The Effect of Market-Based Environmental Regulations on Green Technology Innovation—The Regulatory Effect Based on Corporate Social Responsibility

Abstract

This study explores the impact of market-based environmental regulations on green technological innovation and the differential regulatory effects of corporate social responsibility (CSR) on different levels of green technological innovation. By analyzing data from 746 Chinese A-share listed companies from the period of 2008–2021, this paper examines the effect of market-based environmental regulations on corporate green technology innovation. The research findings are as follows: (1) Market-based environmental regulations have a significant promoting effect on green technology innovation in enterprises. (2) CSR amplifies the positive influence of market-based environmental on green technological innovation, but it has a greater impact on strategic innovations, like utility model patents, rather than substantial ones, like invention patents. Corporate may use CSR to superficially meet regulatory pressures and stakeholder expectations, focusing more on short-term compliance than on long-term sustainable innovation. Companies might utilize CSR as a superficial means to appease regulatory demands, concentrating on immediate compliance rather than fostering enduring innovation. (3) Market-based environmental regulations facilitate green technological innovation by alleviating enterprise financing constraints and improving the efficiency of innovation resource allocation. (4) The promotion effect of market-based environmental regulations on green technological innovation is particularly evident in state-owned enterprises, heavily polluted industries, and regions with high regulatory levels. The research contribution is to provide valuable insights into the implementation of market-based environmental regulations and firms’ green technological innovation. Specifically, it elucidates the nuanced regulatory effects of corporate social responsibility, presenting a fresh lens through which to reconsider the intricate mechanism of CSR’s role as a conduit between environmental policy and innovative practices.

1. Introduction

Technological innovation stands as an intrinsic catalyst of sustainable economic expansion, particularly in the context of the rapidly evolving exogenous milieu [1]. As the ramifications of global challenges, such as resource scarcity and ecological decay, intensify, a burgeoning consensus has emerged among economies worldwide—spanning both industrialized and emerging nations—with a pronounced focus on sustainable and eco-friendly growth, a trend particularly pronounced in the latter [2]. Green innovation and green development, as a development model to achieve a balanced economic, social, and ecological environment, is based on the principles of recycling and sustainable and low emissions, and focuses on improving the efficiency and capacity of green development [3,4].

From the perspective of international trends, the adoption of environmental regulatory policies to catalyze the green metamorphosis of corporations represents a prevalent international strategy. The promotion of green technological innovation and sustainable development has experienced a new round of global scientific and technological revolution and is an important new area of enterprise market competition [5]. Central to the achievement of sustainable development objectives is the imperative to attenuate the resource intensity across key economic sectors and to embrace a circular economic paradigm. Green technology innovation focuses on reducing consumption, reducing pollution, improving the supply of ecological technology, and promoting the transition of the economy and society to a green mode of development and lifestyle [6] Such innovation promises a dual-fold advantage: it is capable of mitigating environmental contamination and bolstering a firm’s environmental stewardship, while concurrently enhancing its core competitiveness. This positions green technology innovation as a pivotal instrument in actualizing the symbiotic triumph of economic prosperity and environmental conservation [7].

From the viewpoint of domestic trends, since the 18th National Congress of the Communist Party of China (NCCPC), the government of China has repeatedly emphasized the new development concept of green and sustainable development. The report of the 20th NCCPC once again emphasized high-quality economic development and the green transformation of accelerated development methods, promoting the formation of green and low-carbon production and lifestyle. This underscores that pursuing green development is a critical strategy for the national economy and people’s livelihood, and is an inevitable choice for achieving high-quality development in China. Numerous studies have indicated that green and sustainable industrial activities and technological innovation have significantly increased under the guidance of national sustainable development policies [8,9].

Practice has shown that relying solely on micro-entities, such as enterprises, to achieve green technology innovation and economic structural transformation is often insufficient [8,9,10,11,12]. Meanwhile, according to the perspective of institutional economics, a reasonable external institutional environment design can effectively improve the performance of micro-entities [13]. However, whether the series of environmental regulatory policies proposed by the government can achieve their intended goals is often influenced by factors such as the response strategies of micro-entities and the internal and external environment [14,15]. The existing studies have demonstrated that, under command-based environmental regulatory tools, firms tend to engage in more strategic innovation behaviors, which can adversely affect the quality of green innovation [11,12,14,15]. Consequently, Chinese regulators have increasingly emphasized market-based environmental regulatory tools, such as carbon emissions trading [16], environmental protection tax law, and sewage charging system [17,18]. Hu et al. (2020) and Guo (2019) emphasize the important role of market-based environmental regulation in promoting technological innovation. However, the impact of market-based environmental regulatory instruments on firms’ green technological innovation still requires further in-depth investigation [16,17,18,19,20]. The existing studies lack comprehensive and detailed investigations into this issue. Whether market-based environmental regulation can promote substantive green innovation by firms is still an unanswered question.

Concurrently, as the concept of green development—“green mountains and clear waters are mountains of gold and silver”—becomes deeply ingrained in public consciousness, there is increasing attention on the green innovation activities of enterprises. In addition, in the era of self-media, the supervision of enterprises by external groups, such as the public, has significantly increased. Therefore, corporate social responsibility, as a corporate behavior that the public can directly pay attention to, is bound to have a certain impact on the innovation of enterprises, especially green innovation [21,22,23].

The existing studies have pointed out that CSR can promote the level of technological innovation, the improvement in innovation efficiency, and the increase in innovation output [24,25], which is conducive to the enhancement in enterprise value and competitiveness [26,27]; the fulfilment of CSR can alleviate the financing constraints of enterprises, enhance the employees’ career acquisition sense, reduce management’s short-sighted behaviors, and thus promote corporate innovation [21,22,23,24,25,26]. The positive impact of CSR has been widely recognized. However, whether CSR influences the effectiveness of market-oriented environmental regulations remains to be investigated. Whether CSR acts as a “catalyst” that assists in the implementation of environmental regulations or as a means of concealment requires further research [27,28,29]. The existing research has not thoroughly explored this issue, and in-depth investigation is needed.

In summary, many scholars have examined the impact of environmental regulations and green technology innovation from both theoretical and empirical perspectives. However, there is a clear gap in the existing literature on the impact of market-based environmental regulation on firms’ green technological innovation, especially when considering the role of corporate social responsibility (CSR) in terms of market-based environmental regulation and green technological innovation. Against this background, this study aims to explicitly investigate the following research questions: how does market-based environmental regulations affect green technological innovation among Chinese firms, and what are the roles of CSR and financing constraints in this context?

Accordingly, this study selected a sample of 746 A-share listed companies in China from 2008 to 2021. It adopted a two-way fixed-effects model, a moderated-effects test model, and a mediated-effects test procedure to study the impact of market-based environmental regulation on corporate green technological innovation. Additionally, the study examined how CSR influences the underlying mechanisms mediating between environmental regulation and green innovation, providing a comprehensive analysis of this relationship. The research has found that market-oriented environmental regulations have a significant promoting effect on green technology innovation in enterprises. In addition, the reinforcing effect of CSR is particularly evident in strategic green innovation, but not in substantive green innovation, suggesting the existence of a “masking effect” of CSR, whereby firms symbolically respond to policy pressures from government regulators through the fulfilment of their social responsibilities. Market-oriented environmental regulations promote substantial green technology innovation by alleviating financing constraints on enterprises, improving the efficiency of innovation resource allocation, and ultimately promoting substantial green technology innovation in enterprises.

The contributions of this paper are threefold. Firstly, it expands the theoretical research on the impact of market-oriented environmental regulation on enterprises’ green technological innovation, offering a more detailed understanding of this relationship. Secondly, it transcends the limitations of the existing studies that primarily focus on CSR within the framework of command-and-control and public-participation environmental regulation. This study integrates CSR into the analytical framework of market-based environmental regulation and green technological innovation, exploring the mechanism through which CSR regulates the effect of environmental regulation on the promotion of corporate green technological innovation and validating the “masking effect” of CSR. Lastly, this study explores the mechanism of financing constraints between market-oriented environmental regulations and corporate green technology innovation, providing a new perspective for understanding the relationship between environmental regulations and corporate green technology innovation.

The structure of the remaining sections of this study is outlined as follows: Section 2 delineates the research hypotheses of this paper. Section 3 details the research methodology, encompassing the selection of samples, data sources, variable definition, and measurement, and model setup. Section 4 reports the empirical results and discussion. Section 5 describes the conclusions of the study, policy recommendations, limitations, and future research directions.

2. Literature Review and Research Hypotheses

2.1. Market-Based Environmental Regulation and Green Technological Innovation

Early environmental regulatory instruments, such as environmental legislation [4] and penalties for environmental violations [8], have predominantly relied on command-and-control approaches [10,11]. Jing et al. found that the implementation effect of environmental regulatory policies also depends on the choice of business entities [10].

Command-and-control regulations have limited incentivizing effects on green innovation activities and, to some extent, even generate a “crowding out effect” on the enterprise’s green technological innovation [11]. With the advancement of regulatory processes, China has gradually implemented market-oriented and informal environmental regulations (also known as public participation environmental regulations). Currently, market-based environmental regulations in China include sewage charges, environmental taxes, and carbon emissions trading mechanisms. Market-oriented environmental regulations have a significant promoting effect on corporate technological innovation [16,17,18,19], meaning that the “compensation effect” exceeds the “crowding out effect” [30,31].

In the current macro-context of economic development entering a new normal, in order to achieve the goal of green and sustainable development, the government should fully respect market rules, stimulate the vitality of market entities [32], and use market mechanisms to motivate enterprises to better enhance their green innovation capabilities in the face of environmental regulations [32,33].

Market-based environmental regulation relies on market principles to guide and incentivize enterprises to proactively engage in substantive green technological innovation [15]. By employing financial measures, taxes, and fees, market-based environmental regulation is more targeted and practical, significantly elevating the level of green technological innovation within enterprises [18]. By its very nature, market-based environmental regulations rely on the principle of “whoever pollutes pays”, which can transform the negative externalities of enterprises into internal business decision-making problems, forcing enterprises to consider the adverse effects of business activities on the external environment and society when implementing internal controls [30,31,32,33].

As a result, under market-oriented environmental regulations, enterprises often choose green innovation strategies that are more favorable for their long-term development, ensuring that the “compensation effect” of green technology innovation surpasses the “crowding out effect”. When subjected to market-based regulations, enterprises actively engage in green technological innovation activities.

Based on the above analysis, this paper puts forward the following research hypothesis:

H1: 

Market-based environmental regulation has a positive facilitating effect on firms’ green technology innovation.

2.2. Corporate Social Responsibility, Market-Based Environmental Regulation, and Green Technological Innovation

The majority of the existing studies have demonstrated that corporate social responsibility (CSR) plays a pivotal role in enhancing the technological innovation level, efficiency, and output of enterprises [21,22,23], which is conducive to the enhancement in enterprise value and competitiveness [24]. The fulfillment of corporate social responsibility can alleviate financing constraints, enhance employee career satisfaction, reduce management’s short-sighted behavior, and promote green technology innovation in enterprises [25,26]. However, a minority of scholars have posited alternative views, suggesting that corporate social responsibility may be seen as a tool for business operations, as a means of concealing a company’s poor situation [27,28], or as a rent-seeking tool and political contribution [34]. Drawing from signal theory, in situations where the external environment is uncertain, companies can release positive performance signals by fulfilling social responsibility, attracting the attention of stakeholders and obtaining corresponding economic and social resources [22,25]. Consequently, governments and other regulators are more willing to provide a series of tax incentives and industrial support to companies that fulfill social responsibility, resulting in a certain “masking effect”. Furthermore, it plays a certain promoting role in the technological innovation of enterprises.

In addition, with the increasing public and media attention to corporate social responsibility behavior and environmental regulatory policies in recent years, enterprises are inevitably influenced by the combined effects of environmental regulations and corporate social responsibility. Meanwhile, corporate social responsibility can to some extent promote the alignment of corporate executives’ awareness with the government’s pursuit of long-term sustainable development goals [21,25], This implies that companies that are more inclined to undertake corporate social responsibility are generally more likely to prioritize the unity of economic and social benefits and to overcome short-sighted behaviors [23,24,25]. Such firms are also more aware of the importance of green technological innovation and are more motivated to engage in it. Therefore, companies that actively fulfill their social responsibility tend to make substantive technological innovations rather than strategic ones. Stakeholders, such as governments, consumers, and employees, are more likely to support such companies after receiving positive signals of social responsibility fulfillment. Based on this analysis, we propose the following hypothesis:

H2: 

CSR can strengthen the promotion effect of market-based environmental regulation on firms’ green technology innovation.

2.3. Market-Based Environmental Regulation, Financing Constraints, and Corporate Green Technology Innovation

Market-based environmental regulations aim to steer enterprises towards green transformation by augmenting their environmental costs through the implementation of pollution charges and environmental protection taxes. In the context of green development, stakeholders, such as the government and the public, will increase their credit support for green industries, low-carbon technologies, and energy-saving and environmental protection projects. Conversely, heavily polluting industries encounter restricted access to credit resources, and stringent measures, such as the implementation of a one-vote veto system, are applied to enterprises with severe environmental pollution. This significantly amplifies the financing constraints faced by these enterprises, negatively impacting their access to credit resources [35]. Consequently, enterprises with higher pollution emissions face heightened economic pressures and financing limitations [16,17,36]. Extensive examples in the literature point out that strict financing constraints can limit companies’ green technology innovation [19,20,31,37]. As a response to environmental pressure, enterprises are more inclined to adopt green technology innovation to reduce pollution emissions and mitigate financing risks. The alleviation of financing constraints enables enterprises to access a more abundant and sufficient pool of credit resources, optimizing the innovation resources of firms according to the resource-based theory, thereby enhancing their innovation capabilities. Market-based environmental regulation and green credit policies play a vital role in fostering the enterprise’s inclination and demand for green technological innovation.

Firstly, enterprises can only secure credit resources through the adoption of green technological innovations. Secondly, once enterprises effectively implement green technology innovation measures to enhance environmental benefits, financial institutions become more inclined to provide financing support [16,17,35,36,37,38]. Consequently, the enterprise’s desire and need for green technological innovation are bolstered by these two factors. Therefore, market-based environmental regulation serves as a catalyst for technological innovation by alleviating enterprises’ financing constraints.

Based on the above theoretical analysis, we formulate the following research hypothesis:

H3: 

Market-based environmental regulation facilitates firms’ green technology innovation by alleviating financing constraints.

3. Methodology

3.1. Sample Selection and Data Sources

The sample utilized in this study consisted of listed companies in China’s A-shares between 2008 and 2021. The selection of this specific period was motivated by the following reasons: (1) The disclosure of information by listed companies improved significantly after 2008. Consequently, data from this period are readily accessible and ensured the consistency of the statistical scope of the research sample in this paper. Therefore, 2008 was chosen as the starting year for the sample. (2) China’s emphasis on green development and market-based environmental regulation has intensified notably since the 12th Five-Year Plan.

In this study, data on market-based environmental regulation and corporate green technology innovation were from the China Research Data Service Platform (CNRDS). Corporate social responsibility (CSR) data came from the CSR evaluation provided by https://www.hexun.com (accessed on 23 December 2022). Data on micro-level control variables were from the CSMAR database. Data on macro-level control variables were from the China Statistical Yearbook. In order to ensure data accuracy and reliability, the data from various databases underwent manual processing and comparison.

The industry standard employed in this study adheres to the 2012 version of the industry classification standard by China Securities Regulatory Commission. The regional categorization of listed companies was determined according to the provincial cities specified in the relevant database. To ensure the accuracy of the results of the study, referring to Xing et al. (2023) [4] and Yu et al. (2024) [38], we processed the data according to the following steps: (1) Firms with ST, *ST, and PT statuses were excluded. (2) Samples from the financial sector and real estate sector were excluded. (3) Samples lacking data on the core variables were excluded. (4) Continuous variables were Winsorized by 1% on both ends to mitigate the influence of extreme values. Finally, this study contained 3854 sample observations of enterprises, totaling 746 listed enterprises. The data processing software used was Stata16.0.

3.2. Variable Definition and Measurement

3.2.1. Explained Variable: Green Technological Innovation (GI)

This study assessed the green technological innovation of enterprises by considering two dimensions: green input and green output. Building upon the research conducted by Hu et al. (2020) [19], Wang et al. (2023) [15], and Huang et al. (2023) [11], green input is measured by the ratio of the enterprise’s R&D expenses to total assets (RD). On the other hand, to quantify green output, this study employed the logarithmic value of the combined count of green invention and green utility model patents for listed companies within the current year (LnGIA).

3.2.2. Explanatory Variables: Market-Based Environmental Regulation (MBER)

During the sample period of this article, pollutant discharge fees were the main market-based environmental regulatory measures faced by enterprises. Therefore, this article adopted the annual pollution discharge fees of enterprises to measure market-oriented environmental regulations. Unlike the existing studies that use regional pollution fees to measure environmental regulations, drawing on the ideas of Li and Xiao (2020) [39], this article measured market-oriented environmental regulations based on the total amount of pollution fees paid by enterprises in the current year. To mitigate the impact of quantitative scale variations, this value was standardized and subsequently utilized as a proxy variable for market-based environmental regulation.

3.2.3. Moderating Variable: Corporate Social Responsibility (CSR)

Taking into account the credibility of the CSR evaluation conducted by https://www.hexun.com (accessed on 23 December 2022), this study adopted a methodology inspired by Yang et al. (2021) [22] to measure CSR. Specifically, the assessment of CSR is based on the scores and ratings provided by https://www.hexun.com (accessed on 23 December 2022), whereby higher scores and ratings are indicative of superior performance in fulfilling CSR obligations. The Hexun.com CSR evaluation system categorizes corporate responsibility into a total of five dimensions, namely social responsibility (Csr1), environmental responsibility (Csr2), supplier customer and consumer rights responsibility (Csr3), employee responsibility (Csr4), and shareholder responsibility (Csr5). In further analyses, we assess the impact of the five responsibility dimensions on different green technology innovations.

3.2.4. Mediating Variable: Financing Constraints (SA)

In this study, we employed the SA index introduced by Hadlock and Pierce (2010) [40] as a metric to gauge the financing constraints encountered by firms. The SA index serves as an indicator of the magnitude of these constraints, with larger values indicating lower levels of financing constraints, and conversely, smaller values suggesting higher levels of financing constraints faced by firms.

3.2.5. Control Variables

Drawing on the experience of the prior research conducted by Qi et al. (2018) [41], Yu et al. (2024) [38], and Huang et al. (2023) [11], this study incorporated both macro-level and micro-level control variables. The micro-level variables mainly refer to the economic characteristics related to listed companies, including firm size (Size), firm age (FirmAge), profitability (ROA), nature of ownership (SOE), and equity concentration (Top1). On the other hand, the macro-level control variables encompass tax burden level (Tax), command environmental regulation (ER), foreign direct investment (FDI), industry concentration (IndustryC), and energy structure (Energy). For a detailed understanding of the variable definitions, please refer to

Table 1. Definition of variables.

Variable Type	Variable Name	Variable Symbol	Definition of Variables
Explained variables	Green innovation outputs	LnGIA	Logarithm of green patent applications
	Green innovation inputs	RD	R&D investment as a percentage of total assets
Explanatory variables	Market-based environmental regulation	MBER	Normalized value of sewage charges paid by enterprises in the current year
Moderating variable	Corporate social responsibility	CSR	CSR ratings and scores published by https://www.hexun.com (accessed on 23 December 2022)
Mediating variables	Financing constraints	SA	SA index
Micro-control variables	Enterprise size	Size	Natural logarithm of total assets
	Age of business	FirmAge	Natural logarithm of company years
	Profitability	ROA	Net profit to total assets
	Nature of property rights	SOE	State-owned enterprises are assigned a value of 1, otherwise 0
	Shareholding concentration	Top1	Percentage of shares held by the largest shareholder
Macro-control variables	Tax burden level	Tax	Tax revenue to GDP ratio
	Command environmental regulation	ER	Ratio of investment in environmental pollution control to value-added of industry
	Overseas foreign direct investment	FDI	Foreign direct investment as a percentage of GDP
	Industrial concentration	IndustryC	Employment as the ratio of the administrative area
	Energy structure	Energy	Electricity consumption as a percentage of national total
	Year	Year	Annual dummy variables
	Sector	Industry	Industry dummy variables

.

3.3. Model Construction

To validate the aforementioned research hypothesis H1, this study, referring to Yu et al. (2024) [38] and Huang et al. (2023) [11], formulated the following regression model (1). The explanatory variable was market-based environmental regulation (MBER), whereas the dependent variable was enterprise green technology innovation (GI), encompassing research and development (RD) on the input side and logarithm of green innovation activity (LnGIA) on the output side. Furthermore, the model included a constant term (a₀), year dummy variables (Year), industry dummy variables (Industry), and a random disturbance term (u). Similarly, model (2) was constructed to examine research hypothesis H2. Additionally, models (3) and (4) were devised to assess research hypothesis H3. To control for relevant fixed effects, industry and year fixed effects were inclusively accounted for. Robust standard errors clustered at the firm level were employed as the default method in this study.

$${GI}_{i,t}=a_0+a_{1}MB{ER}_{i,t}+a_{2}Controls+Year+Industry+u$$

(1)

$${LnGIA}_{i,t}=a_0+a_{1}MB{ER}_{i,t}+a_2{CSR}_{i,t}+a_{3}MB{ER}_{i,t}\ast {CSR}_{i,t}+a_{4}Control+Year+Industry+u$$

(2)

$${MBER}_{i,t}=a_0+a_1{SA}_{i,t}+a_{2}Controls+Year+Industry+u$$

(3)

$${GI}_{i,t}=a_0+a_{1}MB{ER}_{i,t}+a_2{SA}_{i,t}+a_{3}Controls+Year+Industry+u$$

(4)

4. Empirical Analysis

4.1. Descriptive Statistics

Table 2. Descriptive statistics of the main variables.

Variable	Obs	Mean	Std. Dev	Min	Max
LnGIA	3854	0.358	0.724	0.000	4.635
MBER	3854	0.017	0.046	0.000	1.000
FDI	3854	0.020	0.012	0.000	0.082
ER	3854	0.028	0.028	0.000	0.310
Tax	3854	0.081	0.028	0.042	0.200
IndustryC	3854	0.032	0.037	0.000	0.217
Energy	3854	0.050	0.029	0.001	0.099
Size	3854	22.397	1.261	9.399	27.293
SOE	3854	0.490	0.500	0.000	1.000
ROA	3854	0.040	0.069	−0.531	0.816
Top1	3854	0.361	0.146	0.041	0.900
FirmAge	3854	2.848	0.354	0.693	3.829
RD	1343	0.018	0.015	0.000	0.159

presents the descriptive statistics of the main variables. The mean value of the number of enterprise green technology innovation patents (LnGIA) is 0.358, indicating that less than half of the enterprises in the sample have achieved green innovation, thereby reflecting the overall low level of green technology innovation among Chinese enterprises. Moreover, the standard deviation of this variable is 0.724, signifying significant differences in the green technology innovation levels of distinct enterprises. Moreover, the mean value of market-based environmental regulation (MBER) stands at 0.017, indicating a relatively low level of market-based environmental regulation across the entire sample. This finding underscores the need for significant improvements in the current state of market-based environmental regulation in China. Additionally, the data characteristics of the remaining control variables align with those reported in previous studies [14,21,39], reinforcing the reliability of the data selection methodology adopted in this research.

4.2. Correlation Coefficient Analysis and Multicollinearity Test

This study also examined the correlation coefficients between the variables and the variance inflation factors (VIFs) of each variable. Due to space limitations, the table detailing the correlation coefficients and VIF was not included in the main text but is available for reference. It is noted that none of the correlation coefficients among the variables exceed 0.7, and the VIF values for all variables do not surpass 1.7, except for industrial industry concentration and tax burden level, which exhibit VIF values of 3.02 and 3.7, respectively. The average VIF value across all variables is 1.62, well below the critical threshold of 10. These findings indicate the absence of significant multicollinearity issues within the model.

4.3. Verification of Hypothesis H1

This paper explored the impact of market-based environmental regulation on firms’ green technological innovation based on Equation (1).

Table 3. Regression results of MBER on GI.

	M(1)	M(2)	M(3)	M(4)
	LnGIA	LnGIA	RD	RD
MBER	0.652 **	0.680 **	0.024 ***	0.021 ***
	(2.29)	(2.40)	(3.14)	(2.73)
Size	0.100 ***	0.081 ***	−0.003 ***	−0.004 ***
	(6.80)	(5.21)	(−7.66)	(−8.10)
SOE	0.070 *	0.094 **	−0.000	−0.000
	(1.79)	(2.26)	(−0.43)	(−0.43)
ROA	0.074	0.112	0.009 ***	0.008 ***
	(0.52)	(0.77)	(3.13)	(2.84)
Top1	0.005	0.071	0.002	0.007 **
	(0.04)	(0.65)	(0.58)	(2.26)
Age	0.038	−0.125 **	−0.002	−0.006 ***
	(0.89)	(−1.96)	(−0.82)	(−2.71)
FDI	−1.389	−2.693 **	−0.052	0.041
	(−1.20)	(−2.00)	(−1.12)	(0.85)
ER	−0.132	−0.202	−0.068 ***	−0.032 *
	(−0.33)	(−0.43)	(−4.39)	(−1.88)
Tax	−0.234	−1.401	−0.027	0.035
	(−0.30)	(−1.13)	(−1.26)	(1.47)
IndustryC	0.381	−8.333 ***	0.055 ***	0.004
	(0.59)	(−3.27)	(3.19)	(0.20)
Energy	0.738	8.552 ***	0.111 ***	0.096 ***
	(1.05)	(2.97)	(5.63)	(5.07)
Constant	−2.040 ***	−0.582	0.095 ***	0.087 ***
	(−6.64)	(−1.18)	(8.32)	(6.30)
Year-FE	NO	YES	NO	YES
Industry-FE	NO	YES	NO	YES
N	3854	3854	1343	1343
Adj_R2	0.083	0.163	0.177	0.306

Note: ① ***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively. ② Values in brackets are the adjusted t-values, the same below, and will not be repeated. ③ All models in the following text are controlled by year and industry, and will not be reiterated. ④ After the correlation test conducted in this study, it was determined that random effects are more appropriate for the model. After controlling for individual fixed effects in the company, it was found that the regression results were still significantly positive. However, the model’s R² experienced a substantial decline; therefore, this article did not control for fixed effects.

presents the findings of the benchmark regression analysis on the impact of market-based environmental regulation on firms’ green technological innovation. Across all models, market-based environmental regulation has a positive effect on enterprises’ green technological innovation. In Model M(2), which controls for year and industry effects based on Model (1), the conclusion remains unchanged. The regression results of Model M(2) (a = 0.680, p < 0.05) indicate a significant and positive promoting effect of market-based environmental regulation on enterprises’ green patent applications. Furthermore, the results of Model (4) (a = 0.021, p < 0.01) reveal a significant positive promotion effect of market-based environmental regulation on the proportion of R&D investment by enterprises. As illustrated by the regression outcomes in Table 3, Hypothesis H1 is validated, supported by empirical evidence indicating a noteworthy positive impact of market-based environmental regulation on enterprises’ green technological innovation. This beneficial effect extends to both the input and output dimensions of innovation, suggesting that market-based environmental regulation can boost enterprises’ R&D investments and advance their level of green technological innovation.

These outcomes demonstrate the potential of market-based environmental regulation to facilitate sustainable economic and social development by steering the green transformation of enterprises. In addition, according to Table 3, we find that firm size has a positive effect on firms’ green technology innovation output and a negative effect on green resource input. Other factors such as the nature of property rights and the age of the enterprise all have different degrees of influence on green technology innovation.

4.4. Endogeneity and Robustness Tests

In order to verify the robustness of the findings above, this paper performed the following four robustness tests.

4.4.1. Substitution of Dependent Variables

This paper adapted the measurement of green technology innovation in terms of innovation resource inputs and outputs. Regarding green output metrics, they were substituted with the natural logarithm of the number of green invention patent applications (LnGA1) and the natural logarithm of the number of authorized green patents (LnGIG), respectively. Green invention patents, distinguished from green utility model patents, represent a higher level of complexity and technological sophistication, providing a more precise gauge of enterprises’ core green technology innovation. Consequently, this article utilized the number of green invention patent applications (LnGA1) as the dependent variable for robustness testing. Past research underscores that green patents subject to regulatory review and approval offer a more accurate reflection of enterprises’ genuine green technology innovation [8]. Thus, this study adopted the number of authorized green patents of enterprises (LnGIG) as the measure for green technology innovation.

The input dimension was substituted with the logarithm of R&D input (LnRD). In

Table 4. Robustness test I: replacement of the explained variables and instrumental variables.

	Replacement of Explained Variables			IV-Two Step
	M(1)	M(2)	M(3)	M(4)	M(5)
	LnGA1	LnGIG	LnRD	LnGIA	RD
MBER	0.353 *	0.891 ***	1.844 *	0.691 **	0.02 ***
	(1.56)	(3.43)	(1.95)	(2.45)	(2.72)
Control	YES	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES	YES
N	3854	3854	1343	3854	1343
Adj_R2	0.141	0.046	0.543	0.122	0.309

***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively.

, M(1)–M(2) present the regression results with the output dimension—green patents—as the independent variable, and M(3) displays the regression result with the input dimension—R&D inputs. The empirical results of the models in Table 4 corroborate the robustness of the benchmark regression findings.

4.4.2. Instrumental Variable Method

To address potential reverse causality, this study employed an instrumental variable approach using the two-stage least squares regression technique. The instrumental variable selected for this regression is the standardized mean value of sewage charges within the same industry and period, excluding the company in question [39]. The rationale is that, while the industry average of sewage charges can influence a company’s own charges, it is unlikely to have a direct bearing on the firm’s green technology innovation endeavors, thus qualifying as an appropriate instrument.

The adjusted regression results yield positive coefficients (a = 0.691, p < 0.05; a = 0.020, p < 0.01) that surpass the significance thresholds of 5% and 1%, respectively. These results, as delineated in Table 4, reinforce the robustness of the study’s conclusions, corroborating the integrity of the empirical analysis in the face of potential endogeneity concerns.

4.4.3. Substitution of Explanatory Variables

To further validate the robustness of the findings from the initial benchmark regression, this study conducted a robustness test by substituting the explanatory variables. The benchmark regression in this paper utilized the standardized value of sewage charges. For the robustness test, this paper adopted the approach suggested by Li and Xiao (2020) [39] to adjust the scale of sewage charges by utilizing the values of four dimensions: total assets, operating revenues, total operating revenues, and administrative expenses. This adjustment involved dividing the sewage charges by the corresponding subjects (referred to as Pwf1, Pwf2, Pwf3, and Pwf4). The regression results, following the alteration in measurement methodology as presented in

Table 5. Robustness test II: replacement of the explanatory variables.

	M(1)	M(2)	M(3)	M(4)
	LnGIA	LnGIA	RD	RD
Pwf1	12.23 ***		0.435 ***
	(2.60)		(4.06)
Pwf2		5.038 *		0.232 ***
		(1.87)		(3.78)
Control	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES
N	3854	3854	1343	1343
Adj_R2	0.104	0.104	0.105	0.105

***, and * denote significance at the 1%, and 10% levels, respectively.

, indicate significantly positive coefficients across all eight models (due to space limitations, only partial results are reported). These results affirm the robustness of the conclusions drawn from the benchmark regression. Consequently, the assertion that market-based environmental regulation markedly stimulates firms’ green technological innovation is reaffirmed.

4.4.4. Other Robustness Tests

Additionally, this paper performed several other robustness tests, including excluding samples with zero sewage charges, lagging the explanatory variables by one and two periods, lagging all control variables by one period, and shrinking the upper and lower tails by 2.5% and 5%. The regression results from these tests are not presented in the main text due to space limitations but are available for reference. Notably, all the results obtained from these tests confirm the findings of the benchmark regression. This paper also evaluated the impact of other types of market-based environmental regulatory instruments, such as the carbon emissions trading mechanism, and we built a DID model to evaluate the impact of carbon emissions trading policies on firms’ green technological innovation, drawing on the methodology of Hu et al. (2020) [19] and Zhang et al. (2022) [16]. The results show that the carbon trading policy, which is also a market-based environmental regulatory tool, also has a significant impact on enterprises’ green technological innovation (see

Table A1. Impact of other types of market-based environmental regulation on green technology innovation.

	(1)	(2)	(3)	(4)	(5)
	LnGIA	LnGA1	LnGA2	RD	LnRd
Tpjy1	0.027 **	0.029 ***	0.011	0.005 ***	0.228 ***
	(2.06)	(2.58)	(1.10)	(6.31)	(4.24)
Constant	−2.200 ***	−1.892 ***	−1.475 ***	0.098 ***	−3.355 ***
	(−15.48)	(−15.94)	(−13.98)	(10.45)	(−4.73)
Controls	YES	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES	YES
N	33082	33082	33082	12706	12706
r2	0.187	0.169	0.180	0.232	0.456
chi2	2138.382	1904.192	1615.313	1771.452	6328.297

t statistics in parentheses. ** p < 0.05, *** p < 0.01.

in Appendix A at the end of this paper for the specific regression results). This further validates the facilitating effect of market-based environmental regulation on corporate green innovation and demonstrates the robustness of the core findings of this paper.

4.5. Verification of Hypothesis H2

To investigate the moderating effect of corporate social responsibility (CSR) on the relationship between market-based regulation and green technological innovation, this study empirically tested hypothesis H2 based on Equation (2) (refer to

Table 6. Moderating effect test of CSR.

	M(1)	M(2)	M(3)	M(4)	M(5)	M(6)
	LnGIA	LnGA1	LnGA2	LnGIA	LnGA1	LnGA2
MBER	0.525 *	0.257	0.538 **	0.421	0.228	0.425 *
	(1.73)	(1.06)	(2.29)	(1.35)	(0.92)	(1.77)
HI	0.012	−0.005	0.012
	(0.56)	(−0.32)	(0.75)
HI*MBER	0.624 **	0.237	0.690 ***
	(2.56)	(1.22)	(3.66)
Mark.				−0.006	−0.010	−0.003
				(−0.42)	(−0.85)	(−0.30)
Mark*MBER				0.577 **	0.153	0.673 ***
				(2.42)	(0.81)	(3.65)
Control	YES	YES	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES	YES	YES
N	3326	3326	3326	3234	3234	3234
Adj_R2	0.113	0.116	0.087	0.115	0.117	0.090

***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively.

for the regression results). Given that green invention patents are believed to be more innovative than utility model patents and better reflect the core level of green technological innovation, the natural logarithm of the number of green invention patent applications (LnGA1) was used to measure the substantive green technological innovation of firms, while the natural logarithm of the number of green utility model patent applications (LnGA2) was used to measure the strategic innovation of firms. These two variables serve as explanatory variables for regression analysis to identify the impact of CSR on different types of technological innovation. Inspired by Yang et al. (2021) [22], https://www.hexun.com/ (accessed on 23 December 2022) scores and ratings of CSR were utilized to measure CSR from both quantitative and qualitative perspectives. We assessed the impact of the five responsibility dimensions on different green technology innovations.

Models M(1)–M(3) in Table 6 measure CSR using ratings (HI) based on scores published by Hexun.com (converted to 1 to 5 points) with higher scores indicating higher CSR performance. Conversely, Models M(4)–M(6) use the logarithmic measure of CSR (Mark) based on the ratings released by Hexun.com, with higher scores also indicating a better CSR performance.

The regression outcomes derived from Model M(1) in Table 6 reveal that the cross-multiplier term coefficients (HI*MBER) of CSR and market-based environmental regulation successfully surpass the 5% significance level threshold, thereby substantiating hypothesis H2. This indicates that CSR enhances the promotional effect of market-based environmental regulation on green technological innovation. Conversely, the findings of Models M(2) and M(5) suggest that CSR’s influence on green invention patents lacks significance. However, the regression results of Models M(3) and M(6) demonstrate that CSR positively moderates the relationship between market-based environmental regulation and green utility model patents, with cross-multiplier term coefficients that pass the 1% significance level test. These empirical results suggest that CSR primarily strengthens the relationship between market-based environmental regulation and green utility model patents while having no significant effect on green invention patents.

And in the regression analysis of the five dimensions of CSR, after distinguishing between substantive and strategic green innovation, it was found that the three dimensions of environmental responsibility (Csr2), responsibility for suppliers’ customers’ and consumers’ rights and interests (Csr3), and employees’ responsibility (Csr4) have a significant and positive effect on promoting strategic green innovation of the enterprise, while it does not have a significant promotion of the enterprise substantive green innovation effect. This is consistent with the results we assessed using the total CSR score and rating (the specific regression results by dimension are shown in

Table A2. Examining the moderating effect of sub-dimensional CSR on green innovation.

	(1)	(2)	(3)	(4)	(5)
	LnGIA	LnGIA	LnGIA	LnGIA	LnGIA
MBER	0.620 *	0.587 *	0.587 *	0.481	0.599 *
	(1.87)	(1.93)	(1.93)	(1.57)	(1.80)
MBER*Csr1	−0.048
	(−0.43)
Csr1	−0.002
	(−0.68)
MBER*Csr2		0.065 **
		(2.42)
Csr2		0.002
		(1.21)
MBER*Csr3			0.091 **
			(2.23)
Csr3			0.002
			(0.62)
MBER*Csr4				0.129 ***
				(2.81)
Csr4				0.002
				(0.55)
MBER*Csr5					−0.012
					(−0.26)
Csr5					0.007 ***
					(2.60)
Constant	−1.121 **	−1.022 **	−1.050 **	−1.060 **	−0.998 **
	(−2.39)	(−2.18)	(−2.24)	(−2.25)	(−2.14)
Controls	YES	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES	YES
N	3326	3326	3326	3326	3326
r2	0.115	0.117	0.115	0.115	0.117
chi2	164.120	172.990	169.323	172.964	171.466

t statistics in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

,

Table A3. Examining the moderating effect of sub-dimensional CSR on substantial green innovation.

	(1)	(2)	(3)	(4)	(5)
	LnGA1	LnGA1	LnGA1	LnGA1	LnGA1
MBER	0.348	0.280	0.282	0.235	0.355
	(1.32)	(1.16)	(1.17)	(0.97)	(1.34)
MBER*Csr1	−0.059
	(−0.66)
Csr1	−0.000
	(−0.13)
MBER*Csr2		0.024
		(1.12)
Csr2		0.000
		(0.01)
MBER*Csr3			0.032
			(1.00)
Csr3			−0.001
			(−0.37)
MBER*Csr4				0.051
				(1.39)
Csr4				−0.002
				(−0.60)
MBER*Csr5					−0.027
					(−0.71)
Csr5					0.006 ***
					(2.77)
Constant	−1.013 ***	−1.013 ***	−1.026 ***	−1.051 ***	−0.922 **
	(−2.78)	(−2.77)	(−2.81)	(−2.86)	(−2.54)
Controls	YES	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES	YES
N	3326	3326	3326	3326	3326
r2	0.118	0.118	0.117	0.116	0.122
chi2	142.607	143.549	142.906	144.229	151.380

t statistics in parentheses. ** p < 0.05, *** p < 0.01.

and

Table A4. Examining the moderating effect of sub-dimensional CSR on strategic green innovation.

	(1)	(2)	(3)	(4)	(5)
	LnGA2	LnGA2	LnGA2	LnGA2	LnGA2
MBER	0.550 **	0.601 **	0.607 ***	0.498 **	0.555 **
	(2.15)	(2.57)	(2.59)	(2.12)	(2.16)
MBER*Csr1	0.027
	(0.31)
Csr1	−0.003
	(−0.95)
MBER*Csr2		0.075 ***
		(3.58)
Csr2		0.002
		(1.31)
MBER*Csr3			0.102 ***
			(3.26)
Csr3			0.002
			(0.87)
MBER*Csr4				0.129 ***
				(3.64)
Csr4				0.002
				(0.85)
MBER*Csr5					0.009
					(0.24)
Csr5					0.002
					(1.13)
Constant	−0.684 *	−0.581	−0.600 *	−0.603 *	−0.630 *
	(−1.93)	(−1.64)	(−1.70)	(−1.70)	(−1.79)
Controls	YES	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES	YES
N	3326	3326	3326	3326	3326
r2	0.089	0.091	0.089	0.089	0.087
chi2	138.880	155.912	150.685	154.098	140.077

t statistics in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

in the Appendix A at the end of this document).

Therefore, this implies that companies strategically leverage CSR as a tool to symbolically fulfill their social responsibilities, aiming to address or mitigate environmental policy pressures or controls, rather than focusing on substantial green technological innovation aligned with long-term development objectives. This strategic utilization of CSR underscores a superficial and strategic approach adopted by firms to navigate regulatory landscapes and stakeholder expectations, emphasizing short-term compliance objectives over enduring sustainability-driven innovation endeavors.

4.6. Verification of Hypothesis H3

To further test the research hypothesis H3 based on Equations (3) and (4), which examined the mediating effect of financing constraints between market-based environmental regulation and green technological innovation, this study employed the SA index to capture the extent of financing constraints faced by enterprises. A higher SA index implies lower financing constraints. This discovery provides a new perspective for us to understand the relationship between environmental regulations and green technology innovation behavior of enterprises, as well as the role of financing constraints. In order to ensure the scientific validity and rigor of the mediating effect mechanism test, we conducted both the Sobe test and repeated 1000 sampling based on the bootstrap method. The relevant regression results are reported in

Table 7. Tests for the mediating effect of financial constraints.

	M(1)	M(2)	M(3)	M(4)
	SA	LnGIA	LnGA1	LnGA2
MBER	0.476 ***	0.566 *	0.241	0.520 **
	(15.48)	(1.93)	(1.03)	(2.31)
SA		0.213 *	0.230 **	0.149
		(1.66)	(2.26)	(1.53)
Sobel Z-value		3.39 ***	2.82 ***	3.70 ***
p-value		0.000	0.004	0.000
Bootstrap Z-value		2.52 **	2.31 **	2.48 **
p-Value		0.012	0.021	0.013
r(ind_eff) 95% conf. interval		[0.069 0.554]	[0.031 0.379]	[0.053 0.454]
Control	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES
N	3854	3854	3854	3854
Adj_R2	0.759	0.126	0.111	0.102

***, **, and * denote significance at the 1%, 5%, and 10% levels, respectively.

. These rigorous measures ensure that the regression results for the mediated effects in the table below are scientifically plausible.

The empirical results of model M(1) reveal a significant coefficient of 0.476 for MBER at a 1% confidence level. This indicates that market-based environmental regulation alleviates financing constraints faced by enterprises. Furthermore, the regression results of model M(2) demonstrate positive and statistically significant coefficients for both market-oriented environmental regulation (a = 0.566, p < 0.1) and financing constraints (a = 0.213, p < 0.1) on enterprises’ green technological innovation. These findings suggest that financing constraints serve as a mediating factor in the relationship between market-based environmental regulation and enterprises’ green technological innovation. In other words, the “compensatory effect” of market-based environmental regulation is confirmed. The improvement in the regulatory level in a market-oriented environment will reduce the degree of financing constraints for enterprises, and the improvement in financing constraints will be conducive to the enhancement in the green technology innovation capabilities of enterprises.

Potential economic explanations for this are as follows: Firstly, higher levels of market-based environmental regulation impose greater environmental responsibilities and pressures on enterprises, necessitating the adoption of green technological innovations to address these challenges. Government environmental regulations, emission limits, and other forms of regulatory requirements compel firms to undertake green technological innovations in line with the imperatives of sustainable development. Secondly, alleviating financing constraints encourages firms to prioritize the efficiency and quality of their technological innovations. Model M(3) provides supporting evidence for this interpretation. Models M(3) and M(4) utilize green invention patents and green utility model patents as independent variables respectively. These patents are typically considered to represent the core innovation capabilities of enterprises due to the substantial difficulty and stringent requirements associated with green invention patents. The regression results of Models M(3) and M(4) indicate that the compensatory effects of environmental regulations and financing constraints are more pronounced for green invention patents and less prominent for green utility model patents. This indicates that improvements in financing constraints direct enterprises’ attention toward substantive green technological innovation. In other words, both market-based environmental regulations and financing constraints exert significant influences on enterprises’ green technological innovation. Higher levels of market-based regulation stimulate firms to engage in greater green technological innovation, while improved financing constraints drive firms to focus on the efficiency and quality of technological innovation.

4.7. Heterogeneity Analysis

4.7.1. Heterogeneity of Property Rights

The differences in property rights possessed by enterprises directly result in significant variations in resource endowment across firms. Based on this, this study classified enterprises into state-owned and non-state-owned entities based on their nature of property rights and conducted sub-sample regressions (refer to

Table 8. Heterogeneity analysis.

	Nature of Property Rights		Industry Attributes		Degree of Supervision
	State Firm	No-State Firm	Heavily Polluting	Non-Heavily Polluting	Highly Regulated	Low Regulatory
	M(1)	M(2)	M(3)	M(4)	M(5)	M(6)
	LnGIA	LnGIA	LnGIA	LnGIA	LnGIA	LnGIA
MBER	0.847 **	0.436	1.565 ***	0.215	1.514 ***	0.179
	(2.40)	(0.88)	(3.41)	(0.61)	(2.97)	(0.50)
Control	YES	YES	YES	YES	YES	YES
Year-FE	YES	YES	YES	YES	YES	YES
Industry-FE	YES	YES	YES	YES	YES	YES
N	1887	1967	2114	1740	2510	1344
Adj_R2	0.132	0.172	0.223	0.088	0.218	0.106

*** and ** denote significance at the 1%, and 5%levels, respectively.

for regression results).

The empirical findings derived from the regression Models M(1)–M(2) reveal that state-owned enterprises (SOEs) manifest statistically significant responses to market-based environmental regulations, with the regression coefficient (α = 0.847, p < 0.01) surpassing the conventional 1% level of significance. This suggests a robust positive effect of market-based environmental regulation on the green technological innovation within SOEs. In stark contrast, the analogous impact upon non-state-owned firms fails to reach statistical significance, implying a muted influence of market-based environmental regulation on their green innovation endeavors. These results underscore the notion that the efficacy of market-based environmental regulation in fostering green technological innovation is intricately linked to the proprietary nature of the enterprises.

The distinctive economic attributes of SOEs, which include their reliance on government-backed credibility and a relatively ample endowment of resources in comparison to their private counterparts, confer upon them an inherent competitive edge in market-driven scenarios. Considering the socio-economic fabric of China, SOEs are often entrusted with a heightened degree of social responsibilities, such as maintaining employment levels and ensuring economic stability. This positioning renders SOEs more inclined and equipped to embrace and advance green technological innovation initiatives.

4.7.2. Industry Heterogeneity

There are substantial variations in environmental pollution levels across different industries, leading to significant discrepancies in the environmental regulations imposed on them. In order to drive economic structural transformation and foster sustainable development, the prioritization of green transformation within heavily polluting industries is imperative. To this end, this study categorizes industries into heavy and non-heavy pollution sectors based on the 2012 version of the China Securities Regulatory Commission industry classification standards. Specifically, the heavy pollution industries examined in this paper encompass mining, textiles, paper and paper products, petroleum, chemical manufacturing, synthetic fibers, non-ferrous metal smelting and processing, rubber and plastics, pharmaceuticals, and fur products. According to this industry classification, sub-sample regressions are performed, and the regression results are detailed in Table 8.

The empirical results M(3) and M(4) reveal that market-based environmental regulation exerts a significantly positive influence on the green technological innovation of enterprises operating within heavily polluting industries. The regression coefficients for total green patents held by enterprises (a = 1.565, p < 0.01) are all notably positive and surpass the 1% significance threshold. In contrast, this positive effect is not statistically significant in non-heavy polluting industries. The economic underpinnings of our findings are succinctly outlined: in highly polluting sectors, the introduction of sewage fees and environmental taxes incentivizes firms to increase green technology R&D investments, enhancing environmental performance and sustainability. The pronounced emission levels in these industries amplify the emission reduction and cost-saving benefits of green innovation, thereby confirming the significant positive effect of market-based environmental regulation on technological advancement. In contrast, industries with lower pollution profiles may not experience the same urgency or cost benefits from environmental regulation, highlighting a differential industry response to regulatory incentives and their influence on green innovation.

4.7.3. Heterogeneity in the Degree of Environmental Regulation

The different levels of regulation directly lead to significant differences in the illegal costs of corporate environmental pollution and incentives for green technology innovation.

This study quantitatively assessed the stringency of environmental regulation by evaluating the ratio of environmental penalties to total penalties per province, utilizing the Peking University Law Database. Provinces with ratios above the median are categorized as high-regulation regions, while those below are deemed low-regulation areas. Subsequent sub-sample regression analyses were then performed.

The regression outcomes presented in Table 8 demonstrate that enterprises situated in highly regulated areas have a significant promoting effect of market-oriented environmental regulations on their green technology innovation. Specifically, the regression result of Model M(5) (a = 1.514, p < 0.01) is notably positive, surpassing the 1% significance threshold. Conversely, Model M(6) yields statistically insignificant results. This phenomenon can be explained by the fact that firms operating in highly regulated areas contend with more stringent environmental mandates and penalties, thereby cultivating stronger incentives to innovate using green technologies. Market-based environmental regulation heightens the cost burden for these firms, compelling them to enhance their environmental performance through initiatives such as sewage charges and environmental taxes. In contrast, enterprises in low-regulation regions face comparatively limited environmental pressures and, thus, lack the necessary impetus to innovate using green technologies.

5. Conclusions and Implications

5.1. Conclusions and Limitations

5.1.1. Research Conclusions

Based on the data from listed companies in China spanning the period spanning from 2008 to 2021, this study systematically examines the pivotal role of market-based environmental regulatory instruments in fostering corporate green technological innovation. The findings underscore the profound impact of such regulatory mechanisms on enhancing sustainable development initiatives within the enterprise sector. We have drawn the following conclusions:

Firstly, we find that market-based environmental regulation tools have a significant role in promoting enterprises’ green technological innovation, and the research in this paper demonstrates the significance of adopting market-based regulation tools by the government and other regulators in promoting enterprises’ green innovation and sustainable development.

Secondly, this study shows that CSR does not always have the same positive effects as declared by corporate managers. Compared to previous studies that have more often recognized the positive effects of CSR, this paper offers a new perspective. It indicates that, under the aegis of market-based environmental regulation, CSR initiatives may be reduced to mere business strategies, potentially limiting their contribution to substantive green innovation.

Thirdly, this study shows that financing constraints are the mechanism of market-based environmental regulation and corporate green technological innovation, which demonstrates the significance of market-based environmental regulation in alleviating corporate financing constraints, and accordingly promotes the green transformation and sustainable development of enterprises.

Lastly, the promotion effect of market-based environmental regulations on substantive green technological innovation is predominantly observed in state-owned enterprises, heavily polluted industries, and regions with high regulatory stringency.

5.1.2. Limitations

This study, while providing valuable insights, acknowledges its inherent limitations primarily attributed to data availability and scope. Firstly, the research considered R&D investment as a proxy for the investment dimension in corporate green technology innovation. This approach, though methodologically sound, could be further refined. Future studies might benefit from disentangling the specific costs associated with green technology innovation from general R&D expenditure, thereby enhancing the precision of the research design. Secondly, the present study’s analysis of market-based environmental regulation was confined to sewage charges and environmental taxes. Future research should integrate a wider range of these regulatory mechanisms into its framework to strengthen the empirical soundness of the findings.

5.2. Policy Recommendations and Management Insights

This paper proposes the following policy recommendations and management insights based on the empirical findings.

5.2.1. Policy Recommendations

Firstly, government departments must steadfastly promote the implementation of market-based environmental regulations and continue harnessing their promotional impact on enterprises’ green technological innovation. Simultaneously, efforts should be directed towards bolstering the protection of green intellectual property rights, fostering a fair and equitable environment for green innovation, and mitigating the dual negative externalities associated with enterprises’ green technological innovation.

Secondly, corporate social responsibility (CSR) plays a pivotal role in fortifying the positive influence of market-based environmental regulations on enterprises’ green technological innovation. Thus, the government should persist in incentivizing enterprises to fortify their CSR construction. Additionally, recognizing the heterogeneous impact of CSR on various types of green technological innovation, the government should enhance the identification mechanism for enterprises’ commitment to fulfilling their social responsibilities. It is crucial to develop a robust mechanism for assessing the authenticity of CSR activities and their alignment with social responsibilities. By integrating environmental regulation with fiscal policies, governments can incentivize genuine technological innovation. This can be achieved by seamlessly integrating environmental regulatory measures with tax and related systems to amplify incentives for core technological innovation endeavors. Enterprises can also be guided to fulfill substantive technological innovation activities as part of their social responsibility and to diminish the propensity for strategic technological innovation.

Thirdly, policymakers should consider implementing strategic financial incentives. These could include targeted subsidies for green technology R&D, streamlined access to green financing, and fiscal relief programs to ease the financial burden on enterprises. By doing so, governments can foster an environment that promotes green technology innovation and supports the sustainable growth of businesses.

Fourth, considering the disparate impact of market-based environmental regulations across property rights, it is imperative for policymakers to bolster state-owned enterprises’ green innovation initiatives, harnessing their resources to cultivate enduring competitive edges. Simultaneously, acknowledging the constrained financial and innovation capacities of private firms, the government should strategically expand financial mechanisms and refine the entrepreneurial landscape. This approach should encompass the development of societal cost-sharing frameworks aimed at green technology, thereby incentivizing heightened R&D expenditures and enhancing the overall caliber of green innovation.

Fifth, the heterogeneity analysis of regulatory regions indicates that, for highly regulated areas, the government should further increase environmental regulation efforts, strengthen the implementation of measures such as pollution discharge fees and environmental protection taxes, and consider providing appropriate tax reductions and funding subsidies to promote enterprises to increase investment in green technology innovation. In low regulatory areas, the government should strengthen environmental supervision, enhance environmental publicity and education for enterprises, and encourage enterprises to actively engage in green technology innovation through reward mechanisms and information disclosure.

Sixth, given the industry-level disparities in responsiveness to market-based environmental regulations, it is essential for policymakers to concentrate regulatory enhancements on industries with high pollution emissions. This targeted approach should aim to accelerate the adoption of green technological innovations within these sectors, facilitating a swift transition towards sustainable practices. Governmental strategies should be directed towards guiding these industries towards cleaner and circular production models, complemented by the provision of resources and support systems that bolster innovation and development efforts. This proactive policy alignment is crucial for leveraging market mechanisms to induce substantive environmental improvements in sectors most in need of green transformation.

5.2.2. Management Insights

Firstly, in the realm of sustainable green development and environmental regulation, the implementation of green technological innovation becomes an inevitable choice for enterprises striving for high-quality development. Therefore, enterprise managers should be more aware of the importance of green technology innovation and adopt active green innovation strategies to increase R&D investment in enterprises.

Secondly, organizations should recalibrate their CSR strategies to transcend superficial compliance and align closely with environmental sustainability mandates. CSR endeavors must be authentically integrated with the core objectives of ecological preservation and the advancement of innovative green technologies, ensuring they are congruent with and bolstered by market-based environmental policy frameworks.

Thirdly, enterprises ought to strategically engage with financial institutions to navigate financial impediments to green transformation. This proactive engagement may involve tapping into green financing mechanisms, securing governmental grants and subsidies, and forging public–private alliances. Such initiatives are designed to augment investment in research and development (R&D) and accelerate the deployment of cutting-edge green technologies, thereby facilitating a robust and sustainable transition.

Fourth, businesses should be encouraged to participate actively in the policy-making process, offering empirical knowledge and strategic recommendations to enhance the efficacy of environmental regulations and drive sustainable industry practices.