Next Article in Journal
Eco-Driving Optimization with the Traffic Light Countdown Timer in Vehicle Navigation and Its Impact on Fuel Consumption
Previous Article in Journal
New Urbanization and Low-Carbon Energy Transition in China: Coupling Coordination, Spatial–Temporal Differentiation, and Spatial Effects
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Leveraging Board Experience Diversity to Enhance Corporate Green Technological Innovation

School of Business, Macau University of Science and Technology, Macao, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(8), 3351; https://doi.org/10.3390/su17083351
Submission received: 14 February 2025 / Revised: 27 March 2025 / Accepted: 1 April 2025 / Published: 9 April 2025

Abstract

This study examines the role of board experience diversity in fostering corporate green technological innovation (CGTI), focusing on the moderating effects of absorptive capacity and director network location. Integrating upper echelons theory with absorptive capacity theory, we explore how board experience diversity enhances strategic decision-making and innovation. We hypothesize that board experience diversity improves CGTI by broadening cognitive perspectives. We also examine the moderating effect of absorptive capacity on the relationship between board experience diversity and innovation. We examine Chinese A-share listing firms, finding that board experience diversity positively affects CGTI, and absorptive capacity strengthens this effect. Additionally, we show that director network location, proxied by centrality in inter-board networks, not only strengthens the association between board experience diversity and innovation but also affects innovation. Furthermore, we conducted heterogeneity and mechanism tests, confirming the robustness of these relationships. These findings contribute to the literature on corporate governance and sustainability by emphasizing the roles of board experience diversity, absorptive capacity, and network position in driving CGTI.

1. Introduction

In the current wave of sustainable development, enterprises are encountering unprecedented environmental pressures and challenges. The intensification of climate change, resource depletion, and the increasing vulnerability of ecosystems have compelled governments worldwide to implement more stringent environmental regulations and policies, necessitating a re-evaluation of corporate production and operational models [1,2]. The heightened global emphasis on sustainability has rendered environmental performance within global supply chains a critical component of corporate reputation and competitiveness. Corporate green technological innovation (CGTI) assumes particular significance in this context. CGTI serves not only as a pivotal mechanism for fulfilling corporate social responsibility and achieving sustainable development but also as a strategic initiative for enhancing core competitiveness and penetrating new markets [3,4,5]. However, CGTI is frequently associated with substantial research and development costs, technological risks, and extended return on investment periods [6]. This scenario demands that firms engage in scientifically grounded strategic planning, emphasizing leadership and the accumulation of managerial experience. Consequently, conducting in-depth research and optimizing strategic decision-making mechanisms in CGTI is of paramount importance for advancing corporate sustainability objectives [7].
CGTI is influenced by a multitude of factors, which are typically categorized into internal and external determinants. Internal factors encompass a firm’s resource allocation [8], research and development (R&D) investment [9], technological capabilities, organizational culture, and strategic decisions made by top management [10,11,12]. External factors include government policies, market demand, competitive pressure, and the ecological environment [13]. Existing research has primarily focused on how firms drive CGTI by integrating internal and external resources, acquiring new technologies, and establishing effective innovation incentive mechanisms [14]. For instance, R&D investment, technological collaboration networks, and alignment with environmental regulations are considered critical drivers of CGTI. However, the impact of board experience diversity on CGTI remains underexplored, particularly at the theoretical level, with a lack of in-depth examination of how this factor influences corporate decision-making processes [15]. Theoretically, board experience diversity is posited to provide more diversified decision support, especially in the context of complex and highly uncertain CGTI endeavors. Having board members with diverse backgrounds not only provides varied expertise and perspectives but also aids firms in identifying potential innovation opportunities and effectively managing risks. For example, board experience diversity can foster the development of more comprehensive and innovative strategies in CGTI, thereby enhancing competitive advantage in green technologies [16]. Nevertheless, research centered on demographic diversity often characterizes enhanced oversight (i.e., governance) as a key mechanism through which board experience diversity impacts firm outcomes [17,18]. Conversely, other studies caution that stringent oversight may impede corporate exploration and argue that “weak governance is the necessary evil to stimulate innovation” [19,20]. Therefore, considering the existing divergent findings on the role of board experience diversity, it remains unclear whether a diverse board in terms of experience facilitates CGTI.
While board experience diversity plays a pivotal role in driving CGTI, its effectiveness is contingent upon other factors [21]. This study introduces absorptive capacity and director network location as moderating variables to elucidate the underlying mechanisms. While board experience heterogeneity provides resources, absorptive capacity theory highlights a firm’s capacities to acquire, maintain, and apply external knowledge [22]. It shows how firms build upon available resources, assimilate new technologies, and respond to evolving environments, thereby enhancing the contribution of board experience diversity to the realization of CGTI [23]. The network location of a director is important as it meaningfully magnifies the impact of board experience diversity. Central directors in inter-board networks gain access to vital external information and influential organizations and facilitate knowledge transfer; they are essential for developing CGTI. Therefore, directors’ positions in networks amplify the effect of board experience diversity on firms’ innovation activities, especially in the area of sustainability and green technologies.
This study not only addresses the theoretical gap between board experience diversity and CGTI but also offers a novel perspective on the current field of environmental technology innovation. Firstly, the traditional CGTI literature typically focuses on internal and external resources, technology integration, and R&D investment, with limited attention given to governance structures, particularly at the board level [24]. Within corporate governance theory, the role of board experience diversity has not been systematically incorporated into the research framework promoting CGTI. By integrating board experience diversity into CGTI, this study provides theoretical value in exploring the role of executives in driving CGTI. Unlike conventional research, this study emphasizes the impact of board experience diversity on CGTI, particularly under the moderating effect of absorptive capacity. Traditional theories suggest that board experience diversity enhances decision-making diversity but often overlook how this diversity interacts with internal firm capabilities, such as absorptive capacity, to foster innovation [25]. This study fills this gap by introducing absorptive capacity as a moderating variable, revealing how a firm’s absorptive capacity influences the effect of board experience diversity on CGTI. From a theoretical innovation perspective, while absorptive capacity theory initially focused on how firms respond to external changes and sustain innovation in dynamic environments, it seldom addressed the roles of board decision-makers [26]. This study contributes to the theory by incorporating board experience diversity into the absorptive capacity framework, elucidating its role in the decision-making processes of CGTI. Furthermore, this study also highlights the importance of director network location, suggesting that the centrality of board members within inter-board networks can amplify the effects of board experience diversity. This is crucial because access to diverse sources of information and expertise enhances a firm’s capacity to capitalize on board experience diversity, driving CGTI. Directors’ network positions serve as vital conduits for knowledge transfer, enabling companies to harness a broader range of insights and opportunities that are essential for sustainable innovation.

2. Theoretical Framework

2.1. Board Experience Diversity and Its Role in Driving Corporate Green Technological Innovation

CGTI has become an important strategy for sustainable development in the context of rapid changes in the modern business environment. The board of directors is the highest decision-making body in an organization and is key in making decisions on resource allocation and innovation strategies [27]. Above all, a wide variety of experience among board members is a primary contributor to a firm’s CGTI capacity. A diverse board renders multifaceted support for CGTI through cognitive, resource network, and strategic perspectives.
Upper echelons theory postulates that top executives’ experiences and cognitive biases impact their interpretations and choices, which, in turn, dictate organizational strategies and innovativeness [28]. Having certain members on the board from diverse levels of professions, higher education, and industry brings different cognitive frameworks to the table, which assist the organization in dealing with environmental complexity while exposing itself to opportunities. For instance, technically knowledgeable directors assess the feasibility of technological innovation, managerial directors coordinate firm resources, and policy experts on a board assist the firm in capturing the value of opportunities that result from dynamic regulatory contexts. This cognitive diversity allows for a larger set of possibilities to be considered, helps to overcome path dependency, and fosters organizational agility in response to environmental challenges.
According to resource dependence theory, having a heterogeneous board in terms of experience broadens a firm’s access to external resources and schemas. Diversity of experience opens doors to external relationships, which lead to partnerships with others, such as institutions of higher learning, research agencies, policymakers, and investors. In CGTI, where the long development cycles and the high uncertainty of market acceptance require a substantial amount of support, this acquisition of external resources has been particularly important. Directors with international experience, for example, can help companies align with global green technology standards, while those with technical backgrounds can facilitate partnerships with research institutions [29]. Access to firm resources not only reduces risks in innovation but also enhances a firm’s competitive position in green technology markets. In addition, diversity of experience adds strategic guidance by integrating different insights into the process of setting innovation targets. For instance, a diverse board is better positioned to weigh competing priorities across many axes, including economic feasibility, technological possibility, and societal consequences [30]. Such a balancing strategy not only maximizes the development space of low-carbon technologies but also reduces the risk of excessive investment in a single technology pathway. In this way, directors with different functional expertise, such as in markets, management, and technology for renewable energy technologies, will jointly ensure a balanced and all-encompassing innovation strategy.
However, board experience diversity is not without challenges. Cognitive differences and conflicting priorities among directors may slow decision-making and reduce efficiency, particularly in determining resource allocation and the prioritization of innovation initiatives [31]. Furthermore, the benefits of diversity cannot be realized without organizational mechanisms that integrate and transform these diverse perspectives and resources into actionable outcomes. As such, relying solely on the external advantages of board experience diversity may not suffice for CGTI, which requires stronger internal mechanisms to bridge the gap between strategy and execution.

2.2. Absorptive Capacity as an Organizational Mechanism Enabling Innovation

While board experience diversity significantly supports CGTI, its effectiveness often hinges on the organization’s internal capabilities. Beyond the diversity of perspectives and access to resources, organizations must possess the ability to integrate these advantages and adapt to dynamic external environments [32,33]. The absorptive capacity framework, comprising sensing, integrating, and reconfiguring dimensions, provides a robust theoretical lens to understand how organizations achieve these objectives and realize CGTI outcomes.
The concept of absorptive capacity emerges initially through a firm’s ability to identify environmental changes. Thus, organizations are now able to identify changes and transitions in market demand, regulatory policies, and technological advancements and eventually convert them into meaningful innovation opportunities [34]. Whereas a diverse board is rich in inputs and external perspectives, absorptive capacity is the organization’s relevance filter that ensures such information is prioritized and synthesized into relevant innovation objectives. Systemic sensing mechanisms enhance the strategic potential of the board’s experience diversity by translating external knowledge and understanding into exploratory and prognostic environmental innovation strategies [35].
The integrating dimension of absorptive capacity is vital in allowing coherent innovation strategies by processing the spectrum of resources and insights the board contributes [36]. The diversity of a board widens its constituents, both internally and externally, providing the board with mutualized resources, such as positional information, technical know-how, policy links, and market access, that might otherwise be siloed and disconnected. Absorptive capacity, acting as a connective tissue, allows better allocation of resources and unity of efforts across fields. That said, a company may need to choose between competing research and development projects or adjust current production facilities to meet updated environmental codes [37]. These resource-intensive projects take on the organization’s strategic goals, and the integration capabilities ensure the effective execution of CGTI initiatives.
Absorptive capacity also underpins the reconfiguring processes necessary for adapting to rapidly evolving environments. CGTI often involves significant uncertainty, such as shifts in regulatory frameworks, changes in consumer preferences, or disruptions in technological trajectories [38]. Reconfiguring capabilities allows firms to realign resources and adapt organizational structures to remain competitive in these conditions. For instance, when faced with stricter carbon emission regulations, firms with robust absorptive capacity can quickly adjust production processes, incorporate low-carbon technologies, and mitigate compliance risks. While board experience diversity provides high-level guidance on strategic adjustments, absorptive capacity operationalizes these adjustments, bridging the gap between strategic vision and implementation [39].
Moreover, the relationship between absorptive capacity and upper echelons theory further emphasizes organizational mechanisms enabling CGTI. The diversity of a group of directors brings cognitive frameworks and strategic insights, but absorptive capacity facilitates the translation of these contributions into tangible outcomes [40]. In that regard, our interaction pinpoints how the harmonization of governance structures with internal mechanisms is needed to address this. Board experience heterogeneity and absorptive capacity recruitment can jointly improve a firm’s ability to cope with the complex domain of green tech innovation.
The relationship between board experience diversity and absorptive capacity aids CGTI in terms of synergy. Diversity allows the firm to obtain and interpret external resources and insights, while absorptive capacity offers the organizational capabilities to adapt and execute strategies based on these resources [41]. Integrating governance mechanisms with internal capabilities enables companies to respond effectively to external risks and leverage opportunities for sustainable development through environmental-related technological innovation.

3. Hypothesis Development

3.1. Board Experience Diversity as a Catalyst for Environmental Technological Innovation

Corporate green technological innovation (CGTI) is defined as an enterprise-specific study that addresses environmentally friendly risks and sustainable growth by creating technical amendments. Successfully implementing CGTI will require not just large tech spend and external pressure; it will also take guidance and coordination of the type that the board of directors can provide [42]. As the primary governing body of a firm, the board members’ diverse professional backgrounds propel a company’s innovation outcomes. Based on theoretical perspectives and existing studies [43,44,45], diverse board member experience is expected to positively affect CGTI through various channels.
First, from the perspective of upper echelons theory, board experience diversity enhances decision-making by enriching the cognitive frameworks available to the organization. A board with varied professional, technical, and industrial backgrounds brings a broader understanding of the external environment, which allows for a more nuanced approach to strategic decisions [46]. Diverse boards are better equipped to assess the risks and opportunities in CGTI, leading to more balanced and rational evaluations. For instance, directors with technical expertise may focus on the technical feasibility of green technologies, while those with managerial or financial expertise might prioritize resource efficiency and economic returns [47].
Second, according to resource dependence theory, board experience diversity facilitates access to critical external resources necessary for CGTI, including capital, technology, and favorable policies [48]. Directors from diverse backgrounds expand organizational networks, effectively linking firms to vital external stakeholders. Politically experienced directors can help secure policy incentives for green technology, while technically skilled directors foster collaborations with research institutions [49]. Such connections not only lower innovation costs but also significantly support technology development and commercialization.
Third, board experience diversity shapes firms’ strategic orientation by encouraging inclusive decision-making and long-term strategic thinking, both essential for CGTI. Given the inherent risks and prolonged timelines of CGTI, a diverse board helps balance immediate financial objectives with long-term sustainability goals [15]. For instance, directors experienced in environmental policy highlight social and ecological benefits, whereas those with market expertise emphasize commercial viability and adaptability. Integrating these varied perspectives enhances strategic balance, enabling firms to compete effectively in green innovation markets. Based on the above theoretical reasoning, the following hypothesis is proposed:
H1: 
Board experience diversity positively influences corporate environmental technological innovation.

3.2. Unlocking the Potential of Board Experience Diversity for Corporate Green Technological Innovation Through Absorptive Capacity

CGTI represents a critical strategic response to environmental challenges, requiring advanced technological capabilities, resource integration, and strategic alignment [49]. While board experience diversity provides essential cognitive perspectives, external resources, and strategic guidance to firms, its impact on CGTI significantly depends on internal absorptive capacity [49]. Absorptive capacity, which is defined as a firm’s ability to assimilate, reconfigure, and apply knowledge to adapt effectively to dynamic environments, is essential in translating the potential benefits of board diversity into tangible innovation outcomes [50]. As absorptive capacity strengthens, the positive impact of board experience diversity on CGTI becomes more pronounced [51].
First, absorptive capacity facilitates the effective acquisition and integration of external knowledge from diverse board experiences, enabling firms to convert this knowledge into coherent CGTI strategies [52,53]. Companies with high absorptive capacity can efficiently process diverse external insights—such as regulatory trends, market demands, and technological advancements—and integrate them into a unified innovation approach [54]. For example, firms capable of combining regulatory expertise from policy-oriented directors with technological insights from R&D-focused directors are better positioned to navigate complex regulatory environments and effectively promote sustainable technologies [55].
Second, absorptive capacity enhances a firm’s ability to assimilate heterogeneous knowledge, maximizing the value derived from board experience diversity [56]. In the context of CGTI, firms with robust absorptive capacity can effectively synthesize the financial insights, technological expertise, and market intelligence contributed by directors from different backgrounds. This capability allows the firm to align resources swiftly with emerging market opportunities, accelerating the development and commercialization of green technologies [57].
Third, absorptive capacity significantly contributes to a firm’s strategic adaptability in volatile and unpredictable CGTI environments. It allows firms to respond rapidly to external shifts, such as sudden changes in market demand or regulatory requirements [58]. It allows firms to respond rapidly to external shifts, such as sudden changes in market demand or regulatory requirements. Firms with high absorptive capacity can promptly reallocate resources and adjust innovation priorities, efficiently implementing any diverse innovation strategies proposed by their boards [59]. This strategic agility is crucial for maintaining competitive advantage amid the uncertainties inherent in CGTI [60]. Based on this reasoning, the following hypothesis is proposed:
H2: 
The positive relationship between board experience diversity and corporate green technological innovation is strengthened by absorptive capacity.

3.3. Unlocking the Potential of Board Experience Diversity for Environmental Innovation Through Directors’ Networks

The moderating effects of board networks and board experience diversity have increasingly become focal points in corporate governance and innovation research. Firms pursuing corporate green technology innovation (CGTI) face multiple barriers, including technical obstacles, regulatory pressures, market volatility, and resource constraints [14]. While board experience diversity can assist in addressing these challenges, the effectiveness of diversity is significantly enhanced by the moderating role of board members’ social networks, which facilitate resource exchange and information flows.
First, CGTI represents a core strategy for sustainable development, depending heavily on technological advancement and policy support. Board experience diversity is pivotal among internal factors, as directors from varied backgrounds provide distinct perspectives and comprehensive problem-solving approaches [61]. Working on boards with different backgrounds and experiences enhances a company’s ability to tackle simple and complex problems from distinct standpoints and domains [62]. However, according to resource dependence theory, successful innovation also relies heavily on external resources [63]. Although diverse boards possess multifaceted knowledge and strategic insights, their effectiveness can be constrained by information asymmetries and internal communication barriers [42]. Board social networks alleviate these constraints by promoting knowledge exchange and resource access, thereby maximizing the innovative potential stemming from board diversity [64].
Second, director networks, characterized by interpersonal relationships among board members, facilitate essential knowledge sharing and resource acquisition [65]. Drawing on information asymmetry theory, firms pursuing CGTI frequently encounter information bottlenecks regarding external technological, regulatory, and market dynamics [66]. Director networks effectively reduce these bottlenecks by expanding the flow of information and enhancing the quality of decision-making processes [67]. Consequently, these networks accelerate communication and coordination among board members, improving their collective effectiveness and fostering more successful CGTI outcomes. Third, while board experience diversity provides valuable cognitive insights for CGTI, communication and coordination challenges may reduce its overall effectiveness [68]. Director networks moderate this relationship by facilitating effective collaboration and providing essential external resources such as financial support, technological expertise, and strategic partnerships [69]. These networks enable boards to overcome resource constraints and enhance decision-making capabilities, ultimately driving more effective implementation of CGTI strategies. Therefore, firms aiming for sustained innovation performance must strategically leverage both board diversity and robust director networks. Based on this reasoning, the following hypothesis is proposed:
H3: 
The positive relationship between board experience diversity and corporate green technological innovation is strengthened by directors’ networks.

4. Methodology

4.1. Data and Sample

We constructed our sample using all A-share listed Chinese companies from 2007 to 2022, focusing on firms engaged in green technological innovation and the role of board experience diversity, director network location, and absorptive capacity. Following prior studies on corporate CGTI and governance structures, we implemented a rigorous screening process to ensure the sample’s robustness and reliability [14,70]. First, we excluded firms flagged as Special Treatment (ST) or Particular Transfer (PT) due to their financial distress, as well as companies in the financial sector, given their distinct business models and regulatory frameworks. Second, we excluded firms with asset/liability ratios exceeding 1.0, as excessive leverage can distort investment behavior and corporate innovation strategies. Third, we eliminated firms lacking key variables essential for examining how board experience diversity, director network location, and absorptive capacity affect CGTI. To mitigate the influence of extreme values, continuous variables were winsorized at the 99% and 1% percentiles, and robust standard errors were applied in all regression models to account for heteroskedasticity and potential biases.
Data on CGTI, including green patent applications and grants, were obtained from the China Research Data Service Platform (CNRDS). Macro-level data, such as regional environmental policies and economic development indicators, were sourced from the China Statistical Yearbook. The China Stock Market and Accounting Research (CSMAR) database was used to extract firm-level financial and governance information.

4.2. Variables

4.2.1. Dependent Variables

Corporate green technological innovation (CGTI) was measured by using the number of green technological patent (the sum of independently and jointly obtained patents) applications and patent grants by listed companies based on existing research [71,72]. We used Green_Tech_Inno as a proxy for CGTI, where both patent applications and patent grants reflect firms’ engagement in green technological innovation. CNRDS provides a patent classification system that matches the Green Patent List released by the State Patent Statistics Bureau and the World Intellectual Property Organization (WIPO), which helps identify green technological patents. We further categorized these patents into three variables: GreTotal (total number of green patents), GreInvia (green invention patent applications), and GreUmia (green utility patent applications). Specifically, GreInvia refers to the number of green invention patent applications, and GreUmia refers to the number of green utility model patent applications. While green technological patent applications represent the volume of a firm’s engagement in green technology development, granted patents serve as a quality indicator, reflecting innovations that have passed rigorous examination and approval. We provide a comprehensive measure of CGTI in Chinese firms by considering both applications and grants. Additionally, to conduct robustness checks, we used authorized patents as an alternative measure, as this focuses on the quality of CGTI. We added a value of 1 to the actual patent counts before taking the natural logarithm to prevent the loss of firm-year observations with zero patents.

4.2.2. Independent Variable

To measure board experience diversity (BED), we created a multidimensional index based on directors’ educational, industrial, and organizational experiences. This index reflects how board experience diversity enhances strategic decision-making and innovation, particularly in green technological innovation. Through quantifying the backgrounds of directors by using data from CSMAR, WIND, and the company reports, we highlight their capacity to incorporate external knowledge and sustainability-aligned competency into governance. Directors are equipped with diverse career paths, leading to different cognitive skills and problem-solving approaches, and can eventually achieve better innovation outputs [19]. This is in accordance with the upper echelons and resource dependence theories, which assert that the heterogeneous experiences of board members increase a firm’s absorptive capacity, enabling firms to seize opportunities related to green technology.
For educational diversity, we calculated the inverse Herfindahl index of the undergraduate institutions attended by board members, reflecting their academic network breadth and technological foresight [30]. For industrial experience, we computed the inverse Herfindahl index of directors’ work across different industries (three-digit SIC), capturing their familiarity with various technological ecosystems and regulatory landscapes. Finally, for organizational experience, we measured the number of additional boards on which directors serve, reflecting their access to external knowledge and inter-firm innovation networks [73,74]. These dimensions provide a comprehensive framework to assess how board members navigate green technological challenges and integrate sustainability-oriented knowledge into strategies. We computed the board experience diversity index as follows:
B o a r d   E x p e r i e n c e   D i v e r s i t y = N u m b e r   o f   O t h e r   B o a r d s H H I I n d u s t r i a l   E x p e r t i s e H H I B a c h e l o r   I n s t i t u t i o n s
where Number of Other Boards represents the average number of external board seats held by directors, H H I I n d u s t r i a l   E x p e r t i s e is the Herfindahl concentration index for measuring directors’ industrial work experience diversity, and H H I B a c h e l o r   I n s t i t u t i o n s is the Herfindahl concentration index for capturing the diversity of educational backgrounds. Each component was normalized by its mean and standard deviation before constructing the final index. This method enabled us to empirically evaluate how board experience diversity enhances CGTI, with director network location serving as a key moderator and absorptive capacity acting as a facilitating mechanism.

4.2.3. Moderating Variables

To capture the director’s network location, we defined director network connection as an independent director serving on two or more boards within the same year. In our network structure, each independent director serving concurrently on multiple boards is considered a link, while the board of directors of each company represents a node. Our study excludes intra-company director connections and repeated links to multiple common independent directors, focusing instead on the inter-company director network formed through shared independent directorships.
Independent directors are the focal point of our analysis due to their prominent role as a bridge in corporate governance networks. Unlike internal directors, whose positions are relatively isolated and less mobile, independent directors facilitate information flow, external knowledge acquisition, and resource mobilization across firms. According to the weak tie theory [75], independent directors occupy key weak connections in director networks, enabling them to act as conduits for external expertise, regulatory insights, and innovation-relevant resources. This makes them particularly influential in CGTI, as they help firms access external knowledge, strategic collaborations, and regulatory guidance. We employed three centrality indicators commonly used in social network analysis to measure director network location: degree centrality, closeness centrality, and betweenness centrality [76]. First, we have degree centrality. The degree centrality of a director, Degree i , is calculated as follows:
Degree i = j X j i / g 1
where i and j represent different directors in the network, and X j i equals 1 if directors i and j serve on the same board; otherwise, the value is 0. g is the total number of directors in the network in a given year, and g 1 is used to adjust for network size differences. A higher degree of centrality indicates that a director is well-connected and has extensive direct ties with other board members, facilitating efficient knowledge transfer and governance influence.
Second, we have betweenness centrality. The betweenness centrality of a director, Betweenness i , is measured as follows:
Betweenness i = j < k g j k n i g j k / g 1 g 2 2
where g j k is the number of shortest paths connecting director j and director k , and g j k n i represents the number of these paths that pass through director i . This measure indicates the extent to which a director acts as an intermediary in the network, controlling the flow of information between otherwise disconnected boards. Directors with high betweenness centrality serve as key brokers who facilitate access to external technological knowledge and strategic opportunities in CGTI ecosystems.
Third, we have closeness centrality. The closeness centrality of a director, Closeness i , is computed as follows:
Closeness i = g 1 / j = 1 g d i , j
Each company’s board network location (DNL) indicator is constructed by standardizing three centrality measures—closeness centrality, betweenness centrality, and degree centrality—on an annual basis and then averaging these values to obtain a comprehensive DNL score for each year. Specifically, where d i , j is the shortest path distance between director i and director j , a higher closeness centrality indicates that a director has shorter average paths to all other directors, enabling faster access to critical information and decision-making processes. This is particularly relevant in green technological innovation, where the ability to rapidly disseminate regulatory changes, technological breakthroughs, and best practices can significantly influence firm innovation strategies.
By integrating these three standardized centrality measures into a single composite score, we can comprehensively represent a director’s network location and its potential impact on CGTI. Directors with higher network centrality are better positioned to channel external knowledge, foster inter-organizational collaborations, and mitigate information asymmetry, thereby enhancing firms’ capabilities in green technology development and sustainability-driven strategic decisions.
Second, we explored absorptive capacity (AC), represented by R&D intensity, as discussed by Cohen and Levinthal and Tsai [77,78]. Absorptive capacity captures a firm’s ability to effectively identify, assimilate, and apply external knowledge. While recognizing the multidimensional nature of absorptive capacity, we operationalized it through R&D intensity, which is quantified as the ratio of a firm’s R&D expenditures to annual sales revenue; this is a widely accepted proxy in strategic management research [79].

4.2.4. Control Variables

Building on prior research on CGTI [9], we incorporated a set of control variables to account for factors that may influence the dependent variable. These controls include firm size (Size), years since listing (ListAge), board experience diversity (Board), proportion of independent directors (Indep), CEO duality (Dual), ownership concentration (Top1), Tobin’s Q (TobinQ), leverage ratio (Lev), and cash flow ratio (Cashflow). Additionally, we controlled for industry (Industry) and year (Year) effects to account for industry-specific dynamics and temporal variations that could influence green technological innovation. Definitions for all variables are provided in Table 1.

4.3. Model Specifications

By building on firm-level panel data, this study employs a fixed-effects model to examine the impact of board experience diversity (BED) on corporate green technological innovation (CGTI) while considering the moderating effects of absorptive capacity (AC) and director network location (DNL). The fixed-effects approach effectively mitigates endogeneity concerns by controlling for time-invariant firm-specific characteristics, industry-specific shocks, and macroeconomic trends. To ensure robustness, this model accounts for within-firm variations over time, isolating the impact of BED on CGTI while minimizing omitted variable bias. Diagnostic tests revealed the presence of heteroskedasticity (Breusch–Pagan test, chi-squared = 49.73, p < 0.01) and first-order autocorrelation (Wooldridge test, F = 36.553, p < 0.01) in the residuals. Consequently, robust standard errors and autocorrelation-adjusted methods were used to address these issues and ensure the validity of the results. The baseline empirical model is specified as follows:
C G T I i , t + 1 = α 0 + α 1 B E D i , t + α k C o n t r o l i , t + I n d u s t r y + Y e a r + ε i , t
where CGTI represents corporate green technological innovation, measured through the number of green patent applications and granted patents, which include GreTotal (total number of green patents), GreInvia (green invention patent applications), and GreUmia (green utility patent applications). BED denotes board experience diversity, capturing the diversity of educational, industrial, and organizational experiences among board members. The variable C o n t r o l i , t represents the set of control variables for firm i at time t . These control variables are included in the model to account for other factors that may influence the dependent variable CGTI, aside from board experience diversity (BED). The error term, ε i , t , captures any remaining unobserved variation.
To test Hypotheses 2 and 3, we extended the baseline model by incorporating interaction terms to assess the moderating effects of director network location and absorptive capacity. The extended model is specified as follows:
C G T I i , t + 1 = β 0 + β 1 B E D i , t + β 2 M o d e r a t o r i , t + β 3 B E D i , t × M o d e r a t o r i , t + β k C o n t r o l i , t + I n d u s t r y + Y e a r + ε i , t
In this equation, the moderating variables represent either absorptive capacity (AC) or director network location (DNL). The interaction terms allow us to examine whether stronger director networks and higher absorptive capacity amplify the effect of BED on CGTI. If the coefficient for the interaction term is positive and significant, it suggests that the moderator strengthens the relationship between board experience diversity and green technological innovation. By applying firm-level fixed effects, the model accounts for unobserved heterogeneity across firms, isolating within-firm variations over time. This empirical framework enables a rigorous analysis of the role of governance mechanisms and absorptive capacity in shaping CGTI.

5. Empirical Results

5.1. Descriptive Statistics

Table 2 provides descriptive statistics for the main regression variables. Over the sample period, the average value of the total number of green patent applications (GreTotal) is 0.409, with a standard deviation of 0.823, suggesting that green technology innovation remains relatively infrequent among firms. The mean value of green invention patents (GreInvia) is 0.280, with a standard deviation of 0.658, indicating limited variation in green invention patents across firms. The mean value of green utility model patents (GreUmia) is 0.240, with a standard deviation of 0.588, further reflecting the infrequency of this type of innovation. The mean value of board experience diversity (BED) is 0.287, with a standard deviation of 0.194, showing moderate variation across firms. Absorptive capacity (AC) has an average value of 0.033, with a standard deviation of 0.044, highlighting substantial variability in R&D investment across firms.

5.2. Main Results

Table 3 reports the baseline regression results. Model 1 incorporates all control variables, with total green patent applications (GreTotal), green invention patents (GreInvia), and green utility patents (GreUmia) serving as dependent variables in Columns (1), (2), and (3), respectively. The results presented in Table 3 indicate that the coefficient of BED is positive and statistically significant in all models. Specifically, in Column (1), the coefficient for BED is 0.112 and is statistically significant at the 1% level; in Column (2), it is 0.065 and significant at the 5% level, and in Column (3), it is 0.065 and statistically significant at the 1% level. These results suggest that firms with more diverse board experience are more likely to engage in green technology innovation, as indicated by the positive coefficients across the three measures of green patents.
To validate the robustness of these findings, we ensured three criteria were met. First, as shown in Column (1) of Table 3, BED is positive and statistically significant. Second, the relationship between BED and green technology innovation is consistently positive across all three models (Columns 2 and 3). Third, the significance of BED across all models strengthens the argument that board experience diversity is crucial for fostering CGTI. These results provide strong support for Hypothesis 1.

5.3. Moderating Effect Results

To test the moderating effect of organizational absorptive capacity (AC) on the relationship between board experience diversity (BED) and green technology innovation, the model incorporates AC, BED × AC, and the interaction term BED × AC. The results in Column (1) of Table 4 indicate that the coefficient for the interaction term BED × AC is both positive and statistically significant (β = 1.905, p < 0.01), providing strong empirical support for the moderating role of absorptive capacity. The positive coefficient suggests that as organizational absorptive capacity increases, the positive impact of board experience diversity on CGTI is strengthened. This relationship remains robust across different specifications, as shown in Columns (2) and (3), where the dependent variable remains total green patent applications (GreTotal), with the interaction term continuing to show statistical significance.
In addition to AC, the model also tests the moderating effect of director network location (DNL), as reflected in the interaction term BED × DNL. The coefficient for BED × DNL is positive and statistically significant (β = 0.047, p < 0.01) in both Columns (2) and (3), further supporting the hypothesis that the relationship between board experience diversity and green technology innovation is enhanced by the position of directors within valuable networks. This suggests that firms with directors in well-connected positions can better leverage the board’s diverse experiences to drive CGTI.
The research findings also highlight how both organizational absorptive capacity and the location of directors in an external network will promote the relationship between the diversity of board experience and green technology innovation. The moderating effects of AC and DNL thus indicate that AC and directors with a strong position within a network make it easier for firms to translate diverse board diversity experiences into successful outcomes in CGTI. The results offer credible support to the belief that, besides managerial characteristics, such as diversity of board experience or network location, organizational capabilities are key drivers of sustainable innovation.

5.4. Robustness Tests

When faced with dynamic relationships, we employed a single-step system GMM estimation to mitigate concerns about endogeneity and ensure uniform estimators. Its system GMM estimator is particularly suitable for dealing with dynamic panel data models since the variables’ lagged values are used as internal instruments to account for potential simultaneity and unobserved heterogeneity. The outcomes of the GMM model, a dynamic panel system, can be seen in Table 5. The coefficients for diversity of board experience are significant and positive across all models; board experience diversity (BED) is strongly associated with innovation in green technological innovation and is found to be approximately 2.704 (FTotal), 2.152 (FGreInvia), and 2.367 (FGreUmia). Bigger companies may not be more committed to CGTI because of the negative relationship with firm size, which is statistically insignificant. Tobin’s Q negatively affects FGreUmia and FTotal, which measures potential growth, leading to the belief that companies with less favorable prospects for growth may prioritize investing in CGTI. Diagnostic tests such as AR1, AR2, and the Sargan test were used to confirm the robustness of the results by verifying the model’s accuracy.
To further assess the robustness of the results, we conducted additional tests using alternative model specifications, as shown in Table 6, where we analyzed the impact of board experience diversity (BED) on authorized green patents. The results are consistent across all models, indicating the robustness of the relationship between BED and green technological innovation. In Column (1), where the dependent variable is total green patents (GreTotal), BED has a coefficient of 0.858 (p < 0.01), demonstrating a strong positive effect. In Column (2), with green invention patents (GreInvia) as the dependent variable, BED shows a coefficient of 0.469 (p < 0.05), while in Column (3), where the dependent variable is green utility patents (GreUmia), the coefficient is 0.389 (p < 0.01).
These findings suggest that board experience diversity has a consistent and significant positive effect across different types of green patents, further supporting the notion that diverse managerial experiences play a key role in fostering innovation in green technologies. The results remain robust across all models, showing that the positive relationship between BED and CGTI holds for both invention and utility patents. This provides strong evidence that board experience diversity is a crucial driver of CGTI, regardless of the specific patent category.
To address the distinct structure of the dependent variables, which exhibit a significant accumulation of zero values alongside a continuous distribution for the positive values, we replaced the regression model with the Tobit model for robustness testing. The Tobit model is appropriate for these types of data, as it accounts for the censoring effect at zero, ensuring that the relationship between the independent variables and green technology innovation is properly modeled. The results presented in Table 7 show that BED has a significant positive effect on all three measures of CGTI.
In Column (1), where the dependent variable is total green patent applications (GreTotal), the coefficient for BED is 0.430 (p < 0.01), indicating a strong positive relationship between board experience diversity and CGTI. Similarly, in Column (2), where the dependent variable is green invention patents (GreInvia), the coefficient for BED is 0.450 (p < 0.01). In Column (3), where the dependent variable is green utility patents (GreUmia), the coefficient is 0.328 (p < 0.01). These results suggest that board experience diversity significantly drives CGTI across all types of patents, further validating the importance of diverse managerial perspectives. These findings confirm the robustness of the results, showing that the relationship between board experience diversity and CGTI remains significant even after accounting for censoring effects in the dependent variables.
To further validate the robustness of the results, we conducted an analysis by excluding the impact of the 2008 and 2015 financial crises, which could have influenced CGTI due to significant economic disruptions. The results in Table 8 show that after removing these periods, the relationship between BED and green technology innovation remains largely unchanged. The coefficient for BED is 0.113 in Column 1, 0.063 in Column 2, and 0.065 in Column 3, all of which are statistically significant at the 1% and 5% levels. These results suggest that the relationship between board experience diversity and CGTI continues to hold even after excluding the crisis years.

5.5. Heterogeneity Test

As demonstrated in Table 9, board experience diversity (BED) significantly impacted green technological innovation in non-SOEs. The heterogeneity test showed that board experience diversity was positively correlated with GreTotal, GreInvia, and GreUmia. The impact of BED on SOEs is statistically minimal and unimportant. Hence, it seems that the impact of board diversity is stronger for CGTI in non-SOEs than for SOEs. Although size is positively correlated with CGTI in both firm types, Size and Top1 also have varying effects.

5.6. Mechanism Test

In Table 10, the mechanism test results show the coefficient for board experience diversity (BED) in Column (3) is lower than in Column (1), from 0.103 to 0.100. This decrease occurs with the inclusion of R&D intensity (RDS) as a mediating variable, indicating that RDS partially mediates the relationship between BED and CGTI (GTotal). The positive and significant coefficient for RDS in Column (3) (0.009) supports the existence of this mediation effect. Thus, R&D intensity acts as a channel through which board experience diversity influences innovation outcomes.

6. Conclusions and Implications

6.1. Conclusions

This study examined the impact of board experience diversity on corporate green technological innovation and explored the moderating roles of absorptive capacity and director network location. Utilizing firm-level panel data and a fixed-effects model, we constructed a board experience diversity index to empirically assess its influence on green technological innovation, providing micro-level economic evidence on how governance structures shape corporate sustainability strategies. The findings reveal that board experience diversity significantly enhances CGTI, as diverse backgrounds among board members help to expand a firm’s knowledge boundaries, improve strategic decision-making, and optimize resource allocation for CGTI. Moreover, absorptive capacity positively moderates the relationship between board experience diversity and green technological innovation. This suggests that firms with higher absorptive capacity can more effectively integrate and leverage the knowledge and resources brought by board experience diversity, thereby amplifying its impact. Director network location further strengthens this positive effect, as centrally positioned directors enhance access to external knowledge, foster inter-firm collaboration, and accelerate the diffusion of sustainability-oriented strategies. Based on the heterogeneity test, board diversity has a greater impact on CGTI in non-state-owned enterprises than in state-owned enterprises. Meanwhile, the mechanism test demonstrated that R&D intensity is a channel through which board experience diversity affects innovation outcomes. These results emphasize the need for firms to develop internal capabilities and optimize external networks to fully leverage board experience diversity. Firms should improve their absorptive capacity to enhance knowledge transfer and use director networks to access external resources, ultimately boosting green technological innovation.

6.2. Theoretical Contributions

This study makes several important theoretical contributions to the literature on corporate green technological innovation (CGTI), corporate governance, and strategic management.
First, traditional CGTI research has primarily focused on factors such as policies, regulations, technological resources, and capital investments [63]. Institutional, resource-based, and open innovation theories have offered valuable insights into the mechanisms driving CGTI [70]. However, these studies have often overlooked the role of board experience diversity in shaping CGTI. While the existing literature emphasizes the impact of internal resources and external collaborations, it has given limited attention to how the background diversity of board members influences the innovation process [80,81]. Introducing the concept of board experience diversity, this study fills an important theoretical gap, highlighting the crucial role that diversified board members—armed with rich industry experience, technical expertise, and international backgrounds—play in decision-making and execution related to green technology innovation. This research not only broadens the scope of the influencing factors of CGTI but also provides a fresh theoretical perspective for understanding the contribution of board experience diversity to CGTI.
Second, this study further enriches upper echelons theory by integrating it with absorptive capacity theory. As a core framework in strategic management and innovation, absorptive capacity explores how firms achieve a competitive advantage by dynamically reconfiguring their resources and capabilities in complex and uncertain environments [58,82]. While prior research on absorptive capacity has focused mainly on how firms adapt to environmental changes, it has often neglected the role of top management teams (TMTs) in influencing innovation behaviors [11]. This study examines how board members’ diverse experiences enhance a firm’s absorptive capacity, enabling the firm to better identify, integrate, and execute opportunities for green technological innovation. Framing this within the lens of absorptive capacity, the study extends the theoretical understanding of how board experience diversity influences TMT decision-making processes. It demonstrates that diverse board members provide firms with a broader knowledge base and perspective, thus facilitating the identification and execution of green innovation opportunities, even in complex decision-making environments. This contribution both broadens the application of absorptive capacity theory and deepens upper echelons theory, showing how absorptive capacity facilitates decision-making and innovation in diverse TMTs.
Third, this study contributes to the corporate governance and innovation literature by emphasizing the moderating role of director network location in the relationship between board experience diversity and CGTI. While previous research on corporate governance has largely focused on the direct effects of board composition on firm outcomes, it has often overlooked the broader social networks in which boards operate [83,84]. Through incorporating director network location as a key moderator, this study introduces a social network perspective to corporate governance, demonstrating how directors’ external connectivity and inter-organizational linkages shape the effectiveness of board experience diversity in fostering innovation. Directors in central positions within corporate networks act as conduits for critical information, resource acquisition, and strategic collaboration, thus allowing firms to leverage the diverse expertise of board members to drive CGTI. This perspective extends social network theory to the corporate governance domain, highlighting the importance of the structural positioning of directors within inter-firm networks in amplifying the benefits of board experience diversity. Through integrating director network theory into the discussion about board governance and CGTI, this study offers a more comprehensive understanding of the external relational mechanisms that enhance board effectiveness in driving sustainable corporate innovation.

6.3. Practical Contributions

This study has many practical contributions. First, it highlights the importance of optimizing criteria for selecting board members to promote diversity across areas such as industry experience, technical expertise, and international perspectives. Board members specialized in green technology and sustainable development usually have new perspectives; furthermore, they are familiar with future technological trends, which could offer firms more diversified decision-making support for environmental-related technological innovation. Moreover, firms are recommended to enhance cross-disciplinary partnerships and set up interactions and communications between board members through frequent strategic workshops and seminars; this would enable experience and information sharing, creative thinking, and promote developing and executing green technology innovation strategies. In addition, it is important for firms to strengthen the board’s focus on strategic green technology innovation and to provide training in the field of green technologies on a continuous basis in order to improve the knowledge and awareness of board members and encourage them to participate more actively in decision-making and resource allocation related to CGTI.
Second, besides establishing the diversity of board experience, firms should work towards building absorptive capacity to enable them to innovate in dynamic market environments. Continuing technological learning, interdepartmental collaboration, and knowledge sharing can further enhance diverse, internally dynamic adaptability in organizations. Firms could then address uncertainty and risk factors that correlate with CGTI through these practices. Companies must also develop decision-making processes and resource allocation structures that can be flexibly adjusted to adapt their strategies, resources, and operations to rapidly evolving technology and shifting markets. This will boost the company’s ability to seize and capture opportunities arising in episodes of green technology innovation; in turn, this will increase innovation efficiency and success rates.
Third, firms should enhance the strategic flexibility of their boards by encouraging board members to be more focused on not just long-term planning but also being in tune with the rapid shifts in both the green technology and policy domains. As a result, companies will be able to respond to technological trends, policy developments, and market needs—frequently reviewed and included in the discussions at the board level—in a timely manner and pivot their ever-changing strategic direction. Moreover, enterprises should constantly enhance cross-industry innovation cooperation, collaborating with external organizations, research institutions, and other entities to organically integrate external resources and promote green technology innovation.

6.4. Limitations and Future Research

This study has some limitations, paving the way for future research. First, we restricted its scope to the direct effect of the heterogeneity of board experience on corporate environmental innovation. Alternatively, the diversity of experience on boards may impact innovation in more nuanced ways by guiding knowledge flows within the firm or promoting cross-discipline collaboration. Future research could investigate the development of board experience diversity over time, its impact at different stages of the innovation process, and how the interaction among board members helps to spur innovations.
Second, the study relies on data from Chinese companies; context-driven political, economic, and cultural peculiarities may render the results less generalizable. Future studies could enhance the sample by including firms located in other regions, mainly representing emerging markets and developed nations. A cross-regional comparative study should be conducted considering a broader diversity of cultural, policy, and market backgrounds. Further, expanding the field of study to include multinational organizations may provide a wider and more comprehensive view of how the diversity of board experience extends to innovation capabilities.
Third, this study does not take into account other possible moderating variables, such as firm size, industry characteristics, and market competition. Future research can build on the variables used in the current study to investigate how the impact of board experience diversity on innovation is contextual. Larger companies or those in more competitive industries, for example, could depend more on diverse boards, although, in some sectors, homogenous boards might be better at making strategic decisions. Investigating these moderating influences would allow for more precise theoretical models and address more generalizable practical applications of the findings.

Author Contributions

Conceptualization, X.Z. and X.W.; Methodology, X.Z. and X.W.; Formal analysis, X.Z. and S.W.; Investigation, X.Z. and S.W.; Writing—original draft, X.Z. and S.W.; Writing—review & editing, X.Z., S.W. and X.W.; Project administration, X.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available in China Research Data Service Platform (CNRDS), the China Statistical Yearbook and China Stock Market and Accounting Research (CSMAR) database (https://data.csmar.com/).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Zhang, X.S.; Jiang, Q.Q.; Cifuentes-Faura, J.; Hu, X.J.; Li, Y.Y. Do tax incentives matter in promoting corporate ESG performance toward sustainable development? Bus. Strateg. Environ. 2025, 34, 57–69. [Google Scholar] [CrossRef]
  2. Zhang, L.G.; Yang, R.Y.; Liu, Y.R.; Wang, Y.C. The embedding of party organizations and green innovation of privately owned firms. Technol. Forecast. Soc. Change 2024, 208, 123639. [Google Scholar] [CrossRef]
  3. Tu, Y.; Wu, W. How does green innovation improve enterprises’ competitive advantage? The role of organizational learning. Sustain. Prod. Consum. 2021, 26, 504–516. [Google Scholar] [CrossRef]
  4. Wang, W.-C.; Lin, C.-H.; Chu, Y.-C. Types of competitive advantage and analysis. Int. J. Bus. Manag. 2011, 6, 100. [Google Scholar]
  5. Guerrero-Villegas, J.; Sierra-García, L.; Palacios-Florencio, B. The role of sustainable development and innovation on firm performance. Corp. Soc. Responsib. Environ. Manag. 2018, 25, 1350–1362. [Google Scholar] [CrossRef]
  6. Gong, R.; Wu, Y.-Q.; Chen, F.-W.; Yan, T.-H. Labor Costs, Market Environment and Green Technological Innovation: Evidence from High-Pollution Firms. Int. J. Environ. Res. Public Health 2020, 17, 522. [Google Scholar] [CrossRef]
  7. Liao, Y.; Qiu, X.; Wu, A.; Sun, Q.; Shen, H.; Li, P. Assessing the impact of green innovation on corporate sustainable development. Front. Energy Res. 2022, 9, 800848. [Google Scholar]
  8. Song, Y.G.; Du, C.M.; Du, P.L.; Liu, R.; Lu, Z. Digital transformation and corporate environmental performance: Evidence from Chinese listed companies. Technol. Forecast. Soc. Change 2024, 201, 123159. [Google Scholar] [CrossRef]
  9. Sarpong, D.; Boakye, D.; Ofosu, G.; Botchie, D. The three pointers of research and development (R&D) for growth-boosting sustainable innovation system. Technovation 2023, 122, 102581. [Google Scholar] [CrossRef]
  10. Sheng, J.C.; Ding, R.; Yang, H.Q. Corporate green innovation in an aging population: Evidence from Chinese listed companies. Technol. Forecast. Soc. Change 2024, 202, 123307. [Google Scholar] [CrossRef]
  11. Wang, S.; Lv, J. CEO-TMT faultline and corporate green innovation: The contextual role of Confucian culture. Manag. Decis. Econ. 2023, 44, 4422–4438. [Google Scholar] [CrossRef]
  12. Adeel, T.; Badir, Y.F.; Safdar, U.; Tariq, W.; Badar, K. Linking firms’ life cycle, capabilities, and green innovation: IMS. J. Manuf. Technol. Manag. 2020, 31, 284–305. [Google Scholar] [CrossRef]
  13. Leonidou, L.C.; Christodoulides, P.; Kyrgidou, L.P.; Palihawadana, D. Internal drivers and performance consequences of small firm green business strategy: The moderating role of external forces. J. Bus. Ethics 2017, 140, 585–606. [Google Scholar] [CrossRef]
  14. Shao, Y.M.; Li, J.L.; Zhang, X.L. Outward foreign direct investment and green technology innovation: A company and host country perspective. Technol. Forecast. Soc. Change 2024, 203, 123379. [Google Scholar] [CrossRef]
  15. Zhang, C.; Tian, X.Y.; Sun, X.J.; Xu, J.; Gao, Y. Digital Transformation, Board Diversity, and Corporate Sustainable Development. Sustainability 2024, 16, 7788. [Google Scholar] [CrossRef]
  16. Wright, C.E.F.; Wilkie, B. Small worlds: Institutional isomorphism and Australia’s corporate elite, 1910–2018. Bus. Hist. 2024, 24, 1–24. [Google Scholar] [CrossRef]
  17. Wright, C.E.F. “Bossyboots”: Postfeminism and the construction of Australia’s “Corporate Woman”. Gend. Work. Organ. 2025, 32, 743–762. [Google Scholar] [CrossRef]
  18. Sauerwald, S.; Norlander, P. Political Directors and the Recruitment of Foreign Workers. J. Manag. 2024, 51, 1–31. [Google Scholar] [CrossRef]
  19. Saeed, A.; Baloch, M.S.; Liedong, T.A.; Rajwani, T. Board gender diversity, nonmarket strategy and firm performance: Evidence from emerging markets MNCs. Res. Int. Bus. Financ. 2024, 71, 102462. [Google Scholar] [CrossRef]
  20. Rau, P.R.; Sandvik, J.; Vermaelen, T. IPO price formation and board gender diversity. J. Corp. Financ. 2024, 88, 102629. [Google Scholar] [CrossRef]
  21. Pham, T.M.; Rizov, M.; Vo, X.V. Board Gender Diversity and Firm Performance in an Emerging Economy: The Role of Women Directors’ Attributes. Int. J. Financ. Econ. 2024, 29, 1–19. [Google Scholar] [CrossRef]
  22. Singh, A.K.; Jain, N.K.; Sharma, M.G.; Nigam, S. Reconceptualization of absorptive capacity as potential and realized absorptive capacity for project-based organizations. Int. J. Proj. Manag. 2023, 41, 102449. [Google Scholar]
  23. Shaik, A.S.; Jain, M.; Mendiratta, A.; Alarifi, G.; Arrigo, E. Role of strategic knowledge management practices in enhancing strategic perspectives of an organisation to improve entrepreneurial performance. J. Knowl. Manag. 2024, 28, 1648–1675. [Google Scholar]
  24. Hao, X.L.; Miao, E.R.; Sun, Q.Y.; Li, K.; Wen, S.F.; Xue, Y. The impact of digital government on corporate green innovation: Evidence from China. Technol. Forecast. Soc. Change 2024, 206, 123570. [Google Scholar] [CrossRef]
  25. Gao, P.; He, J.; Vochozka, M.; Hu, S.Y. Deterrent effects of central environmental protection inspection on green technology innovation cycles: Evidence from the listed state-owned firms in China. Technol. Forecast. Soc. Change 2024, 209, 123783. [Google Scholar] [CrossRef]
  26. Dogah, K.E.; Wesseh, P.K., Jr.; Adomako, S. Green credit policy, technological innovation, and corporate financial performance: Evidence from the energy industry. Bus. Strateg. Environ. 2025, 34, 1171–1188. [Google Scholar] [CrossRef]
  27. Korphaibool, V.; Chatjuthamard, P.; Jiraporn, P.; Treepongkaruna, S. Exploring the influence of military experience directors on corporate governance: Evidence from Thai-listed companies. Corp. Soc. Responsib. Environ. Manag. 2024, 32, 2237–2253. [Google Scholar]
  28. Collevecchio, F.; Temperini, V.; Barba-Sanchez, V.; Meseguer-Martinez, A. Sustainable Governance: Board Sustainability Experience and the Interplay with Board Age for Firm Sustainability. J. Bus. Ethics 2024, 197, 371–389. [Google Scholar]
  29. Ma, A.K.F.; Chen, Y. Board attributes, ownership structure, and corporate social responsibility: Evidence from A-share listed technological companies in China. Soc. Bus. Rev. 2024, 19, 181–206. [Google Scholar]
  30. Alzayed, N.; Batiz-Lazo, B.; Eskandari, R. Does board diversity mitigate risk? The effect of homophily and social ties on risk-taking in financial institutions. Res. Int. Bus. Financ. 2024, 70, 102306. [Google Scholar] [CrossRef]
  31. Ali, W.; Wilson, J.; Frynas, J.G. Corporate governance mechanisms and carbon disclosure: A multilevel and multitheory literature survey. Corp. Soc. Responsib. Environ. Manag. 2024, 31, 5670–5689. [Google Scholar] [CrossRef]
  32. Fernandes, E.; Burcharth, A. Why traditional firms from the same industry reject digital transformation: Structural constraints of perception and attention. Long Range Plan. 2024, 57, 19. [Google Scholar] [CrossRef]
  33. Erhan, T.P.; Japutra, A.; Van Doorn, S. Digital product development team external knowledge processes and ambidexterity: A multi-mediation analysis of the absorptive capacity framework. J. Knowl. Manag. 2024, 28, 2610–2634. [Google Scholar] [CrossRef]
  34. Dimakopoulou, A.; Gkypali, A.; Tsekouras, K. Technological and non-technological innovation synergies under the lens of absorptive capacity efficiency. J. Bus. Res. 2024, 176, 114593. [Google Scholar]
  35. Cumming, D.; Leung, T.Y. Board diversity and corporate innovation: Regional demographics and industry context. Corp. Gov. Int. Rev. 2021, 29, 277–296. [Google Scholar]
  36. Chirico, F.; Kellermanns, F.W. When does time enhance family firm performance? Examining family generation in control and family control dispersion through a mixed-gamble logic. Long Range Plan. 2024, 57, 102272. [Google Scholar]
  37. Capolupo, P. Mapping research on knowledge management in family firms: A bibliometric analysis. J. Knowl. Manag. 2024, 28, 2564–2589. [Google Scholar]
  38. Bhatti, S.H.; Jabeen, F.; Ahmed, A.; Romano, M.; Pascucci, F. How do knowledge-intensive business services improve innovation? A resource-based model for antecedents of innovation in a developing country. J. Knowl. Manag. 2025, 29, 92–112. [Google Scholar] [CrossRef]
  39. Agnihotri, A.; Bhattacharya, S.; Vrontis, D.; Monge, F. Managerial values and sustainable oriented innovation: Examining the role of knowledge exploration versus exploitation practices. J. Knowl. Manag. 2024, 28, 2793–2817. [Google Scholar] [CrossRef]
  40. Abebe, M.A.; Tangpong, C.; Ndofor, H. Hitting the ‘reset button’: The role of digital reorientation in successful turnarounds. Long Range Plan. 2024, 57, 102102. [Google Scholar]
  41. Belitski, M.; Delgado-Márquez, B.L.; Pedauga, L.E. Your innovation or mine? The effects of partner diversity on product and process innovation. J. Prod. Innov. Manag. 2024, 41, 112–137. [Google Scholar] [CrossRef]
  42. Nicoletti, B.; Appolloni, A. Green Logistics 5.0: A review of sustainability-oriented innovation with foundation models in logistics. Eur. J. Innov. Manag. 2024, 27, 542–561. [Google Scholar] [CrossRef]
  43. Lin, X.; Yu, L.; Zhang, J.; Lin, S.; Zhong, Q. Board Gender Diversity and Corporate Green Innovation: Evidence from China. Sustainability 2022, 14, 15020. [Google Scholar] [CrossRef]
  44. Quan, X.; Ke, Y.; Qian, Y.; Zhang, Y. CEO foreign experience and green innovation: Evidence from China. J. Bus. Ethics 2021, 182, 535–557. [Google Scholar] [CrossRef]
  45. Usman, M.; Javed, M.; Yin, J. Board internationalization and green innovation. Econ. Lett. 2020, 197, 109625. [Google Scholar] [CrossRef]
  46. Tao-Schuchardt, M.; Kammerlander, N. Board diversity in family firms across cultures: A contingency analysis on the effects of gender and tenure diversity on firm performance. J. Fam. Bus. Strategy 2024, 15, 16. [Google Scholar] [CrossRef]
  47. Liu, X.Q.; Cifuentes-Faura, J.; Yang, X.D.; Pan, J.Y. The green innovation effect of industrial robot applications: Evidence from Chinese manufacturing companies. Technol. Forecast. Soc. Change 2025, 210, 10. [Google Scholar] [CrossRef]
  48. Liu, T.; Cao, X. Going green: How executive environmental awareness and green innovation drive corporate sustainable development. J. Knowl. Econ. 2024, 1–28. [Google Scholar] [CrossRef]
  49. Li, R.; Ramanathan, R. The interactive effect of environmental penalties and environmental subsidies on corporate environmental innovation: Is more better or worse? Technol. Forecast. Soc. Change 2024, 200, 123193. [Google Scholar] [CrossRef]
  50. Riggs, R.; Felipe, C.M.; Roldán, J.L.; Real, J.C. Information systems capabilities value creation through circular economy practices in uncertain environments: A conditional mediation model. J. Bus. Res. 2024, 175, 17. [Google Scholar] [CrossRef]
  51. Åberg, C.; Fjellvær, H.; Seierstad, C. Board diversity: The impact of dynamic capabilities, absorptive capacity and ambidexterity. In Research Handbook on Diversity and Corporate Governance; Edward Elgar Publishing: Cheltenham, UK, 2023; pp. 45–61. [Google Scholar]
  52. Perotti, F.A.; Troise, C.; Ferraris, A.; Hirwani Wan Hussain, W.M. Bridging Innovation Management and Circular Economy: An Empirical Assessment of Green Innovation and Open Innovation. Creat. Innov. Manag. 2024. early view. [Google Scholar] [CrossRef]
  53. Rani, S.; Devi, E.B. Impact of collective knowledge on individual research competence: Exploring the mediating influence of knowledge management processes. Eur. J. Innov. Manag. 2024. [Google Scholar] [CrossRef]
  54. Tsai, B.-H. Applying Fuzzy Decision-Making Trial and Evaluation Laboratory and Analytic Network Process Approaches to Explore Green Production in the Semiconductor Industry. Sustainability 2024, 16, 7163. [Google Scholar] [CrossRef]
  55. Parmentier, G.; Sheet, Z.; Jeannot, F.; Rampa, R. Development of a multidimensional scale to measure organizational creative capabilities. J. Prod. Innov. Manag. 2024, 41, 1184–1209. [Google Scholar] [CrossRef]
  56. Farooq, M.W.; Nawaz, F.; Sabir, R.I. To Gain Sustainable Competitive Advantages (SCA) Using Artificial Intelligence (AI) Over Competitors. Bull. Bus. Econ. (BBE) 2024, 13, 1026–1033. [Google Scholar] [CrossRef]
  57. Xu, J.; Hu, W. How do external resources influence a firm’s green innovation? A study based on absorptive capacity. Econ. Model. 2024, 133, 106660. [Google Scholar] [CrossRef]
  58. Mishra, D.; Maheshwari, N. Crowdsourcing-based social linkage and organizational innovation competence: Knowledge transfer effectiveness and absorptive capacity as serial mediators. J. Knowl. Manag. 2024, 28, 2013–2037. [Google Scholar] [CrossRef]
  59. Jin, J.L.; Wang, L.; Wang, K.; Fu, X. Concentrating or dispersing? The double-edged sword effects of supplier concentration on firm financial and innovation performance. J. Bus. Res. 2025, 186, 114946. [Google Scholar] [CrossRef]
  60. Ji, M.; Zhang, X. Assessing the impacts and mechanisms of green bond financing on the enhancement of green management and technological innovation in environmental conservation enterprises. J. Knowl. Econ. 2024, 15, 12709–12750. [Google Scholar] [CrossRef]
  61. Yan, C.; Xiao, Y.; Li, J.; Xia, C. Impact of diversity of top management team on firm’s green innovation: Evidence from China. Manag. Decis. Econ. 2024, 45, 4919–4929. [Google Scholar] [CrossRef]
  62. Fernandez, W.D.; Thams, Y. Board diversity and stakeholder management: The moderating impact of boards’ learning environment. Learn. Organ. 2019, 26, 160–175. [Google Scholar] [CrossRef]
  63. Ren, X.; Li, W.; Li, Y. Climate risk, digital transformation and corporate green innovation efficiency: Evidence from China. Technol. Forecast. Soc. Change 2024, 209, 123777. [Google Scholar] [CrossRef]
  64. Qiu, Q.; Yu, J. Impact of independent director network on corporate green innovation: Evidence from Chinese listed companies. Corp. Soc. Responsib. Environ. Manag. 2023, 30, 3271–3293. [Google Scholar] [CrossRef]
  65. Yang, T.; Tsang, Y.P.; Wu, C.H.; Chung, K.T.; Lee, C.K.M.; Yuen, S.S.M. Mixed reality-based online 3D pallet loading problem to achieve augmented intelligence in e-fulfilment processes. Oper. Manag. Res. 2023, 1–16. [Google Scholar] [CrossRef]
  66. Wu, B.H.; Zhu, P.H.; Yin, H.; Wen, F.H. The risk spillover of high carbon enterprises in China: Evidence from the stock market. Energy Econ. 2023, 126, 21. [Google Scholar] [CrossRef]
  67. Lyu, K.; Cai, D.X.; Hao, M. Dynamic Innovation Collaboration Based on Complex Network Analysis: Evidence from the “Belt and Road” Initiative. J. Knowl. Econ. 2024, 1–26. [Google Scholar] [CrossRef]
  68. Ferraro, G.; Passaro, R.; Quinto, I.; Thomas, A. The process supporting the emergence of the environmental innovation capabilities within small businesses: An empirical investigation. Bus. Strategy Environ. 2025, 34, 1027–1042. [Google Scholar] [CrossRef]
  69. Davi-Arderius, D.; Schittekatte, T. Carbon emissions impacts of operational network constraints: The case of Spain during the Covid-19 crisis. Energy Econ. 2023, 128, 107164. [Google Scholar] [CrossRef]
  70. Kong, X.R.; Yan, C.; Ho, K.C. The impact of climate change on credit cycles: Evidence from China’s bond market. Technol. Forecast. Soc. Change 2024, 206, 13. [Google Scholar] [CrossRef]
  71. Jin, C.F.; Monfort, A.; Chen, F.; Xia, N.; Wu, B. Institutional investor ESG activism and corporate green innovation against climate change: Exploring differences between digital and non-digital firms. Technol. Forecast. Soc. Change 2024, 200, 20. [Google Scholar] [CrossRef]
  72. Ji, C.L.; Feng, Y.W. Evaluating the Innovation-Boosting Potential of Low-Carbon Pilot Policies: A Multi-Subject Co-Governance Perspective. J. Knowl. Econ. 2024, 40. [Google Scholar] [CrossRef]
  73. Beckman, C.M.; Schoonhoven, C.B.; Rottner, R.M.; Kim, S.-J. Relational pluralism in de novo organizations: Boards of directors as bridges or barriers to diverse alliance portfolios? Acad. Manag. J. 2014, 57, 460–483. [Google Scholar] [CrossRef]
  74. Boeker, W. Strategic change: The influence of managerial characteristics and organizational growth. Acad. Manag. J. 1997, 40, 152–170. [Google Scholar] [CrossRef]
  75. Granovetter, M.S. The strength of weak ties. Am. J. Sociol. 1973, 78, 1360–1380. [Google Scholar] [CrossRef]
  76. El-Khatib, R.; Fogel, K.; Jandik, T. CEO network centrality and merger performance. J. Financ. Econ. 2015, 116, 349–382. [Google Scholar] [CrossRef]
  77. Cohen, W.M.; Levinthal, D.A. Absorptive capacity: A new perspective on learning and innovation. Adm. Sci. Q. 1990, 35, 128–152. [Google Scholar] [CrossRef]
  78. Tsai, W. Knowledge transfer in intraorganizational networks: Effects of network position and absorptive capacity on business unit innovation and performance. Acad. Manag. J. 2001, 44, 996–1004. [Google Scholar] [CrossRef]
  79. Shi, W.; Connelly, B.L.; Cirik, K. Short seller influence on firm growth: A threat rigidity perspective. Acad. Manag. J. 2018, 61, 1892–1919. [Google Scholar] [CrossRef]
  80. Hussain, M.; Yang, S.; Maqsood, U.S.; Zahid, R.A. Tapping into the green potential: The power of artificial intelligence adoption in corporate green innovation drive. Bus. Strateg. Environ. 2024, 33, 4375–4396. [Google Scholar] [CrossRef]
  81. Xu, R.; Pata, U.K.; Dai, J. Sustainable growth through green electricity transition and environmental regulations: Do risks associated with corruption and bureaucracy matter? Politická Ekon. 2024, 72, 228–254. [Google Scholar] [CrossRef]
  82. Xu, R.; Murshed, M.; Li, W. Does Political (De) stabilization Drive Clean Energy Transition? Politická Ekon. 2024, 72, 357–374. [Google Scholar] [CrossRef]
  83. Lee, H.S.; Pattnaik, C.; Gaur, A.S. Internationalization of I-business Firms: The role of distance on location choice. J. Bus. Res. 2023, 164, 114010. [Google Scholar] [CrossRef]
  84. Xu, R.; Chen, X.; Dong, P. Nexus among financial technologies, oil rents, governance and energy transition: Panel investigation from Asian Economies. Resour. Policy 2024, 90, 104746. [Google Scholar] [CrossRef]
Table 1. Definition of variables.
Table 1. Definition of variables.
VariableSymbolMeasure
Corporate Green Technological Innovation (CGTI)Green_Tech_InnoTotal number of green patent applications and granted patents annually.
Board Experience Diversity (BED)BEDMultidimensional index reflecting directors’ educational, industrial, and organizational experiences.
Director Network Location (DNL) DNLComposite measure based on the degree centrality, closeness centrality, and betweenness centrality of independent directors.
Absorptive Capacity (AC)ACR&D intensity, calculated as the ratio of R&D expenditures to annual sales revenue.
Firm SizeSizeNatural logarithm of the total assets of the enterprise.
Years Since ListingListAgeNumber of years the company has been listed on the stock exchange.
Proportion of Independent DirectorsIndepRatio of independent directors to the total number of directors.
CEO DualityDualDummy variable (equal to 1 if the CEO also serves as the chairperson of the board; otherwise, it is 0).
Ownership ConcentrationTop1Shareholding ratio of the largest shareholder.
Tobin’s QTobinQRatio of market value of assets to replacement cost, used to measure firm’s growth prospects.
Leverage RatioLevRatio of total liabilities to total assets.
Cash Flow RatioCashflowCash flow ratio, reflecting the firm’s cash flow relative to its total assets.
Table 2. Descriptive statistics.
Table 2. Descriptive statistics.
VariablesObservationsMeanSDMinMedianMax
GreTotal24,5460.4090.8230.0000.0003.829
GreInvia24,5460.2800.6580.0000.0003.401
GreUmia24,5460.2400.5880.0000.0002.944
BED24,5460.2870.1940.0000.3460.500
AC24,5460.0330.0440.0000.0240.271
DNL24,5460.9291.195−0.7260.7923.175
Size24,54621.9771.21419.40621.81626.430
ListAge24,5462.0980.8850.0002.3033.367
Board24,5462.1400.1991.6092.1972.708
Indep24,5460.3720.0530.2500.3330.600
Dual24,5460.2560.4370.0000.0001.000
Top124,5460.3400.1440.0840.3190.758
TobinQ24,5462.0671.2420.8861.6687.984
Lev24,5460.4160.2030.0270.4120.925
Cashflow24,5460.0490.070−0.2240.0470.283
Table 3. Baseline regression results.
Table 3. Baseline regression results.
(1)(2)(3)
GreTotalGreInviaGreUmia
BED0.112 ***0.065 ***0.065 ***
(3.545)(2.587)(2.634)
Size0.071 ***0.062 ***0.036 ***
(5.428)(5.763)(3.806)
ListAge−0.042 ***−0.027 **−0.026 **
(−2.601)(−2.005)(−2.139)
Board0.0480.0430.002
(1.113)(1.096)(0.073)
Indep10.0530.053−0.037
(0.388)(0.495)(−0.342)
Dual−0.016−0.013−0.016
(−1.123)(−1.096)(−1.526)
Top1−0.119−0.089−0.045
(−1.453)(−1.305)(−0.699)
TobinQ0.009 **0.009 **0.002
(2.010)(2.176)(0.770)
Lev0.0590.0520.045
(1.412)(1.490)(1.490)
Cashflow0.001−0.0180.046
(0.017)(−0.360)(1.104)
Constant−1.446 ***−1.323 ***−0.653 ***
(−4.445)(−5.132)(−2.692)
Industry FEYesYesYes
Year FEYesYesYes
N24,54624,54624,546
Adj. R20.0440.0410.028
Note: **, and *** indicate significance at the 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 4. Moderating effect results.
Table 4. Moderating effect results.
(1)(2)(3)
GreTotalGreTotalGreTotal
BED0.114 ***0.111 ***0.113 ***
(3.625)(3.513)(3.590)
AC0.735 *** 0.738 ***
(3.670) (3.693)
BED × AC1.905 *** 1.883 ***
(2.884) (2.861)
DNL −0.003−0.003
(−0.817)(−0.768)
BED × DNL 0.047 ***0.047 ***
(2.673)(2.676)
Size0.070 ***0.072 ***0.070 ***
(5.328)(5.441)(5.341)
ListAge−0.038 **−0.043 ***−0.039 **
(−2.359)(−2.687)(−2.448)
Board0.0470.0500.049
(1.092)(1.145)(1.121)
Indep0.0590.0490.055
(0.434)(0.361)(0.406)
Dual−0.016−0.016−0.016
(−1.102)(−1.118)(−1.098)
Top1−0.115−0.119−0.115
(−1.405)(−1.449)(−1.401)
TobinQ0.009 *0.009 **0.009 *
(1.821)(2.014)(1.826)
Lev0.0690.0610.071 *
(1.644)(1.449)(1.682)
Cashflow0.010−0.0010.009
(0.173)(−0.009)(0.147)
Constant−1.383 ***−1.419 ***−1.386 ***
(−4.256)(−4.359)(−4.264)
Industry FEYesYesYes
Year FEYesYesYes
N24,54624,54624,546
Adj. R20.0450.0440.046
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 5. The results for the dynamic panel system GMM model.
Table 5. The results for the dynamic panel system GMM model.
(1)(2)(3)
FTotalFGreInviaFGreUmia
Total0.309 ***
(3.251)
GreInvia 0.155 **
(2.145)
GreUmia 0.315 **
(2.557)
BED2.704 ***2.152 **2.367 *
(2.798)(2.306)(1.849)
Size−0.514−0.391−0.355
(−1.091)(−0.882)(−0.647)
ListAge0.3400.2680.029
(0.943)(0.761)(0.057)
Board−0.285−0.3830.863
(−0.189)(−0.331)(0.348)
Indep4.8212.7816.460
(1.133)(0.878)(1.433)
Dual0.0610.446−0.111
(0.140)(1.248)(−0.199)
Top1−1.611−0.8981.564
(−0.454)(−0.293)(0.273)
TobinQ−0.561 ***−0.318 **−0.885 **
(−3.157)(−2.009)(−2.269)
Lev−0.5480.5130.578
(−0.373)(0.365)(0.296)
Cashflow3.848 *1.7561.917
(1.830)(0.951)(0.902)
Industry FEYesYesYes
Year FEYesYesYes
N19,74719,74719,747
AR10.0000.0000.039
AR20.1960.1250.475
Sargan testp = 1.000p = 1.000p = 1.000
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 6. Authorized patents.
Table 6. Authorized patents.
(1)(2)(3)
GreTotalGreInviaGreUmia
BED0.858 ***0.469 **0.389 ***
(2.962)(2.425)(2.957)
Size0.434 ***0.219 **0.215 ***
(3.021)(2.015)(3.702)
ListAge−0.359 **−0.207 **−0.152 *
(−2.240)(−2.108)(−1.733)
Board1.3481.0680.280
(1.092)(1.131)(0.891)
Indep12.4822.0620.420
(0.713)(0.769)(0.455)
Dual−0.190 **−0.059 **−0.130 **
(−2.375)(−2.168)(−2.171)
Top10.7120.912−0.200
(0.781)(1.099)(−0.792)
TobinQ0.027−0.0140.040 **
(0.615)(−0.370)(2.159)
Lev0.3270.0620.264 **
(1.137)(0.278)(2.145)
Cashflow−0.040−0.0710.031
(−0.085)(−0.214)(0.133)
Constant−13.155 ***−7.818 **−5.337 ***
(−2.973)(−2.301)(−3.601)
Industry effectYesYesYes
Year effectYesYesYes
N22,60622,60622,606
Adj. R20.0080.0040.010
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 7. Tobit model.
Table 7. Tobit model.
(1)(2)(3)
GreTotalGreInviaGreUmia
BED0.430 ***0.450 ***0.328 ***
(4.232)(4.314)(3.102)
Size0.773 ***0.781 ***0.642 ***
(36.364)(35.689)(29.077)
ListAge−0.619 ***−0.544 ***−0.587 ***
(−23.182)(−19.805)(−20.981)
Board0.1170.161−0.039
(1.060)(1.431)(−0.339)
Indep10.0070.0600.127
(0.019)(0.154)(0.318)
Dual0.077 *0.107 **0.062
(1.854)(2.536)(1.450)
Top1−0.659 ***−0.765 ***−0.460 ***
(−5.058)(−5.738)(−3.422)
TobinQ0.112 ***0.134 ***0.031
(6.350)(7.495)(1.606)
Lev0.631 ***0.520 ***0.769 ***
(5.645)(4.538)(6.575)
Cashflow−0.664 **−0.785 ***−0.425
(−2.425)(−2.786)(−1.496)
Constant−19.303 ***−19.873 ***−16.624 ***
(−36.587)(−36.406)(−29.744)
Industry effectYesYesYes
Year effectYesYesYes
N24,54624,54624,546
Pseudo R20.0900.0980.098
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 8. Excluding the impact of the 2008 and 2015 financial crises.
Table 8. Excluding the impact of the 2008 and 2015 financial crises.
(1)(2)(3)
GreTotalGreInviaGreUmia
BED0.113 ***0.063 **0.065 **
(3.406)(2.321)(2.495)
Size0.071 ***0.057 ***0.040 ***
(5.232)(5.159)(4.092)
ListAge−0.042 **−0.028 **−0.026 **
(−2.505)(−1.965)(−2.011)
Board0.0540.058−0.009
(1.149)(1.379)(−0.245)
Indep10.0860.080−0.036
(0.576)(0.693)(−0.297)
Dual−0.015−0.015−0.012
(−0.994)(−1.252)(−1.101)
Top1−0.132−0.079−0.058
(−1.598)(−1.143)(−0.896)
TobinQ0.010 *0.010 **0.006
(1.959)(2.103)(1.615)
Lev0.0480.0540.030
(1.091)(1.521)(0.930)
Cashflow−0.032−0.0390.021
(−0.513)(−0.719)(0.459)
Constant−1.425 ***−1.243 ***−0.682 ***
(−4.138)(−4.656)(−2.623)
Industry FEYesYesYes
Year FEYesYesYes
N21,63821,63821,638
Adj. R20.0430.0380.030
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 9. Heterogeneity test results.
Table 9. Heterogeneity test results.
(1)(2)(3)(4)(5)(6)
SOEsNon-SOEs
GreTotalGreInviaGreUmiaRetotaledGreInviaGreUmia
BED0.0820.0590.0420.108 ***0.051 *0.073 **
(1.530)(1.328)(1.052)(2.827)(1.671)(2.371)
Size0.054 **0.053 ***0.0180.088 ***0.072 ***0.052 ***
(2.545)(3.092)(1.183)(5.241)(5.210)(4.298)
ListAge−0.037−0.020−0.036−0.0050.004−0.007
(−1.096)(−0.713)(−1.499)(−0.279)(0.246)(−0.488)
Board0.0680.069−0.0120.0360.0210.024
(1.059)(1.194)(−0.239)(0.619)(0.406)(0.595)
Indep10.1450.102−0.033−0.057−0.021−0.032
(0.743)(0.641)(−0.196)(−0.301)(−0.145)(−0.241)
Dual0.0020.002−0.001−0.022−0.018−0.023 *
(0.062)(0.079)(−0.056)(−1.191)(−1.163)(−1.664)
Top1−0.357 ***−0.277 **−0.1680.0450.0470.036
(−2.688)(−2.426)(−1.568)(0.451)(0.582)(0.476)
TobinQ0.0030.005−0.0030.013 **0.011 **0.005
(0.387)(0.801)(−0.525)(2.188)(2.183)(1.217)
Lev0.1010.0950.0530.0180.0120.032
(1.353)(1.551)(1.025)(0.388)(0.297)(0.904)
Cashflow−0.012−0.0190.0530.0290.0000.046
(−0.130)(−0.248)(0.758)(0.392)(0.007)(0.898)
Constant−0.960 *−1.089 **−0.083−2.014 ***−1.682 ***−1.219 ***
(−1.826)(−2.531)(−0.215)(−4.430)(−4.982)(−3.492)
Industry FEYesYesYesYesYesYes
Year FEYesYesYesYesYesYes
N10,32710,32710,32714,21914,21914,219
Adj. R20.0620.0600.0350.0360.0310.026
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 10. Mechanism test results.
Table 10. Mechanism test results.
(1)(2)(3)
GTotalRDSGTotal
BED0.103 ***0.401 **0.100 ***
(3.289)(2.133)(3.201)
RDS 0.009 ***
(4.003)
Size0.071 ***0.442 ***0.070 ***
(5.454)(5.382)(5.338)
ListAge−0.016−0.297 ***−0.017
(−0.995)(−3.407)(−1.036)
Board0.0330.2840.031
(0.816)(1.107)(0.772)
Indep−0.026−0.898−0.022
(−0.203)(−1.304)(−0.171)
Dual−0.018−0.036−0.018
(−1.272)(−0.425)(−1.261)
Top1−0.108−1.386 ***−0.102
(−1.316)(−3.197)(−1.242)
TobinQ0.008 *0.0450.008 *
(1.807)(1.348)(1.725)
Lev0.078 *−1.982 ***0.090 **
(1.818)(−7.261)(2.106)
Cashflow−0.019−0.498−0.010
(−0.337)(−1.634)(−0.182)
Constant−1.450 ***−6.026 ***−1.437 ***
(−4.493)(−3.387)(−4.453)
Industry FEYesYesYes
Year FEYesYesYes
N22,47722,47722,477
Adj. R20.0500.1640.052
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
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.

Share and Cite

MDPI and ACS Style

Zhao, X.; Wang, S.; Wu, X. Leveraging Board Experience Diversity to Enhance Corporate Green Technological Innovation. Sustainability 2025, 17, 3351. https://doi.org/10.3390/su17083351

AMA Style

Zhao X, Wang S, Wu X. Leveraging Board Experience Diversity to Enhance Corporate Green Technological Innovation. Sustainability. 2025; 17(8):3351. https://doi.org/10.3390/su17083351

Chicago/Turabian Style

Zhao, Xin, Shuyang Wang, and Xiaoyu Wu. 2025. "Leveraging Board Experience Diversity to Enhance Corporate Green Technological Innovation" Sustainability 17, no. 8: 3351. https://doi.org/10.3390/su17083351

APA Style

Zhao, X., Wang, S., & Wu, X. (2025). Leveraging Board Experience Diversity to Enhance Corporate Green Technological Innovation. Sustainability, 17(8), 3351. https://doi.org/10.3390/su17083351

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop