1. Introduction
Green technology innovation, characterized by its dual emphasis on resource efficiency and environmental protection, has become a pivotal driver of sustainable development and ecological civilization [1]. Although governments and investors increasingly favor firms engaged in such innovation [2], corporate adoption remains limited due to inherent challenges: the public-good nature of environmental benefits [3], the high costs and risks of green R&D (research and development) [4], and the cross-disciplinary complexity of integrating sustainability into production [5]. China’s emergence as a global leader in green patent filings—dominated by universities and state-owned enterprises, rather than private firms [6]—reveals a structural imbalance that hinders market-driven green innovation. This disparity raises a critical question: How can firms, particularly those in pollution-intensive industries, overcome these barriers to become effective innovators?
Corporate governance, particularly the role of boards of directors, may hold the key. Directors wield significant influence over strategic decisions, yet their potential to drive green innovation remains underexplored. Grounded in upper echelons theory [1] and imprinting theory [2], it is proposed that directors with green backgrounds—those with prior environmental education, work experience, or technical expertise—carry cognitive imprints that shape firms’ sustainability trajectories. Such directors are not only more likely to prioritize environmental considerations in resource allocation [3] but also possess the technical acumen to navigate green innovation’s unique risks [4]. Empirically, the appointment of green-background directors in China’s heavily polluting firms has surged from 24.9% in 2015 to 41.9% in 2020, paralleling a rise in their average board authority. However, existing research overlooks a critical dimension: the heterogeneity of these directors’ actual power within boards, which may determine their ability to translate environmental commitment into tangible innovation outcomes.
While the impact of green innovation on corporate performance has been extensively studied [2], the underlying mechanisms driving such innovation remain underexplored. The current literature on board governance and sustainability has predominantly focused on demographic characteristics and directors’ capital [7], while paying insufficient attention to how directors’ professional experiences influence green innovation outcomes. Imprinting theory [8] offers a valuable theoretical lens, suggesting that formative environmental experiences create enduring cognitive and behavioral imprints that persist when sufficiently profound [9]. In fact, directors play a dual role in green innovation by shaping both strategic direction and technical execution. Those with green technical expertise enhance innovation capabilities through specialized knowledge, while heterogeneous backgrounds diversify cognitive frames and strategic advising. Unlike conventional innovation, green innovation demands higher technical proficiency and carries greater risk, often discouraging investment [10]. This raises a pivotal question: How do green-background directors leverage their “expert effects” to overcome these barriers? The answer to this question can bridge a critical gap in understanding how board composition translates into measurable green innovation outcomes [7,11,12,13,14].
Based on the above, this study investigates how directors with environmental expertise impact corporate green innovation. We consider both the appointment and the power of green-background directors. At the same time, we use the manually collected data from China’s heavily polluting listed firms between 2014 and 2020. This study also analyzes the regulatory effects of firm size, local marketization level, board diligence, and green investors. Furthermore, the mediation effect is analyzed by focusing on the effects of corporate environmental attention and government green subsidies. Finally, this study presents a further discussion on the influence of green-background directors on the quality of corporate green innovation and the influence continuity of green-background directors on corporate green innovations. The study’s results provide useful information for enterprises to make reasonable management decisions and policies, and to conduct scientific policy guidance.
The innovation of this study lies in three key aspects: First, employing empirical research methods, it provides an in-depth examination of the impact of green-background directors on green innovation performance and its underlying mechanisms. Prior studies have predominantly focused on CEOs or interlocking directors with environmental expertise, neglecting a comprehensive analysis of board directors as a whole. Second, this paper develops a novel, China-specific measurement for assessing the influence of green-background directors—leveraging their ranking in the board member list as a proxy for their decision-making power. This approach offers a more precise gauge of their actual authority in shaping corporate sustainability strategies. Third, this study identifies and empirically validates the mechanisms through which green-background directors enhance green innovation: namely, by elevating corporate environmental awareness and facilitating access to government environmental subsidies. These mediating effects bridge a critical gap in understanding how board-level sustainability expertise translates into tangible innovation outcomes.
The rest of this paper is structured as follows: Section 2 reviews the previous literature. Section 3 describes the hypotheses, research methods, and data used in this study. Section 4 describes the results, and Section 5 provides conclusions and policy recommendations.
2. Literature Review and Hypothesis
2.1. Literature Review
2.1.1. The Impact of Green Innovation on Enterprise Performance
Green innovation is usually called environmental innovation, ecological innovation, or sustainable innovation [5,6]. Green innovation mainly emphasizes the sustainability of innovation and reduces the environmental burden, and it includes innovation in technology to save resources and energy and reduce environmental pollution [15]. It has good environmental externalities, which can significantly reduce carbon emissions and improve environmental quality [8]. According to Porter’s hypothesis [9], enterprises actively implement green innovation strategies, which can bring sustainable development of economic and environmental benefits for themselves. Green innovation can not only effectively improve the enterprise’s resource utilization rate and optimize the environmental benefits in the product life cycle [10] but also help enterprises meet the requirements of environmental protection and avoid punishment by government regulatory authorities [7], so that enterprises that gain environmental legitimacy may have a better external reputation, participate in the competition more effectively, undergo further development, and finally, bring positive economic performance and social benefits to enterprises [11].
In this case, scholars have begun to study the influencing factors of corporate green innovation [12]. Some studies have investigated the institutional factors, enterprise factors, and senior management factors of green innovation, and they have analyzed the impacts of environmental regulations, local government environmental governance, green credit environmental, social, and governance (ESG) ratings, and foreign direct investment [13,14].
2.1.2. The Influencing Factors of Corporate Green Innovation
Prior research has primarily examined the determinants of corporate green innovation from the perspectives of environmental regulation and firm-level characteristics. Regarding environmental regulation, based on the Porter hypothesis [9], studies have explored the effects of different types of environmental policies. Command-and-control regulations, such as energy restrictions and environmental enforcement, have been found to influence green innovation [16,17,18]. Market-based instruments, including pollution taxes, carbon emissions trading, and environmental rights trading, also play a role [19,20]. Some scholars have argued that the impact of environmental regulations is heterogeneous. For instance, Bu et al. [21] found that after the implementation of command-and-control regulations, voluntary certifications like ISO 14001 [22] significantly enhanced corporate green innovation. Institutional pressures may also drive firms to adopt compliance strategies to gain legitimacy. Chen et al. [23] demonstrated that coercive institutional pressures promote green innovation, while Zhu et al. [24] showed that low-carbon city pilot policy had a greater effect on non-pilot cities than on pilot cities. Zhang et al. [25] revealed that the green credit guidelines increased the quantity but not the quality of green innovation in regulated industries. Additionally, incentive-based policies, such as environmental subsidies, can stimulate green innovation. Zhang and Zhao [26] highlighted that emissions trading pilots positively affected green patents in heavily polluting firms.
Given the radical and resource-intensive nature of green technologies [27], firms with abundant resources are more likely to invest in green innovation to mitigate risks [28]. However, cost–benefit considerations may lead firms to prioritize risk avoidance over innovation [29]. At the micro level, green innovation can reduce equity financing costs [30], alleviate financial constraints [31], and improve firms’ performance [32]. Corporate governance also influences green innovation by shaping CSR-related decisions [33]. Studies have examined the roles of strategic deviation [34], institutional investor site visits [35], and political connections [36]. Furthermore, firm resources and capabilities—such as political ties, financing, slack resources, supply chain collaboration, and green management—affect green innovation [37]. Stakeholders, including competitors and eco-conscious consumers, also play a role [38].
Regarding executive characteristics, Zhang et al. [39] found that CEOs’ green experience promotes green innovation, while Zhang and Sun [40] showed that interlocking directors’ green backgrounds mitigate information asymmetry and resource constraints. Despite these advances, research on how directors’ green backgrounds—particularly their power—affect green innovation remains scarce. Directors influence information asymmetry, resource allocation, and strategic decisions, and their authority is critical to translating these effects into organizational outcomes. Drawing on imprinting theory, this study investigates whether and how green-background directors and their power shape corporate green innovation.
2.1.3. The Impact of Managers’ Characteristics on Enterprise Performance
The recent literature grounded in imprinting theory and upper echelons theory has explored how executive traits influence environmental performance. Demographic studies have examined innate characteristics (e.g., gender, age) and their effects on green entrepreneurial orientation [41]. Other research has focused on acquired traits, such as overconfidence [42], temporal cognition, hometown ties, academic experience [43], and overseas exposure [44].
At the executive level, female leaders tend to exhibit greater environmental sensitivity and responsibility than their male counterparts, potentially fostering green innovation [45]. Galbreath [46] found that firms with female executives are more likely to innovate in green technologies, with female leadership strengthening the positive link between export intensity and green innovation. While innate traits like gender have been widely studied, acquired experiences remain underexplored. Decision-makers often evaluate activities based on their personal backgrounds, leading to behavioral biases. For example, functional specialization (e.g., production vs. sales roles) shapes executives’ priorities and perceptions.
Existing research on green innovation has largely centered on internal and external governance mechanisms. As a key governance body, the board of directors warrants closer scrutiny, especially given the growing emphasis on director diversity. Directors with green expertise—through education or professional experience—may prioritize environmental considerations during governance, steering innovation toward green technologies. Their specialized knowledge could enhance firms’ environmental awareness and innovation performance. However, empirical evidence on directors’ green backgrounds remains limited, particularly regarding how their power moderates these effects.
2.2. Hypothesis Development
2.2.1. Main Effect: Green-Background Directors and Corporate Green Innovation
Imprinting theory posits that early experiences shape individuals’ long-term cognitive and behavioral traits [2], with environmental professional backgrounds creating enduring “eco-cognitive schemas” that systematically influence decision-making [2]. Green innovation, a complex multistage process, requires substantial support from top management, particularly the board of directors [28], as their approval is critical for allocating resources to high-risk, long-term sustainability projects [47]. A green background serves as a distinctive imprint, shaping directors’ environmental moral cognition through normative socialization (e.g., environmental science training or sustainability-focused career paths) and green professional capabilities, thereby enhancing their ability to evaluate and advocate for green initiatives beyond symbolic compliance [48]. Additionally, greater director capital facilitates strategic shifts [49], particularly in sustainability transitions where specialized knowledge reduces uncertainty about green technologies’ commercial viability [27].
Externally, stakeholder and institutional theories suggest that stricter environmental supervision forces firms to meet compliance requirements through green innovation. However, mere regulatory pressure often leads to reactive, minimal compliance [11]. Directors with green backgrounds leverage their policy literacy (e.g., understanding emissions trading schemes or circular economy regulations) to proactively transform external pressures into competitive strategic actions, reducing non-compliance risks while identifying innovation opportunities embedded in sustainability mandates [50]. Internally, these directors reconcile shareholder short-termism with long-term environmental responsibilities by framing green innovation as both ethically imperative and financially viable through life-cycle cost analyses [51], thereby aligning divergent stakeholder interests. Thus, we hypothesize the following:
Green-background directors positively influence corporate green innovation.
The translation of environmental expertise into organizational change, however, hinges on power dynamics within the boardroom [52]. Finkelstein [53] conceptualized power as an actor’s ability to exert their will. In the context of corporate governance, power distribution within boards is inherently asymmetric [52]. Asymmetric power distributions often marginalize sustainability agendas unless green directors hold formal authority to allocate R&D budgets, mobilize resources by linking green projects to investor expectations [54], and leverage cultural leadership to institutionalize environmental priorities [1]. Their strategic networks further facilitate access to cutting-edge green technologies, creating a power–competence synergy that overcomes inertia [55]. Without such influence, even highly skilled green directors struggle to prioritize innovation against financial performance pressures [49], underscoring the contingent effect captured in H1b.
The power of green-background directors strengthens their positive impact on corporate green innovation.
2.2.2. Moderating Effects Analysis
Upper echelons theory suggests that executive characteristics influence corporate green innovation [1], but their impact is contingent on the availability of complementary organizational resources that enable the translation of environmental expertise into actionable outcomes. According to the resource-based view (RBV) and capability-based theories [56], complementary resources create competitive advantage. That is to say, firms with distinct resource endowments can better leverage green directors’ competencies to achieve a competitive advantage in sustainability. In this context, larger firms’ greater financial, technological, and human resources enable green-background directors to leverage institutional backing for environmental projects, which facilitates access to government grants, green financing, and collaborative R&D partnerships [57]. Furthermore, larger enterprises are also exposed to more diverse stakeholder pressures [58], including activist investors and regulatory scrutiny, which amplify the strategic value of green directors’ expertise in navigating complex sustainability demands [47]. Their established industry reputation also attracts talent, investments, and partnership opportunities for green initiatives [59], creating a reinforcing cycle where green directors’ initiatives gain momentum due to the firm’s pre-existing resource infrastructure. We therefore hypothesize the following:
The positive relationship between green-background directors and corporate green innovation is stronger for larger firms.
The institutional environment, particularly regional marketization levels, further moderates green directors’ effectiveness by shaping the availability of external support mechanisms and competitive dynamics. In regions with higher marketization levels, improved institutional environments provide policy support, resource accessibility, and consumer demand for green innovation [60]. However, these systemic advantages may paradoxically reduce the marginal effect of green-background directors, as firms in such regions already face strong institutional pressures to adopt sustainable practices [36]. Intense competition in high-marketization regions further compels firms to enhance their environmental performance, reducing reliance on director-specific expertise. Conversely, in less-marketized regions where regulatory enforcement is weaker and sustainability infrastructure is underdeveloped, green directors play a more critical role in interpreting fragmented policies and mobilizing scarce resources. We therefore hypothesize the following:
The positive relationship between green-background directors and corporate green innovation is weaker in regions with higher regional marketization levels.
Board diligence implies meeting frequency and preparation intensity [61], serving as a governance amplifier for green directors by institutionalizing sustainability priorities within strategic decision-making. Diligent boards systematically incorporate environmental considerations into agenda-setting, allocate dedicated discussion time to green innovation projects, and establish monitoring mechanisms to track progress against sustainability targets [49]. They also align executive compensation with environmental performance metrics [47], ensuring long-term commitment beyond symbolic gestures. Frequent interactions among diligent board members further strengthen shared environmental norms, creating a governance culture where green directors’ proposals receive more rigorous evaluation and support [62]. Additionally, frequent director interactions foster stronger social networks and promote cultural transmission [63], further embedding environmental values into organizational norms. We therefore hypothesize the following:
The positive relationship between green-background directors and corporate green innovation is stronger in firms with more diligent boards.
Green investors enhance the impact of green directors by reshaping corporate financial incentives and legitimizing sustainability-driven strategies [64]. This influence operates primarily through capital allocation effects that prioritize funding for environmentally friendly firms and innovative solutions [65]. Green investors’ pressure leads to more corporate disclosure practices [54], which, in turn, elevate the importance of environmental considerations in decision-making. Then, market recognition not only enhances brand equity but also creates imitation effects industry-wide, fostering sustainability-oriented competition. Furthermore, green investors facilitate inter-organizational collaboration by connecting firms with research institutions and clean-tech startups, enabling green directors to leverage external knowledge networks [66]. This is critical for cross-disciplinary green innovation. We therefore hypothesize the following:
The positive relationship between green-background directors and corporate green innovation is stronger in firms with green investor ownership.
2.2.3. Mediating Effects Analysis
The mediating role of environmental attention stems from green-background directors’ unique capacity to shape organizational cognitive priorities through both formal governance and informal influence [2]. Drawing on the attention-based view [67], these directors systematically redirect managerial focus toward sustainability by structuring board discussions around environmental best practices [52], leveraging their specialized knowledge to frame green innovation as a strategic imperative rather than a compliance obligation. They prioritize environmental issues in strategic agendas through their decision-making authority [68], while their role-modeling of sustainability values cultivates an organizational culture where environmental considerations permeate daily operations beyond boardroom policies [69]. This dual governance–cognitive influence enables experts and governors to leverage cognitive resource allocation toward environmental opportunities by aligning the firm’s “attention hierarchy” with long-term ecological goals [70], thereby translating director-level expertise into organizational action. We hypothesize the following:
Green-background directors improve corporate green innovation by enhancing environmental attention.
Government green subsidies serve as a critical financial conduit for green innovation, particularly given its resource-intensive nature [71]. Green-background directors facilitate subsidy acquisition efficiency through two complementary channels: regulatory navigation, and technical credibility. Their understanding of environmental regulations helps navigate complex application processes. To be specific, their familiarity with environmental policy landscapes allows them to identify and tailor projects to funding criteria, while their technical expertise ensures that proposals meet stringent qualification standards [72]. Beyond mere access, subsidies secured through their involvement carry signaling value by validating the firm’s green commitments to external stakeholders [73], thereby attracting additional resources from investors who perceive subsidized projects as lower-risk opportunities [73]. This creates a self-reinforcing cycle where initial subsidy success enhances the firm’s reputation for environmental competence, further amplifying green directors’ ability to mobilize future resources [27].
We hypothesize the following:
Green-background directors improve corporate green innovation by facilitating access to government green subsidies.
To systematically integrate the theoretical relationships reflected in the above hypotheses, Figure 1 is introduced to show the consolidated framework.
3. Methodology
3.1. Variable Descriptions and Sample Selection
Our initial sample consists of A-share listed firms in heavily polluting industries on the Shanghai and Shenzhen stock exchanges from 2014 to 2019. Given the lagged nature of green patent applications, this study followed conventional practice [28] by using green innovation data from 2015 to 2020. To ensure sample purity, we excluded (1) firms with explicitly environmental names (e.g., containing “environment” or “ecology”), as these may specialize in green technologies; (2) ST/*ST firms, due to financial abnormalities; and (3) firms with less than three years of listing history. After removing observations with missing core variables and winsorizing continuous variables at the 1st and 99th percentiles to mitigate outlier effects, we obtained an unbalanced panel of 4368 firm-year observations covering 886 heavily polluting firms.
3.1.1. Dependent Variable
The dependent variable in this study is corporate green innovation, which has been measured in prior research through various proxies, including green R&D expenditures, eco-label product certifications, and patent outputs [23,28]. For the Chinese market context, green patent counts have emerged as the most widely adopted metric for assessing green innovation performance, due to data availability considerations [74], with higher patent quantities indicating superior green innovation capabilities. To further distinguish innovation quality, this study followed conventional patent classification by measuring strategic green innovation through utility model and design patent applications, while using invention patent applications to capture substantive green innovation [75].
3.1.2. Independent Variables
The independent variables in this study focus on green-background directors and their power. This study identified these directors through systematic screening of executive resumes. Directors were classified as having green backgrounds if their profiles contained any of the following keywords: “environmental protection,” “sustainability,” “recycling,” “pollution control,” “energy conservation,” or related terms, consistent with the operational definitions used in recent China-focused studies [76].
To measure director power, this study adapted the board ranking approach validated by Tran and Turkiela [77] for the Chinese institutional context. This method accounts for the hierarchical nature of corporate governance in China, where formal position rankings significantly influence decision-making authority [53]. Specifically, this study first created a binary indicator (GD) that equaled 1 for firms with at least one green-background director in a given year, and 0 otherwise. Second, this study calculated the number of green-background directors per firm-year. Third, this study computed individual power scores using Formula (1), based on their ordinal position in the board roster:
(1)
where GRANK represents the disclosed ranking of directors in the company’s annual report, and max denotes the total number of board members. GPOWER ranges from 0 to 1, indicating the relative power of an individual green-background director in a given year. The aggregate standardized value of GPOWER yields the green-background director power index (GP).This measurement approach has been empirically validated in emerging market governance research [52] and addresses the unique characteristics of China’s corporate landscape, where formal hierarchy carries substantial weight [78].
The green-background director power index (GP) was constructed through a systematic procedure. First, this study identified each green-background director’s ranking position (GRANK) in the board roster from annual reports, where higher rankings indicated greater power. Individual power scores (GPOWER) were normalized to range between 0 (lowest power) and 1 (highest power), based on their relative position within the board. This study then aggregated all green-background directors’ GPOWER values per firm-year to obtain the total green-director power. This aggregate measure was standardized by the board’s total power score to generate our primary metric (GP). This design ensures that firms benefit from both having more green-background directors and placing them in higher-ranking positions.
3.1.3. Moderating Variables
This study examines four theoretically grounded moderating variables: firm size, regional marketization level, board diligence, and green investor presence. These variables collectively capture the multi-level institutional and organizational conditions shaping corporate green innovation. These moderators were selected through integration of resource-based, institutional, agency, and stakeholder theories, each addressing distinct mechanisms through which green directors’ influence may be amplified or constrained.
(1) Firm size
The theoretical rationale for selecting firm size as a moderating variable based on the RBV stems from its fundamental impact on organizational resource endowments and allocation capabilities. The core proposition of the RBV emphasizes that heterogeneous resources are the source of competitive advantage [79], while firm size essentially represents the breadth and depth of resource reserves, shaping the impact of green-background directors on green innovation through multiple mechanisms. The inherent resource slack in large firms provides the material foundation for absorbing environmental innovation risks [80], enabling green directors’ expertise to translate into substantive R&D investments rather than remaining merely symbolic commitments. Meanwhile, economies of scale reduce per-unit environmental investment costs and enhance the economic feasibility of boards adopting green initiatives [9,81]. More importantly, the political influence endowed by firm size strategically complements the environmental expertise of green directors to jointly overcome institutional barriers and secure policy support [82], which is a mechanism often constrained by resource limitations in small and medium-sized enterprises. Our selection of firm size as a moderating variable represents an attempt to expand the application boundaries of the RBV in sustainable development research. Following conventional practice in strategic management research [83], this study measured firm size using the natural logarithm of total assets at year-end. This operationalization reflects a firm’s resource base while minimizing skewness in the distribution.
(2) Regional marketization level
Drawing on institutional theory, the selection of regional marketization level as a moderating variable is theoretically grounded in its fundamental role as a proxy for institutional environment maturity, where higher marketization levels create stronger regulatory pressures through rigorous environmental enforcement [84], normative expectations via developed industry associations and media oversight [85], and mimetic isomorphism through faster diffusion of sustainable practices among firms [47]. These mechanisms collectively enhance green directors’ ability to translate their expertise into substantive innovation outcomes. The marketization level’s moderating effect manifests through two interconnected paths: it expands critical resource channels for green innovation (including specialized technology markets and green financing access) while simultaneously resolving institutional logic conflicts that often hinder environmental initiatives in less-developed regions [86].
China’s economic transition since 1978 has created significant regional variations in institutional development [87]. This study captured these differences using the provincial marketization index developed by Fan et al. [88], which assesses five dimensions: (1) government–market relations, (2) development of non-state sectors, (3) product market development, (4) factor market development, and (5) legal institutional environment. The composite index provides a comprehensive measure of regional institutional quality.
(3) Board diligence
Grounded in agency theory, the selection of board diligence as a moderating variable stems from its critical role in mitigating principal–agent conflicts through enhanced monitoring intensity. Diligent boards, characterized by frequent and substantive meetings [61], are more likely to scrutinize managerial proposals—including those from green directors—thereby reducing information asymmetry and ensuring that environmental initiatives align with long-term shareholder value rather than managerial self-interest [89]. This oversight mechanism is particularly salient for sustainability decisions, where the tangible returns are often delayed and opaque [47], as diligent boards persistently demand performance metrics and cost–benefit analyses before approving investments. Moreover, diligent boards counteract managerial short-termism by institutionalizing rigorous evaluation processes [90], which transform green directors’ advocacy from symbolic gestures into actionable strategies with clear accountability. Crucially, the moderating effect of board diligence operates through two synergistic channels: it amplifies the credibility of green directors’ expertise by subjecting it to collective scrutiny, while simultaneously curbing potential “green-washing” behaviors that might arise from agency conflicts [48], thus bridging the gap between environmental commitments and their execution.
Board meeting frequency serves as a proxy for board engagement and oversight intensity. This study followed Vafeas [61] by using the natural logarithm of annual board meetings to measure diligence. This transformation addresses the right-skewness typical of count data while preserving the ordinal nature of the measure.
(4) Green investors
Environmentally oriented investors influence corporate behavior through both active engagement and selective capital allocation [54]. Green investors, by explicitly prioritizing environmental performance in capital allocation decisions [54], create normative pressure that amplifies the legitimacy of green directors’ proposals within boardrooms, as firms increasingly recognize sustainability as a critical path to secure long-term financing. Their presence signals to management that environmental initiatives align with the interests of powerful financial stakeholders [91], thereby reducing resistance to green innovation investments that might otherwise be perceived as conflicting with short-term profit motives. Simultaneously, green investors provide specialized knowledge networks and market access, which complement green directors’ technical expertise and enhance the feasibility of implementing sustainable strategies. This symbiotic relationship between green investors and directors transforms stakeholder demands into actionable governance outcomes, illustrating how external stakeholder pressures interact with internal governance mechanisms to drive substantive environmental change [90]. This study identified green investors by manually screening fund prospectuses for environmental keywords (e.g., “eco-friendly,” “clean energy,” “sustainability”), following the methodology of Dixon-Fowler et al. [92]. A binary indicator (1/0) identified firms with such investors. Firms with 1 or more qualifying investor were coded as 1 (0 otherwise).
3.1.4. Mediating Variables
This study examined two critical mediating mechanisms through which green-background directors influence corporate green innovation: government green subsidies and corporate environmental attention. These variables help explain the underlying processes of the observed relationship.
(1) Government green subsidies
Green-background directors facilitate access to government green subsidies through their specialized knowledge and networks [73]. These subsidies, while not directly funding innovation projects, enable firms to reallocate internal resources toward green R&D by offsetting compliance costs [93]. This study identified subsidy recipients through a comprehensive manual review of annual report disclosures, searching for terms like “environmental protection,” “clean production,” and “energy efficiency.” This study coded this as a binary variable (1 = received subsidies; 0 = otherwise).
(2) Corporate environmental attention
The presence of green-background directors elevates environmental considerations in strategic decision-making [69]. This study measured this cognitive focus through quantitative text analysis of annual reports using the Chinese environmental term dictionary developed by Bao and Liu [94], which included key phrases such as: “Emission reduction”, “Environmental strategy”, “Sustainable development”, and “Circular economy”.
3.1.5. Control Variables
Based on previous firm-level studies, this study employed 11 control variables to account for potential confounding factors influencing green innovation [27,95].
First, variables reflecting board governance were controlled. This study primarily focuses on the influence of green-background directors, a specific aspect of board governance, while the effectiveness of a firm’s existing board governance mechanisms may influence the role of these green-background directors. Following established measurement approaches in corporate governance research, this study selected board size (Board), proportion of independent directors (Indep), and CEO–chair duality (Dual) as control variables for board governance. Specifically, board size was measured by the natural logarithm of the number of board members. The independent director ratio was calculated as the percentage of independent directors relative to total board membership. CEO–chair duality was operationalized as a dummy variable indicating whether the CEO and board chair positions are held by the same individual.
Furthermore, other firm-level characteristics were controlled. The effectiveness of green-background directors is influenced by the internal environment of the firm [96]. This paper selected the following control variables for firm characteristics: R&D investment (RD), leverage ratio (Lev), return on assets (ROA), revenue growth rate (Growth), cash flow ratio (Cash), business years (BY), Tobin’s Q (TobinQ), institutional investor holding percentage (Inst), and shareholding concentration (Top10). Specifically, R&D investment was calculated with the natural logarithm of the amount of the R&D investment. The leverage ratio was defined as the total liabilities divided by total assets at the fiscal year-end. Return on assets was calculated using net profit relative to total assets. The revenue growth rate was computed as the percentage change in operating income between consecutive years. The cash flow ratio was measured by operating cash flow scaled by total assets. Business years were operationalized through the natural logarithm of the firm’s operating history. Tobin’s Q was approximated using the market-to-asset ratio. Institutional ownership was quantified as institutional shareholdings divided by total floating shares. Ownership concentration was determined by the aggregate stake of the top ten shareholders.
3.2. Data Sources
This study utilized data from two primary sources: board member profiles and financial indicators from the China Stock Market & Accounting Research (CSMAR) database, and corporate green innovation metrics from the China National Intellectual Property Administration (CNIPA). The sample focused on heavily polluting industries, identified through China Securities Regulatory Commission (CSRC) sector classifications, following environmental economics research conventions [97]. Eighteen target sectors were identified: coal mining and washing (B06), gas extraction (B07), ferrous metal mining (B08), non-ferrous metal mining (B09), non-metallic mining (B10), textiles (C17), apparel (C18), leather products (C19), paper manufacturing (C22), petroleum processing (C25), chemical materials (C26), pharmaceuticals (C27), chemical fibers (C28), plastics (C29), non-metallic products (C30), ferrous metal smelting (C31), non-ferrous metal smelting (C32), and power/heat production (D44).
The dependent variable, corporate green innovation, was constructed using patent application and authorization data from the CNIPA, with green patents identified through manual screening based on International Patent Classification (IPC) codes. Corporate green innovation performance was measured as the annual sum of green utility model patents (strategic innovation) and green invention patents (substantive innovation). The independent variables, green-background directors and their power, were obtained from the CSMAR database’s executive profiles and annual report disclosures. Moderating variables, mediating variables, and additional controls were extracted from the corresponding CSMAR sub-databases, following data validation protocols.
3.3. Models
This paper used Formula (2) to examine the effect of green-background directors on corporate green innovation:
(2)
Corporate green innovation (GPAT) is the natural logarithm of the number of green patent applications plus one. “GD” is a dummy variable, which equals 1 if the corporate board has green-background directors and 0 otherwise. Detailed variable definitions are provided in Table 1. When measuring the influence of directors’ power, this study replaced the GD variable in Formula (2) with the green-background director power index (GP). In addition, this study replaced the dependent variable with corporate environmental attention (EA) to explore the influence path of green-background directors on corporate green innovation.
This study used Formula (3) to examine the effects of moderating variables:
(3)
where M represents the moderating variables used in this paper. These include influencing factors at the corporate level, such as firm size (Size) and board diligence (BD), as well as factors influencing external corporate governance, such as regional marketization level (Market) and green investors (GI).4. Empirical Results
This section conducts empirical analysis based on the established theoretical framework and collected dataset. First, this study investigated the impact of green-background directors and their power on corporate green innovation using the fixed-effects model. Second, this study validated the influence of the moderating variables and mediating variables. Furthermore, it investigated how green-background directors affect both the quality and continuity of corporate green innovation.
4.1. Descriptive Statistics and Correlation Analysis
Table 2 provides the descriptive statistics for the study variables. The mean value of green patent applications (GPAT) was 0.970, indicating the weak corporate commitment to green innovation in China, highlighting the imperative need to improve green innovation performance. In total, 36.1% of companies had green-background directors (GD), with a maximum of seven such directors per firm annually. It was common for enterprises to employ green-background directors. The mean value of the power of green-background directors (GP) was 0.065, and the standard deviation was 0.123. This suggests that boards with environmental expertise wielded relatively limited influence, albeit with notable cross-firm variability.
Table 3 presents the correlation matrix and diagnostic statistics. Regarding core variables, the green innovation index (GPAT) demonstrated a statistically significant positive correlation with green-background directors (GD). Similarly, it demonstrated a significant association with green-background directors’ power (GP) at the 1% level. Regarding control variables, the cash flow ratio (Cash), leverage ratio (Lev), revenue growth rate (Growth), board size (Board), ownership concentration (Top10), institutional ownership (Inst), and operating years (BY), were all significant positively correlated with corporate green innovation at the 1% significance level. The mean variance inflation factor (VIF) for all variables was below 2, which indicated no significant multicollinearity.
4.2. Basic Results Analysis
4.2.1. The Influence of the Appointment of Green-Background Directors on the Corporate Green Innovation
Table 4 reports the baseline results of green-background directors’ influence on corporate green innovation. Specifically, column (1) applies a pooled OLS model without control variables and fixed effects. Column (2) adds control variables within the pooled OLS framework. Columns (3)–(5) progressively introduce industry fixed effects, year fixed effects, and two-way fixed effects, respectively. The regression coefficients of green-background directors on corporate green innovation remained consistently positive and statistically significant at the 1% level across all model specifications. The two-way fixed-effects model indicated that appointing green-background directors increased corporate green innovation by 12.4%. These results validate H1a. While the existing literature confirms the general positive association between green directors and corporate sustainability [92], our study extends this understanding by narrowing down to the corporate green innovation, thereby bridging governance research with the innovation literature. This aligns with the RBV’s emphasis on knowledge-based competitive advantages [98]. The coefficients are generally stable (0.315 *** to 0.124 ***), despite progressive controls for industry and temporal heterogeneity, indicating that green directors’ impact persists even when accounting for institutional isomorphic pressures [99]—a nuance overlooked in earlier governance studies.
4.2.2. The Influence of the Power of Green-Background Directors on Corporate Green Innovation
Table 5 reports regression results examining the influence of the power of green-background directors on corporate green innovation. Specifically, column (1) applies a pooled OLS model without control variables and fixed effects. Following the methodological progression from Table 4, columns (2)–(5) progressively introduce pooled OLS, control variables, and fixed-effects specifications. The regression coefficients of the power of green-background directors on corporate green innovation were consistently positive and statistically significant at the 1% level. The results were robust after incorporating fixed effects and control variables, indicating that the power of green-background directors can improve corporate green innovation. These findings validate H1b. The stability of the coefficients from 1.320 *** (column (1)) to 0.623 *** (column (5)) under increasingly stringent controls suggests that power effects persist even after accounting for industry and temporal heterogeneity, indicating that structural power operates through both universal mechanisms (e.g., resource allocation) and context-dependent processes (e.g., institutional legitimacy), as predicted by resource dependence theory [100]. Comparing the results in Table 4 and Table 5 allows this study to refine our understanding of power’s role in sustainability transitions. The magnitude of the coefficients (e.g., 0.623 in column (5), Table 5) suggests that formal power amplifies green directors’ influence more substantially than their baseline appointment (0.124 in column (5), Table 4), supporting the “power–competence synergy” hypothesis in sustainability governance [101], where authority and expertise interact multiplicatively.
4.3. Robustness Tests
4.3.1. Changing the Measurement of Green-Background Directors and Their Power
To verify the robustness of the findings, the explanatory variables were replaced. In order to verify the impact of the appointment of green-background directors, the number of green-background directors (GDN) was chosen as a proxy variable for green-background directors. Table 6 reports the robustness check results. Column (1) applies a pooled OLS model without control variables and fixed effects. Column (2) introduces control variables within the pooled OLS framework. Subsequent columns progressively incorporate fixed effects: Column (3) adds industry fixed effects. Column (4) implements year fixed effects. Column (5) adopts a two-way fixed-effects model controlling for both industry and year variations. The results are all significant at the 1% level, validating the robustness of H1a: that the number of green-background directors improves corporate green innovation.
In addition, to further validate the robustness of the power of green-background directors, this study employs green-background directors’ positional authority as a proxy for power measurement. Given China’s unique institutional context, where state ownership dominates, the absence of the owner leads to a more prominent influence of the chairman [102]. The CEO is in a key position in the firm and plays a central role in the firm’s strategic decision-making [103]. Therefore, the directors are categorized into executive directors (including core directors and ordinary executive directors) and independent directors.
As reported in Table 7, column (1) demonstrates the impact of green-background executive directors on corporate green innovation. Column (2) excludes core directors and examines the effects of executive directors with green backgrounds on corporate green innovation. Column (3) specifically evaluates core directors’ influence. These results are significant at the 1% level, indicating that executive directors with a green background have a positive impact on corporate green innovation, and that core directors with a green background have a greater impact on corporate green innovation. Column (4) examines the effect of green-background independent directors on corporate green innovation, showing no statistically significant associations. Green-background independent directors have an insignificant impact on corporate green innovation. These findings confirm that the power of green-background directors can affect corporate green innovation. The more power the green-background directors have, the more they can enhance the firm’s green innovation performance [53,104]. The results verify the robustness of the findings of H1b.
4.3.2. Changing the Measurement of Corporate Green Innovation
To verify the robustness of green-background directors’ impact on corporate green innovation, the ratio of green technology patent applications to total patent applications was employed as an alternative innovation measure [105]. Table 8 reports the results. Columns (1) and (2) use pooled OLS models, while columns (3) and (4) incorporate industry and year fixed effects. As shown in columns (1) and (3), green-background directors significantly increase the proportion of green patents. After fixing the industry and year, the share of green patent applications can be increased by 1.7% when enterprises employ directors with green backgrounds. Columns (2) and (4) demonstrate that the magnitude of the power of green-background directors can significantly increase the share of green patents of enterprises. After fixing the industry and year, for every unit increase in the power of green-background directors of enterprises, the share of green patent applications can be increased by 12.1%. The robustness checks demonstrate that firms appointing green-background directors exhibit a significantly higher proportion of corporate green innovation, confirming both green-background directors and their power as critical determinants of eco-innovation outcomes. These results reaffirm the robustness of H1a and H1b.
4.3.3. Changing the Regression Model
Given the non-negative distribution, with substantial zero observations and skewed non-negative integer values of the dependent variable corporate green innovation, Tobit and Poisson regression models were employed for estimation. Table 9 reports robustness checks using alternative estimation approaches. Columns (1) and (2) apply pooled OLS–Tobit models, columns (3) and (4) utilize random-effects Tobit models, and columns (5) and (6) implement Poisson regressions to evaluate the effects of green-background directors and their power on corporate green innovation. The results align with previous findings. Both green-background directors and their power significantly increase corporate green innovation at the 1% significance level. The robustness of H1a and H1b is again verified. Hence, even after changing the estimation method, the effect of green-background directors on corporate green innovation remains robust.
4.3.4. Relieving Endogenous Factors
To address potential endogeneity concerns arising from sample selection bias, this study implemented propensity score matching (PSM) and enhanced firm fixed effects for robustness checks. First, PSM was applied to match listed firms with green-background directors to comparable firms without such directors. The results are shown in columns (1) and (2) of Table 10. Second, firm fixed effects were strengthened in the regression models to absorb unobserved heterogeneity, as reported in columns (3) and (4). The results consistently demonstrate that both the presence of green-background directors and the power of green-background directors significantly enhance corporate green innovation at the 1% significance level. These findings confirm that the positive impacts remain robust after mitigating endogenous selection bias, thereby reinforcing the validity of H1a and H1b.
4.4. Moderating Effect Test
4.4.1. Moderating Effect of Firm Size
Table 11 presents empirical results on firm size’s moderating role. Columns (1)–(2) use green-background directors and the power of green-background directors as the explanatory variables, respectively. The interaction terms, Interact1 and Interact2, between the explanatory variables and firm size demonstrate positive coefficients significant at the 1% level. This indicates that firm size strengthens the impact of green-background directors on corporate green innovation. The regression results verify H2a. The stronger moderating effect for director power (Interact2) versus baseline appointment (Interact1) aligns with resource dependence theory’s prediction that structural authority becomes more consequential in complex organizations where cross-functional coordination is paramount [100]. These findings refine our understanding of the role of firm size in two key respects: First, the robust coefficients (p < 0.01) across both specifications suggest that size effects are not merely artifacts of scale economies but reflect strategic resource orchestration capabilities [106]—larger firms appear better at aligning green directors’ knowledge with complementary assets like R&D teams and supplier networks. Second, the results challenge the assumption that small firms are inherently more agile in sustainability transitions; rather, the 0.343 *** interaction for powered directors indicates that formal authority in large firms can overcome bureaucratic inertia through centralized decision-making [107].
4.4.2. Moderating Effect of Local Marketization Level
Table 12 presents results examining the moderating role of regional marketization level. The findings demonstrated that green-background directors and their power had positive effects on corporate green innovation, while regional marketization level showed insignificant impact. The interaction term between green-background directors and marketization level revealed a negative coefficient. This suggests that higher regional marketization levels weakened green-background directors’ positive impact on corporate green innovation, indicating a significant substitution relationship between green-background directors and regional marketization level. The diminishing influence of green-background directors in more marketed regions stems from three key factors: formal environmental regulations and ESG frameworks replace their informal influence, developed markets enable external access to green expertise, and widespread environmental awareness reduces their unique value. This reflects the natural evolution from personal influence to institutionalized governance as markets mature.
These regression results validate H2b.
4.4.3. Moderating Effect of Board Diligence
Table 13 presents empirical results on board diligence’s moderating role. The interaction terms between board diligence and the power of green-background directors were positive and statistically significant at the 10% level. This indicates that board diligence strengthened the positive effects of the power of green-background directors, suggesting green-background directors exert a stronger driving force for corporate green innovation in firms with more diligent boards. These findings support H2c. Contrasting with Mansour et al. (2025)’s finding that board independence hampers carbon disclosure, possibly due to symbolic compliance pressures [108], our results show that green-background directors leverage their expertise to overcome governance inertia, particularly when supported by board diligence. Meanwhile, the interaction terms between board diligence and green-background directors were insignificant, indicating that diligence primarily amplifies green directors’ influence when coupled with formal power (interact6: 0.610 *) rather than general appointment (interact5: 0.105). This aligns with Westphal and Bednar’s [109] findings about ritualistic diligence in symbolic governance, suggesting that without power backing, diligent oversight may degenerate into procedural box-ticking rather than substantive environmental stewardship. The significant Interact6 coefficient (p < 0.1) further supports Haynes and Hillman’s “governance synergy hypothesis” [110], where the combination of structural power and intensive monitoring creates unique accountability channels for sustainability innovation.
4.4.4. Moderating Effect of Green Investors
This paper further examined the moderating role of green investors. Table 14 reports the empirical results. Column (1) demonstrates the moderating effect of green investors on the relationship between green-background directors and corporate green innovation. While both green-background directors and green investors were significant drivers of corporate green innovation, their interaction term Interact7 was statistically significant at the 1% level. Column (2) reveals that the term Interact8 between green investors and the power of green-background directors was significantly positive at the 1% level, indicating that green investors positively amplified this relationship. This suggests that strategic alignment between green investors and internal governance structures optimizes green innovation. These results validate H2d. While prior research establishes green investors’ standalone impact on sustainability performance [54], our results reveal their synergistic role in amplifying directors’ effectiveness—particularly for those with formal power (Interact8’s 1.032 *** vs. Interact7’s 0.126 ***). This aligns with Brookes (2013)’s “coalitional power” theory, where investor–director alliances overcome innovation resistance by simultaneously providing financial resources and market legitimacy [111]. The stronger moderation for powered directors (GP) suggests that green investors strategically target influenceable board members, consistent with the “strategic shareholder activism” framework [112].
4.5. Mediating Effect Test
4.5.1. Mediating Effect of Corporate Environmental Attention
According to mediation analysis, this study investigated the mechanisms underlying the influence of green-background directors on corporate green innovation. As shown in Table 15, both green-background directors and their power exhibited statistically significant positive relationships with corporate environmental attention at the 1% level. These results indicate that green-background directors enhanced firms’ environmental focus. Green-background directors imprinted their influence by heightening environmental consciousness, which subsequently improved green innovation performance. Corporate environmental attention exerted a mediating effect on the relationship between green-background directors and corporate green innovation. These results confirm H3a. Unlike Xu et al. (2025)’s emphasis on fiscal subsidies [113], our findings reveal that green directors leverage non-financial channels (e.g., environmental attention allocation, investor signaling) to drive innovation. The strikingly significant coefficient (GP: 3.955 ***) in Table 15 indicates that green-background directors with formal power have a super-linear increase in their impact on environmental attention. This effect far exceeds the baseline level (GD: 0.714 ***), indicating that power not only increases attention allocation but also reconstructs the organization’s attention architecture [114], giving disproportionate strategic priority to sustainable development issues.
4.5.2. Mediating Effect of Government Green Subsidies
As shown in Table 16, both green-background directors and their power exhibited statistically significant positive effects on firms’ acquisition of government green subsidies. This indicates that green-background directors enhance firms’ ability to secure subsidies. Government green subsidies were identified as a mediating variable in the relationship between green-background directors and corporate green innovation, suggesting that green-background directors improve green innovation performance by enabling firms to obtain subsidies. These results confirm H3b. While the smaller effect sizes compared to other mechanisms (e.g., environmental attention) might suggest a limited direct impact, they align with Haldar et al.’s (2024) [115] finding that subsidies primarily act as “enabling catalysts” rather than primary drivers of green innovation—particularly when directors lack implementation authority (GD’s weaker effect).
4.6. Further Discussions
The above has thoroughly discussed the impact of green-background directors on corporate green innovation, the influence mechanisms, and the moderating effects of internal and external corporate environments. This subsection extends the analysis to investigate how green-background directors affect both the quality and continuity of corporate green innovation, to comprehensively understand the impact of green-background directors on corporate green innovation.
4.6.1. The Influence of Green-Background Directors on the Quality of Corporate Green Innovation
To examine whether green-background directors truly achieve “quality improvement and quantity increase” for corporate green innovation or “green-washing” behavior, this study distinguished their influence on substantive (invention patents) and strategic (utility models) green innovation. Table 17 presents the test results using the fixed-effects model. Specifically, columns (1)–(3) test the effects of green-background directors on overall green innovation, substantive green innovation, and strategic green innovations, respectively. Columns (4)–(6) test the influence of the power of green-background directors on these green innovations. All coefficients were positive and statistically significant at the 1% level. These findings confirm that green-background directors drove both strategic and substantive green innovation, achieving “quality–quantity synergy” in green innovation outcomes. The stronger effects of green-background directors on strategic green innovation (column (3)) compared to substantive innovation (column (2)) indicate that director-level environmental expertise primarily shapes symbolic sustainability outcomes rather than deep technical breakthroughs. However, the significant GP coefficients (columns (5) and (6)) reveal that formal power enables directors to bridge this gap by converting symbolic gestures into substantive R&D reallocation through their authority.
4.6.2. The Influence Continuity of Green-Background Directors on Corporate Green Innovation
Appointing green-background directors enhances green innovation awareness, and the time lag from innovation practice to patent application prolongs the impact [116]. This study examined the sustained impact of green-background directors on corporate green innovation over a three-year time span. Since the original data of GD and GP were already lagged by one period, tests were conducted with GD and GP lagged by two periods. Table 18 presents the lagged effects. Columns (1) and (4), (2) and (5), and (3) and (6) correspond to t + 1, t + 2, and t + 3 results, respectively. The sustained impact of appointing green-background directors on corporate green innovation existed and decreased year by year. In the third year, this impact became insignificant. The declining coefficients for green-background directors from lag1 to lag3 align with the findings of Hedman and Henningsson (2016) [117], suggesting that environmental expertise requires continuous reinforcement to sustain innovation impacts. In contrast, the impact of their power exhibits a U-shaped trajectory over time: while it declines significantly in the second lag year (lag2), it subsequently rebounds marginally in the third lag year (lag3), with the effect remaining statistically significant at the 10% level. This persistent significant impact demonstrates its capacity to embed sustainability into organizational routines, consistent with You (2017)’s finding that formal power triggers virtuous cycles [118].
5. Conclusions and Policy Recommendations
This paper investigated the relationship between green-background directors and corporate green innovation using data from 2014 to 2020 for listed firms in China’s heavily polluting industries. The analysis extended existing research on the green background of board members and the determinants of corporate green innovation.
The findings confirmed that green-background directors were pivotal drivers of firms’ green transformation, with the power of green-background directors significantly amplifying their impact. These results indicated that green-background directors effectively promoted corporate green innovation, and their influence was fundamentally reliant on the power of green-background directors within corporate governance structures. The moderating mechanism analysis revealed that firm size and board diligence strengthened the positive effect of green-background directors, while regional marketization level acted as a substitute in promoting corporate green innovation. Additionally, green investors enhanced the influence of green-background directors. This study proposed that green-background directors facilitated corporate green innovation by improving corporate environmental attention and securing government green subsidies. This suggested that green-background directors provided enterprises with the resources needed for green innovation. Further analysis decomposed green innovation into substantive and strategic types, according to the different types of green patent applications. This study found that green-background directors not only improved the substantive green innovation of enterprises but also improved the strategic green innovation of enterprises, actually achieving “quality improvement and quantity increase”. It also found that the impact of green-background directors on corporate green innovation was persistent.
The findings of this study provide important implications for governments and enterprises seeking to enhance green innovation performance. For enterprises, it is crucial to prioritize the appointment of directors with green backgrounds, particularly in regions with lower levels of marketization, where introducing directors with environmental qualifications becomes even more essential. Strengthening the authority of green directors by incorporating them into core governance bodies, such as strategy committees, ensures their influence on major decision-making processes. Conducting green competency training through regular professional programs on environmental management and carbon trading systematically builds their ecological awareness and skills. Proactively engaging with green investors by introducing ESG-focused investment institutions not only demonstrates environmental responsibility but also secures resources for sustainable development. For governments, it is imperative to advance green talent policies by improving certification systems for green skills and providing targeted subsidies and qualification support for corporate director training. Implementing tailored incentive measures, such as environmental subsidies and green credit interest discounts for companies that appoint directors with green backgrounds, helps reduce institutional transition costs. Enhancing regional policy coordination by introducing disclosure guidelines for directors’ green performance in less-marketized areas can narrow governance disparities across regions.
This study faces limitations. First, due to limited data availability, it is difficult for this paper to directly examine the impact of green-background directors on enterprises’ green credit, environmental protection subsidies, and green information on green innovation. Second, the identification of green-background directors relies on keyword-based screening of professional backgrounds, limiting more detailed classification of their experience types. Third, the measurement of directorial power assumes stepwise authority differences, potentially overlooking extreme intra-firm disparities. Fourth, this study only focuses on the heavily polluted industries in China, limiting the generalizability of the research results to other industries or countries with different regulatory environments. The results might differ in less-polluting industries, or in economies with stronger/weaker environmental regulations.
Conceptualization, L.L.; methodology, H.D.; software, H.D.; validation, L.L.; formal analysis, L.Q.; investigation, L.L.; resources, L.L.; data curation, H.D.; writing—original draft preparation, H.D. and L.Q.; writing—review and editing, L.L.; visualization, H.D.; supervision, L.L.; project administration L.L.; funding acquisition, L.L. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
The data in this paper come from the China Stock Market & Accounting Research (CSMAR) Database and the China National Intellectual Property Administration (CNIPA).
The authors declare no conflicts of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Figure 1 The theoretical framework.
Definition of variables.
| Variables | Acronym | Definition |
|---|---|---|
| Green-background directors | GD | Dummy variable, which equals 1 for firms with at least one green-background director in a given year, and 0 otherwise. |
| Power of green-background directors | GP | Aggregate standardized value of GPOWER |
| Corporate green innovation | GPAT | Natural logarithm of the number of green patent applications per firm-year |
| Firm size | Size | Natural logarithm of total assets at year-end |
| Regional marketization level | Market | Marketization level of the province where the company is located |
| Board diligence | BD | Natural logarithm of the number of board meetings held by the company |
| Green investors | GI | Dummy variable, which equals 1 if the company has green investors, and 0 otherwise |
| Corporate environmental attention | EA | Number of environmental keywords in annual report |
| Government green subsidies | EP | Dummy variable, which equals 1 if the company received a government environmental subsidy that year, and 0 otherwise |
| Board size | Board | Natural logarithm of the number of board members |
| Proportion of independent directors | Indep | Number of independent directors divided by total directors |
| CEO–chair duality | Dual | Dummy variable, which equals 1 if the CEO also serves as the board chair, and 0 otherwise |
| R&D investment | RD | Natural logarithm of the R&D investment |
| Leverage ratio | Lev | Total liabilities divided by total assets at year-end |
| Return on assets | ROA | Net profit relative to total assets |
| Revenue growth rate | Growth | (Current year revenue/previous year revenue) − 1 |
| Cash flow ratio | Cash | Operating cash flow scaled by total assets |
| Business years | BY | Natural logarithm of the firm’s operating history |
| Tobin’s Q | TobinQ | (Market value + non-tradable shares × net asset per share + liabilities)/total assets |
| Institutional investor holding percentage | Inst | Shares held by institutional investors divided by total tradable shares |
| Shareholding concentration | Top10 | Shareholding ratio of the top 10 shareholders |
Results of descriptive statistics.
| Variable | Observations | Mean | Std. Dev. | Min | Max |
|---|---|---|---|---|---|
| GD | 4368 | 0.361 | 0.480 | 0 | 1 |
| GP | 4368 | 0.065 | 0.123 | 0 | 0.611 |
| GPAT | 4368 | 0.970 | 1.110 | 0 | 4.443 |
| Size | 4368 | 22.24 | 1.267 | 20.15 | 26.00 |
| Market | 4368 | 9.086 | 1.791 | 0.647 | 11.49 |
| BD | 4368 | 2.283 | 0.342 | 0 | 3.638 |
| GI | 4252 | 0.442 | 0.497 | 0 | 1 |
| RD | 4368 | 17.99 | 1.369 | 14.20 | 21.37 |
| EA | 4368 | 4.483 | 5.414 | 0 | 48 |
| EP | 4252 | 0.393 | 0.489 | 0 | 1 |
| Board | 4368 | 2.137 | 0.188 | 1.609 | 2.639 |
| Indep | 4368 | 0.372 | 0.0510 | 0.333 | 0.571 |
| Dual | 4368 | 0.280 | 0.449 | 0 | 1 |
| Lev | 4368 | 0.383 | 0.192 | 0.060 | 0.844 |
| ROA | 4368 | 0.0520 | 0.0570 | −0.127 | 0.210 |
| Growth | 4368 | 0.150 | 0.299 | −0.408 | 1.662 |
| Cash | 4368 | 0.0610 | 0.0610 | −0.105 | 0.223 |
| BY | 4368 | 2.847 | 0.297 | 1.386 | 3.714 |
| TobinQ | 4368 | 1.989 | 1.209 | 0 | 7.230 |
| Inst | 4368 | 0.377 | 0.240 | 0 | 0.870 |
| Top10 | 4368 | 0.594 | 0.147 | 0.254 | 0.902 |
Correlation analysis of major variables.
| Variables | GPAT | GD | GP | RD | Lev | Cash | Growth | Indep | Board | Top10 | TobinQ | Inst | BY | Dual | Roa |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GPAT | 1 | ||||||||||||||
| GD | 0.136 *** | 1 | |||||||||||||
| GP | 0.146 *** | 0.700 *** | 1 | ||||||||||||
| RD | 0.391 *** | 0.0131 | −0.0236 | 1 | |||||||||||
| Lev | 0.320 *** | 0.070 *** | 0.088 *** | 0.203 *** | 1 | ||||||||||
| Cash | 0.072 *** | 0.009 | −0.033 ** | 0.168 *** | −0.140 *** | 1 | |||||||||
| Growth | 0.065 *** | 0.051 *** | 0.054 *** | 0.107 *** | −0.002 | 0.015 | 1 | ||||||||
| Indep | −0.020 | −0.057 *** | 0.011 | 0.0159 | 0.002 | −0.036 ** | 0.007 | 1 | |||||||
| Board | 0.217 *** | 0.064 *** | −0.013 | 0.132 *** | 0.196 *** | 0.042 *** | −0.033 ** | −0.586 *** | 1 | ||||||
| Top10 | 0.066 *** | −0.023 | −0.018 | 0.104 *** | −0.109 *** | 0.116 *** | 0.140 *** | 0.047 *** | −0.005 | 1 | |||||
| TobinQ | −0.218 *** | −0.057 *** | −0.072 *** | −0.181 *** | −0.320 *** | 0.084 *** | 0.017 | 0 | −0.109 *** | −0.068 *** | 1 | ||||
| Inst | 0.277 *** | −0.019 | −0.006 | 0.276 *** | 0.254 *** | 0.105 *** | −0.007 | −0.026 * | 0.203 *** | 0.269 *** | 0.044 *** | 1 | |||
| BY | 0.071 *** | 0.035 ** | 0.047 *** | 0.0615 *** | 0.147 *** | 0.013 | −0.055 *** | −0.007 | 0.079 *** | −0.196 *** | −0.058 *** | 0.138 *** | 1 | ||
| Dual | −0.190 *** | −0.041 *** | −0.026 * | −0.0624 *** | −0.129 *** | 0.004 | 0.039 *** | 0.084 *** | −0.166 *** | 0.080 *** | 0.068 *** | −0.202 *** | −0.065 *** | 1 | |
| Roa | −0.040 *** | −0.020 | −0.054 *** | 0.147 *** | −0.459 *** | 0.446 *** | 0.288 *** | −0.042 *** | −0.047 *** | 0.232 *** | 0.242 *** | −0.062 *** | −0.074 *** | 0.099 *** | 1 |
Note: * p < 0.1, ** p < 0.05, *** p < 0.01.
The impact of green-background directors on corporate green innovation.
| Variables | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| GPAT | GPAT | GPAT | GPAT | GPAT | |
| GD | 0.315 *** | 0.248 *** | 0.137 *** | 0.232 *** | 0.124 *** |
| (9.082) | (8.270) | (4.769) | (7.536) | (4.274) | |
| RD | 0.214 *** | 0.272 *** | 0.206 *** | 0.264 *** | |
| (18.293) | (21.577) | (16.104) | (20.772) | ||
| Lev | 1.034 *** | 0.511 *** | 1.071 *** | 0.554 *** | |
| (10.931) | (5.753) | (11.245) | (6.182) | ||
| Cash | 0.553 ** | 0.027 | 0.577 ** | 0.057 | |
| (2.048) | (0.106) | (2.146) | (0.224) | ||
| Growth | 0.114 ** | 0.107 ** | 0.090 | 0.078 | |
| (2.213) | (2.128) | (1.621) | (1.506) | ||
| Indep | 1.588 *** | 1.275 *** | 1.603 *** | 1.289 *** | |
| (4.449) | (3.842) | (4.380) | (3.912) | ||
| Board | 0.783 *** | 0.580 *** | 0.800 *** | 0.599 *** | |
| (7.842) | (5.937) | (7.405) | (6.152) | ||
| Top10 | 0.089 | −0.146 | 0.022 | −0.198 * | |
| (0.797) | (−1.425) | (0.203) | (−1.923) | ||
| TobinQ | −0.093 *** | −0.046 *** | −0.098 *** | −0.048 *** | |
| (−7.002) | (−3.880) | (−7.736) | (−3.877) | ||
| Inst | 0.539 *** | 0.507 *** | 0.579 *** | 0.540 *** | |
| (7.500) | (7.343) | (7.920) | (7.784) | ||
| BY | −0.031 | −0.065 | −0.094 * | −0.126 ** | |
| (−0.613) | (−1.345) | (−1.774) | (−2.460) | ||
| Dual | −0.260 *** | −0.170 *** | −0.261 *** | −0.172 *** | |
| (−7.838) | (−5.903) | (−8.720) | (−6.023) | ||
| Roa | 0.607 * | 0.610 * | 0.664 * | 0.644 ** | |
| (1.724) | (1.858) | (1.940) | (1.970) | ||
| Constants | 0.856 *** | −5.624 *** | −5.715 *** | −5.313 *** | −5.427 *** |
| (41.123) | (−14.553) | (−14.912) | (−12.791) | (−14.092) | |
| Year FE | No | No | No | Yes | Yes |
| Ind FE | No | No | Yes | No | Yes |
| N | 4368 | 4368 | 4368 | 4368 | 4368 |
| R 2 | 0.019 | 0.280 | 0.378 | 0.286 | 0.383 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
The impact of green-background directors’ power on corporate green innovation.
| Variables | (1) | (2) | (3) | (4) | (5) |
|---|---|---|---|---|---|
| GPAT | GPAT | GPAT | GPAT | GPAT | |
| GP | 1.320 *** | 1.088 *** | 0.685 *** | 1.028 *** | 0.623 *** |
| (9.776) | (8.979) | (5.226) | (7.798) | (4.766) | |
| RD | 0.219 *** | 0.274 *** | 0.210 *** | 0.265 *** | |
| (18.741) | (21.699) | (16.514) | (20.875) | ||
| Lev | 1.014 *** | 0.509 *** | 1.053 *** | 0.552 *** | |
| (10.750) | (5.723) | (11.086) | (6.160) | ||
| Cash | 0.611 ** | 0.073 | 0.636 ** | 0.102 | |
| (2.273) | (0.290) | (2.392) | (0.405) | ||
| Growth | 0.105 ** | 0.101 ** | 0.078 | 0.070 | |
| (2.042) | (2.015) | (1.407) | (1.365) | ||
| Indep | 1.528 *** | 1.245 *** | 1.547 *** | 1.264 *** | |
| (4.298) | (3.759) | (4.240) | (3.842) | ||
| Board | 0.831 *** | 0.611 *** | 0.846 *** | 0.629 *** | |
| (8.348) | (6.286) | (7.906) | (6.492) | ||
| Top10 | 0.086 | −0.142 | 0.018 | −0.195 * | |
| (0.774) | (−1.390) | (0.167) | (−1.893) | ||
| TobinQ | −0.090 *** | −0.045 *** | −0.095 *** | −0.048 *** | |
| (−6.768) | (−3.838) | (−7.487) | (−3.829) | ||
| Inst | 0.522 *** | 0.498 *** | 0.563 *** | 0.533 *** | |
| (7.289) | (7.211) | (7.738) | (7.672) | ||
| BY | −0.040 | −0.070 | −0.105 ** | −0.131 ** | |
| (−0.797) | (−1.430) | (−1.984) | (−2.557) | ||
| Dual | −0.262 *** | −0.171 *** | −0.263 *** | −0.174 *** | |
| (−7.922) | (−5.975) | (−8.788) | (−6.089) | ||
| Roa | 0.625 * | 0.625 * | 0.678 ** | 0.657 ** | |
| (1.781) | (1.905) | (1.988) | (2.013) | ||
| Constants | 0.884 *** | −5.740 *** | −5.777 *** | −5.421 *** | −5.484 *** |
| (47.075) | (−14.899) | (−15.074) | (−13.107) | (−14.233) | |
| Year FE | No | No | No | Yes | Yes |
| Ind FE | No | No | Yes | No | Yes |
| N | 4368 | 4368 | 4368 | 4368 | 4368 |
| R 2 | 0.021 | 0.285 | 0.380 | 0.292 | 0.385 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
Changing the measurement of the green-background directors.
| (1) | (2) | (3) | (4) | (5) | |
|---|---|---|---|---|---|
| GPAT | GPAT | GPAT | GPAT | GPAT | |
| GDN | 0.242 *** | 0.183 *** | 0.101 *** | 0.175 *** | 0.095 *** |
| (12.389) | (10.711) | (5.592) | (9.261) | (5.217) | |
| Constants | 0.847 *** | −5.443 *** | −5.612 *** | −5.149 *** | −5.335 *** |
| (43.900) | (−14.154) | (−14.664) | (−12.495) | (−13.874) | |
| Year FE | No | No | No | Yes | Yes |
| Ind FE | No | No | Yes | No | Yes |
| Control variables | No | Yes | Yes | Yes | Yes |
| N | 4368 | 4368 | 4368 | 4368 | 4368 |
| R 2 | 0.034 | 0.287 | 0.380 | 0.293 | 0.385 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) *** p < 0.01.
Changing the measurement of the green-background directors’ power.
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| GPAT | GPAT | GPAT | GPAT | |
| GUNIND | 0.174 *** | 0.131 *** | ||
| (4.781) | (2.806) | |||
| GC | 0.198 *** | |||
| (3.887) | ||||
| GIND | 0.049 | |||
| (1.324) | ||||
| RD | 0.265 *** | 0.248 *** | 0.266 *** | 0.254 *** |
| (20.923) | (19.073) | (20.883) | (18.477) | |
| Lev | 0.546 *** | 0.577 *** | 0.552 *** | 0.564 *** |
| (6.094) | (6.305) | (6.147) | (5.890) | |
| Cash | 0.101 | 0.309 | 0.085 | 0.248 |
| (0.399) | (1.170) | (0.334) | (0.888) | |
| Growth | 0.076 | 0.061 | 0.077 | 0.055 |
| (1.467) | (1.134) | (1.496) | (0.980) | |
| Indep | 1.326 *** | 1.465 *** | 1.341 *** | 1.279 *** |
| (4.043) | (4.336) | (4.083) | (3.606) | |
| Board | 0.602 *** | 0.599 *** | 0.632 *** | 0.499 *** |
| (6.211) | (5.834) | (6.501) | (4.586) | |
| Top10 | −0.201 * | −0.123 | −0.199 * | −0.141 |
| (−1.952) | (−1.156) | (−1.930) | (−1.272) | |
| TobinQ | −0.047 *** | −0.043 *** | −0.046 *** | −0.047 *** |
| (−3.801) | (−3.379) | (−3.716) | (−3.561) | |
| Inst | 0.532 *** | 0.506 *** | 0.529 *** | 0.451 *** |
| (7.649) | (7.057) | (7.624) | (5.940) | |
| BY | −0.125 ** | −0.139 *** | −0.137 *** | −0.071 |
| (−2.445) | (−2.600) | (−2.681) | (−1.251) | |
| Dual | −0.177 *** | −0.172 *** | −0.166 *** | −0.150 *** |
| (−6.175) | (−5.797) | (−5.762) | (−4.812) | |
| Roa | 0.624 * | 0.632 * | 0.598 * | 0.591 * |
| (1.918) | (1.871) | (1.828) | (1.663) | |
| Constants | −5.459 *** | −5.247 *** | −5.493 *** | −5.245 *** |
| (−14.193) | (−13.087) | (−14.204) | (−12.329) | |
| Year FE | Yes | Yes | Yes | Yes |
| Ind FE | Yes | Yes | Yes | Yes |
| N | 4368 | 3932 | 4368 | 3483 |
| R 2 | 0.384 | 0.378 | 0.383 | 0.355 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
Changing the measurement of corporate green innovation.
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| GPP | GPP | GPP | GPP | |
| GD | 0.028 *** | 0.017 *** | ||
| (6.264) | (3.657) | |||
| GP | 0.166 *** | 0.121 *** | ||
| (9.509) | (5.335) | |||
| RD | −0.007 *** | −0.006 *** | −0.000 | −0.000 |
| (−3.772) | (−3.413) | (−0.158) | (−0.082) | |
| Lev | 0.103 *** | 0.099 *** | 0.062 *** | 0.061 *** |
| (7.274) | (7.039) | (4.219) | (4.168) | |
| Cash | 0.030 | 0.037 | 0.003 | 0.011 |
| (0.749) | (0.921) | (0.065) | (0.240) | |
| Growth | 0.008 | 0.006 | 0.005 | 0.004 |
| (1.017) | (0.774) | (0.798) | (0.538) | |
| Indep | −0.035 | −0.042 | −0.036 | −0.038 |
| (−0.663) | (−0.784) | (−0.740) | (−0.784) | |
| Board | 0.013 | 0.019 | −0.004 | 0.001 |
| (0.866) | (1.281) | (−0.323) | (0.097) | |
| Top10 | −0.038 ** | −0.039 ** | −0.044 ** | −0.043 ** |
| (−2.296) | (−2.329) | (−2.577) | (−2.522) | |
| TobinQ | −0.007 *** | −0.006 *** | −0.006 *** | −0.006 *** |
| (−3.497) | (−3.234) | (−3.008) | (−2.969) | |
| Inst | 0.030 *** | 0.029 *** | 0.032 *** | 0.032 *** |
| (2.819) | (2.671) | (2.910) | (2.832) | |
| BY | −0.005 | −0.007 | −0.007 | −0.007 |
| (−0.664) | (−0.878) | (−0.795) | (−0.877) | |
| Dual | −0.024 *** | −0.024 *** | −0.017 *** | −0.017 *** |
| (−4.905) | (−4.936) | (−3.608) | (−3.649) | |
| Roa | 0.117 ** | 0.120 ** | 0.100 * | 0.103 * |
| (2.223) | (2.295) | (1.803) | (1.870) | |
| Constants | 0.182 *** | 0.165 *** | 0.132 ** | 0.119 ** |
| (3.157) | (2.865) | (2.338) | (2.100) | |
| Year FE | No | No | Yes | Yes |
| Ind FE | No | No | Yes | Yes |
| N | 4368 | 4368 | 4368 | 4368 |
| R 2 | 0.049 | 0.060 | 0.121 | 0.127 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
Replacing the regression model.
| (1) | (2) | (3) | (4) | (5) | (6) | |
|---|---|---|---|---|---|---|
| GPAT | GPAT | GPAT | GPAT | GPAT | GPAT | |
| GD | 0.405 *** | 0.259 *** | 0.240 *** | |||
| (8.188) | (5.065) | (7.576) | ||||
| GP | 1.791 *** | 1.328 *** | 1.012 *** | |||
| (9.508) | (6.131) | (9.277) | ||||
| 2015.year | 0.000 | 0.000 | ||||
| (.) | (.) | |||||
| 2016.year | 0.263 *** | 0.261 *** | ||||
| (3.998) | (3.978) | |||||
| 2017.year | 0.298 *** | 0.305 *** | ||||
| (4.720) | (4.826) | |||||
| 2018.year | 0.317 *** | 0.327 *** | ||||
| (5.092) | (5.261) | |||||
| 2019.year | 0.190 *** | 0.198 *** | ||||
| (3.030) | (3.167) | |||||
| 2020.year | 0.290 *** | 0.291 *** | ||||
| (4.637) | (4.658) | |||||
| Constants | −8.980 *** | −9.121 *** | −9.250 *** | −9.328 *** | −5.186 *** | −5.325 *** |
| (−14.018) | (−14.280) | (−11.956) | (−12.121) | (−13.407) | (−13.715) | |
| var (e.GPAT) | 2.077 *** | 2.060 *** | ||||
| (32.274) | (32.278) | |||||
| sigma_u | 1.113 *** | 1.103 *** | ||||
| (29.670) | (29.613) | |||||
| sigma_e | 0.922 *** | 0.921 *** | ||||
| (58.477) | (58.497) | |||||
| Control variables | Yes | Yes | Yes | Yes | Yes | Yes |
| N | 4368 | 4368 | 4368 | 4368 | 4368 | 4368 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) *** p < 0.01.
Relieving endogeneity.
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| GPAT | GPAT | GPAT | GPAT | |
| GD | 0.126 *** | 0.095 *** | ||
| (4.316) | (2.639) | |||
| GP | 0.649 *** | 0.559 *** | ||
| (5.195) | (3.121) | |||
| Constants | −5.510 *** | −5.569 *** | 0.323 | 0.221 |
| (−13.763) | (−13.903) | (0.248) | (0.170) | |
| Control variables | Yes | Yes | Yes | Yes |
| Year and Ind FEs | Yes | Yes | No | No |
| Year and Code FEs | No | No | Yes | Yes |
| N | 4164 | 4164 | 4298 | 4298 |
| R-sq | 0.383 | 0.386 | 0.765 | 0.765 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) *** p < 0.01.
The moderating effect of firm size.
| Variables | (1) | (2) |
|---|---|---|
| GPAT | GPAT | |
| GD | 0.132 *** | |
| (4.688) | ||
| GP | 0.654 *** | |
| (5.613) | ||
| Size | 0.321 *** | 0.321 *** |
| (14.320) | (14.358) | |
| Interact1 | 0.082 *** | |
| (3.519) | ||
| Interact2 | 0.343 *** | |
| (3.924) | ||
| Constants | −9.580 *** | −9.663 *** |
| (−21.044) | (−21.248) | |
| Year FE | Yes | Yes |
| Ind FE | Yes | Yes |
| Control variables | Yes | Yes |
| N | 4368 | 4368 |
| R 2 | 0.419 | 0.422 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) *** p < 0.01.
The moderating effect of regional marketization level.
| Variables | (1) | (2) |
|---|---|---|
| GPAT | GPAT | |
| GD | 0.124 *** | |
| (4.308) | ||
| GP | 0.647 *** | |
| (5.289) | ||
| market | −0.006 | −0.006 |
| (−0.788) | (−0.804) | |
| Interact3 | −0.064 *** | |
| (−4.273) | ||
| Interact4 | −0.296 *** | |
| (−4.322) | ||
| Constants | −5.364 *** | −5.446 *** |
| (−13.941) | (−14.127) | |
| Year FE | Yes | Yes |
| Ind FE | Yes | Yes |
| Control variables | Yes | Yes |
| N | 4368 | 4368 |
| R 2 | 0.385 | 0.388 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) *** p < 0.01.
The moderating effect of board diligence.
| Variables | (1) | (2) |
|---|---|---|
| GPAT | GPAT | |
| GD | 0.116 *** | |
| (4.030) | ||
| GP | 0.579 *** | |
| (4.616) | ||
| BD | 0.171 *** | 0.168 *** |
| (4.181) | (4.138) | |
| Interact5 | 0.105 | |
| (1.221) | ||
| Interact6 | 0.610 * | |
| (1.661) | ||
| Constants | −5.730 *** | −5.789 *** |
| (−14.753) | (−14.902) | |
| Year FE | Yes | Yes |
| Ind FE | Yes | Yes |
| Control variables | Yes | Yes |
| N | 4368 | 4368 |
| R 2 | 0.385 | 0.387 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, *** p < 0.01.
The moderating effect of green investors.
| Variables | (1) | (2) |
|---|---|---|
| GPAT | GPAT | |
| GD | 0.126 *** | |
| (4.285) | ||
| GP | 0.677 *** | |
| (5.436) | ||
| GI | 0.146 *** | 0.148 *** |
| (4.720) | (4.792) | |
| Interact7 | 0.126 ** | |
| (2.102) | ||
| Interact8 | 1.032 *** | |
| (4.125) | ||
| Constants | −5.245 *** | −5.300 *** |
| (−13.190) | (−13.383) | |
| Year FE | Yes | Yes |
| Ind FE | Yes | Yes |
| Control variables | Yes | Yes |
| N | 4252 | 4252 |
| R 2 | 0.386 | 0.390 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) ** p < 0.05, *** p < 0.01.
Mechanism checking of corporate environmental attention.
| Variables | (1) | (2) |
|---|---|---|
| EA | EA | |
| GD | 0.714 *** | |
| (4.190) | ||
| GP | 3.955 *** | |
| (4.585) | ||
| RD | 0.122 * | 0.128 * |
| (1.653) | (1.736) | |
| Lev | 1.400 ** | 1.382 ** |
| (2.519) | (2.491) | |
| Cash | 4.955 *** | 5.231 *** |
| (3.536) | (3.741) | |
| Growth | −0.034 | −0.081 |
| (−0.120) | (−0.292) | |
| Indep | 2.335 | 2.199 |
| (1.210) | (1.138) | |
| Board | 0.636 | 0.816 |
| (1.114) | (1.445) | |
| Top10 | −0.358 | −0.336 |
| (−0.633) | (−0.596) | |
| TobinQ | −0.305 *** | −0.300 *** |
| (−4.786) | (−4.728) | |
| Inst | 0.462 | 0.419 |
| (1.190) | (1.085) | |
| BY | −0.303 | −0.332 |
| (−1.107) | (−1.209) | |
| Dual | −0.683 *** | −0.693 *** |
| (−4.345) | (−4.385) | |
| Roa | 0.182 | 0.269 |
| (0.100) | (0.148) | |
| Constants | 0.659 | 0.288 |
| (0.292) | (0.127) | |
| Year FE | Yes | Yes |
| Ind FE | Yes | Yes |
| N | 4368 | 4368 |
| R 2 | 0.193 | 0.197 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
Mechanism checking of government green subsidies.
| Variables | (1) | (2) |
|---|---|---|
| EP | EP | |
| GD | 0.025 * | |
| (1.672) | ||
| GP | 0.099 * | |
| (1.649) | ||
| RD | −0.015 ** | −0.015 ** |
| (−2.406) | (−2.375) | |
| Lev | 0.206 *** | 0.206 *** |
| (4.161) | (4.169) | |
| Cash | 0.359 *** | 0.367 *** |
| (2.592) | (2.646) | |
| Growth | −0.008 | −0.008 |
| (−0.287) | (−0.319) | |
| Indep | 0.050 | 0.044 |
| (0.279) | (0.244) | |
| Board | −0.031 | −0.026 |
| (−0.600) | (−0.499) | |
| Top10 | −0.378 *** | −0.378 *** |
| (−6.619) | (−6.619) | |
| TobinQ | −0.034 *** | −0.034 *** |
| (−4.631) | (−4.610) | |
| Inst | 0.164 *** | 0.163 *** |
| (4.583) | (4.538) | |
| BY | 0.027 | 0.026 |
| (1.012) | (0.966) | |
| Dual | −0.033 ** | −0.034 ** |
| (−2.026) | (−2.062) | |
| Roa | −0.075 | −0.073 |
| (−0.430) | (−0.416) | |
| Constants | 0.775 *** | 0.769 *** |
| (3.797) | (3.766) | |
| Year FE | Yes | Yes |
| Ind FE | Yes | Yes |
| N | 4252 | 4252 |
| R 2 | 0.122 | 0.122 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
Quality analysis of corporate green innovation.
| Variables | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| GPAT | GSub | GSym | GPAT | GSub | GSym | |
| GD | 0.124 *** | 0.066 *** | 0.094 *** | |||
| (4.274) | (2.621) | (3.839) | ||||
| GP | 0.641 *** | 0.273 ** | 0.559 *** | |||
| (5.170) | (2.509) | (5.217) | ||||
| RD | 0.264 *** | 0.202 *** | 0.182 *** | 0.265 *** | 0.203 *** | 0.183 *** |
| (20.772) | (17.536) | (16.578) | (20.875) | (17.563) | (16.682) | |
| Lev | 0.554 *** | 0.259 *** | 0.535 *** | 0.552 *** | 0.259 *** | 0.532 *** |
| (6.182) | (3.292) | (7.133) | (6.160) | (3.292) | (7.088) | |
| Cash | 0.057 | 0.071 | 0.103 | 0.102 | 0.092 | 0.141 |
| (0.224) | (0.318) | (0.499) | (0.405) | (0.413) | (0.688) | |
| Growth | 0.078 | 0.056 | 0.048 | 0.070 | 0.054 | 0.040 |
| (1.506) | (1.252) | (1.096) | (1.365) | (1.203) | (0.932) | |
| Indep | 1.289 *** | 1.467 *** | 0.949 *** | 1.264 *** | 1.452 *** | 0.932 *** |
| (3.912) | (5.021) | (3.253) | (3.842) | (4.966) | (3.200) | |
| Board | 0.599 *** | 0.527 *** | 0.439 *** | 0.629 *** | 0.541 *** | 0.464 *** |
| (6.152) | (6.088) | (5.003) | (6.492) | (6.241) | (5.333) | |
| Top10 | −0.198 * | 0.000 | −0.060 | −0.195 * | 0.001 | −0.056 |
| (−1.923) | (0.005) | (−0.680) | (−1.893) | (0.010) | (−0.640) | |
| TobinQ | −0.048 *** | −0.023 ** | −0.036 *** | −0.048 *** | −0.023 ** | −0.036 *** |
| (−3.877) | (−2.185) | (−3.647) | (−3.829) | (−2.150) | (−3.606) | |
| Inst | 0.540 *** | 0.389 *** | 0.361 *** | 0.533 *** | 0.385 *** | 0.355 *** |
| (7.784) | (6.577) | (6.161) | (7.672) | (6.506) | (6.066) | |
| BY | −0.126 ** | −0.089 ** | −0.084 ** | −0.131 ** | −0.091 ** | −0.087 ** |
| (−2.460) | (−2.003) | (−1.975) | (−2.557) | (−2.061) | (−2.067) | |
| Dual | −0.172 *** | −0.111 *** | −0.121 *** | −0.174 *** | −0.112 *** | −0.122 *** |
| (−6.023) | (−4.508) | (−5.230) | (−6.089) | (−4.550) | (−5.295) | |
| Roa | 0.644 ** | 0.352 | 0.263 | 0.657 ** | 0.357 | 0.276 |
| (1.970) | (1.257) | (0.987) | (2.013) | (1.273) | (1.036) | |
| Constants | −5.427 *** | −4.671 *** | −3.941 *** | −5.484 *** | −4.690 *** | −3.996 *** |
| (−14.092) | (−13.500) | (−11.475) | (−14.233) | (−13.528) | (−11.655) | |
| Year FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Ind FE | Yes | Yes | Yes | Yes | Yes | Yes |
| N | 4368 | 4368 | 4368 | 4368 | 4368 | 4368 |
| R 2 | 0.383 | 0.303 | 0.349 | 0.385 | 0.303 | 0.352 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
Hysteresis test.
| Variables | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| GPAT | GPAT | GPAT | GPAT | GPAT | GPAT | |
| GD_lag1 | 0.113 *** | |||||
| (3.391) | ||||||
| GD_lag2 | 0.081 ** | |||||
| (2.067) | ||||||
| GD_lag3 | 0.047 | |||||
| (0.985) | ||||||
| GP_lag1 | 0.498 *** | |||||
| (3.387) | ||||||
| GP_lag2 | 0.349 ** | |||||
| (2.022) | ||||||
| GP_lag3 | 0.412 ** | |||||
| (2.062) | ||||||
| RD | 0.279 *** | 0.293 *** | 0.294 *** | 0.280 *** | 0.294 *** | 0.295 *** |
| (18.863) | (17.808) | (14.668) | (18.925) | (17.828) | (14.762) | |
| Lev | 0.567 *** | 0.626 *** | 0.714 *** | 0.569 *** | 0.626 *** | 0.713 *** |
| (5.410) | (5.010) | (4.783) | (5.430) | (5.016) | (4.796) | |
| Cash | 0.108 | 0.024 | 0.295 | 0.148 | 0.059 | 0.327 |
| (0.366) | (0.070) | (0.737) | (0.503) | (0.173) | (0.818) | |
| Growth | 0.094 | 0.073 | −0.008 | 0.087 | 0.069 | −0.012 |
| (1.596) | (1.046) | (−0.091) | (1.480) | (0.995) | (−0.140) | |
| Indep | 1.442 *** | 1.457 *** | 1.882 *** | 1.425 *** | 1.440 *** | 1.910 *** |
| (3.848) | (3.325) | (3.625) | (3.810) | (3.284) | (3.678) | |
| Board | 0.667 *** | 0.643 *** | 0.750 *** | 0.689 *** | 0.656 *** | 0.768 *** |
| (5.958) | (4.919) | (4.948) | (6.164) | (5.011) | (5.068) | |
| Top10 | −0.178 | −0.252 * | −0.475 *** | −0.174 | −0.247 * | −0.473 *** |
| (−1.438) | (−1.696) | (−2.599) | (−1.411) | (−1.661) | (−2.584) | |
| TobinQ | −0.050 *** | −0.060 *** | −0.052 ** | −0.049 *** | −0.060 *** | −0.050 ** |
| (−3.606) | (−3.217) | (−2.106) | (−3.570) | (−3.205) | (−2.023) | |
| Inst | 0.493 *** | 0.482 *** | 0.431 *** | 0.484 *** | 0.474 *** | 0.426 *** |
| (6.068) | (5.085) | (3.756) | (5.944) | (4.999) | (3.722) | |
| BY | −0.114 * | −0.108 | −0.149 | −0.118 * | −0.111 | −0.155 * |
| (−1.860) | (−1.467) | (−1.638) | (−1.928) | (−1.509) | (−1.706) | |
| Dual | −0.178 *** | −0.169 *** | −0.181 *** | −0.179 *** | −0.168 *** | −0.179 *** |
| (−5.350) | (−4.281) | (−3.795) | (−5.377) | (−4.267) | (−3.769) | |
| Roa | 0.263 | 0.283 | 0.257 | 0.268 | 0.269 | 0.227 |
| (0.706) | (0.647) | (0.502) | (0.719) | (0.615) | (0.443) | |
| Constants | −5.878 *** | −6.040 *** | −6.207 *** | −5.921 *** | −6.064 *** | −6.280 *** |
| (−13.347) | (−12.317) | (−10.825) | (−13.411) | (−12.320) | (−10.890) | |
| Year FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Ind FE | Yes | Yes | Yes | Yes | Yes | Yes |
| N | 3379 | 2496 | 1704 | 3379 | 2496 | 1704 |
| R 2 | 0.399 | 0.410 | 0.422 | 0.400 | 0.410 | 0.424 |
Notes: (1) regression coefficients above parentheses, t-values in parentheses; (2) * p < 0.1, ** p < 0.05, *** p < 0.01.
1. Hambrick, D.C.; Mason, P.A. Upper Echelons: The Organization as a Reflection of Its Top Managers. Acad. Manag. Rev.; 1984; 9, pp. 193-206. [DOI: https://dx.doi.org/10.2307/258434]
2. Marquis, C.; Tilcsik, A. Imprinting: Toward a Multilevel Theory. Acad. Manag. Ann.; 2013; 7, pp. 195-245. [DOI: https://dx.doi.org/10.5465/19416520.2013.766076]
3. Snihur, Y.; Zott, C. The Genesis and Metamorphosis of Novelty Imprints: How Business Model Innovation Emerges in Young Ventures. AMJ; 2020; 63, pp. 554-583. [DOI: https://dx.doi.org/10.5465/amj.2017.0706]
4. Dass, N.; Kini, O.; Nanda, V.; Onal, B.; Wang, J. Board Expertise: Do Directors from Related Industries Help Bridge the Information Gap?. Rev. Financ. Stud.; 2014; 27, pp. 1533-1592. [DOI: https://dx.doi.org/10.1093/rfs/hht071]
5. Schiederig, T.; Tietze, F.; Herstatt, C. Green Innovation in Technology and Innovation Management—An Exploratory Literature Review. RD Manag.; 2012; 42, pp. 180-192. [DOI: https://dx.doi.org/10.1111/j.1467-9310.2011.00672.x]
6. Ahmad, M.; Jiang, P.; Murshed, M.; Shehzad, K.; Akram, R.; Cui, L.; Khan, Z. Modelling the Dynamic Linkages between Eco-Innovation, Urbanization, Economic Growth and Ecological Footprints for G7 Countries: Does Financial Globalization Matter?. Sustain. Cities Soc.; 2021; 70, 102881. [DOI: https://dx.doi.org/10.1016/j.scs.2021.102881]
7. Horbach, J. Determinants of Environmental Innovation—New Evidence from German Panel Data Sources. Ecol. Econ.; 2008; 63, pp. 205-215. [DOI: https://dx.doi.org/10.1016/j.respol.2007.08.006]
8. Hu, Y.; Wang, C.; Zhang, X.; Wan, H.; Jiang, D. Financial Agglomeration and Regional Green Innovation Efficiency from the Perspective of Spatial Spillover. J. Innov. Knowl.; 2023; 8, 100434. [DOI: https://dx.doi.org/10.1016/j.jik.2023.100434]
9. Porter, M.E.; van der Linde, C. Toward a New Conception of the Environment-Competitiveness Relationship. J. Econ. Perspect.; 1995; 9, pp. 97-118. [DOI: https://dx.doi.org/10.1257/jep.9.4.97]
10. Chen, Y.S.; Lai, S.B.; Wen, C.T. The Influence of Green Innovation Performance on Corporate Advantage in Taiwan. J. Bus. Ethics; 2006; 67, pp. 331-339. [DOI: https://dx.doi.org/10.1007/s10551-006-9025-5]
11. Testa, F.; Iraldo, F.; Frey, M. The Effect of Environmental Regulation on Firms’ Competitive Performance: The Case of the Building & Construction Sector in Some EU Regions. J. Environ. Manag.; 2011; 92, pp. 2136-2144. [DOI: https://dx.doi.org/10.1016/j.jenvman.2011.03.039]
12. Zhou, C.; Lin, F. Does Global Diversification Promote or Hinder Green Innovation? Evidence from Chinese Multinational Corporations. Technovation; 2024; 129, 102905. [DOI: https://dx.doi.org/10.1016/j.technovation.2023.102905]
13. Tong, L.; Chiappetta Jabbour, C.J.; Belgacem, S.b.e.n.; Najam, H.; Abbas, J. Role of Environmental Regulations, Green Finance, and Investment in Green Technologies in Green Total Factor Productivity: Empirical Evidence from Asian Region. J. Clean. Prod.; 2022; 380, 134930. [DOI: https://dx.doi.org/10.1016/j.jclepro.2022.134930]
14. Wang, H.; Qi, S.; Zhou, C.; Zhou, J.; Huang, X. Green Credit Policy, Government Behavior and Green Innovation Quality of Enterprises. J. Clean. Prod.; 2022; 331, 129834. [DOI: https://dx.doi.org/10.1016/j.jclepro.2021.129834]
15. Geissdoerfer, M.; Vladimirova, D.; Evans, S. Sustainable Business Model Innovation: A Review. J. Clean. Prod.; 2018; 198, pp. 401-416. [DOI: https://dx.doi.org/10.1016/j.jclepro.2018.06.240]
16. Zhao, L.; Zhang, L.; Sun, J.; He, P. Can Public Participation Constraints Promote Green Technological Innovation of Chinese Enterprises? The Moderating Role of Government Environmental Regulatory Enforcement. Technol. Forecast. Soc. Change; 2022; 174, 121198. [DOI: https://dx.doi.org/10.1016/j.techfore.2021.121198]
17. Qi, X.; Wu, Z.; Xu, J.; Shan, B. Environmental Justice and Green Innovation: A Quasi-Natural Experiment Based on the Establishment of Environmental Courts in China. Ecol. Econ.; 2023; 205, 107700. [DOI: https://dx.doi.org/10.1016/j.ecolecon.2022.107700]
18. Peng, H.; Shen, N.; Ying, H.; Wang, Q. Can Environmental Regulation Directly Promote Green Innovation Behavior?—— Based on Situation of Industrial Agglomeration. J. Clean. Prod.; 2021; 314, 128044. [DOI: https://dx.doi.org/10.1016/j.jclepro.2021.128044]
19. Hu, H.; Qi, S.; Chen, Y. Using Green Technology for a Better Tomorrow: How Enterprises and Government Utilize the Carbon Trading System and Incentive Policies. China Econ. Rev.; 2023; 78, 101933. [DOI: https://dx.doi.org/10.1016/j.chieco.2023.101933]
20. Yan, Z.; Yu, Y.; Du, K.; Zhang, N. How Does Environmental Regulation Promote Green Technology Innovation? Evidence from China’s Total Emission Control Policy. Ecol. Econ.; 2024; 219, 108137. [DOI: https://dx.doi.org/10.1016/j.ecolecon.2024.108137]
21. Bu, M.; Qiao, Z.; Liu, B. Voluntary Environmental Regulation and Firm Innovation in China. Econ. Model.; 2020; 89, pp. 10-18. [DOI: https://dx.doi.org/10.1016/j.econmod.2019.12.020]
22.
23. Chen, X.; Yi, N.; Zhang, L.; Li, D. Does Institutional Pressure Foster Corporate Green Innovation? Evidence from China’s Top 100 Companies. J. Clean. Prod.; 2018; 188, pp. 304-311. [DOI: https://dx.doi.org/10.1016/j.jclepro.2018.03.257]
24. Zhu, B.; Nakaishi, T.; Kagawa, S. Neighbor’s Profit or Neighbor’s Beggar? Evidence from China’s Low Carbon Cities Pilot Scheme on Green Development. Energ. Polic.; 2024; 195, 114318. [DOI: https://dx.doi.org/10.1016/j.enpol.2024.114318]
25. Zhang, S.; Wu, Z.; He, Y.; Hao, Y. How Does the Green Credit Policy Affect the Technological Innovation of Enterprises? Evidence from China. Energy Econ.; 2022; 113, 106236. [DOI: https://dx.doi.org/10.1016/j.eneco.2022.106236]
26. Zhang, M.; Zhao, Y. Does Environmental Regulation Spur Innovation? Quasi-Natural Experiment in China. World Dev.; 2023; 168, 106261. [DOI: https://dx.doi.org/10.1016/j.worlddev.2023.106261]
27. Amore, M.D.; Bennedsen, M. Corporate Governance and Green Innovation. J. Environ. Econ. Manag.; 2016; 75, pp. 54-72. [DOI: https://dx.doi.org/10.1016/j.jeem.2015.11.003]
28. Berrone, P.; Fosfuri, A.; Gelabert, L.; Gomez-Mejia, L.R. Necessity as the Mother of “green” Inventions: Institutional Pressures and Environmental Innovations. Strategy Manag. J.; 2013; 34, pp. 891-909. [DOI: https://dx.doi.org/10.1002/smj.2041]
29. Ambec, S.; Lanoie, P. Does It Pay to Be Green? A Systematic Overview. Acad. Manag. Perspect.; 2008; 22, pp. 45-62. [DOI: https://dx.doi.org/10.5465/amp.2008.35590353]
30. Alkebsee, R.; Habib, A.; Li, J. Green Innovation and the Cost of Equity: Evidence from China. China Account. Financ. Rev.; 2023; 25, pp. 368-395. [DOI: https://dx.doi.org/10.1108/CAFR-06-2022-0075]
31. Zhang, Y.; Xing, C.; Wang, Y. Does Green Innovation Mitigate Financing Constraints? Evidence from China’s Private Enterprises. J. Clean. Prod.; 2020; 264, 121698. [DOI: https://dx.doi.org/10.1016/j.jclepro.2020.121698]
32. Rennings, K. Redefining Innovation—Eco-Innovation Research and the Contribution from Ecological Economics. Ecol. Econ.; 2000; 32, pp. 319-332. [DOI: https://dx.doi.org/10.1016/S0921-8009(99)00112-3]
33. Hao, J.; He, F. Corporate Social Responsibility (CSR) Performance and Green Innovation: Evidence from China. Financ. Res. Lett.; 2022; 48, 102889. [DOI: https://dx.doi.org/10.1016/j.frl.2022.102889]
34. Wen, W.; Qiao, F.; He, Y. Strategic Deviation and Corporate Green Innovation. Financ. Res. Lett.; 2023; 54, 103806. [DOI: https://dx.doi.org/10.1016/j.frl.2023.103806]
35. Jiang, L.; Bai, Y. Strategic or Substantive Innovation?—The Impact of Institutional Investors’ Site Visits on Green Innovation Evidence from China. Technol. Soc.; 2022; 68, 101904. [DOI: https://dx.doi.org/10.1016/j.techsoc.2022.101904]
36. Zhang, C.; Zhou, B.; Tian, X. Political Connections and Green Innovation: The Role of a Corporate Entrepreneurship Strategy in State-Owned Enterprises. J. Bus. Res.; 2022; 146, pp. 375-384. [DOI: https://dx.doi.org/10.1016/j.jbusres.2022.03.084]
37. Wang, M.; Li, Y.; Li, J.; Wang, Z. Green Process Innovation, Green Product Innovation and Its Economic Performance Improvement Paths: A Survey and Structural Model. J. Environ. Manag.; 2021; 297, 113282. [DOI: https://dx.doi.org/10.1016/j.jenvman.2021.113282]
38. Singh, S.K.; Del Giudice, M.; Chiappetta Jabbour, C.J.; Latan, H.; Sohal, A.S. Stakeholder Pressure, Green Innovation, and Performance in Small and Medium-Sized Enterprises: The Role of Green Dynamic Capabilities. Bus. Strategy Environ.; 2022; 31, pp. 500-514. [DOI: https://dx.doi.org/10.1002/bse.2906]
39. Zhang, D.; Li, B.; Fu, Q.; Tang, W.; Fatima, T. Impact of CEOs’ Environmental Experience on Corporate Green Innovation. Corp. Soc. Responsib. Environ. Manag.; 2025; 32, pp. 3290-3312. [DOI: https://dx.doi.org/10.1002/csr.3087]
40. Zhang, X.; Sun, W. The Role of Interlocking Directorates and Managerial Characteristics on Corporate Green Innovation. Financ. Res. Lett.; 2025; 74, 106818. [DOI: https://dx.doi.org/10.1016/j.frl.2025.106818]
41. Le, Y.; Zhang, X. The Driving Path of Green Entrepreneurial Orientation from a Configuration Perspective. J. Environ. Manag.; 2025; 380, 125064. [DOI: https://dx.doi.org/10.1016/j.jenvman.2025.125064] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/40121984]
42. Du, J.; Zhu, R.; Ye, Q. Managers’ Overconfidence, Institutional Investors’ Shareholding, and Corporate ESG Performance. Financ. Res. Lett.; 2025; 72, 106594. [DOI: https://dx.doi.org/10.1016/j.frl.2024.106594]
43. He, K.; Chen, W.; Zhang, L. Senior management’s academic experience and corporate green innovation. Technol. Forecast. Soc. Change; 2021; 166, 120664. [DOI: https://dx.doi.org/10.1016/j.techfore.2021.120664]
44. Kong, D.; Zhao, Z. Overseas Exposures, Global Events, and Mutual Fund Performance. Int. Rev. Econ. Financ.; 2024; 91, pp. 848-863. [DOI: https://dx.doi.org/10.1016/j.iref.2024.01.055]
45. Javed, M.; Wang, F.; Usman, M.; Ali Gull, A.; Uz Zaman, Q. Female CEOs and Green Innovation. J. Bus. Res.; 2023; 157, 113515. [DOI: https://dx.doi.org/10.1016/j.jbusres.2022.113515]
46. Galbreath, J. Drivers of Green Innovations: The Impact of Export Intensity, Women Leaders, and Absorptive Capacity. J. Bus. Ethics; 2019; 158, pp. 47-61. [DOI: https://dx.doi.org/10.1007/s10551-017-3715-z]
47. Withers, M.C.; Fitza, M.A. Do board chairs matter? The influence of board chairs on firm performance. Strategy Manag. J.; 2017; 38, pp. 1343-1355. [DOI: https://dx.doi.org/10.1002/smj.2587]
48. Hawn, O.; Ioannou, I. Mind the Gap: The Interplay Between External and Internal Actions in the Case of Corporate Social Responsibility. Strategy Manag. J.; 2016; 37, pp. 2569-2588. [DOI: https://dx.doi.org/10.1002/smj.2464]
49. Walls, J.L.; Berrone, P. The Power of One to Make a Difference: How Informal and Formal CEO Power Affect Environmental Sustainability. J. Bus. Ethics; 2017; 145, pp. 293-308. [DOI: https://dx.doi.org/10.1007/s10551-015-2902-z]
50. Delmas, M.A.; Montes-Sancho, M.J. An Institutional Perspective on the Diffusion of International Management System Standards: The Case of the Environmental Management Standard ISO 14001. Bus. Ethics Q.; 2011; 21, pp. 103-132. [DOI: https://dx.doi.org/10.5840/beq20112115]
51. Eccles, R.G.; Ioannou, I.; Serafeim, G. The Impact of Corporate Sustainability on Organizational Processes. Manag. Sci.; 2014; 60, pp. 2835-2857. [DOI: https://dx.doi.org/10.1287/mnsc.2014.1984]
52. Adams, R.B.; Hermalin, B.E.; Weisbach, M.S. The Role of Boards of Directors in Corporate Governance: A Conceptual Framework and Survey. J. Econ. Lit.; 2010; 48, pp. 58-107. [DOI: https://dx.doi.org/10.1257/jel.48.1.58]
53. Finkelstein, S. Power in Top Management Teams: Dimensions, Measurement, and Validation. Acad. Manag. J.; 1992; 35, pp. 505-538. [DOI: https://dx.doi.org/10.2307/256485] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/10120413]
54. Dyck, A.; Lins, K.V.; Roth, L.; Wagner, H.F. Do Institutional Investors Drive Corporate Social Responsibility?. J. Financ. Econ.; 2019; 131, pp. 693-714. [DOI: https://dx.doi.org/10.1016/j.jfineco.2018.08.013]
55. Aguilera-Caracuel, J.; Ortiz-de-Mandojana, N. Green Innovation and Financial Performance: An Institutional Approach. Organ. Environ.; 2013; 26, pp. 365-385. [DOI: https://dx.doi.org/10.1177/1086026613507931]
56. Wernerfelt, B. A Resource-Based View of the Firm. Strategy Manag. J.; 1984; 5, pp. 171-180. [DOI: https://dx.doi.org/10.1002/smj.4250050207]
57. Darnall, N.; Henriques, I.; Sadorsky, P. Do Environmental Management Systems Improve Business Performance in an International Setting?. J. Int. Manag.; 2008; 14, pp. 364-376. [DOI: https://dx.doi.org/10.1016/j.intman.2007.09.006]
58. Donaldson, T.; Preston, L.E. The Stakeholder Theory of the Corporation: Concepts, Evidence, and Implications. Acad. Manag. Rev.; 1995; 20, pp. 65-91. [DOI: https://dx.doi.org/10.2307/258887]
59. Hart, S.L. A Natural-Resource-Based View of the Firm. Acad. Manag. Rev.; 1995; 20, pp. 986-1014. [DOI: https://dx.doi.org/10.2307/258963]
60. North, D.C. Institutions, Institutional Change and Economic Performance; Cambridge University Press: Cambridge, UK, 1990.
61. Vafeas, N. Board Meeting Frequency and Firm Performance. J. Financ. Econ.; 1999; 53, pp. 113-142. [DOI: https://dx.doi.org/10.1016/S0304-405X(99)00018-5]
62. Aureli, S.; Del Baldo, M.; Lombardi, R.; Nappo, F. Nonfinancial Reporting Regulation and Challenges in Sustainability Disclosure and Corporate Governance Practices. Bus. Strategy Environ.; 2020; 29, pp. 2392-2403. [DOI: https://dx.doi.org/10.1002/bse.2509]
63. Nahapiet, J.; Ghoshal, S. Social Capital, Intellectual Capital, and the Organizational Advantage. Acad. Manag. Rev.; 1998; 23, 242. [DOI: https://dx.doi.org/10.2307/259373]
64. Pástor, Ľ.; Stambaugh, R.F.; Taylor, L.A. Sustainable Investing in Equilibrium. J. Financ. Econ.; 2021; 142, pp. 550-571. [DOI: https://dx.doi.org/10.1016/j.jfineco.2020.12.011]
65. Hong, H.; Kacperczyk, M. The Price of Sin: The Effects of Social Norms on Markets. J. Financ. Econ.; 2009; 93, pp. 15-36. [DOI: https://dx.doi.org/10.1016/j.jfineco.2008.09.001]
66. Gillan, S.L.; Starks, L.T. Corporate Governance Proposals and Shareholder Activism: The Role of Institutional Investors. J. Financ. Econ.; 2000; 57, pp. 275-305. [DOI: https://dx.doi.org/10.1016/S0304-405X(00)00058-1]
67. Ocasio, W. Towards an Attention-Based View of the Firm. Strategy Manag. J.; 1997; 18, pp. 187-206. [DOI: https://dx.doi.org/10.1002/(SICI)1097-0266(199707)18:1+<187::AID-SMJ936>3.0.CO;2-K]
68. Sharma, S.; Vredenburg, H. Proactive Corporate Environmental Strategy and the Development of Competitively Valuable Organizational Capabilities. Strategy Manag. J.; 1998; 19, pp. 729-753. [DOI: https://dx.doi.org/10.1002/(SICI)1097-0266(199808)19:8<729::AID-SMJ967>3.0.CO;2-4]
69. Bansal, P.; Roth, K. Why Companies Go Green: A Model of Ecological Responsiveness. Acad. Manag. J.; 2000; 43, pp. 717-736. [DOI: https://dx.doi.org/10.2307/1556363]
70. Slawinski, N.; Bansal, P. Short on Time: Intertemporal Tensions in Business Sustainability. Organ. Sci.; 2015; 26, pp. 531-549. [DOI: https://dx.doi.org/10.1287/orsc.2014.0960]
71. Aghion, P.; Van Reenen, J.; Zingales, L. Innovation and Institutional Ownership. Am. Econ. Rev.; 2013; 103, pp. 277-304. [DOI: https://dx.doi.org/10.1257/aer.103.1.277]
72. Hart, S.L.; Dowell, G. A Natural-Resource-Based View of the Firm: Fifteen Years After. J. Manag.; 2011; 37, pp. 1464-1479. [DOI: https://dx.doi.org/10.1177/0149206310390219]
73. Flammer, C. Corporate Green Bonds. J. Financ. Econ.; 2019; 142, pp. 499-516. [DOI: https://dx.doi.org/10.1016/j.jfineco.2021.01.010]
74. Dechezleprêtre, A.; Neumayer, E.; Perkins, R. Environmental regulation and the cross-border diffusion of new technology: Evidence from automobile patents. Res. Polic.; 2015; 44, pp. 244-257. [DOI: https://dx.doi.org/10.1016/j.respol.2014.07.017]
75. Lian, G.; Xu, A.; Zhu, Y. Substantive green innovation or symbolic green innovation? The impact of ER on enterprise green innovation based on the dual moderating effects. J. Innov. Knowl.; 2022; 7, 100203. [DOI: https://dx.doi.org/10.1016/j.jik.2022.100203]
76. Huang, R.; Wei, J. Does CEOs’ Green Experience Affect Environmental Corporate Social Responsibility? Evidence from China. Econ. Anal. Policy; 2023; 79, pp. 205-231. [DOI: https://dx.doi.org/10.1016/j.eap.2023.06.012]
77. Tran, H.; Turkiela, J. The Powers That Be: Concentration of Authority within the Board of Directors and Variability in Firm Performance. J. Corp. Financ.; 2020; 60, 101537. [DOI: https://dx.doi.org/10.1016/j.jcorpfin.2019.101537]
78. Luo, X.R.; Wang, D.; Zhang, J. Whose Call to Answer: Institutional Complexity and Firms’ CSR Reporting. AMJ; 2017; 60, pp. 321-344. [DOI: https://dx.doi.org/10.5465/amj.2014.0847]
79. Barney, J. Firm Resources and Sustained Competitive Advantage. J. Manag.; 1991; 17, pp. 99-120. [DOI: https://dx.doi.org/10.1177/014920639101700108]
80. Vanacker, T.; Collewaert, V.; Zahra, S.A. Slack Resources, Firm Performance, and the Institutional Context: Evidence from Privately Held European Firms. Strategy Manag. J.; 2016; 38, pp. 1305-1326. [DOI: https://dx.doi.org/10.1002/smj.2583]
81. Hart, S.L.; Ahuja, G. Does It Pay to Be Green? An Empirical Examination of the Relationship Between Emission Reduction and Firm Performance. Bus. Strategy Environ.; 1996; 5, pp. 30-37. [DOI: https://dx.doi.org/10.1002/(SICI)1099-0836(199603)5:1<30::AID-BSE38>3.0.CO;2-Q]
82. Hillman, A.J.; Keim, G.D.; Schuler, D. Corporate Political Activity: A Review and Research Agenda. J. Manag.; 2004; 30, pp. 837-857. [DOI: https://dx.doi.org/10.1016/j.jm.2004.06.003]
83. Waddock, S.; Graves, S. The Corporate Social Performance-Financial Performance Link. Strategy Manag. J.; 1997; 18, pp. 303-319. [DOI: https://dx.doi.org/10.1002/(SICI)1097-0266(199704)18:4<303::AID-SMJ869>3.0.CO;2-G]
84. Marquis, C.; Qian, C. Corporate Social Responsibility Reporting in China: Symbol or Substance?. Organ. Sci.; 2014; 25, pp. 127-148. [DOI: https://dx.doi.org/10.1287/orsc.2013.0837]
85. Scott, W.R. Institutions and Organizations; Sage Publications: Thousand Oaks, CA, USA, 1995.
86. Zhou, Y.; Zhu, S.; He, C. How Do Environmental Regulations Affect Industrial Dynamics? Evidence from China’s Pollution-Intensive Industries. Habitat Int.; 2017; 60, pp. 10-18. [DOI: https://dx.doi.org/10.1016/j.habitatint.2016.12.002]
87. Brandt, L.; Ma, D.; Rawski, T.G. From Divergence to Convergence: Reevaluating the History behind China’s Economic Boom. J. Econ. Lit.; 2014; 52, pp. 45-123. [DOI: https://dx.doi.org/10.1257/jel.52.1.45]
88. Fan, G.; Wang, X.; Zhang, L. Annual Report 2000 Marketization Index for China’s Provinces. China World Econ.; 2001; 5, pp. 1-12.
89. Jensen, M.C. Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers. Am. Econ. Rev.; 1986; 76, pp. 323-329.
90. Gam, Y.K.; Gupta, P.; Im, J.; Shin, H. Evasive shareholder meetings and corporate fraud. J. Corp. Financ.; 2021; 66, 101807. [DOI: https://dx.doi.org/10.1016/j.jcorpfin.2020.101807]
91. Barko, T.; Cremers, M.; Renneboog, L. Shareholder Engagement on Environmental, Social, and Governance Performance. J. Bus. Ethics; 2022; 180, pp. 777-812. [DOI: https://dx.doi.org/10.1007/s10551-021-04850-z]
92. Dixon-Fowler, H.R.; Ellstrand, A.E.; Johnson, J.L. The Role of Board Environmental Committees in Corporate Environmental Performance. J. Bus. Ethics; 2017; 140, pp. 423-438. [DOI: https://dx.doi.org/10.1007/s10551-015-2664-7]
93. Tian, J.; Dong, Y.; Vagnani, G.; Liu, P. Green Innovation and the Stock Market Value of Heavily Polluting Firms: The Role of Environmental Compliance Costs and Technological Collaboration. Bus. Strategy Environ.; 2023; 32, pp. 4938-4953. [DOI: https://dx.doi.org/10.1002/bse.3401]
94. Bao, R.; Liu, T. How Does Government Attention Matter in Air Pollution Control? Evidence from Government Annual Reports. Resour. Conserv. Recycl.; 2022; 185, 106435. [DOI: https://dx.doi.org/10.1016/j.resconrec.2022.106435]
95. Lee, K.-H.; Min, B. Green R&D for Eco-Innovation and Its Impact on Carbon Emissions and Firm Performance. J. Clean. Prod.; 2015; 108, pp. 534-542. [DOI: https://dx.doi.org/10.1016/j.jclepro.2015.05.114]
96. Diamond, D.W. Reputation Acquisition in Debt Markets. J. Political Econ.; 1989; 97, pp. 828-862. [DOI: https://dx.doi.org/10.1086/261630]
97. Hering, L.; Poncet, S. Environmental Policy and Exports: Evidence from Chinese Cities. J. Environ. Econ. Manag.; 2014; 68, pp. 296-318. [DOI: https://dx.doi.org/10.1016/j.jeem.2014.06.005]
98. Aragón-Correa, J.A.; Sharma, S. A Contingent Resource-Based View of Proactive Corporate Environmental Strategy. Acad. Manag. Rev.; 2003; 28, pp. 71-88. [DOI: https://dx.doi.org/10.5465/amr.2003.8925233]
99. DiMaggio, P.J.; Powell, W.W. The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields. Am. Sociol. Rev.; 1983; 48, pp. 147-160. [DOI: https://dx.doi.org/10.2307/2095101]
100. Pfeffer, J.; Salancik, G.R. The External Control of Organizations: A Resource Dependence Perspective; Stanford University Press: Redwood City, CA, USA, 2003.
101. Humphery-Jenner, M.; Sautner, Z.; Suchard, J.-A. Cross-border mergers and acquisitions: The role of private equity firms. Strategy Manag. J.; 2017; 38, pp. 1688-1700. [DOI: https://dx.doi.org/10.1002/smj.2623]
102. Lin, L.-W. State Ownership and Corporate Governance in China: An Executive Career Approach. Columbia Bus. Law Rev.; 2014; 2013, 743. [DOI: https://dx.doi.org/10.7916/cblr.v2013i3.2873]
103. Westphal, J.D.; Fredrickson, J.W. Who Directs Strategic Change? Director Experience, the Selection of New CEOs, and Change in Corporate Strategy. Strategy Manag. J.; 2001; 22, pp. 1113-1137. [DOI: https://dx.doi.org/10.1002/smj.205]
104. Hillman, A.J.; Cannella, A.A.; Paetzold, R.L. The Resource Dependence Role of Corporate Directors: Strategic Adaptation of Board Composition in Response to Environmental Change. J. Manag. Stud.; 2000; 37, pp. 235-256. [DOI: https://dx.doi.org/10.1111/1467-6486.00179]
105. Hottenrott, H.; Peters, B. Innovative Capability and Financing Constraints for Innovation: More Money, More Innovation?. Rev. Econ. Stat.; 2012; 94, pp. 1126-1142. [DOI: https://dx.doi.org/10.1162/REST_a_00227]
106. Sirmon, D.G.; Hitt, M.A.; Ireland, R.D. Resource Orchestration to Create Competitive Advantage. J. Manag.; 2011; 37, pp. 1390-1412. [DOI: https://dx.doi.org/10.1177/0149206310385695]
107. Dessein, W. Incomplete Contracts and Firm Boundaries: New Directions. J. Law Econ. Organ.; 2014; 30, pp. i13-i36. [DOI: https://dx.doi.org/10.1093/jleo/ews044]
108. Mansour, M.; Abu-Allan, A.J.; Alshdaifat, S.M. Board Effectiveness and Carbon Emission Disclosure: Evidence from ASEAN Countries. Discov. Sustain.; 2025; 6, 604. [DOI: https://dx.doi.org/10.1007/s43621-025-01405-4]
109. Westphal, J.D.; Bednar, M.K. The Symbolic Management of Strategic Change: Sensegiving via Framing and Decoupling. Acad. Manag. J.; 2005; 49, pp. 1173-1193. [DOI: https://dx.doi.org/10.5465/amj.2005.19573104]
110. Haynes, K.T.; Hillman, A. The Effect of Board Capital and CEO Power on Strategic Change. Strategy Manag. J.; 2010; 31, pp. 1145-1163. [DOI: https://dx.doi.org/10.1002/smj.859]
111. Brookes, M. Varieties of Power in Transnational Labor Alliances: An Analysis of Workers’ Structural, Institutional, and Coalitional Power in the Global Economy. Labor Stud. J.; 2013; 38, pp. 181-200. [DOI: https://dx.doi.org/10.1177/0160449X13500147]
112. Benton, R.A.; You, J. Governance Monitors or Market Rebels? Heterogeneity in Shareholder Activism. Strategy Organ.; 2019; 17, pp. 329-351. [DOI: https://dx.doi.org/10.1177/1476127018776482]
113. Xu, H.; Lin, K.; Wang, H. Does Local Green Governance Promote Corporate Green Innovation? A New Perspective from Green Officials. Empir. Econ.; 2025; 68, pp. 1861-1892. [DOI: https://dx.doi.org/10.1007/s00181-024-02682-0]
114. Tan, M. CEO Power and Open Innovation: Evidence from China. Eur. J. Innov. Manag.; 2025; 28, pp. 403-425. [DOI: https://dx.doi.org/10.1108/EJIM-04-2023-0298]
115. Haldar, M.; Nath, S.; Sengupta, D. The Race for Net-Zero: Assessing the Role of Energy Efficiency and Conversion Technologies. Int. J. Appl. Eng. Res.; 2024; 19, pp. 231-240.
116. Liu, M.; Zhao, J.; Liu, H. Digital Transformation, Employee and Executive Compensation, and Sustained Green Innovation. Int. Rev. Financ. Anal.; 2025; 97, 103873. [DOI: https://dx.doi.org/10.1016/j.irfa.2024.103873]
117. Hedman, J.; Henningsson, S. Developing Ecological Sustainability: A Green IS Response Model. Inf. Syst. J.; 2016; 26, pp. 259-287. [DOI: https://dx.doi.org/10.1111/isj.12095]
118. You, J. Trust and Corruption. The Oxford Handbook of Social and Political Trust; Uslaner, E.M. Oxford University Press: New York, NY, USA, 2017.
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.