CEO Power and Green Innovation: Evidence from China

Abstract

The relationship between CEO power and risk-taking remains a controversial topic, with no consensus regarding whether CEO power promotes green innovation. To address this unresolved issue, this research explores the correlation between CEO power and green innovation, distinguishing between green product innovation and green process innovation. It also examines the moderating roles of media coverage and government regulation in these relationships. By using panel data on Chinese manufacturing for the period from 2010 to 2022, we draw several important conclusions. First, CEO power is found to be negatively associated with green product innovation but positively correlated with green process innovation. Additionally, media coverage and government regulation reinforce the positive impact of CEO power on green process innovation; however, they do not meaningfully affect the impact on green product innovation. These findings may represent valuable insights for firms and policymakers committed to sustainable development.

1. Introduction

Sustainable development is known to enhance enterprises’ resource efficiency and competitiveness while more broadly improving environmental quality and generating positive impacts on society [1]. Green innovation represents a critical approach to achieving sustainable development. Existing research highlights the enduring financial and environmental advantages for enterprises that pursue green innovation [2,3]. However, it also involves inherent risks, such as uncertain market demand, unstable investment returns, and the complexities of technology implementation [4,5]. Given the coexistence of high risks and high returns associated with green innovation, enterprises and managers must be prepared to navigate significant complexities.

Previous research has extensively explored how CEO’s personal characteristics, such as age [6], compensation [7], and tenure [8], influence corporate risk-taking. Recent scholarly endeavors have predominantly focused on examining the influence of CEO power. However, the connection between CEO power and risk-taking continues to be a subject of debate. On one hand, a sense of power may lead a CEO to overly optimistic evaluations of strategic decisions and a higher likelihood of risk-taking [9,10,11]. Powerful CEOs are often inclined to make unilateral decisions and adopt higher-risk strategies, including increased investment in risky projects driven by overconfidence [12,13]. In this regard, existing research has also found that the power of CEOs can promote green innovation [14]. On the other hand, agency theory [15] indicates that the alignment of a CEO’s wealth and career with company success may encourage risk aversion. For instance, Zhou [16] discovered that CEOs tend to make more conservative decisions when they operate within unstable corporate governance structures. Under pressure from shareholders and stakeholders, CEOs may prioritize maintaining their power over taking significant risks. This lack of consensus underscores a need to better understand whether CEO power promotes green innovation, considering its high-risk, high-reward nature. Since the CEO is the direct formulator of the enterprise’s innovation strategy, it is crucial to pay attention to the relationship between the CEO’s power and green innovation.

Green innovation has a rich connotation, encompassing multiple dimensions such as green product innovation and green process innovation [17]. Many studies examining the relationship between CEO power and green innovation tend to treat green innovation as a single, undifferentiated factor [18]; while this approach allows for facile comparisons of green innovation performance across firms, it does not account for the differential impacts of CEO power on various dimensions of green innovation. Enterprises bear different degrees of risks and have different strategic objectives when engaging in different types of green innovation [17]. This gap may result in varied interpretations concerning the correlation between CEO power and green innovation.

The present study addresses these issues by distinguishing between green product innovation and green process innovation, informed by previous studies [19,20]. Green product innovation centers on the design and implementation of products that reduce environmental impacts, such as those comprising environmentally friendly and energy-efficient materials [21]. Green process innovation aims to optimize production processes in order to attain lower consumption levels, minimized waste generation, and enhanced efficiency in the utilization of resources and energy [18]. Previous studies have shown that the risks undertaken by firms in the development of green product innovation and green process innovation are different. Therefore, we believe that this classification can explain the paradoxical relationship between CEOs and green innovation.

In addition, internal and external factors can also affect the relationship between CEO power and green innovation. Existing research has discussed the moderating effects of internal factors such as performance feedback and independent directors. Although some studies have explored the moderating effects of external moderators such as institutional investors and market competition [19,22], the moderating roles of two external factors, namely media coverage and government regulation, on the relationship between CEO power and green innovation have not been investigated yet. Successful green innovation hinges on internal decision-making and resource allocation within enterprises, while external oversight is essential to ensure sustainability and effectiveness [23]. External supervision, including government regulation and media scrutiny, ensures that enterprise innovation aligns with environmental and social interests and encourages firms to invest more in green innovation. To more fully understand how CEO power influences green innovation, this study not only examines the direct impact of CEO power but also investigates the effects of two significant external moderating factors: media coverage and government regulation. The technological level and enterprise scale are also factors that cannot be ignored. High-tech enterprises and large enterprises usually have significant advantages in technological innovation and R&D investment. In contrast, enterprises with a lower technological level, as well as small and medium-sized enterprises, may face more resource constraints and innovation challenges [17]. Therefore, this paper will consider these two factors in the heterogeneity analysis.

This study uses data from Chinese listed companies to investigate these relationships. China provides an ideal context for this investigation, as China’s government has prioritized environmental issues in recent years by implementing stringent environmental protection policies and ensuring compliance through oversight. Increased media reporting has heightened public awareness of environmental protection, thus contributing to the promotion of the development of green products and processes. Chinese enterprises have also made significant progress in green innovation, demonstrating a good commitment to environmental responsibility and highlighting the crucial role of green innovation in enhancing sustainability and competitiveness.

This research enriches the understanding of the intricate connection between CEO power and green innovation. It differentiates between two types of green innovation, thereby delving deeper into their relationship. Moreover, through an examination of the moderating effects of media coverage and government regulation, it expands the boundary conditions of the relationship between CEO power and green innovation.

2. Literature Review and Hypothesis Development

2.1. Green Innovation

Green innovation refers to the inventive efforts of companies aimed at minimizing environmental damage, enhancing resource efficiency, conserving energy, and fostering sustainable development. These efforts involve creating or significantly improving products or processes [16]. There are various environmental factors that exert an impact on green innovation [24].

Firstly, laws and regulations affect green innovation. Governments exert pressure on enterprises by formulating environmental protection standards and penalty mechanisms through regulatory policies, compelling firms to adopt environmental protection measures [18,21]. Furthermore, the government-mandated disclosure of information on green production and emissions incentivizes firms to pursue green innovation to avoid financial losses and reputational damage [23].

Secondly, competition significantly influences enterprises’ decisions regarding green innovation. The pressure to maximize competitiveness often drives CEOs to take more risks, facilitating strategic transformations [25]. In highly competitive markets, companies often seek differentiation strategies to maintain their edge [26]. Green innovation is a key approach to achieving differentiation, which can make the influence of CEOs more pronounced, and they are more likely to steer companies toward green innovation in order to meet the growing market demand for eco-friendly products.

Moreover, according to the stakeholder theory, enterprises are required not merely to center on shareholders’ interests but also to take into account the demands and interests of other stakeholders [27]. Corporate social responsibility (CSR) efforts represent a crucial means by which enterprises can build favorable connections with stakeholders. By implementing CSR initiatives, enterprises can inspire their employees to actively participate in green innovation, fulfill environmental responsibilities, and build a solid network of relationships with various stakeholders, thereby significantly promoting green innovation activities [18].

Thirdly, from the perspective of upper echelons theory, the personal traits of CEOs are also capable of affecting their stances and choices regarding green innovation [22]. Research has shown that factors such as a CEO’s gender [28], international experience [29], educational background [22], and hometown identity [30] influence the execution and efficacy of corporate green innovation. Although previous research shows that CEO power significantly impacts innovation in a more general sense [31], there has been limited exploration of its specific role in green innovation.

2.2. CEO Power and Green Innovation

CEO power refers to the ability to influence the outcomes of important decisions within a company [31,32,33,34]. Green product innovation runs throughout the process, which means that environmental impacts and resource efficiency need to be considered in every step of the process, from product design, raw material selection, and the production process to product use and final disposal [20]. This comprehensive approach to innovation increases the hazard, which makes even powerful CEOs more likely to adopt risk-averse behaviors, such as inaction, due to concern over their careers and risk exposure, and this can result in reduced investment in green product innovation. Chang [31] notes that green product innovation demands more financial resources, time, and effort compared to green process innovation, potentially jeopardizing a CEO’s authority and position. Consequently, more powerful CEOs may avoid these high-risk projects in favor of less risky initiatives with lower potential returns. Zhao [19], among other scholars, similarly suggests that when the profitability of green innovation is unclear and the associated risks threaten a CEO’s standing or influence within the company, the CEO may leverage their power to impede such projects. Compared with the Western markets where consumers have a preference for green products, existing research shows that consumers in emerging countries such as China place more emphasis on the physical attributes of products rather than their green attributes. This further increases the market perils of green products [35]. In summary, given the high risks and uncertain profitability inherent to green product innovation, we hypothesize the following:

Hypothesis 1 (H1).

CEO power is negatively associated with green product innovation.

In contrast, green process innovation primarily emphasizes the enhancement of production processes [36]. This can include raw material substitution, recycling of resources, and waste treatment. Unlike green product innovation, green process innovation involves optimizing existing processes rather than completely redesigning products. While it entails some risk, it is generally less risky than green product innovation and has relatively more predictable benefits. This reduced risk makes powerful CEOs more likely to opt for green process innovation. Yuan [18] suggests that the environmental demands of the community can exert pressure on a firm’s products and production, thus prompting the firm to pursue both types of innovation mentioned above. Zhou [16] adds that powerful CEOs can identify strategic choices that positively impact their firm, often disregarding potential risks. Even when green process innovation fails to yield immediate benefits, powerful CEOs can still improve efficiency, enhance the company’s reputation, and contribute to long-term gains [37]. Consequently, CEOs might be more inclined to take calculated risks and invest in this type of innovation.

In summary, given the inherent value and benefits of green process innovations, we propose the following:

Hypothesis 2 (H2).

CEO power is positively correlated with green process innovation.

2.3. Moderating Roles of Media Coverage and Government Regulation

As an external monitor, the media plays a crucial role in demanding transparency from companies regarding their green innovation practices [20]. This scrutiny drives companies to attach more importance to green innovation. In such scenarios, CEOs, as central figures in corporate decision-making, are critically responsible for promoting green innovation. This responsibility compels them to incorporate green innovation into their strategic plans and use their power and influence to advance the company’s green innovation initiatives. The media can also enhance a CEO’s reputation through positive reporting [38], thereby gaining more trust and support for the CEO and reducing the resistance and risk in promoting green innovation. In this case, the CEO is more willing to utilize their power and distribute more resources to green innovation projects. When the media provides positive coverage, it not only boosts the CEO’s standing but also creates a more favorable environment for green innovation initiatives. In this context, the more positive reports, the less performance pressure the company tends to be under, and managers will be more energized to focus on long-term objectives associated with green innovation. Accordingly, we hypothesize the following:

Hypothesis 3 (H3).

Media coverage strengthens the relationship between CEO power and green product innovation.

Hypothesis 4 (H4).

Media coverage strengthens the relationship between CEO power and green process innovation.

Tough government regulation often increases firms’ external pressure through measures such as penalties. This external pressure motivates CEOs to take risks and adopt green innovation measures. When local governments enforce stricter regulations, firms are required to disclose environmental information and thus may place greater emphasis on the effectiveness of green innovation [36,39,40]. Tough government regulation increases the likelihood of taking risks in more powerful CEOs, as non-compliance can lead to significant economic losses, reputational harm, and diminished market positions [37,41]. To mitigate these risks and maintain competitiveness, powerful CEOs are more inclined to implement proactive green innovation measures when facing external pressure. Thus, we hypothesize the following:

Hypothesis 5 (H5).

Government monitoring strengthens the relationship between CEO power and green product innovation.

Hypothesis 6 (H6).

Government monitoring strengthens the relationship between CEO power and green process innovation.

3. Methodology

3.1. Sample and Data Sources

This study focuses on manufacturing companies listed in China from 2010 to 2022. The reason for starting from 2010 is that during the 12th Five-Year Plan period, China began to attach importance to sustainable development [42]. The reason for ending in 2022 is that there is a lack of relevant data on government regulation. This study selected the manufacturing industry. During the production process, manufacturing enterprises usually have high energy consumption and high pollution levels. These characteristics have exerted non-negligible negative effects on the environment. Additionally, the manufacturing industry serves as a crucial pillar of the national economy, and its green innovation activities exert a strong exemplary influence and leadership role. When leading enterprises successfully implement green innovation, they inspire others to follow and thereby drive the green transformation of the entire sector.

The sample for this study was screened using several criteria: (1) financial companies and overseas listed companies were excluded; (2) companies with ST and *ST designations were excluded; (3) firms with missing relevant information were removed. Finally, a sample of 10,285 listed companies was obtained. The local government regulatory data were sourced from Public Information Index on Pollution Source Regulation (PITI) reports for 120 cities. The CNRDS database provided the green patent data, while the financial data for the listed companies was sourced from the China Stock Market and Accounting Research Database (CSMAR). Variables such as CEO power, CEO shareholdings, and concurrent position information all come from CSMAR. For the missing values, we sorted and organized them by reviewing the annual reports of the companies.

3.2. Measurement of Variables

• Dependent variable: green innovation

According to previous research [30], the variable of green innovation in this study is constructed from the data of green patent applications. Patents include three types: invention patents, utility model patents, and design patents. We collected relevant data from the DWPI database. Then, based on the Green Inventory of the International Patent Classification (IPC) released by the World Intellectual Property Organization (WIPO), we determined the green patents, which include green invention patents and green utility model patents. A green invention patent refers to a new technical solution that is proposed for a product, a method, or an improvement thereof. On the other hand, a green utility model patent refers to a new technical solution that is applicable to practical use and is specifically proposed for the shape, structure, or combination of a product. Drawing on the existing literature [17], we use green utility model patents as an indicator of green product innovation and green invention patents as an indicator of green process innovation. Since design patents do not have IPC numbers, and the determination of green patents in this study relies on the IPC as per the WIPO’s Green Inventory, design patents are not included in green patents. This exclusion ensures the consistency and accuracy of the green patent classification in our research.

• Independent variable: CEO power

CEO power, as a core element of executive management, was divided into four dimensions in this study based on Frankenstein’s framework [32]: structural power, ownership power, expert power, and prestige power.

Structural power refers to the authority granted by the CEO’s position within the organizational hierarchy, which allows for control over resources and decision-making. This was measured using two indicators: whether the CEO also serves as the chairman of the board (1 for yes, 0 for no) and whether the CEO is an internal director of the firm (1 for yes, 0 for no) [43]. We obtained the corresponding data by consulting the annual reports of the sample enterprises and CSMAR.

Ownership power stems from the CEO’s equity holdings in the firm. CEOs who own shares have greater influence and control over the firm, particularly when equity is concentrated. This was measured according to whether the CEO owns shares in the firm (1 for yes, 0 for no) and whether the percentage of institutional investment holdings is below the industry median (1 for yes, 0 for no) [44]. The corresponding data were obtained by consulting the annual reports of the sample enterprises and CSMAR.

Expert power is derived from the CEO’s specialized knowledge, skills, or expertise, which makes them a sought-after authority in their field. Two indicators were used to measure this type of power: whether the CEO holds a senior professional title (1 for yes, 0 for no) and whether the CEO’s tenure exceeds the industry median (1 for yes, 0 for no) [45]. The data were sourced from CSMAR.

Prestige power arises from the CEO’s reputation and personal influence, which help to garner support and mitigate uncertainties in the firm’s external environment. This was measured by whether the CEO holds part-time roles in external organizations (1 for yes, 0 for no) and whether the CEO works part-time outside their own firm (1 for yes, 0 for no) [12]. Additionally, eight dummy variables were aggregated across the four dimensions and their mean was calculated, resulting in a proxy value for CEO power that ranges from 0 to 1. The data were sourced from CSMAR.

• Moderating Variables: Media Coverage and Government Regulation

•  Media Coverage

The CNRDS database is a rich repository of data, encompassing over 650 national, local, and industry-specific news publications. This database is updated regularly, and its network data are refreshed daily, ensuring users can access the latest reporting information. CNRDS also offers powerful search capabilities, including various search methods, multi-field searches, and a knowledge network node function. These features enable users to quickly and accurately locate relevant media coverage data. We focused on the reports related to the sample enterprises. According to the existing literature [46], the total amount of media reports is represented by the natural logarithm of the sum of the number of annual media reports of listed companies and one. The media reports here cover two types of sources, namely newspapers and periodicals as well as online media.

•  Government Regulation

We used the Pollution Information Transparency Index (PITI) released by the Institute of Public and Environmental Affairs (IPE) and the Natural Resources Defense Council (NRDC). During the sample matching process, since the corporate headquarters is responsible for the company’s strategic decision-making and the corporate CEO is usually also based at the corporate headquarters, we selected the PITI value of the province where the headquarters of the sample enterprise is located and associated it with the enterprise. In this paper, the pollution information transparency index is used as a proxy indicator for government regulation.

•  Control Variables

The company’s age of establishment (age) reflects its maturity and accumulated experience. Generally, firms that have been established for a longer period of time are likely to possess richer resources and a greater capacity to manage risks, which can influence their investment in and adoption of green innovation projects, we use the logarithm of the result obtained by subtracting the year of the company’s establishment from the company year and then adding 1 as the measurement indicator. Firm size (size) is often directly correlated with a firm’s ability to access resources, exert market influence, and negotiate effectively. Larger firms generally possess greater financial resources and R&D capabilities, which allow them to invest more in green innovation. In this study, the natural logarithm of the company’s total assets is used as a proxy for the company’s size. The gearing ratio (Lev) reflects the firm’s financial structure and solvency. A high gearing ratio may imply increased financial risk that can limit a firm’s ability to allocate resources toward green innovation. In this study, the total liabilities divided by the total assets is used as a representation of Lev. Net profit on total assets (ROA) is an important measure of a firm’s profitability, reflecting how efficiently a firm uses its assets to generate profits. A high ROA suggests strong operational efficiency and a greater ability to reinvest profits into green innovation initiatives. Return on equity (ROE) measures a firm’s capacity to generate profits using shareholder equity; a high ROE indicates efficient utilization of shareholder capital, which may positively influence a firm’s decisions to pursue green innovation projects.

The main variables measured in this study are detailed in

Table 1. Measurements and sources of variables.

Variable	Measurement	Data Source
Dependent variables
Green product innovation (GDI)	Ln (number of green utility model applications + 1)	DWPI
Green process innovation (GOI)	Ln (number of green invention patent applications + 1)	DWPI
Independent variable
CEO Power (CP)	The average of the eight indicators reflecting CEO characteristics	CSMAR
Moderating variables
Media coverage (MC)	Ln (number of newspaper and online media reports + 1)	CNRDS
Government regulation (GR)	The Pollution Information Transparency Index	IPE and NRDC
Control variables
Age	Ln (years since the establishment of a firm + 1)	CSMAR
Size	Ln (total assets + 1)	CSMAR
Lev	Total liabilities divided by total assets	CSMAR
ROA	Net earnings divided by total assets of the firm	CSMAR
ROE	Net profit divided by average balance of shareholders’ equity	CSMAR

.

4. Results

4.1. Descriptive Statistics

Table 2. Descriptive statistics.

Variable	Mean	Std. Dev	Min	Max
GDI	0.403	0.715	0	5.974
GOI	0.363	0.708	0	6.697
CP	0.562	0.191	0	1.042
MC	5.472	0.897	1.099	9.997
GR	4.092	0.277	2.425	4.571
Age	2.823	0.367	1.099	3.611
Size	21.816	1.074	19.585	26.43
Lev	0.358	0.186	0.027	0.925
ROA	0.049	0.067	−0.375	0.254
ROE	0.07	0.123	−0.962	0.414

indicates that the mean value of CEO power is 0.562, with a standard deviation of 0.191. This indicates that the average level CEO power in Chinese manufacturing firms is moderate to low, which may be influenced by factors such as corporate governance structures and shareholding distribution. The relatively small standard deviation indicates that the distribution of CEO power is fairly centralized and does not vary significantly across firms.

4.2. Correlation Analysis

Table 3. Correlation analysis.

Variable	1	2	3	4	5	6	7	8	9	10
GDI	1.000
GOI	0.644 ***	1.000
CP	0.005	0.065 ***	1.000
MC	0.112 ***	0.175 ***	0.027 **	1.000
GR	0.031 **	0.127 ***	0.079 ***	−0.103 ***	1.00
Age	0.053 ***	0.064 ***	0.015	−0.083 ***	0.166 ***	1.000
Size	0.337 ***	0.351 ***	0.007	0.376 ***	0.072 ***	0.196 ***	1.000
Lev	0.236 ***	0.198 ***	−0.028 *	0.149 ***	−0.004	0.158 ***	0.503 ***	1.000
ROA	−0.039 ***	−0.026 **	0.047 ***	0.114 ***	0.013	−0.100 ***	−0.020 **	−0.376 ***	1.000
ROE	0.020 *	0.023 **	0.042 ***	0.133 ***	0.005	−0.066 ***	0.080 ***	−0.235 ***	0.923 ***	1.000

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

presents the Pearson correlation analysis results for the main variables. The average coefficient of the variance inflation factor (VIF) among the variables is 2.97, which is far below the threshold of 10, implying that the model is unaffected by multicollinearity problems.

4.3. Regression Analysis

Table 4. Regression results.

Variables	GDI				GOI
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8
CP	−0.129 ***	−0.129 ***	−0.129 ***	−0.129 ***	0.171 ***	0.172 ***	0.174 ***	0.176 ***
	(−2.90)	(−2.90)	(−2.90)	(−2.90)	(3.95)	(3.97)	(4.03)	(4.07)
MC	−0.021 **	−0.020 **	−0.021 **	−0.020 **	0.022 **	0.022 **	0.023 **	0.023 **
	(−2.17)	(−2.17)	(−2.18)	(−2.17)	(2.40)	(2.43)	(2.47)	(2.51)
GR	−0.127 ***	−0.127 ***	−0.127 ***	−0.127 ***	0.219 ***	0.218 ***	0.228 ***	0.227 ***
	(−4.17)	(−4.17)	(−4.15)	(−4.16)	(7.40)	(7.36)	(7.66)	(7.65)
MC×CP		0.015		0.015		0.093 **		0.110 **
		(0.37)		(0.37)		(2.35)		(2.78)
GR×CP			−0.005	0.001			0.411 ***	0.453 ***
			(−0.04)	(0.01)			(3.33)	(3.64)
Age	0.232 ***	0.232 ***	0.232 ***	0.232 ***	0.067 *	0.133 ***	0.070 *	0.071 *
	(5.61)	(5.61)	(5.61)	(5.61)	(1.66)	(3.373)	(1.75)	(1.76)
Size	0.219 ***	0.219 ***	0.219 ***	0.219 ***	0.206 ***	0.217 ***	0.204 ***	0.203 ***
	(13.30)	(13.30)	(13.30)	(13.29)	(12.84)	(13.57)	(12.71)	(12.68)
Lev	0.010	0.010	0.010	0.01	−0.002	−0.0298	0.002	0.003
	(0.15)	(0.15)	(0.15)	(0.15)	(−0.02)	(−0.462)	(0.04)	(0.05)
ROA	−0.191	−0.193	−0.192	−0.193	−0.010	0.0150	0.017	0.004
	(−0.64)	(−0.65)	(−0.65)	(−0.65)	(−0.03)	(0.0518)	(0.06)	(0.01)
ROE	0.262 *	0.263 *	0.263 *	0.263 *	0.040	0.0172	0.027	0.032
	(1.78)	(1.79)	(1.78)	(1.78)	(0.28)	(0.120)	(0.19)	(0.22)
Constant	−4.349 ***	−4.347 ***	−4.348 ***	−4.347 ***	−5.434 ***	−4.941 ***	−5.445 ***	−5.435 ***
	(−14.64)	(−14.63)	(−14.63)	(−14.63)	(−18.80)	(−17.51)	(−18.85)	(−18.82)
R2	0.075	0.075	0.075	0.075	0.076	0.076	0.077	0.078
FE	YES	YES	YES	YES	YES	YES	YES	YES
Observations	10,285	10,285	10,285	10,285	10,285	10,285	10,285	10,285

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

presents the results of the regression analysis. According to Model 1, the coefficient of CEO power is −0.129, which is significant at the 1% level and indicates a significant negative correlation between CEO power and green product innovation. This finding supports H1.

In contrast, the results of Model 5 show a positive regression coefficient for CEO power, also significant at the 1% level. This suggests that CEO power has a significant positive effect on green process innovation, supporting H2. These findings imply that CEO power plays distinct roles, acting as a disincentive to green product innovation while facilitating green process innovation.

The results of Models 2 and 3 indicate that the interaction terms of CEO power with media coverage and CEO power with government regulation are not statistically significant. This suggests that media coverage and government regulation do not exert a substantial moderating effect on the connection between CEO power and green product innovation. Thus, H3 and H5 are not supported.

However, the findings from Models 6 and 7 reveal that the interaction terms of CEO power with media coverage and government regulation both have significantly positive effects on green process innovation. These findings suggest that media coverage and government regulation play significant positive moderating roles in the relationship between CEO power and green process innovation, supporting H4 and H6. This may be because media coverage enhances public awareness of the firm’s and CEO’s image, prompting powerful CEOs to prioritize green process innovation to address external pressure. Similarly, stronger government regulation provides firms with clear environmental guidelines, which prompt powerful CEOs to more readily adopt green innovation measures to meet regulatory requirements and align with market expectations.

Finally, Models 4 and 8 incorporate all interaction terms into a single regression model, yielding results consistent with the findings of other models.

4.4. Robustness Tests

4.4.1. Replacing Independent Variables

Principal component analysis was applied to the eight indicators measuring CEO power. The first principal component was extracted as a composite indicator of CEO power (Power_pc) and incorporated into the regression model for reanalysis. The results indicate that the estimated coefficients align closely with the findings of other models, thereby confirming the robustness of the results. The detailed empirical results are shown in

Table 5. Robustness test of replacing independent variables.

Variables	GDI	GOI
Power_pc	−0.0174 **	0.0181 **
	(−1.975)	(2.100)
Age	0.202 ***	0.125 ***
	(5.052)	(3.207)
Size	0.208 ***	0.223 ***
	(12.73)	(14.00)
Lev	0.0146	−0.0181
	(0.220)	(−0.281)
ROA	−0.232	0.0438
	(−0.782)	(0.152)
ROE	0.282 *	0.0109
	(1.909)	(0.0761)
Constant	−4.723 ***	−4.863 ***
	(−16.49)	(−17.42)
R2	0.1457	0.1917
FE	YES	YES
Observations	10,285	10,285

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

.

4.4.2. Replacement with Negative Binomial Regression Models

A negative binomial regression model was used to further test the robustness of the findings, as reported in

Table 6. Robustness test of replacing with negative binomial regression models.

Variables	GDI	GOI
CP	−0.127 ***	0.768 ***
	(−3.59)	(8.76)
Age	−0.038	0.018
	(−0.84)	(0.35)
Size	0.357 ***	0.460 ***
	(24.10)	(28.85)
Lev	0.840 ***	0.354 ***
	(7.71)	(2.89)
ROA	−2.903 ***	−2.507 ***
	(−4.22)	(−3.23)
ROE	1.554 ***	1.137 ***
	(4.55)	(3.03)
Constant	−8.959 ***	−11.792 ***
	(−27.76)	(−34.01)
Log likelihood	−8062.6828	−7519.9856
Observations	10,285	10,285
FE	YES	YES

Note: *** p < 0.01.

.

4.4.3. Adding Control Variables

We expanded the set of firm-level control variables to include Tobin’s Q (TobinQ), board of director size (Board), and the growth rate of operating income (Growth). The main results still held after accounting for these additional variables, further verifying the robustness of the analysis. Specific results are shown in

Table 7. Robustness test of adding control variables.

Variables	GDI	GOI
CP	−0.133 ***	0.169 ***
	(−2.97)	(3.89)
Age	0.188 ***	0.098 **
	(4.52)	(2.42)
Size	0.217 ***	0.228 ***
	(12.89)	(13.89)
Lev	0.047	0.005
	(0.70)	(0.07)
ROA	−0.157	0.117
	(−0.52)	(0.40)
ROE	0.292 **	0.022
	(1.98)	(0.15)
TobinQ	0.005	0.010 *
	(0.82)	(1.70)
Board	0.035	0.054
	(0.62)	(0.98)
Growth	−0.053 ***	−0.057 ***
	(−2.83)	(−3.12)
Constant	−4.899 ***	−5.122 ***
	(−15.86)	(−17.02)
Observations	10,285	10,285
R2	0.073	0.071
FE	YES	YES

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

.

4.4.4. The Propensity Score Matching (PSM) Method Was Employed to Conduct a Robustness Test

To address the possible problem of self-selection bias, this study utilizes PSM to ensure the robustness of the research findings. The specific implementation procedures are as follows. Initially, we categorize the sample enterprises based on the median value of CEO power. Sample enterprises with CEO power that is equal to or exceeds the median are labeled as 1, while the remaining sample enterprises are labeled as 0. Subsequently, we apply the 1:3 nearest-neighbor matching technique to match these sample enterprises. Finally, a regression analysis is carried out on the matched samples. As shown in

Table 8. Robustness test based on PSM samples.

Variables	GDI	GOI
CP	−0.0263 **	0.0371 ***
	(0.0115)	(0.0114)
Age	−0.0131	0.00577
	(0.0159)	(0.0159)
Size	0.0881 ***	0.102 ***
	(0.00616)	(0.00607)
Lev	0.000351	−0.0000281
	(0.000286)	(0.000282)
ROA	0.604 ***	0.591 ***
	(0.00834)	(0.00822)
ROE	0.00637	−0.0319
	(0.0306)	(0.0301)
Constant	−1.706 ***	−2.073 ***
	(0.141)	(0.139)
Observations	9391	9361
R2	0.432	0.437

Note: *** p < 0.01, ** p < 0.05.

, the results obtained are consistent with those of the main regression analysis. This outcome provides additional validation for the robustness of the research conclusions.

4.5. Heterogeneity Analysis

4.5.1. Comparison at Technology Level

To account for the potential differences between enterprises with varying technological levels, this article is based on the government certification data in CSMAR [47]. We categorized the sample into high-tech and non-high-tech groups and conducted a comparative analysis. The empirical results reveal that, among high-tech enterprises, there is no significant relationship between CEO power and green product innovation. However, a positive correlation exists between CEO power and green process innovation. This may be attributed to the technological accumulation and R&D capabilities of high-tech enterprises, which allow them to more effectively adopt and apply new technologies to advance green process innovation. Conversely, green product innovation involves higher market risks and greater technological uncertainty. Moreover, high-tech firms may face challenges such as funding shortages and lengthy development cycles during the R&D process. As a result, powerful CEOs in these firms tend to avoid high-risk green product innovation projects.

In non-high-tech industries, CEO power has no significant influence on green product innovation, yet it does have a positive effect on green process innovation. This could be because non-high-tech enterprises typically have fewer R&D resources compared to their high-tech counterparts. They also differ in their capacity to bear risks. When confronted with environmental pressure, CEOs in non-high-tech firms may prioritize lower-risk green process innovations to comply with regulations and improve their performance. Specific results are shown in

Table 9. Regression results for firms with different levels of technology.

Variables	GDI		GOI
	High-Tech Enterprises	Non-High-Tech Enterprises	High-Tech Enterprises	Non-High-Tech Enterprises
CP	0.009	0.069	0.289 ***	0.445 **
	(0.17)	(0.64)	(5.79)	(4.13)
Constant	0.394 ***	0.378 ***	0.191 ***	0.143 ***
	(12.81)	(6.48)	(6.54)	(2.46)
R2	0.0003	0.0023	0.0039	0.0139
FE	YES	YES	YES	YES
Observations	7649	2636	7649	2636

Note: *** p < 0.01, ** p < 0.05.

.

4.5.2. Comparison Between Large Enterprises and SMEs

According to the employment records of the Organization for Economic Co-operation and Development (OECD), enterprises employing fewer than 1000 employees are classified as small and medium-sized enterprises [17]. We use the classification method of large, medium, and small enterprises to assess the levels of resource limitation and risk-taking ability. The larger the scale of the enterprise, the less the resource limitation it faces, and the greater its risk-taking ability; the smaller the scale of the enterprise, the more severe the resource limitation it has, and the lower its risk-taking ability. These differences in resource limitation and risk-taking between these two types of enterprises may lead to differences in the relationship between CEO power and green innovation. The empirical findings indicate that, regardless of whether they are large enterprises or small and medium-sized enterprises, there is no significant relationship between the power of the CEO and green product innovation. Compared with small enterprises, the positive correlation between CEO power and green process innovation is more evident in large enterprises. This could potentially be due to the fact that large enterprises encounter fewer resource constraints, enabling them to allocate a greater amount of resources to green process innovation. Specific results are shown in

Table 10. Regression results for different firm sizes.

Variables	GDI		GOI
	Large Enterprises	SMEs	Large Enterprises	SMEs
CP	0.027	0.000	0.456 ***	0.094 *
	(0.42)	(0.00)	(7.09)	(1.72)
Constant	0.473 ***	0.227 ***	0.185 ***	0.142 ***
	(12.58)	(6.47)	(4.98)	(4.57)
R2	0.0000	0.0031	0.0014	0.0155
FE	YES	YES	YES	YES
Observations	6805	3256	6805	3256

Note: *** p < 0.01, * p < 0.1.

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5. Discussion

This paper aims to analyze the relationship between CEO power and green innovation. Based on a sample of manufacturing enterprises listed in China, it is found that CEO power has differential impacts on different types of green innovation. CEO power is negatively associated with green product innovation. This result aligns with Sajko [48], who reported that CEOs with more power tend to avoid high-risk projects that lack significant short-term benefits. Instead, they focus on initiatives that promise immediate returns. Green product innovation typically requires longer time horizons to realize environmental and economic benefits, so it may not align with the preferences of powerful CEOs.

CEO power is positively associated with green process innovation. This aligns with the findings of Altunbaş et al. [12] and Naveed et al. [49], who observed that CEO power facilitates green innovation. Moreover, Yan et al. [14] also pointed out that CEOs with greater power can more effectively promote green innovation projects within enterprises. They can decide to allocate more funds to the research and development of green technologies or drive enterprises to adopt more environmentally friendly production processes. These findings indicate that CEOs are inclined to assume reasonable risks and direct organizational resources toward green process innovation, which generally offers more immediate and tangible benefits to the firm.

Media coverage and government regulation exhibit differential moderating effects on the relationship between CEO power and green innovation. Media coverage and government regulation reinforce the positive impact of CEO power on green process innovation, but they do not significantly influence green product innovation. Specifically, the positive effect of CEO power on green process innovation becomes more pronounced in the presence of increased media attention and stricter government regulation. This indicates that CEO power is more effective in promoting green process innovation under external pressure from media and regulatory authorities. However, for green product innovation, the moderating effects of media coverage and government regulation are not significant.

6. Conclusions

This study examines the relationship between CEO power and green innovation by using Chinese manufacturing firms listed between 2010 and 2022 as the sample. The findings indicate that (1) CEO power is negatively associated with green product innovation; (2) CEO power is positively correlated with green process innovation; (3) media coverage and government regulation amplify the positive effect of CEO power on green process innovation, but their impact on green product innovation is less significant. The research offers fresh insights and empirical support for understanding the intricate dynamics between CEO power and corporate green innovation. It also enriches the theoretical framework in the areas of corporate innovation management and sustainable development by uncovering the distinct roles of CEO power in different types of green innovation, thus providing a new avenue for future research.

Prior researchers have delved into the relationship between CEO power and green innovation. Nevertheless, the majority of previous studies treated green innovation as a unidimensional concept and conducted analyses on it as an integrated entity [14,29,50]. Even though these studies have, to a certain degree, uncovered the link between CEO characteristics and green innovation, they have failed to take into account the inherent variety within green innovation. To address this issue, this study categorizes green innovation into two distinct dimensions: green product innovation and green process innovation. This division not only offers a fresh perspective on the multidimensional nature of green innovation but also sheds light on how CEO power influences organizational resource allocation, risk-taking, and its impact on different types of green innovation. This differentiation enables a more profound investigation into the ways executive characteristics impact various aspects of green innovation. As a result, it furnishes a more precise foundation for subsequent research.

Additionally, this study explored the role of two external moderators: media coverage and government regulation. By incorporating these moderating variables, the study broadens the understanding of factors influencing green innovation, reveals mechanisms through which the external environment shapes innovation, and elucidates how CEO power affects firms’ green innovation strategies under varying external conditions. In prior research, while certain scholars have taken note of the role that internal factors like CEO power play in green innovation, the exploration of the impact of the external environment remains comparatively scarce [14]. These insights may provide valuable theoretical support for developing effective green innovation policies and managerial practices.

Enterprises can position their green development strategies more precisely. Green product innovation centers on decreasing the environmental impact during the product life cycle while green process innovation centers on reducing pollution and improving efficiency in the production process. Enterprises can choose a suitable green innovation path according to their own strengths and market demand, in order to enhance their market competitiveness and environmental performance. Governments need to formulate and strengthen regulations concerning environmental protection, social responsibility, and enterprise management and establish the responsibilities of enterprises in environmental protection. The legal framework should be used to incentivize enterprises to take on social responsibility and stimulate their innovation.

This article also has the following limitations. Firstly, this paper restricts the study to a specific manufacturing sector and does not consider other industries. This scope may limit the wide applicability of the research results. Due to the possible bias in sample selection, it may have an impact on the representativeness of the research results. For future research, it might be advisable to consider broadening the sample scope. This could contribute to enhancing the generalizability and reliability of the research results. Secondly, this paper uses data from listed companies in China to verify the connection between CEO power and green innovation. However, the samples all consist of listed enterprise samples and do not cover samples of non-listed enterprises. Finally, with regard to the measurement of green innovation, although green patents are a widely used indicator in current research, this single measurement may not fully reflect the complexity and multidimensionality of green innovation. Therefore, future research could consider adopting more diversified indicators to complement and improve the measurement of green innovation. These indicators could include technological innovation investment, the number of patent citations, new product sales revenue, environmental and social performance indicators, and market competitiveness indicators, which can be used to assess the effectiveness of green innovation.