)

The moderating influence of CSR on the new energy promotion policy and enterprises’ green technology innovation is assessed using the following Equation (4), where moderator indicates corporate social responsibility:

$${GP}_{it}={\tau }_0+{\tau }_1{did}_{it}+{\tau }_2{csr}_{it}+{\tau }_3{csr}_{it}\times {did}_{it}+{\tau }_4{Control}_{it}+ϵ$$

(4)

4.2. Variables Chosen

4.2.1. Dependent Variable

Regarding corporate green technology innovation (GP), because data on new energy vehicle companies are readily available, this study uses the World Intellectual Property Organization’s (WIPO) green patent codes to calculate the number of green patents held by listed new energy vehicle companies annually, including both applications and grants. The number of patents serves as a clear quantitative measure of an organization’s R&D activity and advancements in green technology. Companies with a high number of green patent applications demonstrate both their strong technological R&D capabilities and their richer accumulation of green technology innovations, which reflects the level of their green technological innovation of the companies. Building on Li. J. et al., this study uses the green patent applications of listed new energy vehicle companies as dependent variables. To confirm the model’s robustness, the green patent grants of listed new energy vehicle companies are used as replacement dependent variables in the subsequent robustness test [38].

4.2.2. Independent Variable

New energy vehicle promotion policy (treat × time). A total of 54 A-share-listed new energy vehicle companies in China between 2011 and 2022 were chosen as the study’s research objects. Eleven new energy companies that were part of the Catalogue for the Promotion of New Energy Vehicles were used as the experimental group, while the remaining companies served as the control group. Since the Catalogue for the Promotion of New Energy Vehicles was officially launched in 2016, this year is considered the point at which the policy took effect. A dummy variable, treat, represents the grouping of firms, where the value is set to 1 for the 11 new energy companies listed in the Catalogue for the Promotion of New Energy Vehicles and 0 for the remaining companies. Another dummy variable, time, indicates the time grouping, where the years 2011–2015 are coded as 0 and the years 2016–2022 are coded as 1.

4.2.3. Control Variables

To exclude the interference of other influencing factors, seven control variables at the municipal and organizational levels are selected with reference to existing studies. The variables at the firm level encompass enterprise age (AGE), enterprise size (Insize), enterprise asset structure (LEV), and enterprise inventory turnover (ITO), while the variables at the city level include government support (GOV), per capita economic development level (PGDP), and industrial structure (IS).

4.3. Sample and Data Resources

This study selects A-share-listed new energy vehicle companies in China from 2011 to 2022 to examine the effects of promotional policies on the green technology innovation of these organizations. To guarantee data availability, ST, *ST, and significantly missing data samples are omitted, resulting in a selection of panel data from 54 listed new energy vehicle firms. The primary data sources for the study are the China Statistical Yearbook, the China Environmental Statistical Yearbook, provincial statistical yearbooks, as well as variable data from annual reports of publicly listed companies, the China Research Data Service Platform (CNRDS), and the Cathay Pacific database.

5. Results

5.1. Descriptive Statictics

Table 1. Descriptive statistics of variables.

VarName	Obs	Mean	SD	Min	Median	Max
GP	594	8.590	23.567	0	0	153
AGE	594	18.590	5.199	5	19	31
lnsize	594	23.060	1.281	20.660	22.853	26.191
MS	594	0.500	0.164	0.117	0.511	0.857
GOV	594	0.11	0.036	0.046	0.095	0.220
PGDP	594	94,269.040	41,202.561	25,982	82,220.050	187,526
IS	594	1.31	0.648	0.481	1.162	4.768
ITO	594	5.64	4.325	1.024	4.206	23.251

reports that the mean value of the dependent variable, green technological innovation (GP), is 8.59, with a maximum of 153 and a minimum of 0. This indicates a significant disparity in the levels of green technological innovation among the leading new energy vehicle enterprises. In addition, the standard deviation value of enterprise GP is 23.567, which indicates that the level of green technology innovation of most enterprises is still at a relatively low level, with some firms making no notable progress in this area. Regarding the control variables, there is a certain disparity in the age of businesses in new energy vehicles, with the enterprise age having a minimum value of 5 and a maximum value of 31. Furthermore, there are variations in the enterprise’s size, inventory turnover ratio, and the degree of regional economic development where the firms are located.

5.2. The Impact of Promotion Policy on Enterprise Technology Innovation

This research employs a two-way fixed effects model for panel regression to examine the influence of new energy promotion policies on new energy vehicle firms’ green technical innovation, with the regression results presented in

Table 2. Baseline regression.

	GP	GP
did	0.215 ***	0.225 ***
	(7.03)	(6.86)
control variable	clogged	be
individual fixed effect	be	be
time fixed effect	be	be
N	594	594
R2	0.665	0.673

Note: *** indicate significant at the 1% statistical levels, respectively. Standard errors are in parentheses.

. Column (1) presents the estimated effects of the promotion policy on firms’ green technology innovation prior to the inclusion of control variables, with an estimated coefficient of 0.215, which is statistically positive at the 1% level. Column (2) presents the results following the inclusion of control variables, revealing an estimated coefficient of 0.225 for the promotion policy, which remains remarkably positive at the 1 percent level. This finding implies that, following the implementation of the policy, the level of green technological innovation in enterprises increases by 0.225 units, the new energy promotion policy substantially improves new energy enterprises’ ability to innovate in green technologies, and the model construction and variable selection are appropriate. Hypothesis H1 has been validated.

5.3. Robustness Tests

5.3.1. Parallel Trend Test

This study designates 2016 as the baseline year for the new energy promotion policy and selects the period of the first four years and the last five years of the policy implementation to conduct dynamic effect assessment. If the results are not statistically significant during the five years before the policy’s enactment, then the findings indicate that the levels of green technology innovation among firms in both the experimental and control groups exhibit no significant differences before and after the policy’s implementation, thereby satisfying the parallel trend criterion; conversely, if significant differences are observed, then the criterion is not met. The results of the parallel trend test are illustrated in Figure 2. As shown, the short vertical lines representing the estimated coefficients for the five periods preceding the implementation of the new energy promotion policy all intersect at “0”, demonstrating a lack of statistical significance. This indicates that there is no observable difference in the degree of green technical innovation between the firms in the experimental group and those in the control group prior to the policy’s adoption, confirming the validity of the parallel trend test. Following the second year of policy implementation, the estimated coefficient of the promotion policy is markedly positive, signifying that the new energy promotion policy enhances green technology innovation among new energy vehicle firms. The estimated coefficient in the first year after the promotion policy’s introduction is insignificant, suggesting that the policy’s effects may experience a temporal lag.

5.3.2. Placebo Testing

A placebo test is a randomized robustness assessment performed to mitigate the influence of extraneous variables on experimental outcomes. This study employs a placebo test by randomly generating experimental groups to assess the robustness of hypothesis H1. This paper identifies 11 enterprises as the virtual experimental group and 43 enterprises as the virtual control group, based on the number of experimental and control groups in the sample. A total of 500 simulation experiments were conducted, with the results of the placebo test illustrated in Figure 3. In the figure, the estimated coefficients of the difference in differences (DID) are symmetrically distributed around zero and exhibit a normal distribution. Furthermore, the majority of the black nulls significantly diverge from the intersections of the dotted lines (the true estimated coefficients), indicating that the estimated coefficients for the hypothetical extension policy deviate from the actual values. The placebo test is successful.

5.3.3. PSM-DID

This research employs PSM-DID (propensity score matching) to mitigate sample volatility and assess the robustness of hypothesis H1. The control variable is designated as the matching variable, and K-nearest neighbor matching is employed to align the experimental group with the control group. The matching results are presented in column (1) of

Table 3. Results of correlation robustness tests.

	PSM-DID	Substitution of Explanatory Variables	Lag One Phase
did	0.183 ***	0.109 ***	0.237 **
	(3.54)	(6.12)	(3.51)
control variable	be	be	be
individual fixed effect	be	be	be
year fixed effects	be	be	be
N	594	594	540
R2	0.8195	0.717	0.6832

Note: *** and ** indicate significant at the 1% and 5% statistical levels, respectively. Standard errors are in parentheses.

, where the estimated coefficients of the promotional policies remain significantly positive at the 1% level. This indicates that the promotional policies persist in positively impacting the green technological advances of new energy automotive enterprises, even after addressing the discrepancies between the samples, thereby confirming the robustness of the experiment.

5.3.4. Alternative Measure

The delay in corporate patent applications may affect the experimental outcomes. This research employs the quantity of issued green patents as a dependent variable to delineate the extent of green technological innovation among firms, thereby assessing the robustness of the experiment. The experimental results in column (2) of Table 3 indicate that the estimation of the promotion policy is 0.109, which is significantly positive at the 1% level, demonstrating that the new energy promotion policy positively influences the green technological innovation of business, confirming that the findings are robust.

5.3.5. Lagged Independent Variable

To alleviate the possible endogeneity problem in this model, this paper selects one-period lagged explanatory variables as instrumental variables for regression. This is justified because the current-period explanatory variables may affect the outcome, while the explanatory variables that lag by one period precede the explanatory variables in time and are theoretically unaffected by them. The results are shown in column (3) of Table 3, where a one-period lag of the new energy promotion policy is found to still have a significant effect on firms’ green technology innovation, aligning with the results of the benchmark regression.

5.4. Further Analysis

5.4.1. The Mediating Effect Test of Financial Constraints

Referring to Hai. B et al., the absolute value of the SA index of listed firms is used to characterize the level of firms’ financing constraints [57], which is calculated as follows:

$$\mathrm{S}\mathrm{A}=-0.737\times \mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}+0.043\times {\mathrm{s}\mathrm{i}\mathrm{z}\mathrm{e}}^2-0.04\times \mathrm{a}\mathrm{g}\mathrm{e}$$

(5)

Size refers to the firm’s magnitude, defined by its total assets, while age indicates the firm’s longevity, quantified by the duration of company’s operational years. Column (2) of

Table 4. Mechanism test results.

	GP	SA	GP	RD
did	0.225 ***	0.001 ***	0.225 ***	0.001 ***
	(6.86)	(11.84)	(6.86)	(8.57)
control variable	be	be	be	be
individual fixed effect	be	be	be	be
year fixed effects	be	be	be	be
N	594	594	594	594
R2	0.673	0.967	0.673	0.873

Note: *** indicate significant at the 1% statistical levels, respectively. Standard errors are in parentheses.

presents the results, indicating that when the explanatory variable is enterprise financing constraints (SA index), the estimated coefficient for the promotion policy is 0.001 and is significantly positive at the 1% level, suggesting that the promotion policy effectively mitigates the financing constraints faced by new energy vehicle firms. The inclusion of enterprises in the catalogue for promoting new energy applications may result from their compliance with state-established standards. The government provides policy subsidies and resource allocations, signaling to external stakeholders that these enterprises possess favorable development prospects. Relevant stakeholders are more likely to invest in such enterprises, thereby mitigating the pressure of financing constraints to some extent.

Financing constraints significantly influence enterprises’ engagement in green technology innovation activities, with extensive literature supporting the effects of these constraints on such innovations [58,59,60]. Mitigating these financial limitations facilitates the influx of financial resources into the organization, diminishing the risks associated with innovative activities. Furthermore, new energy vehicle companies listed in the new energy promotion catalogue typically possess superior social credibility, operational capacity, and market potential, making them more attractive to external investors and more trusted by financial regulators, thereby facilitating access to financial support and advancing their green technology innovative initiatives. In conclusion, Hypothesis H2 is confirmed.

5.4.2. The Mediating Effect Test of R&D Investment

This article employs the logarithm of the total R&D investment by corporations to delineate the intensity of their R&D expenditures. The outcomes are presented in columns (3) and (4) of Table 4. When the dependent variable is R&D investment (RD), the estimated coefficient of 0.006 for the promotion policy is considerably positive at the 1% level, indicating that the new energy promotion strategy can substantially enhance the R&D investment by new energy vehicle companies. This occurrence can be attributed to the government’s promotion policy, which offers financial subsidies to enterprises listed in the promotion catalogue, thereby enhancing their capacity to invest in R&D activities. Additionally, the new energy vehicles in the catalogue undergo rigorous screening, resulting in superior product and service quality. Consequently, consumers are more inclined to purchase from these enterprises, significantly boosting sales performance and providing them with additional funds for R&D investment, and the new energy vehicles featured in the promotional catalogue are selected based on superior product quality and service standards.

Moreover, the literature indicates that R&D expenditure can encourage companies to proactively participate in green technology innovation initiatives [22,51]. During green technological innovation, firms rely on external resources, with R&D investment serving as a mechanism to acquire and integrate these resources, thereby augmenting their capacity for green technological innovation. Simultaneously, augmenting R&D investment can elevate the project budget of the product development department, invigorate the department’s enthusiasm for innovative endeavors, and assist the enterprise in developing more efficient and energy-saving production equipment and technologies. This can lead to reduced energy consumption and waste emissions while enhancing the enterprise’s ability to participate in green technology innovation. In conclusion, Hypothesis H3 is confirmed.

5.4.3. The Moderating Effects of Corporate Social Responsibility

According to Wang H et al., the logarithmic CSR scores of publicly traded firms on Hexun.com were utilized to assess CSR compliance [61]. The influence of CSR on the correlation between promotional policies and green technology innovation in new energy enterprises was analyzed.

Table 5. Moderation test results for CSR.

	GP
csr	−0.227
	(−0.47)
csr_did	0.052 ***
	(3.58)
control variable	be
individual fixed effect	be
year fixed effects	be
N	594
R2	0.673

Note: *** indicate significant at the 1% statistical levels, respectively. Standard errors are in parentheses.

indicates that the estimated coefficient of the cross-multiplier term (csr*did) between promotional policies and CSR is 0.052, which is markedly positive at the 1% significance level, proving that CSR positively moderates the relationship between promotional policies and enterprises’ green technological innovation.

The influence of the new energy promotion policy is likely compounded by the fulfilment of corporate social responsibility, which signals to stakeholders that their enterprises are committed to low-carbon development. On the one hand, enterprises actively respond to the government’s call to reduce carbon emissions, save energy, and reduce emissions, and the government gives more policy support and resources to enterprises included in the promotion catalogue to help them carry out new energy technology research and development [62]. Additionally, businesses’ green technological innovations not only receive policy support but also improve their reputation by fulfilling their social responsibility. A positive CSR reputation aids in luring prospective investors [63]. Businesses listed in the promotion catalogue address the issue of information asymmetry between businesses and investors and communicate to the public their significant development potential. Enterprises form a virtuous circle by obtaining external resources to carry out a series of green innovation activities [64]. This positive feedback mechanism allows enterprises to continue to invest in green technological innovation. In addition, transparent CSR disclosures demonstrate the company’s commitment to social responsibility, which prompts the enterprise to pay more attention to the creation of long-term value rather than the pursuit of short-term interests. As a result, such enterprises are more inclined to transform the policy subsidies granted by the government into substantive green technological innovations rather than use these resources for short-term arbitrage. This enables enterprises to not only make breakthroughs in technological innovation but also to further enhance their social reputation and market competitiveness. Additionally, as consumers’ awareness of the environment grows over time, businesses are compelled to focus more on social responsibility in order to attract more eco-friendly customers. When customers identify with a brand’s environmental commitment and practical actions, they are more likely to remain loyal to it, which creates a steady stream of product profits [65]. Stable market demand and consumer support provide greater resources and motivation for companies to further increase their green technology R&D efforts. In summary, Hypothesis H4 is verified.

5.5. Heterogeneity Analysis

5.5.1. Effects of SOEs and Non-SOEs

Owing to the disparities in capital investment and resource allocation between state-owned (SOEs) and non-state-owned companies (Non-SOEs), there exists a variation in their investment in green innovation activities. Consequently, this study further investigates whether the promotion policy’s impact on green technology innovation differs depending on the heterogeneity of enterprise ownership, building upon the baseline regression analysis. State-owned firms are designated as “0” and non-state-owned enterprises as “1”, followed by group regression analysis. The data shown in the

Table 6. Results of heterogeneity test.

	(1)		(2)		(3)
	State-Owned Business	Non-State Enterprise	Large-Scale	Small-Scale	Eastern Region	Central Region	Western Region
did	0.156 **	0.375 ***	0.295 ***	−0.005	0.271 ***	0.150 **	−0.161
	(2.58)	(7.18)	(6.22)	(1.38)	(6.23)	(2.59)	(−1.15)
control variable	be	be	be	be	be	be	be
individual fixed effect	be	be	be	be	be	be	be
year fixed effects	be	be	be	be	be	be	be
N	191	402	308	284	418	132	44
R2	0.607	0.759	0.6748	0.5605	0.736	0.581	0.728

Note: *** and ** indicate significant at the 1% and 5% statistical levels, respectively. Standard errors are in parentheses.

indicate that the promotion policy substantially improves green technology innovation in both state-owned and non-state-owned firms. The estimated coefficient for state-owned enterprises is 0.156, significantly positive at the 5% level, while the coefficient for non-state-owned enterprises is 0.375, significantly positive at the 1% level. This indicates that the promotion policy for non-state-owned enterprises has a stronger effect on enhancing the green technological innovation of these enterprises compared to state-owned enterprises. The flexible flat organizational structure of non-state-owned firms fosters a robust atmosphere for innovation, enhancing their propensity to participate in green technology innovation activities following the receipt of supportive promotional policies. State-owned enterprises possess a greater allocation of policies and resources, allowing them to focus on maintaining fundamental business objectives. Consequently, management often adopts a conservative corporate strategy to mitigate risks and exhibits reluctance towards engaging in green technology innovative initiatives.

5.5.2. Effects of Firm Size

The influence of new energy promotion policies on green technology innovation among companies of varying sizes may exhibit distinct differences. This paper classifies enterprise size derived from the median of total assets, designating enterprises with assets exceeding the median as large-scale enterprises, labeled as “1”. Conversely, it also classifies small-scale firms, which are designated as “0”. Group regressions are performed. The data presented in Table 6 indicate that the promotion policy remarkably influences the green technology innovation of large-scale enterprises, with an estimated coefficient of 0.297, which is notably positive at the 1% level, but the promotion policy does not exert a significant effect on the green technology innovation of small-scale enterprises. This may be attributed to the fact that large-scale firms possess more financial resources, skilled technical personnel, and progressive green development philosophies, with management prioritizing both economic gains and environmental conservation. The execution of the promotion strategy concurrently provides additional resources to firms, thereby enhancing the willingness and capacity of major companies to participate in diverse green technology innovation activities. In addition, small-scale companies face challenges in securing financing and lack the necessary manpower and financial resources to advance green technology. Additionally, these firms also face heightened risks, leading many risk-averse small enterprises to prefer adopting existing green technologies rather than investing in costly and risky research and development initiatives.

5.5.3. Effects of Geographical Location

Green development has consistently faced the issue of regional disparities in growth. This article categorizes enterprises into three regions—east, central, and west—based on China’s administrative divisions, designated as “1”, “2”, and “3” for group regression purposes. The table indicates that the promotion policy substantially influences green technology innovation among companies in the eastern area, evidenced by an estimated coefficient of 0.271, which is significantly positive at the 1% level. Additionally, the promotion policy also improves the level of green technology innovation in enterprises in the central region, reflected by an estimated coefficient of 0.150, which is significantly positive at the 1% level. Nevertheless, the promotion policy exerts no significant effect on the green technology innovation of firms in the western region. This may be attributed to the eastern and central regions exhibiting more advanced economic levels compared to the western region. These areas benefit from a more mature market environment and an optimized industrial structure, thereby fully capitalizing on the high-quality development opportunities provided. The eastern region is a developed area with robust economic power, offering attractive incomes, ample employment opportunities, and extensive development potential for talent, thereby attracting individuals and infusing creativity and vitality into organizations.

This paper employs a two-way fixed-effects regression model grounded in the difference-in-differences approach to examine the direct influence of the new energy vehicle promotion policy on enterprises’ green technology innovation. The findings indicate that the new energy promotion policy significantly enhances green technology innovation, thereby validating Hypothesis H1. To ensure the robustness of these findings, the following five types of robustness tests were performed: the parallel trend test, the placebo test, the PSM-DID, the substitution of dependent factors, and the independent lagged analysis. Furthermore, through a two-step mechanism analysis, the impact pathway of the new energy promotion policy on enhancing enterprise green technology innovation was elucidated. It was confirmed that the promotion policy elevates technology innovation by alleviating financing constraints, thereby validating Hypothesis H2. Additionally, it was established that the promotion policy fosters green technology innovation by augmenting enterprise R&D investment, thus confirming Hypothesis H3. The moderating effect model confirmed that CSR strengthens the relationship between promotional policies and organizations’ green technological innovation, validating Hypothesis H4. The study further concluded that, based on variations in the SOEs and Non-SOEs, scale, and geographic location of enterprises, non-state-owned enterprises exhibit a more pronounced enhancement in green technological innovation due to promotional policies; these policies have a more substantial impact on the green technological innovation levels of large enterprises; and they significantly elevate the green technological innovation levels of enterprises located in the eastern and central regions.

6. Conclusions and Discussion

6.1. Conclusions

This article analyzes the impact mechanism of promotional policies on green technology innovation in new energy automobile companies, using panel data from listed companies between 2011 and 2022, and it provides a theoretical foundation for the development of future new energy policies. The research indicates that the promotion program significantly improves the green technology innovation capabilities of new energy automotive firms. Financing limitations, R&D investment, and corporate social responsibility (CSR) serve as mediating factors in the interaction between promotional policies and corporate green technology innovation. The execution of the promotion policy can mitigate the burden of financial constraints on firms, providing sufficient finances to improve their green technology innovation capacity. It also provides incentive to firms to increase their R&D investment, further boosting their green technology innovation. By actively fulfilling their social responsibilities and signaling their commitment to the market, enterprises can attract external investment, thereby amplifying the influence of the promotion policy on their green technology innovation. This research reveals significant heterogeneity, with the promotion policy having a more pronounced effect on non-state-owned enterprises, larger firms, and those located in eastern and central regions. Based on these findings, this paper proposes the following countermeasures.

The government should continue to strengthen new energy promotion strategies and augment R&D financing for firms. It should establish suitable indicators and evaluation criteria tailored to the specific circumstances of firms, ensuring that the evaluation system is both differentiated and relevant. Additionally, incentives and penalties should be introduced, and enterprises demonstrating significant success in green innovation should receive increased subsidies, resource allocation, and tax relief to incentivize ongoing green technological advancements [66]. Additionally, enterprises with limited R&D accomplishments in the promotion catalogue should face penalties, including reduced financial subsidies and formal criticisms. The government should also establish communication channels with enterprises to remain informed about R&D progress, comprehend the challenges faced by these enterprises, and offer assistance, thereby enhancing policy support for green technological innovation.

Social duties should be proactively addressed to mitigate the challenges of business finance limitations. Enterprises should proactively disclose environmental facts promptly and enhance financing conditions to alleviate financial burden. Alongside enhancing their operational and financial conditions, enterprises should enhance communication with investors and creditors, demonstrate their strengths, and communicate their commitment towards environmental responsibility, thereby effectively attracting investors, augmenting financing capabilities, and subsequently elevating their level of green technological innovation [67]. Furthermore, the government should promote the advancement of green credit mechanisms to assist firms in overcoming financial challenges and facilitate their transition to sustainable development [68,69].

To address heterogeneity in enterprise green technology innovation, the government should tailor policies based on the diversity of corporate ownership structures. State-owned firms should integrate green technology innovation into their annual performance assessment criteria, thereby stimulating enthusiasm for innovation across the organization [70]. Additionally, given the differences in enterprise scale, the state should proactively implement policies to assist underperforming small enterprises and to enhance financial subsidies, tax incentives, and other measures to furnish financial support, encouraging their active involvement in green technology innovation initiatives. Finally, to mitigate regional disparities, the government ought to subsidize new energy companies in underdeveloped areas by financial allocations or specialized funds, facilitating their green technology innovation, green product development, and related initiatives.

6.2. Discussion

This research provides a comprehensive analysis of the influence of new energy vehicle promotion policies on corporate green technology innovation, while also exploring the mechanisms connecting the two. Nonetheless, several limitations exist in this study. First, it utilizes the quantity of green patent applications to characterize the extent of green technological innovation among enterprises. However, the number of green patents does not comprehensively reflect the level of innovation, as it merely indicates the output of green technological innovation and fails to accurately assess the actual application impact and market influence of these innovations. Future research can investigate the feasibility of developing a comprehensive indicator that encompasses both the output of green technology and the transformation of green outcomes, thereby providing a more thorough assessment of the extent of green technological innovation within firms. Second, the sample data in this study comprise listed new energy vehicle enterprises in China, and non-listed new energy vehicle companies, as well as entities with inaccessible data, may also contribute to the broader landscape of innovation. This limitation could result in representational bias and could constrain the generalizability of the findings. Efforts should be made to gather data from non-listed new energy vehicle companies via alternative channels, including local governments, industry associations, and third-party databases, to acquire additional information pertaining to financial reports, research and development, and technological innovations of small- and medium-sized, non-listed enterprises.

In addition to addressing the previously mentioned deficiencies, potential future research avenues should encompass the following: A comparison of the effects of new energy policies across different countries could provide valuable insights into how varying policy approaches influence the green technological innovation of enterprises. For instance, the carbon emission limit policy in Europe and the subsidy policy in China exert distinct processes on the green technology innovation of new energy vehicles. Secondly, future studies can further investigate the broader societal and environmental impacts of green technology innovation by new energy vehicle companies, encompassing the reduction of carbon emissions, enhancement of air quality, and facilitation of energy structure transformation. Future policy concerning new energy vehicles may be modified based on the feedback mechanism of externalities.