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Article

Political Connection Heterogeneity and Green Technological Innovation: Evidence from Chinese Listed Companies

School of Business, Macau University of Science and Technology, Macau 999078, China
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Author to whom correspondence should be addressed.
Systems 2025, 13(6), 443; https://doi.org/10.3390/systems13060443
Submission received: 13 May 2025 / Revised: 30 May 2025 / Accepted: 4 June 2025 / Published: 6 June 2025

Abstract

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With the continuous development of today’s economy and the growing interest in green technological innovation, this study investigates the impact of executive political connection heterogeneity (EPCH) on corporate green technological innovation (CGTI) in Chinese listed companies. Specifically, it distinguishes between ascribed and achieved political connections, examining their influence on incremental and radical CGTI. This study employs a quantitative research design, utilizing a sample of Chinese A-share listed companies from 2007 to 2022. Data are sourced from the China Securities Market & Accounting Research (CSMAR) database and the China National Research Data Service (CNRDS) database. The study analysis applies fixed-effect regression models to test the relationships between political connection heterogeneity and innovation outcomes. The findings reveal that ascribed political connections promote incremental innovation, while achieved political connections drive radical innovation. Moreover, strong GEO weakens the effect of ascribed political ties on incremental CGTI while enhancing the effect of achieved political ties on radical CGTI. These results contribute to the understanding of how political ties influence corporate innovation strategies and provide insights into the role of dynamic capabilities in green technological advancements.

1. Introduction

As global environmental challenges intensify, the contribution of enterprises to environmental protection and sustainable development is a matter of heightened concern. Corporate Green Technology Innovation (CGTI) has become the core of improving corporate competitiveness and promoting green transformation, encouraging green economic growth and sustainable social development by reducing the environmental impact of business operations, promoting the efficient use of resources, and creating new market opportunities [1,2]. CGTI is generally categorized as either incremental or radical innovation [3]. While incremental CGTI refers to small-scale, ongoing improvements to existing technologies, processes, or products, radical CGTI involves the transformative introduction of entirely new technologies or business models, but both forms are essential to advancing sustainable development, with incremental innovations often laying the groundwork for more radical breakthroughs [4]. In today’s globalized economy, where environmental regulations have become more stringent, it is clear that environmentally sustainable technological innovation is critical not only to the success of individual companies but also to the wider socio-economic system. However, pursuing CGTI faces significant challenges. For example, it requires large R&D investments and long-term financial commitments, which can be a particularly large burden for companies with limited resources. Not only that, but green technologies carry further risks, as they tend to have a negative impact on the environment [5].
Existing research on CGTI has identified a number of factors affecting its development, including internal resource allocation, organizational structure, corporate culture, and external environmental pressures [6,7]. However, in China, political–business relations are unique, and the government’s role in shaping corporate strategy is particularly significant [3]. Internal factors such as R&D investment, human capital, and managerial innovation awareness play a key role in driving green technological advances [8], but the Chinese political system uniquely shapes the relationship between firms and government resources. In China, government policies often directly incentivize green technological innovation through subsidies, favorable regulations, and state-driven economic plans, making political connections an essential factor in corporate innovation strategies [9]. These unique institutional factors in China necessitate a different approach to understanding the relationship between political ties and CGTI compared to studies conducted in other countries. Our study argues that stakeholder theory plays a crucial role in understanding corporate innovation, emphasizing that pressures and expectations from government entities, consumers, and non-governmental organizations (NGOs) significantly influence firms’ innovation decisions. This argument aligns with the findings of [10], which similarly highlight the role of external stakeholders in shaping innovation strategies. However, despite extensive theoretical and empirical research on the various drivers of CGTI, there are still significant gaps in understanding the impact of executive political connection heterogeneity (EPCH) on green technology innovation.
EPCH means diversity in the type and depth of political relationships among top executives [11], where attributional political relationships are formed through personal backgrounds, family ties, or social status, which typically provide executives with stable, ongoing political resources. Meanwhile, achievement-based political ties are built through personal effort, achievement, or successful program execution, reflecting a more dynamic and contingent corporate structure [12]. While these different types of ties can affect a firm’s CGTI approach in different ways, current research has not yet fully explored how this heterogeneity specifically affects green technology innovation [13]. Based on the complexity of this issue, this study aims to fill this gap by distinguishing between attributional and realization-based political connections and examining their respective effects on CGTI. By examining how these two types of political connections affect corporate environmental innovation, we provide new theoretical insights into the role of political connections in shaping corporate sustainability strategies.
Green Entrepreneurial Orientation (GEO) has also become an important driver of sustainable development. Among them, Green Entrepreneurial Orientation (GEO) is a key link between firms and their strategic environments, and it has a significant impact on green technology innovation [14,15]. However, a single-direction research approach is insufficient to fully elucidate the complex mechanisms by which GEO affects CGTI. Therefore, this study discusses Green Entrepreneurial Orientation in conjunction with organizational dynamic capabilities to provide a more comprehensive theoretical understanding. On the one hand, green venture industry orientations contribute to the firm through international perspectives and diverse knowledge resources [16]. They usually have extensive cross-cultural management experience and insights into the global marketplace, enabling them to identify and adopt advanced environmental technologies and management practices more effectively [17,18]. Overseas experience also enhances managers’ network resources and facilitates international cooperation and knowledge exchange, which improves access to external innovation resources and, in turn, strengthens a firm’s CGTI capabilities [19]. On the other hand, organizational dynamic capabilities, which refer to a firm’s ability to perceive, capture, and reconfigure resources in response to changing environmental conditions, play a crucial role in achieving CGTI. Among these dynamic capabilities is the organization’s ability to identify, capture, transform, and apply external knowledge [20]. In the context of high CGTI, organizations must have strong dynamic capabilities in order to effectively utilize a variety of political resources to drive environmental technology innovation. Organizations with strong dynamic capabilities are better able to integrate the knowledge and resources of executives from different political connections, thus facilitating the successful implementation of innovation projects [21]. Thus, organizational dynamic capabilities are a key moderating variable between executive entrepreneurial orientation and CGTI, influencing the effectiveness of the latter.
This study provides several theoretical contributions. First, it distinguishes between ascribed and achieved political connections and consequently clarifies how EPCH influences CGTI. A persistent theoretical gap in the extant literature lies in the institutional theory’s predominant focus on formal institutional forces—such as markets and regulatory frameworks—while largely neglecting the role of informal institutions, such as political connections. Although institutional theory offers a valuable lens for understanding how political ties influence firms’ green innovation strategies, existing empirical findings remain inconclusive. Some studies suggest that political connections facilitate green strategic initiatives [22], whereas others report null or even negative effects. We argue that this inconsistency stems [23] from an underappreciation of top executives’ roles in mediating institutional pressures. In response, our study extends institutional theory by theorizing political ties as a form of informal institutional arrangement whose influence manifests not only through enhanced access to external resources but also via executives’ political preferences and cognitive framing of environmental imperatives. Furthermore, we contribute to the literature by identifying sources of heterogeneity in institutional effects. Rather than assuming institutional pressures are homogenous exogenous forces, we show that their salience and impact depend critically on executives’ political identities and sense-making processes. Therefore, we offer a contextualized and behaviorally grounded extension of institutional theory, consistent with Barney’s [24] call for “normal science” contributions that redirect existing theory toward novel and theoretically meaningful domains.
Additionally, this study differentiates between incremental CGTI as minor, continuous improvements to existing technologies, processes, or products [25] and radical CGTI, characterized by substantial, transformative changes and entirely new technologies or business models. These distinctions enrich the theoretical discourse on the relationship between political connections and CGTI [26]. While traditional research often ignores the inherent diversity of political connections by treating it as a single-dimensional construct, this study deepens our understanding of the complex mechanisms through which political connections operate by offering a more nuanced perspective.
Second, this research integrates GEO and organizational dynamic capabilities into the theoretical framework, expanding the scope of environmental innovation literature and addressing gaps in moderating mechanisms [27,28]. Whereas previous studies have largely focused on single variables affecting CGTI, the present study utilizes these moderating factors to develop a more comprehensive model to explain how multiple elements collectively influence CGTI. While traditional theories often neglect executive-level heterogeneity [29], this research shows that different types of political connections have varying effects on CGTI under different moderating conditions, thus advancing the theoretical understanding of political connections in corporate green innovation strategies. By exploring the differential impacts of ascribed and achieved political connections alongside executives’ sustainability orientations and dynamic capabilities, this study contributes to the development of political connection theories in environmental innovation.

2. Literature Review

CGTI plays a crucial role in improving environmental sustainability and gaining competitive advantage, particularly in the Chinese context, where political–business relations are deeply embedded in corporate strategy. It involves the development and implementation of technologies that reduce environmental impacts, optimize resource use, and create new market opportunities [30]. In China, CGTI is not only an environmental imperative but also a strategic necessity, influenced significantly by government policies and political connections [31]. Incremental CGTI, such as improved energy efficiency, waste management, and extended product life cycles [32], is essential for companies to minimize disruptions and comply with China’s stringent environmental regulations. These innovations are often driven by ascribed political connections, which offer firms stable access to government resources and incentives. In contrast, radical CGTI, involving more transformative innovations like clean energy technologies, typically requires the dynamic, high-risk strategies fostered by achieved political connections, where firms leverage personal achievements to access government resources and funding for breakthrough innovations [33].
Radical CGTI introduces entirely new technologies or business models compared to incremental ones, such as clean energy technologies, zero-emission manufacturing processes, and circular economy models. Radical innovations, while requiring large investments and longer development times, can have far-reaching environmental benefits [34]. These innovations position companies as sustainability leaders and provide access to emerging markets driven by environmental sustainability. This study builds on recent work by Bu and Chen [35], which explores the relationship between executive political connections and green innovation strategies in firms. Internal factors such as investment in R&D, human capital, and awareness of managerial innovation are key drivers of green technological innovation [36,37]; not only that, but the organizational structure and corporate culture also play an important role by creating an environment conducive to innovation and sustainability. Analyzing the external factors, market demand fluctuations, competitive pressures, regulatory policies, and social responsibility compel firms to innovate in environmental technologies [37,38]. These external factors motivate firms to adapt to changing market dynamics and encourage them to take the lead in sustainable development.
The political connections are access to resources, policy support, and a favorable regulatory environment, which can have a strong influence on CGTI, where political connections can be ascribed and achieved [39]. Ascribed political ties include an executive’s family connections, social standing, or prior government positions; such ties offer permanence and long-term access to policy benefits and resources [40]. Companies that have this type of relationship normally take a conservative, incremental CGTI approach. Due to their already established resource base and existing environmental regulations, they concentrate on maximizing the use of already existing resources and processes, such as enhancing energy efficiency or reducing waste emissions [41].
Conversely, achieved political connections may stem from executives’ demonstrated competencies or the exceptional performance of organizations on specific projects [42]. This relationship is dynamic and competitive, and the parties involved need to consistently validate their business excellence and innovative potential. The ability to leverage existing social networks pushes firms towards aggressive and innovative CGTI strategies [43], such as investing heavily in R&D to develop new technologies or to penetrate emerging markets. Radical CGTI, for example, is characteristic of this strategic orientation, as are clean energy technologies or circular economy models [44]. These innovations require a high degree of investment and risk appetite but present transformative opportunities for firms to position themselves as leaders in sustainability, along with access to environmentally driven emerging markets [45].
Institutional theory provides a foundational lens for understanding how external pressures shape organizational behavior. While prior work has largely treated political ties as a monolithic institutional force, we argue that political connections are heterogeneous in nature—varying in form, depth, and function—and should be theorized as differentiated informal institutional arrangements [46]. This heterogeneity conditions the extent to which firms perceive, interpret, and respond to institutional expectations, leading to divergent strategic outcomes in green innovation. The heterogeneity of political linkages highlights their different impacts on CGTI: attributional linkages provide a stable foundation for incremental improvements, while realization linkages drive firms to transformative and disruptive innovations. Analyzing this duality helps to understand how companies balance regulatory compliance with the pursuit of breakthrough CGTI solutions. The GEO and the dynamic capabilities of a business also influence how political connections translate into CGTI efforts. Leaders committed to sustainability will therefore prioritize environmental goals, which will influence whether the innovations their companies undertake are incremental or radical. Dynamic capabilities—the ability to sense, integrate, and reconfigure resources in a changing environment—enable firms to make the best use of their resources, adapt to environmental change, and effectively implement sustainable technologies.

3. Hypothesis Development

3.1. Ascribed Political Connections and Incremental Corporate Green Technological Innovation

Ascribed political connections offer firms long-term access to government resources such as subsidies and favorable policies [47,48]. These connections provide a stable foundation for pursuing incremental CGTI, which focuses on improving existing technologies and processes with low-risk and moderate investment requirements. Recent studies suggest that these stable political ties reduce uncertainty and allow firms to confidently invest in incremental innovations that improve energy efficiency or reduce emissions [49,50].
First, ascribed political connections can ensure continued government support to promote incremental CGTI strategies. These innovations involve incremental improvements that incorporate increased energy efficiency or reduced emissions, compliance with regulatory expectations, and other strategies that are easier to implement [51]. The long-term nature of political relations reduces uncertainty and allows companies to invest in incremental innovations with confidence.
Secondly, firms can utilize stable political relationships to develop CGTI more vigorously in order to achieve improvements in their environmental performance and sustainability reputation. Thus, firms can maintain political relationships while improving operational efficiency [52]. Low-risk, incremental innovation is well suited to the allocation of resources provided by political relationships, ensuring that firms can focus on incremental improvements without major disruptions.
Thirdly, according to Resource Dependence Theory (RDT), external resources (e.g., those provided by political relationships) are critical for achieving organizational goals [53]. Where ascribed political relationships can ensure a reliable flow of resources and further reduce environmental uncertainty. It can help firms to be able to focus on low-cost, low-risk incremental innovations, which in turn can lead to significant long-term improvements in environmental performance and operational efficiency. Therefore, we propose the following hypothesis:
Hypothesis 1a (H1a).
Firms with a greater number of ascribed political connections generate more incremental CGTI.

3.2. Achieved Political Connections and Radical Corporate Green Technological Innovation

Achieved political linkages are established through firms’ performance, their ability to innovate, and their contribution to government goals [22]. We argue that these linkages are dynamic and that they require firms to continuously demonstrate excellence in innovation and environmental performance. Recent studies suggest that achieved political connections enable firms to access government resources, which facilitates high-risk innovation projects and helps drive radical CGTI, such as the development of clean energy technologies and circular economy models [54,55]. These linkages often allow firms to take the lead in introducing disruptive innovations that transform industries. In this regard, firms will be more motivated to adopt more ambitious strategies, including significant R&D investments to pioneer new technologies or enter emerging markets [56].
First, the achieved political connections gained incentivize companies to pursue radical CGTI, which encompasses many aspects. Examples include breakthrough technologies or new business models, or perhaps new clean energy technologies or zero-emission manufacturing processes. While these innovations are high-risk and require significant investment, they can lead to competitive advantage and market leadership. Firms with access to achieved political connections have an even greater need to comply with high government environmental standards, fully utilize their capacity to innovate, and become market leaders through disruptive technologies [57].
Second, the resource-based view (RBV) argues that firms with superior resources and capabilities will gain more competitive advantage [58]. Therefore, organizations with achieved political connections can leverage their innovative capabilities and performance to gain government support, and this type of support helps firms to be able to engage in high-risk, high-reward radical innovations. Adopting a radical CGTI strategy not only ensures that firms comply with stringent environmental regulations but also differentiates them in the marketplace and further enhances their political and competitive position.
Third, based on attribute characterization, radical CGTIs fit RBV’s VRIN attributes (Valuable, Rare, Inimitable, and Irreplaceable) because these strategies often involve proprietary technologies or unique business models. Firms with achieved political connections create innovations that are difficult to replicate, which in turn consolidate their market position and strengthen their political connections. Pursuing such high-return innovations allows companies to consolidate their position as leaders in environmental sustainability and further expand their growth opportunities. Therefore, we propose the following hypothesis:
Hypothesis 1b (H1b).
Firms with a greater number of achieved political connections generate more radical CGTI.

3.3. Green Entrepreneurship Orientation as a Moderator

Having established how ascribed political connections shape incremental CGTI, we should now discuss executive characteristics. According to upper echelons theory, the values and orientations of top executives have a substantial impact on strategic decisions and organizational outcomes [59]. In this regard, one of the most important aspects influencing GEO includes social responsibility, first-mover advantage, innovative capability, and environmental commitment [60]. Strong GEO firms fuse sustainability in everything they do—the very essence of their entrepreneurial endeavor as well as being good stewards of limited resources—and drive new and improved ways to address ecological dilemmas [61]. Recent studies indicate that firms with strong GEO are more likely to leverage their political connections not only for incremental improvements but also for radical green innovations. These firms tend to align their strategies with long-term sustainability goals, utilizing political connections to pursue transformative innovations that address critical ecological challenges [62,63].
First, GEO affects how firms use their political connections for green innovation. Firms with strong GEOs are more likely to use political connections to support incremental CGTIs that are consistent with their long-term sustainability goals, focusing on high-quality, lasting innovations rather than frequent small changes. This ensures that political resources are utilized to improve environmental performance without disrupting existing operations [64,65].
Second, in today’s climate characterized by rapid technological advances and intense competition, a strong GEO may encourage firms to prioritize long-term, sustainable innovation. As a result, firms will place less emphasis on incremental improvements and be more inclined to adopt more impactful and environmentally friendly technologies. Thus, while firms with stronger GEOs may have fewer innovation programs, their incremental CGTIs are more strategically aligned and determine how political relationships drive innovation. Based on these observations, the following hypothesis is proposed:
Hypothesis 2a (H2a).
A strong GEO attenuates the positive relationship between a firm’s ascribed political connections and the quantity of incremental CGTI.

3.4. Green Entrepreneurship Orientation and Achieved Political Connections

Political connections are achieved that are dynamic and competitive in nature, and firms need to robustly perform in innovation and environmental performance to stay connected and receive benefits. As a result, this network encourages the adoption of broader strategies that require large investments, e.g., investment into the R&D of clean energy technologies, zero-emission processes, and circular economy [66]. Such innovations enable firms to comply with stricter governmental requirements and lead to technological advancement and new business models that position the firm as a leader in the market. Recent studies suggest that firms with strong GEO are more likely to leverage their political connections for both incremental and radical green innovations, aligning their strategies with long-term sustainability goals and gaining a competitive edge in the market [62].
First, we argue that GEO plays a critical role in how firms leverage their achieved political connections to drive radical CGTI. Firms with a strong GEO are more likely to utilize political ties to support ambitious and long-term environmental goals. This fosters an organizational culture that embraces bold innovation efforts, ensuring that political resources are directed towards projects that enhance both environmental performance and competitive positioning [67].
Second, there is inherent uncertainty in radical innovations, and firms with a strong GEO are better positioned to navigate the complexities of fast-moving and competitive industries. A healthy GEO allows companies to pursue risky projects while assuring the resulting initiatives lead to real technological progress and market leadership. The increased positive effect of acquired political assets on borderline innovations enables firms to differentiate themselves in the market [68].
Third, strong GEO executives are more skillful at strategically allocating resources to high-risk, high-reward projects, bolstering their firm’s reputation as an environmental innovator. More policy support and resources attract more availability for the species and amplify the radical CGTI capacity available at the firm [69]. Thus, the positive influence of realized political connections on radical CGTI is stronger in the firms possessing a dedicated GEO than those having a lower commitment to sustainability or weaker technological innovation capabilities. Thus, we propose the following hypothesis:
Hypothesis 2b (H2b).
A strong GEO among firms enhances the positive relationship between a firm’s achieved political connections and radical CGTI.

3.5. Dynamic Capabilities Moderate Ascribed Connections’ Impact on Incremental Innovation

Reliable political relationships can provide companies with access to government resources such as subsidies, tax incentives, and policy support, and such relationships are critical for companies to pursue incremental CGTI. These innovations often involve incremental improvements to existing processes, such as improving energy efficiency or reducing emissions. However, the effectiveness of ascribed political relationships in promoting progressive CGTI may be influenced by the internal capacity of firms.
First, dynamic capabilities theory suggests that a firm’s ability to adapt and reconfigure its internal resources to respond to changing market conditions plays a key role in shaping its innovation outcomes [70]. Firms with high dynamic capabilities are better able to perceive market opportunities, seize them through strategic initiatives, and adjust their operations accordingly. These firms are also less dependent on external resources, including political connections. Recent studies show that firms with strong dynamic capabilities can leverage both internal and external resources more effectively, reducing their reliance on ascribed political connections for incremental innovations [8]. These firms are able to strategically allocate resources to R&D and process optimization, which drives sustainable and impactful green innovations [71].
Second, because dynamic capabilities enhance the ability of firms to manage their internal resources, they may become more self-sufficient in their pursuit of innovation. Therefore, firms that possess strong dynamic capabilities may become less dependent on the inert resources derived from ascribed political connections. We see that they focus on internal capabilities, including R&D, operating solutions, and process optimization, which drive adoption of more strategic incremental CGTI, having long-term implications [72].
Third, the power of dynamic capabilities helps organizations to allocate resources more efficiently and foster a culture of continuous improvement and operational excellence. This enables firms to achieve incremental CGTI and therefore has implications for improving sustainability and environmental performance. This shows that for firms with strong dynamic capabilities, the positive correlation between ascribed political connections and incremental CGTI is pronounced. We therefore propose the following hypothesis:
Hypothesis 3a (H3a).
Robust dynamic capabilities within a firm attenuate the positive relationship between ascribed political connections and the quantity of incremental CGTI.

3.6. Dynamic Capabilities Moderate Achieved Connections’ Impact on Radical Innovation

A firm’s performance, innovation, and contributions to governmental goals cultivate achieved political connections through making them inherently dynamic and competitive. These relationships are common for firms that must constantly prove their innovation and environmental performance so as to keep those relationships and incorporate more [73]. Often times, radical CGTI entails a breakthrough technology or a completely new business model, which has an enhanced risk profile and claims a meaningful investment but which can deliver a much stronger competitive advantage as well as market leadership [74]. Recent studies highlight that firms with strong dynamic capabilities are better equipped to leverage their political connections to promote radical CGTI. These capabilities allow firms to combine external resources, such as government support, with their internal innovation capacity, ensuring that high-risk innovation projects are implemented effectively and deliver substantial environmental and competitive benefits [71,75].
First, dynamic capabilities theory suggests that firms with strong dynamic capabilities are better able to leverage their acquired political connections to promote radical CGTI. These capabilities enable firms to combine external resources, such as government support, with internal capabilities to provide assurances that high-risk innovation projects will be implemented [76]. These organizations are able to successfully navigate the complexity and uncertainty inherent in radical innovations, ensuring that these projects produce significant environmental and competitive benefits.
Second, having a strong dynamic capability is more conducive to the efficient allocation of resources and helps firms to respond quickly to changing market and regulatory demands. Executives who are both dynamic and sustainability-oriented are better positioned to invest in aggressive CGTI programs that meet the firm’s long-term sustainability goals and government environmental standards [77,78]. This proactive approach ensures that firms comply with stringent regulations and establish themselves as technology leaders in the marketplace, thereby strengthening and expanding their political connections.
Third, in fast-changing and competitive industries, firms with superior dynamic and technological capabilities are able to use political connections to reduce competition through radical innovation. This explosive growth in their political power and reputation only further attracts governmental policies and resources to their endeavors. Thus, the impact of secured political connections on radical CGTI is more pronounced among firms with strong dynamic capabilities relative to firms with weak dynamic capabilities. Based on these insights, our final hypothesis is as follows:
Hypothesis 3b (H3b).
Robust dynamic capabilities within a firm enhance the positive relationship between achieved political connections and the quantity of radical CGTI.

4. Methodology

4.1. Data and Sample

This study uses data from Chinese A-share listed companies to examine the relationship between political connections and green technological innovation (CGTI). The focus on Chinese A-share firms is critical, as the political–business relationship in China is distinct due to the country’s unique political system, where government influence is particularly strong in shaping corporate strategies [79,80]. This dataset provides valuable insights into how political connections specifically impact CGTI within the Chinese political and business context, where the government plays an active role in economic development and environmental policy [81]. The China Securities Market & Accounting Research (CSMAR) database was utilized as the primary source for firm-level variables, including company fundamentals, financial metrics, and R&D activities [82]. We supplemented our dataset with information from the China National Research Data Service (CNRDS) database to address gaps in firm-level data within the CSMAR database [82,83]. Government-related data were sourced from official Chinese statistical publications, and official agency names were meticulously matched and merged with firm TMT data to construct indicative variables for political connections [84].
To measure CGTI indicators, this study extracted green patent data from listed companies within the CNRDS database and integrated these with financial and non-financial data to ensure precise CGTI metrics. To maintain data integrity and accuracy, any observations missing critical variable information were excluded from the analysis. Consequently, we assembled an unbalanced panel dataset. During the data preprocessing phase, all continuous variables were winsorized at the 1st and 99th percentiles to mitigate the impact of extreme outliers. This procedure effectively reduced extreme variability within the data, thereby enhancing the reliability and robustness of the model estimations.

4.2. Variables

4.2.1. Dependent Variables

Following established research methods [85,86,87,88,89], we measured CGTI by analyzing the number of green patent applications filed by firms to measure CGTI. This study focuses on patent applications rather than granted patents, a choice made for two main reasons. First, because patent applications reflect innovations in progress prior to the approval process, they provide a more accurate picture of ongoing innovation efforts and management decisions [87]. Second, patent applications (both pending and granted patents) provide a more complete picture of a firm’s innovation pipeline and contribute to a more accurate understanding of the relationship between political connections and firm innovation.
We use green invention patents and utility model patents as a proxy for distinguishing between aggressive and progressive CGTI. This is because these two types of patents differ in terms of filing procedures and examination in China’s patent system. Green invention patents require a higher level of inventiveness and undergo rigorous substantive examination and often lead to more significant technological breakthroughs. As such, these patents represent fundamental innovations, characterized by significant advances in core principles or applications. In contrast, green utility model patents are subject only to formal examination, with lower barriers to entry and shorter approval times. While novelty and some degree of technological improvement are also required, they are typically used for incremental innovations that focus on refining or optimizing existing green technologies. Distinguishing between these two types of patents can therefore help to identify radical versus incremental green innovations, with invention patents reflecting disruptive change and utility models representing more gradual advances.

4.2.2. Independent Variable

Building on the framework developed by Zhang et al. [90], this study categorizes EPCH into inherent and established political connections. Inherent political connections are quantified by the proportion of executives in a firm with government work experience, i.e., each executive has an inherent political connection value of 1 if he or she has served or is serving as a central or local government official [91,92]. Firms’ political connection scores reflect the total number of executives with government experience. In contrast, acquired political connections are measured by the proportion of executives who are members of the National People’s Congress (NPC) or the Chinese People’s Political Consultative Conference (CPPCC).

4.2.3. Moderating Variables

According to Averina et al. [60], the first moderating variable in this study is GEO, which is conceptualized from four key dimensions: social responsibility, first-mover advantage, innovativeness, and environmental commitment. To measure social responsibility, we used the Corporate Social Responsibility (CSR) index derived from the cash flow component, calculated as (net profit + income tax + business tax and surcharges + cash paid to employees + employee compensation changes + financial expenses + donations and environmental remediation expenses) divided by the average number of outstanding shares. The first-mover advantage was measured by the sustainable growth rate from the CSMAR database, which indicates a firm’s capacity to seize early market opportunities. The coefficient ratio between R&D investments and gross revenue denotes an innovative ability, which indicates a firm’s commitment to green innovations. Ultimately, environmental commitment was measured by ISO14001 certification [93] with a binary value for types (ISO and non-ISO), where certified companies were assigned a score of 1 and non-certified companies 0. These measures were combined into a GEO index, which acted as a moderating variable in our analytical model. Together, these steps illustrate a multi-faceted exploration of the phenomenon of GEO, albeit within the wider field of strategic management of strategic management scholars.
The second moderating variable is dynamic capabilities (DCs). Based on Teece’s capability framework [94] and Wu’s measurement approach [95], we measured dynamic capabilities of firms in five dimensions to capture the distinctive characteristics and development paths of listed manufacturing companies in China during a period of rapid economic growth and social change. The five dimensions measured include environmental adaptability (EA), coordination and integration capability (CA), learning and absorptive capacity (LA), resource reconfiguration ability (RA), and innovative transformation capability (IC).
EA was operationalized as the firm’s return on assets (ROA) vis-a-vis the industry average ROA, with larger gaps capturing a stronger competitive advantage and the higher capacity for the firm to accommodate changes from its external environment [96]. Higher ratios indicate a greater degree of converting knowledge into products, and hence CA was measured by the ratio of R&D expense to current operating costs [95]. The proportion of employees with at least a bachelor’s degree served as a proxy for LA in LA and was used to reflect the absorptive capabilities of firm members (individual absorptive capability) and the extent to which they support the acquisition and application of knowledge [72]. The RA was assessed by the net profit margin (the ratio of net profit to total assets), where a larger margin meant higher efficiency in the allocation of resources and adjustment of structure, and thus, better ability for reconfiguration of resources [96]. Finally, we computed the IC ratio based on the yearly growth rate of patent applications as a proxy for the intensity and efficiency of a firm’s innovation and technological transformation efforts [97].
The entropy weighting method was used to integrate these five dimensions into a unified measure of dynamic capabilities. This method assigns appropriate weights to each dimension to ensure that all aspects are fully represented in the final composite score. The entropy weight method not only takes into account the information entropy of each dimension but also effectively reduces the bias that may arise from a single indicator, thus improving the accuracy and reliability of the comprehensive assessment of dynamic capabilities.

4.2.4. Control Variables

We incorporated control variables into our econometric model to mitigate the confounding impact of other factors that might affect CGTI. Referring to the relevant literature [98,99,100], we controlled for firm-level characteristics including firm size (Size), firm age (Age), board size (Board), board independence (Indep), profitability (Roa), financial leverage (Lev), corporate growth (Growth), cash flow (Cash), shareholdings of the five largest shareholders (Top5), and institutional investors (INST). Table 1 presents definitions for each variable and descriptive statistics.

4.3. Model Specifications

Building on firm-level panel data, this study employed a fixed-effects (FE) model in Stata 18 to examine the impact of ascribed and achieved political connections on incremental green innovation (GreUmia) and radical green innovation (GreIn-via). We used firm- and year-fixed effects as they provide a more stringent form of control, accounting for time-invariant company-specific heterogeneity and other company- and time-related factors that might influence CGTI.
To ensure the appropriateness of the fixed-effects model, we conducted the Hausman test. The Hausman test compares the fixed-effects model against the random-effects model by evaluating the consistency of the coefficient estimates. The test statistic was calculated and compared with a critical value at the 0.05 significance level. If the p-value of the Hausman test was found to be less than 0.05, we rejected the null hypothesis that the random-effects model is appropriate, thereby selecting the fixed-effects model for our analysis. Based on the results of the Hausman test, the fixed-effects model was deemed more suitable for this study.
Furthermore, considering that the dependent variable (CGTI) comprises overdispersed count data with a skewed distribution, we followed the standard practice of applying a logarithmic transformation before conducting OLS regression [16]:
GreUmiai t = α 0 + α 1 Ascribed i , t + α 2 Achieved i , t + α k Control i , t + Industry + Year + ϵ i , t
GreInvia t = β 0 + β 1 Ascribed i , t + β 2 Achieved i , t + β k Control i , t + Industry + Year + ϵ i , t
where GreUmia and GreInvia represent incremental and radical CGTI, respectively. Ascribed and Achieved are the primary independent variables measuring ascribed and achieved political connections. Control includes the control variables; Industry and Year denote fixed effects for industry and year, and ε is the error term.
To test the moderating role of GEO, we extended the baseline models by incorporating interaction terms between GEO and the political connections variables. The extended models are specified as follows:
G r e U m i a i t = γ 0 + γ 1 A s c r i b e d i , t + γ 2 A c h i e v e d i , t + γ 3 G E O i , t + γ 4 G E O i , t × A s c r i b e d i , t + γ 5 ( G E O i , t × A c h i e v e d i , t ) + γ 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
G r e I n v i a t = δ γ 0 + δ 1 A s c r i b e d i , t + δ 2 A c h i e v e d i , t + δ 3 G E O i , t + δ 4 ( G E O i , t × A s c r i b e d i , t ) + δ 5 ( G E O i , t × A c h i e v e d i , t ) + δ 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
The interaction terms (GEO × Ascribed and GEO × Achieved) allow us to assess how GEO moderates the relationship between political connections and CGTI. By incorporating these interaction terms, we can evaluate whether the firm’s orientation toward sustainability and green entrepreneurship strengthens or weakens the influence of ascribed and achieved political connections on incremental and radical green innovations.
For the final stage, we extended the baseline models by incorporating interaction terms between DC and the political connections variables to test the moderating role of DC. The extended models are specified as follows:
G r e U m i a i t = γ 0 + γ 1 A s c r i b e d i , t + γ 2 A c h i e v e d i , t + γ 3 D C i , t + γ 4 ( D C i , t × A s c r i b e d i , t ) + γ 5 ( D C i , t × A c h i e v e d i , t ) + γ 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
G r e I n v i a t = δ γ 0 + δ 1 A s c r i b e d i , t + δ 2 A c h i e v e d i , t + δ 3 D C i , t + δ 4 ( D C i , t × A s c r i b e d i , t ) + δ 5 ( D C i , t × A c h i e v e d i , t ) + δ 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
Here, the interaction terms (DC × Ascribed and DC × Achieved) allow us to assess how DC moderates the relationship between political connections and CGTI.

5. Empirical Results

5.1. Descriptive Statistics

Table 2 presents the descriptive statistics for the main regression variables. On average, firms report a radical CGTI (GreInvia) score of 0.295 (SD = 0.660) and an incremental CGTI (GreUmia) score of 0.262 (SD = 0.602), indicating that both types of innovation are relatively infrequent within the sample. The mean proportions of ascribed (Ascribed) and achieved political connections (Achieved) are 0.024 (SD = 0.040) and 0.017 (SD = 0.033), respectively, indicating that political connections are not widespread. GEO has a mean of −0.153 (SD = 0.105), showcasing a diverse range of sustainability-oriented entrepreneurial activities among firms. Dynamic capability (DC) has an average value of 0.068 (SD = 0.029), suggesting moderate levels of adaptability and innovation capacity within the sample. Additionally, in line with previous studies [101], control variables such as size (Mean = 22.047, SD = 1.161) and age—with a mean of 2.145 years (SD = 0.750)—exhibit considerable variation.

5.2. Main Results

Table 3 presents the baseline regression results for incremental (Model 1) and radical (Model 2) CGTI. To test Hypothesis 1a (H1a), we first examine the impact of ascribed political connections on incremental CGTI. Model 1 shows that ascribed political connections exert a significantly positive effect on incremental CGTI (coef. = 0.359, p < 0.01). This finding supports H1a, which posits that firms with more ascribed political connections are more likely to pursue incremental innovations. This result is consistent with Resource Dependence Theory (RDT), which suggests that stable political ties provide firms with reliable access to external resources, enabling them to focus on low-risk, incremental improvements. Ascribed political connections reduce uncertainty and offer long-term support, which is especially conducive to incremental technological innovation. Moreover, the size of the firm also exhibits a positive effect on incremental CGTI (coef. = 0.050, p < 0.01), consistent with Upper Echelon Theory, which argues that larger firms have more resources and organizational capabilities, thereby enabling them to drive incremental innovation.
To test Hypothesis 1b (H1b), we analyze the impact of achieved political connections on radical CGTI. Model 2 demonstrates that achieved political connections significantly enhance the level of radical CGTI (coef. = 0.455, p < 0.01), supporting H1b. This finding aligns with dynamic capabilities theory, which emphasizes that firms with robust dynamic capabilities are better positioned to leverage external resources, such as political connections, to pursue high-risk, high-reward innovations. Firms with stronger achieved political connections are more likely to engage in breakthrough innovations that require substantial investments and technological advancements. Additionally, firm size remains a positive predictor of radical CGTI (coef. = 0.068, p < 0.01), underscoring the role of larger firms in driving more radical technological changes. These findings reinforce the idea that ascribed political connections are more conducive to incremental innovation, while achieved political connections play a crucial role in promoting radical innovation. These results confirm the validity of Hypotheses H1a and H1b.

5.3. Moderating Effect Results

To assess the moderating effects of Green Entrepreneurial Orientation (GEO) and dynamic capabilities (DCs), interaction terms involving GEO, DC, and the two types of political ties were included in the regression models. In Column (1) of Table 4, which examines the impact on incremental CGTI (GreUmia), the interaction between ascribed political ties and GEO (Ascribed × GEO) is significantly negative (coef. = −6.276, p < 0.05). This indicates that a strong GEO weakens the positive relationship between ascribed political ties and incremental green innovation, supporting Hypothesis 2a (H2a). Firms with a robust sustainability orientation, as reflected in GEO, are likely to prioritize long-term ecological goals over leveraging political ties for short-term incremental advancements. This finding is consistent with Upper Echelons Theory, which suggests that executives with a strong focus on sustainability are more inclined to pursue strategic, long-term environmental goals rather than relying on politically driven incremental changes.
By contrast, in Column (2), which focuses on radical CGTI (GreInvia), the interaction between achieved political ties and GEO (Achieved × GEO) is significantly positive (coef. = 16.410, p < 0.05). This suggests that a strong GEO amplifies the positive effect of achieved political ties on radical green innovation, providing support for Hypothesis 2b (H2b). Firms with high levels of GEO are more likely to leverage their political ties for major technological breakthroughs, aligning with dynamic capabilities theory, which emphasizes that firms with a strong sustainability orientation can better harness external resources for high-risk, high-reward innovations.
In Columns (3) and (4), the moderating role of DC is further examined. The interaction between DC and ascribed political connections (Ascribed × DC) in Column (3) is significantly negative (coef. = −6.840, p < 0.05), whereas the interaction between DC and achieved political connections (Achieved × DC) in Column (4) is significantly positive (coef. = 16.794, p < 0.05). These results suggest that DC moderates the relationship between political ties and the type of CGTI in different ways. DC reduces the influence of ascribed political ties on incremental innovation, supporting Hypothesis 3a (H3a). Firms with stronger dynamic capabilities are less reliant on ascribed political connections for incremental innovations, instead leveraging internal resources to drive innovation. On the other hand, DC strengthens the relationship between achieved political ties and radical CGTI, providing support for Hypothesis 3b (H3b). Firms with strong dynamic capabilities are better positioned to effectively use their political resources for transformative green technological innovations. This finding reinforces the idea that firms with robust DC are more adept at leveraging both internal and external resources to foster radical innovation. These results highlight that GEO and DC play significant moderating roles in the relationship between political connections and CGTI. Specifically, GEO weakens the relationship between ascribed political connections and incremental innovation, while it strengthens the relationship between achieved political connections and radical innovation. Similarly, DC moderates the effect of political connections on innovation, reducing the influence of ascribed ties on incremental innovation but enhancing the effect of achieved ties on radical innovation.

5.4. Robustness Tests

To ensure the robustness of our results, we employed an alternative measure of green technological innovation (CGTI) by calculating the CGTI ratio, which is defined as the ratio of green patent applications to the total number of patent applications in a given year. This measure provides a relative assessment of how much a firm focuses on green innovations compared to its overall innovation efforts. By using this alternative measure, we can better understand the emphasis placed on green technologies within the firm’s broader innovation strategy.
The regression results in Table 5 show that ascribed political connections (Wascribed) are positively and significantly related to the incremental CGTI ratio (GreU_ratio) (coef. = 0.021, p < 0.05). This finding supports our main analysis, suggesting that firms with stronger ascribed political connections are more likely to focus on incremental green innovations, which involve improving existing technologies. However, ascribed political connections do not significantly affect the radical CGTI ratio (GreI_ratio) (coef. = −0.003), indicating that these connections are not associated with transformative, high-risk innovations.
In contrast, achieved political connections (Achieved) exhibit a significant positive impact on the radical CGTI ratio (GreI_ratio) (coef. = 0.041, p < 0.001), reinforcing our main finding that radical green innovations are driven by achieved political connections. Firms with stronger achieved political ties are more inclined to pursue disruptive innovations, such as new technologies or business models. However, achieved political connections do not significantly influence the incremental CGTI ratio (WGreU_ratio) (coef. = −0.011). These findings, based on alternative measures, consistently reinforce the validity of our original conclusions, highlighting the distinct roles of political connections in driving different types of green innovation.
To further assess the robustness of our findings, we conducted an additional test by incorporating a one-year lag (T + 1) in the analysis of the impact of political connections on green technological innovation (CGTI). This lagged approach allows us to examine whether the effects of political ties on CGTI are sustained over time or if they are immediate, offering further insight into the temporal dynamics of innovation.
The results presented in Table 6 indicate that ascribed political connections (Ascribed) continue to have a significant positive effect on incremental CGTI (FGreUmiai) (coef. = 0.398, p < 0.01), even when considering a one-year lag. This suggests that firms with higher levels of ascribed political connections maintain a consistent focus on incremental green innovations, which are typically characterized by gradual improvements in existing technologies. The persistence of this effect supports the notion that stable, long-term political relationships continue to foster low-risk, gradual innovation strategies. Achieved political connections (Achieved) do not show a significant effect on incremental CGTI (FGreUmia) (coef. = −0.075), which is consistent with the expectation that achieved political ties, typically based on performance and achievement, are more likely to drive transformative rather than incremental innovation. These findings suggest that achieved political connections are not associated with incremental innovation over time, reinforcing their alignment with more disruptive, high-risk innovation strategies.
For radical CGTI (FGreInvia), the analysis reveals that achieved political connections have a significant positive impact (coef. = 0.468, p < 0.01), indicating that firms with stronger achieved political ties are more inclined to pursue breakthrough green innovations in the subsequent year. This result aligns with the idea that firms with dynamic, performance-based political ties are better positioned to undertake large-scale, transformative innovations. On the other hand, ascribed political connections do not significantly affect radical CGTI (coef. = 0.136), reinforcing the notion that such connections are more conducive to incremental rather than radical innovations.
We conducted a third robustness test using Driscoll–Kraay (D-K) standard errors to address potential autocorrelation and heteroskedasticity in our data. The results presented in Table 7 show that the proportion of ascribed political connections (Ascribed) remains significantly positive for incremental CGTI (GreUmiai), with a coefficient of 0.359 (p < 0.05). This reinforces our main findings, demonstrating that firms with higher levels of ascribed political connections are more likely to pursue incremental green innovations, even after adjusting for autocorrelation and heteroskedasticity. Achieved political connections (Achieved) continue to exhibit a significant positive effect on radical CGTI (GreInvia) (coef. = 0.455, p < 0.01), further supporting the notion that firms with stronger achieved political connections are more inclined to engage in breakthrough innovations. These results suggest that achieved political ties are a key driver of radical green innovations, which often involve higher risks and more substantial investments.
These robustness checks, employing Driscoll–Kraay standard errors, confirm that the relationships between political connections and different types of green technological innovations remain stable across alternative error specifications. This strengthens the reliability of our conclusions and provides additional confidence in the robustness of our analysis.

6. Discussion

This study examines the impact of ascribed and achieved political connections on corporate green technological innovation (CGTI) within Chinese listed firms. First, we find that ascribed political connections significantly foster incremental CGTI, aligning with previous studies by Li and Zhou [49] and Zhang et al. [2]. These studies suggest that stable political ties provide firms with predictable access to external resources, making it easier to pursue low-risk, incremental innovations. Our study builds on this by emphasizing the Chinese context, where government-driven policies play a crucial role in supporting such innovations.
Second, our finding that achieved political connections drive radical CGTI extends existing research on dynamic capabilities theory. Firms with achieved political ties are better positioned to leverage external resources for high-risk, high-reward innovations. This result aligns with Wu et al. [9] but further underscores the importance of China’s unique political environment, where firms with personal achievements and political ties can gain access to critical resources for breakthrough innovations.
Third, we examine the moderating effects of Green Entrepreneurial Orientation (GEO) and dynamic capabilities (DCs). Our results show that GEO weakens the relationship between ascribed political connections and incremental CGTI but strengthens the relationship between achieved political ties and radical CGTI. This suggests that executives with a strong sustainability focus are more likely to prioritize long-term ecological goals rather than relying solely on political connections for incremental innovations. This finding diverges from studies in Western contexts, where GEO tends to have a more consistent positive effect on various types of innovation. Furthermore, DC enhances the relationship between achieved political connections and radical CGTI but reduces the reliance on ascribed political connections for incremental innovation, highlighting the role of internal capabilities in facilitating innovation. Below we discuss the contribution of this study to green innovation research.

6.1. Theoretical Contributions

This study makes three important theoretical contributions to the literature on CGTI. First, it distinguishes between ascribed and achieved political connections and clarifies how executive political connection heterogeneity (EPCH) influences CGTI, specifically within the context of Chinese firms. The unique institutional features of China, including the government’s active role in economic and environmental policy, make this study particularly relevant to understanding how political ties in a state-driven economy shape green innovation strategies [102,103]. This study broadens the scope of the research by exploring how the diverse political connections of executives affect CGTI. This study refines the categorization of political relationships by distinguishing between ascribed and realized political relationships. This new perspective contributes to our understanding of how different types of political relations influence approaches to CGTI [39,104]. We conceptualize the heterogeneity of political connections as an institutionally embedded external force that shapes firms’ capacity to integrate green technologies, strategies, and managerial practices. By highlighting the role of top executives’ role-based cognition, we show how variations in political ties influence organizational alignment across multiple dimensions of green innovation. This perspective aligns with Chatzinikolaou and Vlados [105], who advocate for a systems-based view of green innovation, wherein institutional drivers must interact with firms’ internal strategic orientations and adaptive capabilities to enable effective sustainability transitions.
Second, this study enhances upper echelon theory by incorporating executives’ GEO and distinguishing between CGTI. Upper echelon theory suggests that executives’ traits significantly influence corporate strategy and performance [106]. By introducing GEO, this research demonstrates how executives’ personal values and innovation preferences influence corporate environmental technological innovation decisions, especially when political connections vary. This study also adds to the theory of CGTI by distinguishing between incremental and radical types. Incremental CGTI—characterized by small, continuous improvements to existing technologies, processes, or products—is mainly driven by ascribed political connections, as they provide stability and reliable resources. By contrast, radical CGTI—which involves major, transformative changes and introducing entirely new technologies or business models—is driven by achieved political connections as these relationships encourage significant investment and risk-taking. This dual focus broadens the application of upper echelon theory to CGTI and deepens our understanding of how executive traits affect behaviors within this context [107].
Moreover, this study further incorporates Green Entrepreneurial Orientation and organizational dynamic capabilities into the moderating framework linking political connections and green innovation, thereby uncovering the contextual fit mechanism through which institutional pressures translate into firm-level outcomes. Contrary to the traditional institutional view that depicts organizations as passive recipients of institutional forces [108], we argue that the efficacy of institutional influence depends on the alignment between external pressures and internal organizational configurations. Specifically, Green Entrepreneurial Orientation enhances firms’ proactive responsiveness and value congruence with institutional expectations, while dynamic capabilities enable firms to reconfigure resources and adapt strategically under conditions of institutional uncertainty. These internal attributes condition the extent to which political ties become effective catalysts—or constraints—of green innovation. Our findings respond to Oliver’s [109] theorization of strategic responses to institutional pressures and extend Greenwood et al.’s [110] concept of institutional embeddedness by highlighting that institutional effects are not automatic or uniform but rather embedded within the firm’s idiosyncratic orientations, capabilities, and contextual contingencies. Therefore, we contribute to the micro-foundational development of institutional theory by advancing a nuanced understanding of institution–organization fit, offering a novel lens to explain the heterogeneity in how firms respond to politically embedded institutional logics.
Third, this study advances the upper echelon framework via the inclusion of dynamic capabilities theory [111,112]. By examining how a firm’s dynamic capabilities affect the relationship between the diversity of executive political connections and CGTI, this research highlights how firms use their resources to respond to external pressures and seize innovation opportunities in fast-changing environments. Dynamic capabilities help firms to leverage executives’ political connections for green technological innovation, whereby resources can be integrated and applied more effectively, improving CGTI outcomes. This contribution extends dynamic capabilities theory to environmental technological innovation and provides a new angle for upper echelon theory [113], explaining how firms use internal capabilities to harness political connections and develop CGTI. By integrating dynamic capabilities into the upper echelon framework, this study demonstrates the interaction between internal resource integration and external political resources and enhances the applicability and explanatory power of upper echelon theory in complex and dynamic settings.

6.2. Practical Implications

This research provides multiple important practical contributions. Firms can increase the positive effect of EPCH on CGTI by filling both political and nonpolitical connections in the executive teams. In particular, firms must pay greater attention to recruiting and appointing top management members with executives with diverse political connections and thus maintain desirable ascribed and achieved political connections at the corporate level. Through a diverse executive team, they can integrate and utilize various political resources more effectively to support various types of environmental technological innovation projects. Secondly, firms should have a mechanism to systemically manage political relationships to continuously screen, scramble, and optimize the political networks of executives to ensure the dynamic allocation and effective use of political resources. This mechanism not only strengthens the flexibility of a firm in the face of external policy changes but also assists CGTI in achieving diversification and sustainability.
Second, companies should focus on creating a GEO closely with CGTI projects. This involves training and educating executives to help them understand and prioritize sustainability so they will back environmentally sustainable innovation projects in their decision-making. In addition, a scientific evaluation of performance and incentive mechanisms and policies for the enterprise can be formulated, consistent with sustainable development goals, which will also encourage enterprise cadres and leaders to devote more resources and energy to environmental technology innovation. For example, research in CGTIs can be integrated into the performance appraisal systems of executives to motivate them to guide the organization’s green transformation. It is also crucial to provide the requisite resources and support, like dedicated innovation funds to support executive-led environmental R&D projects, so that executives are empowered to become a bigger part of CGTI.
Third, firms need to strengthen their organizational dynamic capabilities to help moderate the impact of EPCH on CGTI. In practice, this means strengthening the firm’s ability to integrate resources by adopting effective internal resource allocation and management processes, thus enabling the firm to better integrate external political resources and improve innovation capabilities. Therefore, firms should build and execute strong environmental monitoring and analysis systems to be capable of recognizing and responding to changes in the external environment (e.g., regulatory policies, market needs, and technological trends) in a timely manner and fine-tune their CGTI strategies to keep their innovation visibility and adaptability. Implementing a culture of learning can encourage employees and management alike to continue to embrace new environmental technologies. An internal innovation platform can enhance knowledge exchange and technology sharing and thereby improve overall dynamic capabilities and innovation capacity in firms [114]. These measures will prompt firms to make full use of executives’ resources of political connection, lead to the development of green technological innovation, and realize green transformation and sustainable development.

6.3. Limitations and Future Research

Although this study provides valuable insights into the relationship between EPCH and CGTI, it has several limitations that provide potential avenues for future research.
First, though this study analyzes the static influence of executive political connections on CGTI, political connections tend to be dynamic and evolve across time. The political connections of executive-level staff can change as governments change policies and political climates, and personal careers change paths. This variation could impact the effect of political connections on CGTI, potentially changing the strength and direction of such effects. Future work might consider a longitudinal study of the relationship, as the connections and dynamic nature of the arrangement can significantly affect green technology innovation processes.
Second, the emphasis on Chinese firms as the setting for the current study may constrain the generalizability of the findings. Despite its status as a developing country in a global market context, China serves as a rich laboratory of corporate innovation where the government plays an active role. Thus, the effect of EPCH on CGTI found in this work may vary across countries around similar issues depending on levels of government intervention and political arrangements. Thus, future research should expand the sample to firms from other emerging economies or different political settings to corroborate the model in alternative settings.
Third, although this study incorporates important moderating variables, such as GEO and organizational dynamic capacity, it does not cover all possible moderators. Other aspects like corporate governance, industry-specific properties, and environmental regulations may also play an important role in the relationship between this EPCH and CGTI. Moreover, other executive traits beyond sustainability orientation and its still underexplored influences, such as risk tolerance and innovation propensity, could also explain why executives face transparent evidence of sustainable practices and yet fail to adapt accordingly. Future research can consider these and other moderating factors in the understanding of a more holistic view of the relationship between political connection and innovation.

7. Conclusions

This study has the following conclusions. First, this study highlights the distinct roles of ascribed and achieved political connections in shaping corporate green technological innovation (CGTI). Ascribed political connections promote incremental CGTI, while achieved political connections are more conducive to radical CGTI. These findings underscore the need to differentiate between political ties when examining innovation strategies, especially in the Chinese context, where political connections are deeply embedded in the business environment.
Second, our findings on the moderating roles of Green Entrepreneurial Orientation (GEO) and dynamic capabilities (DCs) contribute new insights to the literature. GEO weakens the effect of ascribed political connections on incremental CGTI while strengthening the relationship between achieved political ties and radical CGTI. DC plays a critical role in enhancing the effect of achieved political ties on radical CGTI and reducing the influence of ascribed political connections on incremental innovation.
Third, this study has important implications for policymakers and senior management teams. Policymakers can leverage the findings to design more effective policies that account for the varying impacts of political connections on green innovation. Management teams can use the insights to build dynamic capabilities and encourage a sustainability-focused Green Entrepreneurial Orientation to drive green innovation and sustainable development.

Author Contributions

Conceptualization, S.M. and S.W.; methodology, S.M. and S.W.; software, X.W.; formal analysis, S.M. and X.W.; investigation, X.W. and S.W.; data curation, S.M.; writing—original draft preparation, S.M. and X.W.; writing—review and editing, S.M., X.W. and S.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data underlying this study were obtained from the China Research Data Services Platform (CNRDS) database, the China Securities Market and Accounting Research (CSMAR) database, and the annual "China Statistical Yearbook" published by the National Bureau of Statistics. Restrictions apply to the availability of these data, which were used under license for this study.

Conflicts of Interest

The authors declare no conflict of interests.

References

  1. Li, G.; Wang, X.; Su, S.; Su, Y. How green technological innovation ability influences enterprise competitiveness. Technol. Soc. 2019, 59, 101136. [Google Scholar] [CrossRef]
  2. Zhang, G.; Gao, Y.; Li, G. Research on digital transformation and green technology innovation—Evidence from China’s listed manufacturing enterprises. Sustainability 2023, 15, 6425. [Google Scholar] [CrossRef]
  3. Zhang, Y.; Li, X.; Xing, C. How does China’s green credit policy affect the green innovation of high polluting enterprises? The perspective of radical and incremental innovations. J. Clean. Prod. 2022, 336, 130387. [Google Scholar] [CrossRef]
  4. Forés, B.; Camisón, C. Does incremental and radical innovation performance depend on different types of knowledge accumulation capabilities and organizational size? J. Bus. Res. 2016, 69, 831–848. [Google Scholar] [CrossRef]
  5. Wang, H.; Khan, M.A.S.; Anwar, F.; Shahzad, F.; Adu, D.; Murad, M. Green innovation practices and its impacts on environmental and organizational performance. Front. Psychol. 2021, 11, 553625. [Google Scholar] [CrossRef] [PubMed]
  6. Zhao, X.; Wang, S.; Wu, X. Leveraging Board Experience Diversity to Enhance Corporate Green Technological Innovation. Sustainability (2071-1050) 2025, 17, 3351. [Google Scholar] [CrossRef]
  7. Song, Y.; Du, C.; Du, P.; 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]
  8. Shao, Y.; Li, J.; Zhang, X. Outward foreign direct investment and green technology innovation: A company and host country perspective. Technol. Forecast. Soc. Change 2024, 203, 123379. [Google Scholar] [CrossRef]
  9. Wu, G.; Xu, Q.; Niu, X.; Tao, L. How does government policy improve green technology innovation: An empirical study in China. Front. Environ. Sci. 2022, 9, 799794. [Google Scholar] [CrossRef]
  10. 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]
  11. Ridge, J.W.; Ingram, A.; Hill, A.D. Beyond lobbying expenditures: How lobbying breadth and political connectedness affect firm outcomes. Acad. Manag. J. 2017, 60, 1138–1163. [Google Scholar] [CrossRef]
  12. Jiang, S.; Min, Y. The ability and willingness of family firms to bribe: A socioemotional wealth perspective. J. Bus. Ethics 2023, 184, 237–254. [Google Scholar] [CrossRef]
  13. Ren, S.; Wang, Y.; Hu, Y.; Yan, J. CEO hometown identity and firm green innovation. Bus. Strategy Environ. 2021, 30, 756–774. [Google Scholar] [CrossRef]
  14. Shen, F.; Liu, B.; Luo, F.; Wu, C.; Chen, H.; Wei, W. The effect of economic growth target constraints on green technology innovation. J. Environ. Manag. 2021, 292, 112765. [Google Scholar] [CrossRef]
  15. Shan, S.; Genç, S.Y.; Kamran, H.W.; Dinca, G. Role of green technology innovation and renewable energy in carbon neutrality: A sustainable investigation from Turkey. J. Environ. Manag. 2021, 294, 113004. [Google Scholar] [CrossRef] [PubMed]
  16. Liu, Y.; Zhang, F.; Zhang, H. CEO foreign experience and corporate environmental, social, and governance (ESG) performance. Bus. Strategy Environ. 2024, 33, 3331–3355. [Google Scholar] [CrossRef]
  17. Christmann, P. Effects of “best practices” of environmental management on cost advantage: The role of complementary assets. Acad. Manag. J. 2000, 43, 663–680. [Google Scholar] [CrossRef]
  18. Bekun, F.V. Race to carbon neutrality in South Africa: What role does environmental technological innovation play? Appl. Energy 2024, 354, 122212. [Google Scholar] [CrossRef]
  19. Lee, J.Y.; Ha, Y.J.; Wei, Y.; Sarala, R.M. CEO narcissism and global performance variance in multinational enterprises: The roles of foreign direct investment risk-taking and business group affiliation. Br. J. Manag. 2023, 34, 512–535. [Google Scholar] [CrossRef]
  20. Patrucco, A.S.; Marzi, G.; Trabucchi, D. The role of absorptive capacity and big data analytics in strategic purchasing and supply chain management decisions. Technovation 2023, 126, 102814. [Google Scholar] [CrossRef]
  21. Dabić, M.; Posinković, T.O.; Vlačić, B.; Gonçalves, R. A configurational approach to new product development performance: The role of open innovation, digital transformation and absorptive capacity. Technol. Forecast. Soc. Change 2023, 194, 122720. [Google Scholar] [CrossRef]
  22. Zhang, C.; Zhou, B.; Tian, X. Political connections and green innovation: The role of a corporate entrepreneurship strategy in state-owned enterprises. J. Bus. Res. 2022, 146, 375–384. [Google Scholar] [CrossRef]
  23. Deng, Y.; Wu, Y.; Xu, H. Political connections and firm pollution behaviour: An empirical study. Environ. Resour. Econ. 2020, 75, 867–898. [Google Scholar] [CrossRef]
  24. Barney, J.B. Contributing to theory: Opportunities and challenges. AMS Rev. 2020, 10, 49–55. [Google Scholar] [CrossRef]
  25. Chang, K.; Luo, D.; Dong, Y.; Xiong, C. The impact of green finance policy on green innovation performance: Evidence from Chinese heavily polluting enterprises. J. Environ. Manag. 2024, 352, 119961. [Google Scholar] [CrossRef]
  26. Huang, J.; Wang, Z.; Jiang, Z.; Zhong, Q. Environmental policy uncertainty and corporate green innovation: Evidence from China. Eur. J. Innov. Manag. 2023, 26, 1675–1696. [Google Scholar] [CrossRef]
  27. Mahran, K.; Elamer, A.A. Chief Executive Officer (CEO) and corporate environmental sustainability: A systematic literature review and avenues for future research. Bus. Strategy Environ. 2024, 33, 1977–2003. [Google Scholar] [CrossRef]
  28. Yin, X.; Chen, D.; Ji, J. How does environmental regulation influence green technological innovation? Moderating effect of green finance. J. Environ. Manag. 2023, 342, 118112. [Google Scholar] [CrossRef]
  29. Campbell, J.T.; Bilgili, H.; Crossland, C.; Ajay, B. The background on executive background: An integrative review. J. Manag. 2023, 49, 7–51. [Google Scholar] [CrossRef]
  30. Sjödin, D.; Parida, V.; Kohtamäki, M. Artificial intelligence enabling circular business model innovation in digital servitization: Conceptualizing dynamic capabilities, AI capacities, business models and effects. Technol. Forecast. Soc. Change 2023, 197, 122903. [Google Scholar] [CrossRef]
  31. Li, Z.; Huang, Z.; Su, Y. New media environment, environmental regulation and corporate green technology innovation: Evidence from China. Energy Econ. 2023, 119, 106545. [Google Scholar] [CrossRef]
  32. Wang, C. Green technology innovation, energy consumption structure and sustainable improvement of enterprise performance. Sustainability 2022, 14, 10168. [Google Scholar] [CrossRef]
  33. Zhu, L.; Luo, J.; Dong, Q.; Zhao, Y.; Wang, Y.; Wang, Y. Green technology innovation efficiency of energy-intensive industries in China from the perspective of shared resources: Dynamic change and improvement path. Technol. Forecast. Soc. Change 2021, 170, 120890. [Google Scholar] [CrossRef]
  34. Arekrans, J.; Ritzén, S.; Laurenti, R. The role of radical innovation in circular strategy deployment. Bus. Strategy Environ. 2023, 32, 1085–1105. [Google Scholar] [CrossRef]
  35. Bu, T.; Chen, D. The threshold effect of political connection on the green innovation of businesses: Evidence from China. N. Am. J. Econ. Financ. 2024, 74, 102255. [Google Scholar]
  36. Abbas, J. Does the nexus of corporate social responsibility and green dynamic capabilities drive firms toward green technological innovation? The moderating role of green transformational leadership. Technol. Forecast. Soc. Change 2024, 208, 123698. [Google Scholar] [CrossRef]
  37. Lei, X.; Chen, X.; Zhang, B. Unleashing the spillover potential: Exploring the role of technology-seeking investment in driving green innovation of host countries. Technol. Forecast. Soc. Change 2024, 200, 123200. [Google Scholar] [CrossRef]
  38. Bataineh, M.J.; Sánchez-Sellero, P.; Ayad, F. Green is the new black: How research and development and green innovation provide businesses a competitive edge. Bus. Strategy Environ. 2024, 33, 1004–1023. [Google Scholar] [CrossRef]
  39. Pan, X.; Chen, X.; Sinha, P. Navigating the haze: Environmental performance feedback and CSR report readability. J. Bus. Res. 2023, 166, 114116. [Google Scholar] [CrossRef]
  40. Song, L.; Zou, L.; Liang, Q. Do political connections foster or hamper firm environmental investment? Econ. Res.-Ekon. Istraživanja 2023, 36, 2071–2089. [Google Scholar] [CrossRef]
  41. Yang, J.; Xiong, G.; Shi, D. Innovation and sustainable: Can innovative city improve energy efficiency? Sustain. Cities Soc. 2022, 80, 103761. [Google Scholar] [CrossRef]
  42. Long, Z.; Duan, Y.; Zhan, H. The impact of organizational-level political connection on environmental strategy in private firms. Econ. Model. 2024, 132, 106644. [Google Scholar] [CrossRef]
  43. Sun, P.; Doh, J.; Rajwani, T.; Werner, T.; Luo, X.R. The management of socio-political issues and environments: Toward a research agenda for corporate socio-political engagement. J. Manag. Stud. 2024, 61, 277–306. [Google Scholar] [CrossRef]
  44. Wang, P.; Zhang, Z.; Zeng, Y.; Yang, S.; Tang, X. The effect of technology innovation on corporate sustainability in Chinese renewable energy companies. Front. Energy Res. 2021, 9, 638459. [Google Scholar] [CrossRef]
  45. Liu, X.; Liu, F.; Ren, X. Firms’ digitalization in manufacturing and the structure and direction of green innovation. J. Environ. Manag. 2023, 335, 117525. [Google Scholar] [CrossRef]
  46. Scott, W.R. Institutional theory: Contributing to a theoretical research program. Great Minds Manag. Process Theory Dev. 2005, 37, 460–484. [Google Scholar]
  47. Li, A. Preemptive or promotive: The differential impact of strategic leaders’ political connections on firm long-term investment in China. Long Range Plan. 2022, 55, 102158. [Google Scholar] [CrossRef]
  48. Fu, J.-Y.; Sun, P. Closing the revolving door: What if board political connections are permanently broken? J. Manag. 2024, 50, 2534–2570. [Google Scholar] [CrossRef]
  49. Li, L.; Zhou, S.; Xu, W.; Dai, J. Green innovation’s impact on corporate financing: New insights from BRICS economies. Financ. Res. Lett. 2024, 62, 105172. [Google Scholar] [CrossRef]
  50. Wang, K.; Zhang, Q.; Wang, D.; Yang, D. The impact of political ties on firms’ innovation capability: Evidence from China. Asia Pac. J. Manag. 2024, 41, 1481–1513. [Google Scholar] [CrossRef]
  51. Quttainah, M.A.; Ayadi, I. The impact of digital integration on corporate sustainability: Emissions reduction, environmental innovation, and resource efficiency in the European. J. Innov. Knowl. 2024, 9, 100525. [Google Scholar] [CrossRef]
  52. Wang, Z.; Fu, H.; Ren, X. Political connections and corporate carbon emission: New evidence from Chinese industrial firms. Technol. Forecast. Soc. Change 2023, 188, 122326. [Google Scholar] [CrossRef]
  53. Qin, C.; Ailikamujiang, A.; Jing, T. How green entrepreneurial orientation leads to business success? A resource base and resource dependency perspectives. Bus. Strategy Environ. 2024, 33, 7511–7526. [Google Scholar] [CrossRef]
  54. Wu, L.; Zhu, C.; Wang, G. The impact of green innovation resilience on energy efficiency: A perspective based on the development of the digital economy. J. Environ. Manag. 2024, 355, 120424. [Google Scholar] [CrossRef]
  55. Jia, L.; Zhang, X.; Wang, X.; Chen, X.; Xu, X.; Song, M. Impact of carbon emission trading system on green technology innovation of energy enterprises in China. J. Environ. Manag. 2024, 360, 121229. [Google Scholar] [CrossRef]
  56. Stern, N.; Valero, A. Innovation, growth and the transition to net-zero emissions. Res. Policy 2021, 50, 104293. [Google Scholar] [CrossRef] [PubMed]
  57. Wu, Y.; Li, H.; Luo, R.; Yu, Y. How digital transformation helps enterprises achieve high-quality development? Empirical evidence from Chinese listed companies. Eur. J. Innov. Manag. 2024, 27, 2753–2779. [Google Scholar] [CrossRef]
  58. Cuthbertson, R.W.; Furseth, P.I. Digital services and competitive advantage: Strengthening the links between RBV, KBV, and innovation. J. Bus. Res. 2022, 152, 168–176. [Google Scholar] [CrossRef]
  59. Neely, B.H., Jr.; Lovelace, J.B.; Cowen, A.P.; Hiller, N.J. Metacritiques of upper echelons theory: Verdicts and recommendations for future research. J. Manag. 2020, 46, 1029–1062. [Google Scholar] [CrossRef]
  60. Averina, E.; Frishammar, J.; Parida, V. Assessing sustainability opportunities for circular business models. Bus. Strategy Environ. 2022, 31, 1464–1487. [Google Scholar] [CrossRef]
  61. Tze San, O.; Latif, B.; Di Vaio, A. GEO and sustainable performance: The moderating role of GTD and environmental consciousness. J. Intellect. Cap. 2022, 23, 38–67. [Google Scholar] [CrossRef]
  62. Liu, H.; Wang, Q.; Li, J. Political connections and greenwashing: Chinese evidence. Appl. Econ. 2024, 1–19. [Google Scholar] [CrossRef]
  63. Wang, C.a.; Wang, L.; Zhao, S.; Yang, C.; Albitar, K. The impact of Fintech on corporate carbon emissions: Towards green and sustainable development. Bus. Strategy Environ. 2024, 33, 5776–5796. [Google Scholar] [CrossRef]
  64. Coelho, A.; Ferreira, J.; Proença, C. The impact of green entrepreneurial orientation on sustainability performance through the effects of green product and process innovation: The moderating role of ambidexterity. Bus. Strategy Environ. 2024, 33, 3184–3202. [Google Scholar] [CrossRef]
  65. Zhou, H.; Zhao, S. Green supply chain integration on firm’s green innovation: The moderating role of resource orchestration capability. Oper. Manag. Res. 2024, 1–17. [Google Scholar] [CrossRef]
  66. Kennedy, S.; Whiteman, G.; van den Ende, J. Radical innovation for sustainability: The power of strategy and open innovation. Long Range Plan. 2017, 50, 712–725. [Google Scholar] [CrossRef]
  67. Bento, N.; Gianfrate, G.; Groppo, S.V. Do crowdfunding returns reward risk? Evidences from clean-tech projects. Technol. Forecast. Soc. Change 2019, 141, 107–116. [Google Scholar] [CrossRef]
  68. Bouguerra, A.; Hughes, M.; Rodgers, P.; Stokes, P.; Tatoglu, E. Confronting the grand challenge of environmental sustainability within supply chains: How can organizational strategic agility drive environmental innovation? J. Prod. Innov. Manag. 2024, 41, 323–346. [Google Scholar] [CrossRef]
  69. 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]
  70. Brewis, C.; Dibb, S.; Meadows, M. Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms. Technol. Forecast. Soc. Change 2023, 190, 122402. [Google Scholar] [CrossRef]
  71. Wang, Q.; Sun, T.; Li, R. Does artificial intelligence promote green innovation? An assessment based on direct, indirect, spillover, and heterogeneity effects. Energy Environ. 2025, 36, 1005–1037. [Google Scholar] [CrossRef]
  72. Chen, L.; Shen, Q.; Yu, X.; Chen, X. Knowledge spillovers along the sustainable supply chain of China’s listed companies: The role of long-term orientation. J. Innov. Knowl. 2024, 9, 100478. [Google Scholar] [CrossRef]
  73. Yang, J.; Zhang, J.; Zeng, D. Scientific collaboration networks and firm innovation: The contingent impact of a dynamic environment. Manag. Decis. 2022, 60, 278–296. [Google Scholar] [CrossRef]
  74. Lenderink, B.; Halman, J.I.; Boes, J.; Voordijk, H.; Dorée, A.G. Procurement and innovation risk management: How a public client managed to realize a radical green innovation in a civil engineering project. J. Purch. Supply Manag. 2022, 28, 100747. [Google Scholar] [CrossRef]
  75. Li, M.; Cao, G.; Li, H.; Hao, Z.; Zhang, L. How government subsidies affect technology innovation in the context of Industry 4.0: Evidence from Chinese new-energy enterprises. Kybernetes 2024, 53, 4149–4171. [Google Scholar] [CrossRef]
  76. Chirumalla, K.; Leoni, L.; Oghazi, P. Moving from servitization to digital servitization: Identifying the required dynamic capabilities and related microfoundations to facilitate the transition. J. Bus. Res. 2023, 158, 113668. [Google Scholar] [CrossRef]
  77. Ortiz-Avram, D.; Ovcharova, N.; Engelmann, A. Dynamic capabilities for sustainability: Toward a typology based on dimensions of sustainability-oriented innovation and stakeholder integration. Bus. Strategy Environ. 2024, 33, 2969–3004. [Google Scholar] [CrossRef]
  78. Knoppen, D.; Knight, L. Pursuing sustainability advantage: The dynamic capabilities of born sustainable firms. Bus. Strategy Environ. 2022, 31, 1789–1813. [Google Scholar] [CrossRef]
  79. Dhlamini, J. Strategy: An understanding of strategy for business and public policy settings. J. Contemp. Manag. 2022, 19, 108–134. [Google Scholar] [CrossRef]
  80. Xu, S.; Liu, D. Political connections and corporate social responsibility: Political incentives in China. Bus. Ethics: A Eur. Rev. 2020, 29, 664–693. [Google Scholar] [CrossRef]
  81. Desheng, L.; Jiakui, C.; Ning, Z. Political connections and green technology innovations under an environmental regulation. J. Clean. Prod. 2021, 298, 126778. [Google Scholar] [CrossRef]
  82. China Securities Market & Accounting Research. Available online: https://data.csmar.com/ (accessed on 20 February 2025).
  83. Chinese Research Data Services Platform. Available online: https://www.cnrds.com (accessed on 20 February 2025).
  84. National Bureau of Statistics of China. China Statistical Yearbook. Available online: https://www.stats.gov.cn/sj/ndsj/ (accessed on 20 February 2025).
  85. Balasubramanian, N.; Sivadasan, J. What happens when firms patent? New evidence from US economic census data. Rev. Econ. Stat. 2011, 93, 126–146. [Google Scholar] [CrossRef]
  86. Bronzini, R.; Piselli, P. The impact of R&D subsidies on firm innovation. Res. Policy 2016, 45, 442–457. [Google Scholar]
  87. Chen, S.-H. The influencing factors of enterprise sustainable innovation: An empirical study. Sustainability 2016, 8, 425. [Google Scholar] [CrossRef]
  88. Griliches, Z. Patent Statistics as Economic Indicators: A Survey Part I; NBER: Cambridge, MA, USA, 1990. [Google Scholar]
  89. Pertuze, J.A.; Reyes, T.; Vassolo, R.S.; Olivares, N. Political uncertainty and innovation: The relative effects of national leaders’ education levels and regime systems on firm-level patent applications. Res. Policy 2019, 48, 103808. [Google Scholar] [CrossRef]
  90. Zhang, Z.; Wang, X.; Jia, M. Echoes of CEO entrepreneurial orientation: How and when CEO entrepreneurial orientation influences dual CSR activities. J. Bus. Ethics 2021, 169, 609–629. [Google Scholar] [CrossRef]
  91. Fan, J.P.; Wong, T.J.; Zhang, T. Politically connected CEOs, corporate governance, and Post-IPO performance of China’s newly partially privatized firms. J. Financ. Econ. 2007, 84, 330–357. [Google Scholar] [CrossRef]
  92. Marquis, C.; Qian, C. Corporate social responsibility reporting in China: Symbol or substance? Organ. Sci. 2014, 25, 127–148. [Google Scholar] [CrossRef]
  93. ISO 14001:2015; Environmental Management Systems: Requirements with Guidance for Use. International Organization for Standardization: Geneva, Switzerland, 2015.
  94. Teece, D.J. Technological innovation and the theory of the firm: The role of enterprise-level knowledge, complementarities, and (dynamic) capabilities. In Handbook of the Economics of Innovation; Elsevier: Amsterdam, The Netherlands, 2010; Volume 1, pp. 679–730. [Google Scholar]
  95. Wu, L.-Y. Entrepreneurial resources, dynamic capabilities and start-up performance of Taiwan’s high-tech firms. J. Bus. Res. 2007, 60, 549–555. [Google Scholar] [CrossRef]
  96. Seo, R.; Edler, J.; Massini, S. Can entrepreneurial orientation improve R&D alliance performance? An absorptive capacity perspective. RD Manag. 2022, 52, 50–66. [Google Scholar]
  97. Gambardella, A. Private and social functions of patents: Innovation, markets, and new firms. Res. Policy 2023, 52, 104806. [Google Scholar] [CrossRef]
  98. He, L.; Jiang, M. How does philanthropy influence innovation management systems? A moderated mediation model with a social exchange perspective. Systems 2022, 10, 206. [Google Scholar] [CrossRef]
  99. Huang, J.-W.; Li, Y.-H. Green innovation and performance: The view of organizational capability and social reciprocity. J. Bus. Ethics 2017, 145, 309–324. [Google Scholar] [CrossRef]
  100. Li, W.; Zhang, J.Z.; Ding, R. Impact of directors’ network on corporate social responsibility disclosure: Evidence from China. J. Bus. Ethics 2023, 183, 551–583. [Google Scholar] [CrossRef]
  101. Atif, M.; Liu, B.; Nadarajah, S. The effect of corporate environmental, social and governance disclosure on cash holdings: Life-cycle perspective. Bus. Strategy Environ. 2022, 31, 2193–2212. [Google Scholar] [CrossRef]
  102. Porter, M.E.; Linde, C.v.d. Toward a new conception of the environment-competitiveness relationship. J. Econ. Perspect. 1995, 9, 97–118. [Google Scholar] [CrossRef]
  103. Hart, S.L. A natural-resource-based view of the firm. Acad. Manag. Rev. 1995, 20, 986–1014. [Google Scholar] [CrossRef]
  104. Brugués, F.; Brugués, J.; Giambra, S. Political connections and misallocation of procurement contracts: Evidence from Ecuador. J. Dev. Econ. 2024, 170, 103296. [Google Scholar] [CrossRef]
  105. Chatzinikolaou, D.; Vlados, C. Green organisational reorientations for the new globalisation. J. Sustain. Sci. Manag. 2024, 19, 43–68. [Google Scholar] [CrossRef]
  106. Bromiley, P.; Rau, D. Social, behavioral, and cognitive influences on upper echelons during strategy process: A literature review. J. Manag. 2016, 42, 174–202. [Google Scholar] [CrossRef]
  107. Wang, L.; Zeng, T.; Li, C. Behavior decision of top management team and enterprise green technology innovation. J. Clean. Prod. 2022, 367, 133120. [Google Scholar] [CrossRef]
  108. DiMaggio, P.J.; Powell, W.W. The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. Am. Sociol. Rev. 1983, 48, 147–160. [Google Scholar] [CrossRef]
  109. Oliver, C. Strategic responses to institutional processes. Acad. Manag. Rev. 1991, 16, 145–179. [Google Scholar] [CrossRef]
  110. Greenwood, R.; Raynard, M.; Kodeih, F.; Micelotta, E.R.; Lounsbury, M. Institutional complexity and organizational responses. Acad. Manag. Ann. 2011, 5, 317–371. [Google Scholar] [CrossRef]
  111. Salvato, C.; Vassolo, R. The sources of dynamism in dynamic capabilities. Strateg. Manag. J. 2018, 39, 1728–1752. [Google Scholar] [CrossRef]
  112. Roberson, Q.; Holmes IV, O.; Perry, J.L. Transforming research on diversity and firm performance: A dynamic capabilities perspective. Acad. Manag. Ann. 2017, 11, 189–216. [Google Scholar] [CrossRef]
  113. Heubeck, T. Walking on the gender tightrope: Unlocking ESG potential through CEOs’ dynamic capabilities and strategic board composition. Bus. Strategy Environ. 2024, 33, 2020–2039. [Google Scholar] [CrossRef]
  114. Torkkeli, L.; Kuivalainen, O.; Saarenketo, S.; Puumalainen, K. Institutional environment and network competence in successful SME internationalisation. Int. Mark. Rev. 2019, 36, 31–55. [Google Scholar] [CrossRef]
Table 1. Definition of Variables.
Table 1. Definition of Variables.
VariablesSymbolMeasures
Radical corporate green technological innovationsGreInviaAverage novelty of green patent applications (green invention patents). Measured by rarity of IPC combinations.
Incremental corporate green technological innovationsGreUmiaiAverage conventionality of green patent applications (green utility model patents). Measured by commonality of IPC combinations.
Ascribed political connectionAscribedThe percentage of a firm’s senior managers with government work experience.
Achieved political connectionAchievedThe percentage of a firm’s senior managers within the Chinese People’s Political Consultative Conference (CPPCC)
Green entrepreneurship orientationGEOComposite Index of Sustainability Dimensions are comprised of four components:
1. Social Responsibility (CSR): CSR value per share.
2. First-Mover Orientation: Sustainable growth rate.
3. Innovation Orientation: Ratio of R&D investments to main business revenue.
4. Environmental Commitment: ISO14001 certification status (1 = Certified, 0 = Not Certified).
Dynamic CapabilitiesDCThe entropy method is used to integrate these five dynamic capability dimensions into one indicator.
Firm sizeSizeThe natural logarithm of the total assets of the enterprise
Firm ageAgeThe natural logarithm of the year of establishment of the enterprise
board size BoardNumber of current independent directors
board independenceIndepRatio of independent directors to total number of directors
ProfitabilityROANet profit after tax as a percentage of total assets
financial leverageLevRatio of total liabilities to total assets
corporate growthGrowthThe growth rate of operating income.
Cash flowCashThe ratio of the net cash flow from operations to the total assets.
Top five shareholders’ holdingsTop5Number of shares held by the top five shareholders/total number of shares
Institutional InvestorsINSTInstitutional investors’ holdings/total number of shares
Table 2. Descriptive statistics.
Table 2. Descriptive statistics.
VarNameObsMeanSDMinMedianMax
GreInvia12,1490.2950.6600.0000.0003.497
GreUmia12,1490.2620.6020.0000.0003.045
Ascribed12,1490.0240.0400.0000.0000.188
Achieved12,1490.0170.0330.0000.0000.152
GEO12,149−0.1530.105−0.380−0.1770.524
DC12,1490.0680.0290.0000.0690.138
Size12,14922.0471.16119.40621.90326.430
Age12,1492.1450.7500.6932.3033.367
Board12,1492.1290.1931.6092.1972.708
Indep12,1490.3730.0520.2500.3330.600
ROA12,1490.0420.064−0.3750.0390.254
Lev12,1490.4020.1950.0270.3910.925
Growth12,1490.1640.363−0.6530.1103.808
Cashflow12,1490.0500.066−0.2240.0470.283
Top512,1490.5270.1460.1770.5250.892
INST12,1490.4210.2460.0010.4420.935
Table 3. Baseline regression results.
Table 3. Baseline regression results.
(1)(2)
GreUmiaGreInvia
Ascribed0.359 ***0.135
(2.997)(0.843)
Achieved−0.1570.455 ***
(−0.888)(2.693)
Size0.050 ***0.068 ***
(3.246)(3.638)
Age−0.027−0.045
(−0.851)(−1.363)
Board−0.0410.008
(−0.752)(0.132)
Indep−0.157−0.030
(−0.965)(−0.166)
ROA0.176 **0.072
(2.061)(0.732)
Lev0.0280.013
(0.601)(0.236)
Growth−0.009−0.009
(−0.686)(−0.694)
Cash0.0130.091
(0.176)(1.137)
Top5−0.233 **−0.087
(−2.049)(−0.812)
INST−0.020−0.063
(−0.332)(−0.984)
Constant−0.457−1.157 ***
(−1.228)(−2.838)
Industry FEYesYes
Year FEYesYes
N12,14912,149
Adj. R20.0310.031
Note: This table presents baseline regression models examining the effect of political connection heterogeneity on green innovation. Variable definitions are provided in Table 2. All models include year and industry fixed effects to account for time-specific shocks and sectoral heterogeneity. ** 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)(4)
GreUmiaGreInviaGreUmiaGreInvia
Ascribed0.368 *** 0.370 ***
(3.142) (3.163)
GEO−0.064−0.115 **
(−1.022)(−2.006)
Ascribed × GEO−6.276 **
(−1.983)
Achieved 0.450 *** 0.450 ***
(2.746) (2.737)
Achieved × GEO 16.410 **
(2.448)
DC 1.742 **1.558 **
(2.345)(1.979)
Ascribed × DC −6.840 **
(−2.101)
Achieved × DC 16.794 **
(2.497)
Size0.052 ***0.071 ***0.047 ***0.065 ***
(3.357)(3.796)(3.063)(3.448)
Age−0.028−0.047−0.026−0.044
(−0.891)(−1.432)(−0.830)(−1.337)
Board−0.0430.009−0.0450.006
(−0.780)(0.139)(−0.825)(0.101)
Indep−0.154−0.019−0.158−0.026
(−0.944)(−0.108)(−0.970)(−0.146)
ROA0.175 **0.0830.157 *0.065
(2.054)(0.845)(1.844)(0.664)
Lev0.0260.0120.0320.018
(0.563)(0.217)(0.685)(0.318)
Growth−0.008−0.008−0.007−0.008
(−0.608)(−0.663)(−0.555)(−0.663)
Cash0.0170.0930.0160.090
(0.226)(1.161)(0.218)(1.124)
Top5−0.233 **−0.081−0.249 **−0.097
(−2.054)(−0.759)(−2.186)(−0.906)
INST−0.017−0.062−0.016−0.062
(−0.281)(−0.963)(−0.256)(−0.961)
Constant−0.487−1.217 ***−0.367−1.072 ***
(−1.304)(−2.987)(−0.997)(−2.616)
Industry FEYesYesYesYes
Year FEYesYesYesYes
N12,14912,14912,14912,149
Adj. R20.0310.0320.0320.032
Note: This table introduces Green Entrepreneurial Orientation (GEO) and dynamic capabilities (DCs) as moderating variables in the analysis. Definitions of all variables are provided in Table 2. All models control for year and industry fixed effects to account for temporal shocks and sector-specific heterogeneity; *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 5. Alternative dependent variable measurement results.
Table 5. Alternative dependent variable measurement results.
(1)(2)
GreU_RatioGrei_Ratio
Ascribed0.021 **−0.003
(2.522)(−0.168)
Achieved−0.0110.043 ***
(−0.986)(3.104)
Size0.0000.002
(0.172)(1.283)
Age−0.002−0.003
(−1.317)(−1.275)
Board0.0010.001
(0.147)(0.192)
Indep0.0050.004
(0.461)(0.285)
ROA−0.000−0.021 *
(−0.009)(−1.873)
Lev−0.001−0.008 *
(−0.342)(−1.839)
Growth−0.0010.002
(−0.690)(1.315)
Cash−0.0010.003
(−0.258)(0.372)
Top5−0.014 **−0.009
(−2.454)(−1.174)
INST0.0010.000
(0.330)(0.026)
Constant0.029−0.019
(1.158)(−0.694)
Industry FEYesYes
Year FEYesYes
N12,14912,149
Adj. R20.0110.004
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 6. Lagged Effects of Political Connections on Incremental and Radical CGTI.
Table 6. Lagged Effects of Political Connections on Incremental and Radical CGTI.
(1)(2)
FGreUmiaFGreInvia
Ascribed0.398 ***0.134
(2.661)(0.797)
Achieved−0.0750.468 ***
(−0.431)(2.608)
Size0.040 **0.054 ***
(2.424)(2.641)
Age−0.059 *−0.022
(−1.842)(−0.643)
Board−0.0460.023
(−0.917)(0.334)
Indep−0.073−0.122
(−0.475)(−0.716)
ROA0.307 ***0.418 ***
(2.877)(3.902)
Lev0.0580.063
(0.996)(1.036)
Growth0.003−0.010
(0.274)(−0.788)
Cash0.033−0.094
(0.424)(−1.091)
Top5−0.1550.003
(−1.264)(0.026)
INST−0.015−0.099
(−0.213)(−1.324)
Constant−0.287−0.890 **
(−0.726)(−2.094)
Industry FEYesYes
Year FEYesYes
N1153911539
Adj. R20.0290.024
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
Table 7. Driscoll–Kraay (D-K) standard errors.
Table 7. Driscoll–Kraay (D-K) standard errors.
(1)(2)
GreUmiaGreInvia
Ascribed0.359 **0.135
(2.902)(0.996)
Achieved−0.1570.455 ***
(−1.214)(5.999)
Size0.050 ***0.068 ***
(7.149)(4.721)
Age−0.027−0.045
(−0.928)(−1.088)
Board−0.0410.008
(−1.170)(0.257)
Indep−0.157−0.030
(−1.562)(−0.235)
ROA0.176 ***0.072
(3.954)(1.103)
Lev0.0280.013
(0.847)(0.293)
Growth−0.009−0.009
(−0.730)(−1.017)
Cash0.0130.091
(0.189)(1.352)
Top5−0.233 ***−0.087
(−3.356)(−0.989)
INST−0.020−0.063
(−0.453)(−1.540)
Constant−0.457 *−1.157 ***
(−2.009)(−3.260)
Industry FEYesYes
Year FEYesYes
N12,14912,149
Within R20.0340.035
Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; T-values are shown in brackets.
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Meng, S.; Wu, X.; Wang, S. Political Connection Heterogeneity and Green Technological Innovation: Evidence from Chinese Listed Companies. Systems 2025, 13, 443. https://doi.org/10.3390/systems13060443

AMA Style

Meng S, Wu X, Wang S. Political Connection Heterogeneity and Green Technological Innovation: Evidence from Chinese Listed Companies. Systems. 2025; 13(6):443. https://doi.org/10.3390/systems13060443

Chicago/Turabian Style

Meng, Siqi, Xiaoyu Wu, and Shuyang Wang. 2025. "Political Connection Heterogeneity and Green Technological Innovation: Evidence from Chinese Listed Companies" Systems 13, no. 6: 443. https://doi.org/10.3390/systems13060443

APA Style

Meng, S., Wu, X., & Wang, S. (2025). Political Connection Heterogeneity and Green Technological Innovation: Evidence from Chinese Listed Companies. Systems, 13(6), 443. https://doi.org/10.3390/systems13060443

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