Digital Transformation, CEO Compensation, and ESG Performance: Evidence from Chinese Listed Companies

Abstract

As sustainability reporting and ESG disclosure gain global importance, understanding the factors influencing ESG outcomes becomes crucial for policymakers, investors, and corporate decision-makers. China, a major player in the global economy, has recently taken steps to align its stock exchanges with international ESG reporting standards. In this context, the study examines the individual and joint effects of digital transformation and CEO compensation on ESG performance, considering moderating factors such as firm size, state ownership, and CEO age and gender. The research employs a comprehensive dataset containing 16,205 firm-year observations from 2018 to 2022, combining financial data, ESG ratings, and a matrix of word frequencies related to digital transformation extracted from annual reports. The study adopts a firm-year two-way fixed effect model, utilizing panel data and control variables to address potential endogeneity concerns and unobserved firm heterogeneity. The findings provide evidence supporting the positive impact of digital transformation and CEO compensation on ESG performance. The level of digital transformation is positively associated with ESG performance. This relationship is stronger for larger firms and firms with older CEOs, while state-owned enterprises show mixed results compared to non-SOEs. However, the effect of CEO compensation and ESG performance is stronger for male CEOs. This study thus contributes to the growing literature on ESG performance, digital transformation, and executive compensation by providing insights into their relationships in the context of Chinese listed companies.

1. Introduction

Environmental, Social, and Governance (ESG) disclosure and sustainability reporting have attracted significant attention from researchers, particularly regarding their potential utilization and implications [1,2,3]. ESG reports include a wide array of data, including but not limited to employee health and safety metrics, environmental indicators such as greenhouse gas emissions and water usage, gender diversity statistics, other social metrics involving labor conditions, governance metrics concerning business ethics and the presence of relevant policies, as well as financial metrics illustrating the economic impacts of ESG issues [1,4]. ESG reports have varied uses. Among them are executives’ compensation based on firm ESG performance [3], investing based on the ESG performance [5], use by firms, and use as a base for firm pricing and then again for firms to greenwash and raise their stock price [4].

Lately, the global adoption of reporting standards has reached a pivotal moment. On 6 March 2024, the United States Securities and Exchange Commission (SEC) announced that it had “Adopt[ed] rules to enhance and standardize climate-related disclosures for investors”. The Chinese economy and stock market did not miss the train. In February 2024, China’s three major stock exchanges in Beijing, Shenzhen, and Shanghai published draft sustainability disclosure guidelines open for public consultation. After the consultation process, these sustainability disclosure rules are expected to become mandatory for companies listed on these Chinese exchanges. The new requirements are expected to apply to 2025 corporate sustainability reports, which will be published in 2026.

While there is a growing body of literature on ESG performance and its determinants [6,7,8], there is limited research on the specific roles of digital transformation and CEO compensation in driving ESG outcomes, particularly in the context of Chinese listed companies. Cohen et al. investigated the link between executive compensation and ESG performance from an international perspective but did not include the Chinese market in their analysis [3]. Lu et al. researched the relationship between digital transformation and ESG performance but did not relate it to CEO compensation [9]. The relationship between a CEO’s characteristics, education, and compensation has been studied [10,11], revealing a significant positive correlation. This study examines the individual effects of digital transformation and CEO compensation on the ESG performance of Chinese listed companies and their joint effect.

The main research questions of this study are: (1) How does digital transformation affect ESG performance among Chinese listed companies? (2) How does CEO compensation influence ESG performance in this context? (3) What is the joint effect of digital transformation and CEO compensation on ESG performance? The study also examines several sub-hypotheses regarding moderating factors such as firm size, state ownership, and CEO age and gender. The findings of this study are expected to contribute to the growing literature on ESG performance, digital transformation, and executive compensation while also providing valuable insights for policymakers, investors, and corporate decision-makers in promoting sustainable development and enhancing ESG outcomes.

The results of this study provide evidence supporting the positive impact of digital transformation and CEO compensation on ESG performance, as well as the moderating effects of firm size, state ownership, and CEO age and gender. The findings show that higher levels of digital transformation, particularly in the overall concept of digital transformation, are positively associated with better ESG performance. This relationship is stronger for larger firms and state-owned enterprises. CEO compensation is also found to be positively associated with better ESG performance, with the effect being more pronounced for older CEOs. However, the effect of CEO compensation and ESG performance is stronger for male CEOs. The study employs a comprehensive dataset containing 16,205 firm-year observations from 2018 to 2022, combining financial data, ESG ratings, and word frequency matrices to address these questions.

2. Institutional Background, Theoretical Framework, and Hypothesis Development

2.1. ESG and Sustainability Disclosure

ESG reporting refers to the practice where companies disclose information related to environmental, social, and governance aspects. Christensen, Serafeim, and Sikochi analyzed why ESG ratings from different agencies show substantial disagreement for individual companies [12]. They found that greater ESG disclosure leads to more significant disagreement between ratings, contrary to evidence for other metrics like credit ratings. This effect appears to be stronger for environmental and social disclosures relative to governance. Berg et al. highlighted that the divergence and uncertainty in ESG ratings make it difficult to incorporate these metrics reliably into compensation contracts or disclosure requirements [13]. Jouvenot and Krueger examined a unique law in the United Kingdom that required publicly listed firms to disclose their greenhouse gas emissions in a standardized format in their annual reports and found that affected firms reduced their GHG emissions by approximately 16%, primarily by decreasing energy usage and making costly operational adjustments [14].

Several studies have examined whether following ESG reporting guidelines and third-party verification enhances the credibility and quantity of corporate sustainability disclosures. Darnall et al. analyzed Japanese manufacturing firms, where the government offered process- or content-focused verification to the reports [7]. The article found that those who published reports according to the government’s voluntary ESG reporting guidelines disclosed 39% more sustainability information than non-adopters. In addition, content-focused verification, which involves evaluating the completeness and accuracy of the information in sustainability reports, was linked to 23% more text disclosure than process-focused verification, which looks at procedural compliance. Nevertheless, most major global ESG frameworks emphasize process over content-focused verification. Arvidsson and Dumay argue that further reporting regulations may have little impact [15]; companies should provide timely, relevant, and comparable sustainability data.

ESG research in China has grown substantially in recent years. A decade ago, only a handful—fewer than a hundred companies—were available for research [16]; today, this research encompasses information from more than four thousand companies and their ESG ratings. Though there is an improvement in quantity, there is still room for improvement and further understanding of the market potential [6]. The development of ESG practices in China can be divided into three main stages, with the latest stage beginning in 2020, when the “dual carbon” goal was announced as a national strategy, meaning environmental factors had become a priority [6]. Chen, Hung, and Wang studied the effect of mandatory Corporate Social Responsibility (CSR) disclosure in China [8], finding that firms reduced their pollution levels in response to the disclosure requirements, generating positive externalities for the cities in which they operate. However, this study also suggests that state-owned enterprises’ CSR disclosure spending could have been more efficient, potentially limiting the social benefits of the mandate.

Overall, research suggests that while ESG disclosures are increasing rapidly globally and in China, there are ongoing quality issues. Adopting clear reporting guidelines and more robust verification methods may enhance credibility, and, as discussed earlier, the stock exchanges and world reporting standards boards are trying to do so.

2.2. Theoretical Framework

Theories related to organizational management and corporate governance have evolved over time to encompass a broader set of stakeholder interests and societal considerations. The stakeholder theory emphasizes that organizations should consider the interests of various stakeholders [17], including shareholders, employees, customers, suppliers, and the broader community, in their decision-making processes. This theory recognizes that organizations do not operate in isolation but have multiple stakeholders whose interests must be balanced for long-term success. Building upon this, Al-Shammari et al. suggest that firms should simultaneously fulfill their economic and social responsibilities to achieve superior performance [18]. Their research on S&P 500 companies reveals a positive correlation between CSR and corporate performance, which is more pronounced among firms with greater R&D and operational capabilities. This finding supports Barney’s advocacy for integrating stakeholder theory into the RBV framework [19], emphasizing the pivotal role of firm capabilities in the CSR–performance linkage.

Within this context, the role of top executives, particularly CEOs, has come into the spotlight. Drawing from upper echelons theory and agency theory [20,21], researchers have explored how CEO attributes and compensation structures can shape a company’s ESG performance and its digital transformation [6,22,23,24]. This study emphasizes the importance of balancing market and non-market strategies for superior firm performance and aligns with the notion that ESG initiatives not only contribute to a company’s long-term sustainability but also have far-reaching implications for the well-being of society as a whole.

Along with that, digital transformation has emerged as a critical enabler for organizations to enhance their ESG performance. By leveraging advanced technologies, such as artificial intelligence and big data analytics, companies can improve operational efficiency, reduce their environmental footprint, and promote transparency and accountability in their sustainability efforts [25]. From the perspective of stakeholder theory [17], digital transformation can facilitate better stakeholder engagement and management of stakeholder relationships, which is crucial for creating value for all stakeholders and addressing their diverse interests [26]. Digital transformation can unlock sustainable value creation by enhancing a firm’s ESG performance through improved transparency, stakeholder engagement, and responsible decision-making, which are led by the CEO [27].

By aligning CEO compensation with ESG objectives and facilitating digital transformation initiatives, companies can create a powerful synergy, incentivizing top leadership to prioritize sustainable practices while providing the necessary tools and capabilities to drive meaningful change and improve ESG performance [28,29]. Building upon the theoretical perspectives of stakeholder theory, agency theory, and resource-based view, this study aims to investigate the relationships between CEO compensation structures aligned with ESG goals, digital transformation initiatives, and firms’ ESG performance. It seeks to explore how these factors can be combined within firms to collectively drive improvements in ESG outcomes and contribute to long-term sustainability.

2.3. Digital Transformation and ESG

Digital transformation has emerged as a pivotal force in enhancing corporate ESG performance. Digital transformation was found to effectively promote firms’ ESG performance by strengthening internal control and green innovation capabilities, with this positive relationship being more pronounced in non-state-owned enterprises, manufacturing industries, high-tech firms, firms with a higher proportion of independent directors, and firms with higher analyst coverage [9]. Wang et al. demonstrated that digital transformation significantly reduces firms’ environmental pollution emissions [30], such as waste gas and wastewater discharges, with this effect being more substantial in state-owned enterprises, high-polluting enterprises, and economically developed regions. The authors highlighted that digital transformation is crucial in increasing total factor productivity, driving green innovation, and enhancing internal corporate governance.

The influence of digital technology innovation (DTI), a crucial step in a company’s digital transformation, on corporate ESG performance has also garnered attention. Feng and Nie revealed that DTI substantially improves ESG performance, especially for small-sized and non-state-owned firms [31], with internal control quality and human capital as mediating mechanisms. Additionally, the institutional environment, government digital attention, and corporate digital transformation positively moderated the relationship between DTI and ESG performance. Focusing specifically on heavy polluters in China’s A-share market, Zhao and Cai discovered that firms with a higher degree of digital transformation exhibited higher ESG levels [32], with state-owned heavy polluters demonstrating a more sensitive ESG performance response to digital transformation compared to their non-state-owned counterparts.

Hao et al. measured provincial clean energy efficiency in China from 2013 to 2017 using an enhanced data envelopment analysis method and evaluated digitalization levels through an entropy approach across dimensions like infrastructure, adoption, industrialization, and innovation [25]. They found that digitalization significantly increased clean energy efficiency, attributing over 5% of improvements to digital platforms optimizing production, dispatch, and consumption. Moreover, digitalization’s marginal impact intensified above thresholds for innovation, coal dependence, and population density through boosted connectivity, intelligent systems, and economies of scale.

Ma and Wang explored the relationship between digital transformation, executive compensation, and firm outcomes [33]. They found that the association between executive compensation and digital transformation is initially negative at low levels of compensation. However, as compensation increases, the relationship becomes an inverted U-shape, suggesting a non-linear positive correlation beyond a certain threshold. On the other hand, Kong et al. demonstrated that digital transformation amplifies the within-firm pay gap, with executives’ income growing at a faster pace than that of ordinary employees, particularly in firms facing intense competition, those operating in traditional industries, those larger in size, and those with lower executive shareholdings [34]. A study by Zhou et al. complemented these findings by highlighting the role of executive equity incentives, rather than just compensation, in promoting digital transformation [24]. They found that higher executive equity ownership aligns executives’ interests with long-term corporate goals, motivating them to drive digital transformation initiatives. However, this effect is moderated by factors like ownership concentration, independent board oversight, market distortions, and political connections, underscoring the importance of optimizing governance mechanisms alongside incentive structures.

Collectively, these studies underscore the crucial role of digital transformation and innovation in driving corporate ESG performance. They also highlight the importance of embracing digital technologies to facilitate firms’ transition towards sustainable development goals and stakeholder responsiveness. The literature on sustainability disclosure, ESG investing, CEO compensation, and digital transformation collectively suggests several critical linkages that inform the research question. The growth of ESG disclosure and investing in China highlights the increasing importance of sustainability performance for Chinese listed firms [6,8]. Moreover, the literature on CEO compensation and ESG suggests that tying executive pay to sustainability metrics can improve ESG outcomes [3]. Finally, digital transformation and sustainability studies indicate that digitalization can enhance ESG performance by improving efficiency, transparency, and innovation [25,35].

The theoretical linkage between digital transformation (DT) and ESG performance is anchored in stakeholder theory and the resource-based view (RBV). Stakeholder theory posits that firms must balance the interests of diverse stakeholders, including those advocating for environmental sustainability and social responsibility. DT facilitates this balance by enhancing operational transparency, enabling real-time data sharing, and fostering stakeholder engagement through platforms like AI-driven analytics and blockchain traceability. For instance, Wang et al. demonstrated that DT reduces environmental pollution by optimizing resource allocation, directly addressing stakeholder concerns about ecological impacts [30]. Simultaneously, the RBV frames DT as a strategic resource that drives ESG outcomes by improving internal governance and green innovation capabilities. Lu et al. found that firms leveraging advanced technologies (e.g., IoT, big data) achieve higher ESG ratings due to improved efficiency and compliance [9]. These theoretical perspectives collectively underscore DT’s dual role as both a governance enabler and a catalyst for sustainable value creation, bridging technological advancement with stakeholder-centric ESG objectives.

Existing research indicates that digital transformation can positively influence ESG outcomes by improving operational efficiency, enabling sustainable practices, and facilitating stakeholder engagement [27,36,37]. From the perspective of stakeholder theory [17], digital transformation can facilitate better stakeholder engagement and management of stakeholder relationships, which is crucial for creating value for all stakeholders and addressing their diverse interests [26]. Additionally, the resource-based view suggests that digital technologies can be leveraged as strategic resources to drive improvements in ESG performance, contributing to a firm’s competitive advantage [19].

Existing research has confirmed that digital transformation significantly drives corporate ESG performance. From the environmental perspective, digital technologies reduce carbon emission intensity by optimizing resource allocation. For example, Hao et al. found that industrial digitalization in China increased clean energy efficiency, with energy management systems and smart grids contributing significantly to emission reductions [25]. In the social dimension, artificial intelligence and big data analytics enhance supply chain transparency. Zhao and Cai demonstrated that in China’s heavily polluting industries, an increase in digitalization level led to a significant rise in ESG scores [32]. In terms of governance, blockchain technology reduces the risk of ESG data tampering through distributed ledgers. Wang et al. pointed out that companies implementing blockchain audits experienced a substantial decrease in ESG controversy incidents [30]. Darnall et al. demonstrated that digital tools can enhance the quality of information disclosure [7].

According to agency theory by Jensen and Meckling [21], conflicts can arise between shareholders and management, including conflicts of interest or goals and differences in risk preferences [38]. By aligning digital transformation initiatives with ESG objectives, companies can mitigate these agency conflicts, improve transparency and accountability, and better align the interests of management with those of stakeholders. Based on the preceding discussions, the following hypothesis is established:

H1a: 

Higher levels of digital transformation are positively associated with better ESG performance.

However, in the Chinese context, in which some companies are partially owned by the government (State-Owned Enterprises; SOEs), we might expect different dynamics. Moreover, the impact of digital transformation may be less pronounced in large companies than in smaller firms.

Firm size is another crucial factor to consider when examining the impact of digital transformation on ESG performance. Larger firms typically possess more resources and capabilities to invest in digital technologies and implement comprehensive ESG strategies [39]. They may also face more significant stakeholder pressures and reputational risks, which can drive their commitment to ESG initiatives. In contrast, smaller firms may struggle to allocate sufficient resources to digital transformation and ESG efforts, potentially limiting their benefits from these initiatives [37]. A study by Duan et al. on Chinese manufacturing firms found that better ESG performance significantly increases firm value, with this positive effect being more pronounced for larger firms in the economically developed eastern region due to greater resources and capabilities [40].

SOEs, pivotal in many economies such as China, encounter unique challenges and opportunities in digital transformation and ESG development. SOEs are often subject to greater institutional pressures and public attention, which can incentivize them to prioritize ESG initiatives [41]. In addition, digital transformation can provide SOEs with the tools and capabilities to meet these expectations and enhance their organizational legitimacy. In contrast, SOEs may face bureaucratic barriers and resource constraints that hinder their ability to fully leverage digital technologies for ESG improvements [41].

Alternatively, SOEs might encounter administrative obstacles and limitations in resources, which can impede their capacity to effectively utilize digital advancements for enhancing ESG performance. Bureaucratic decision-making processes can slow down the adoption and implementation of digital initiatives. Moreover, resource allocation within SOEs may not always prioritize digital transformation, especially when competing with other strategic objectives. This can result in a mixed performance in terms of ESG outcomes, where some SOEs excel while others lag behind.

The relationship between digital transformation and ESG performance in SOEs warrants further investigation. Hence, a moderator is introduced into the model to explore the observations further:

H1b: 

Larger firms have a stronger positive relationship between digital transformation and ESG performance.

H1c: 

State-owned enterprises (SOEs) exhibit a stronger relationship between digital transformation and ESG performance than non-SOEs.

2.4. CEO Compensation and ESG

CEO characteristics influence corporate performance and strategic decisions, influencing the company’s sustainability efforts and financial results. For instance, Barber and Odean found that male CEOs tend to trade more excessively than their female counterparts due to overconfidence, leading to lower net returns [22]. This gender difference in behavior highlights the potential influence of CEO gender on corporate decision-making and performance. Similarly, Romano et al. examined the relationship between board gender diversity and ESG engagement, finding that greater gender diversity positively influences ESG performance [42]. However, CEO duality (when the CEO also serves as board chair) can hinder this positive impact.

Furthermore, Garcia-Blandon et al. explored the relationship between CEO characteristics and firm performance, considering financial, ESG, and overall performance [23]. They discovered a strong negative association between financial and ESG performance, with outsider CEOs outperforming insider CEOs in overall performance. The study also explored the age of CEOs but found no significant differences among the three age groups it divided them into. One possible explanation is the low variability in CEO ages within their sample of companies, which may have prevented the adequate capture of age effects. For example, in 85% of cases, the CEO’s age fell between 50 and 65 years [23]. The CEO’s career horizon also affects a firm’s ESG engagement, suggesting that the CEO faces a conflict of interest between career aspirations and legacy considerations, influencing their willingness to pursue ESG initiatives. Maximum ESG engagement is observed when the CEO is around 53 years old [43].

Cohen et al. provided international evidence that basing executive compensation on ESG metrics is rapidly increasing, with over 30% of major global firms now using sustainability KPIs [3]. They found that firms tying pay to ESG goals exhibit subsequent improvements in key ESG outcomes like emissions and ratings. This suggests that incentive alignment between top management pay and sustainability objectives can enhance the accountability and credibility of a company’s ESG efforts. While linking ESG to executive pay and mandated reporting may have benefits, a lack of consensus on measuring sustainability poses challenges in accountability and economic impacts that require further research [2].

Similar research conducted in China by Zhu et al. in Chinese listed companies found that executive compensation incentives have a significant positive effect on ESG performance [44], working through channels such as increased corporate social responsibility, improved internal control quality, and enhanced financial performance. However, the positive relationship is moderated by factors such as management shareholding and the proportion of independent directors.

From the lens of agency theory [21], incorporating ESG metrics into executive compensation schemes can help align the interests of top management with broader stakeholder interests and ESG objectives [10]. Executive compensation is found to incentivize firm ESG performance, as it can align managerial interests with those of shareholders and motivate managers to prioritize sustainability and a long-term perspective [3,44]. This alignment enhances the accountability and credibility of a company’s ESG efforts, as CEOs are incentivized to prioritize and achieve sustainability goals.

H2a: 

Higher CEO compensation is positively associated with better ESG performance.

However, the upper echelons theory suggests that CEO characteristics may influence the effectiveness of such compensation schemes, raising interest in further examining the moderating influence of CEO characteristics in the relationship between CEO compensation and ESG performance [20].

CEO age is a crucial factor to consider when examining the impact of ESG-linked compensation on sustainability outcomes [43]. Younger CEOs may be more receptive to innovative compensation structures prioritizing ESG metrics, as they are more likely to embrace contemporary trends and adapt to changing stakeholder expectations [23]. This aligns with the upper echelons theory [20], which suggests that personal and psychological traits, such as age, can influence CEO decision-making and strategic choices. In contrast, older CEOs may be more resistant to change and less likely to prioritize ESG initiatives, even when incentivized through compensation [23]. This could be due to a shorter-term focus on financial performance or a lack of familiarity with the growing importance of ESG factors in the business environment.

Gender diversity in top management positions has also been linked to improved ESG performance [45]. Female CEOs may be more inclined to prioritize ESG issues and respond positively to compensation schemes that reward sustainability efforts. This could be due to differences in leadership styles, risk preferences, and values between male and female executives [20]. Studies have shown that female leaders exhibit more transformational leadership behaviors, emphasizing collaboration, empowerment, and long-term thinking [42]. These qualities may make female CEOs more likely to embrace ESG initiatives and drive sustainability performance when incentivized through compensation.

Hence, a moderator is introduced into the model to explore the observations further:

H2b: 

The effect of CEO compensation on ESG performance varies with CEO age, such that the effect of CEO compensation on ESG performance is stronger for younger CEOs.

H2c: 

The effect of CEO compensation on ESG performance differs between male and female CEOs, such that the effect of CEO compensation on ESG performance is stronger for female CEOs.

2.5. Digital Transformation, CEO Compensation, and ESG Performance

Building upon the stakeholder theory [17], resource-based view [19], and agency theory [21], the combination of digital transformation and CEO compensation aligned with ESG goals can create a powerful synergy for enhancing a firm’s ESG performance.

The integration of DT and CEO compensation is justified by agency theory and upper echelons theory. Agency theory suggests that aligning CEO incentives (compensation) with long-term goals (ESG) mitigates conflicts between managers and stakeholders. DT provides the tools to achieve these goals efficiently. Upper echelons theory highlights that CEO characteristics (e.g., age, gender) influence how compensation and DT interact to affect ESG. For instance, older CEOs may leverage DT more effectively when incentivized. Prior work shows non-linear relationships between compensation and DT, supporting their joint analysis [33].

After examining the individual effects of digital transformation and CEO compensation on ESG performance in the previous hypotheses (H1 and H2), it is essential to investigate their joint effect. As already demonstrated by Ma and Wang, combining digital transformation and CEO compensation may create a synergistic effect that enhances firm performance [33]. Digital transformation enables companies to adopt more sustainable practices, while CEO compensation aligned with ESG goals incentivizes top management to prioritize ESG initiatives [46].

Moreover, adopting digital technologies can improve the efficiency and effectiveness of ESG-related decision-making and implementation processes. For example, big data analytics can help companies better understand and manage their environmental impact, while artificial intelligence can optimize resource allocation for social responsibility projects. When CEOs are adequately compensated for achieving ESG targets, they are more likely to leverage these digital capabilities to drive ESG performance [28,39].

Based on the preceding discussions, the following hypothesis is established:

H3: 

The interaction between digital transformation and CEO compensation positively affects ESG performance, such that the effect of digital transformation is stronger for firms with higher CEO compensation.

In Figure 1, the study illustrates the conceptual relationships among the variables within our theoretical framework. The primary independent variables are digital transformation (denoted as DT) and CEO compensation. The dependent variable is ESG ratings. The moderators include state ownership (denoted as SOE) and firm size (denoted as lnTA) with respect to DT, as well as CEO gender and CEO age with respect to CEO compensation. These relationships are depicted in Figure 1.

2.6. The Synergistic Effect of Digital Transformation and CEO Compensation

Drawing on resource dependence theory, this study highlights the synergistic interplay between digital transformation and CEO compensation in enhancing ESG performance. Digital transformation equips firms with critical technical resources—such as data analytics, intelligent systems, and operational efficiencies—to advance sustainability goals. Concurrently, CEO compensation mechanisms serve as governance resources that align managerial incentives with ESG objectives, fostering goal congruence between executives and stakeholders. Together, these resources form a self-reinforcing cycle: technological advancements empower firms to operationalize ESG practices, while strategically designed compensation frameworks motivate leaders to prioritize long-term sustainability over short-term financial gains.

This study makes several significant theoretical contributions to the literature on organizational management, corporate governance, and ESG performance, particularly in the context of digital transformation and CEO compensation.

Firstly, the study reinforces and extends stakeholder theory by demonstrating how digital transformation serves as a strategic tool to enhance stakeholder engagement and align corporate actions with broader societal and environmental goals [17]. By linking digital transformation to improved ESG performance, the study also bridges stakeholder theory with the RBV [19], illustrating how digital technologies act as valuable, rare, and inimitable resources that drive sustainable competitive advantage. This dual theoretical lens provides a more nuanced understanding of how firms can leverage digital capabilities to meet stakeholder expectations while achieving long-term sustainability.

Secondly, the study advances agency theory by empirically validating that CEO compensation tied to ESG metrics mitigates agency conflicts [21]. The positive association between CEO compensation and ESG performance underscores the role of incentive alignment in motivating executives to prioritize non-financial goals. Furthermore, the moderating effects of CEO age and gender highlight the importance of upper echelons theory [20], suggesting that executive characteristics influence the effectiveness of compensation structures in driving ESG outcomes. These insights enrich the discourse on how governance mechanisms can be tailored to individual leader profiles.

Thirdly, the study contributes to the emerging literature on digital governance by positioning digital transformation not merely as a technological shift but as a governance enabler. The interaction between digital transformation and CEO compensation reveals a synergistic effect, supporting the notion that digital tools enhance transparency and accountability, thereby reinforcing traditional governance frameworks. This aligns with recent calls to integrate digital strategies into corporate governance models [24].

Theoretically, this study bridges stakeholder theory and the resource-based view by demonstrating how digital technologies amplify stakeholder engagement and create inimitable competitive advantages. It also refines agency theory by illustrating how ESG-aligned incentives mitigate conflicts between executive interests and stakeholder expectations. Furthermore, it expands digital governance scholarship by positioning digital transformation as a governance enabler that enhances transparency and accountability. Collectively, these findings underscore the importance of integrating technological and governance strategies to address complex sustainability challenges in the digital era.

3. Methodology

3.1. Data

The sample data cover Chinese A-listed companies from 2018 to 2022. The financial, ESG, and CEO-related datasets were sourced from the Wind Information database [31,44]. To measure digital transformation frequency, word processing was used on firms’ yearly financial reports, also sourced from Wind, and then processed using RStudio (R version 4.3.1). To mitigate the impact of outliers, all continuous variables were winsorized, replacing outliers’ values below the 1st percentile and above the 99th percentile with the respective percentile values. Observations with missing data for key variables were omitted. The final sample includes 4399 firms and 16,205 firm-year observations.

3.2. Variables

3.2.1. Dependent Variable

Following the literature [31,44], the ESG score given by a credible rating agency was chosen to measure company ESG performance. The Wind ESG rating (ESG Rating) for Chinese A-shares was used. This rigorous ESG rating system, tailored to the Chinese market and backed by data since 2017 (hence, the rating starts from 2018), effectively allows this study to measure Chinese A-stock companies’ ESG performance. According to the rating introduction, the Wind ESG Comprehensive Score (10 points max) consists of the Management & Practices Score (7 points max) and the Controversies Score (3 points max), displayed as AAA to CCC in seven scales. The Wind ESG Rating assesses companies based on three pillars, covering 25 topics and 300+ underlying indicators. It includes more than 22,000+ reliable sources and is powered by AI, big data, and other technologies to ensure data accuracy.

3.2.2. Independent Variables

Digital transformation frequency was extracted using the RStudio “stringr” package. Keywords were counted from yearly reports and then used to measure the firm’s digital transformation quantitatively. The credibility of this method is based on several factors. First, annual reports are the principal means through which the market gains insights into corporate information. They are official documents that outline a company’s financial performance over the fiscal year. Moreover, the textual content of these reports is a vital channel for companies to communicate their strategic priorities, such as digital transformation initiatives. Given the regulatory requirements enforced by the China Securities Regulatory Commission (CSRC), annual report disclosures must be truthful, accurate, complete, and timely. As a result, when confronted with significant changes in the environment—such as technological advancements or policy shifts—companies are likely to address these issues diligently in their annual reports. A higher frequency of specific keywords in the text indicates that digital transformation is a key focus of the firm’s future development strategy.

The selection of keywords in this study is based on the stage-specific characteristics of corporate digital transformation. First, when initiating digital transformation, companies typically clarify their development strategies to differentiate themselves in the market. Accordingly, keywords directly tied to digital transformation concepts are included in the lexicon. Second, during the early stages of transformation, firms primarily adopt digital technologies to optimize daily business processes such as production. Thus, keywords related to specific digital technologies are incorporated. Finally, the ultimate goal of digital transformation lies in the digitization of business practices, prompting the inclusion of keywords associated with digital applications. A total of 123 keywords related to company digital transformation were used and grouped into three stages. These keywords fell under eight comprehensive components: digital transformation concepts, artificial intelligence, blockchain, cloud computing, big data, the Internet of Things, Industry 4.0, and digital applications. These keywords make up a lexicon capturing the terminology associated with organizational digital transformation initiatives (Appendix A).

The frequency of each keyword was used as a proxy measurement, following prior research [47,48]. In practice, the actions represented by the keywords can be further divided into stages along the firm digital transformation process.

In the first stage, when beginning to adopt and discuss digital transformation, companies typically develop strategies to stand out from the competition, incorporating terminology tied directly to digital transformation ideas [49]. In the following stage, firms brought in digital technologies like artificial intelligence, blockchain, cloud computing, and big data to streamline daily processes in production, sales, and customer relationship management [50]. Since the ultimate objective of a company’s digital transformation center is to apply and optimize business practices effectively, the third stage contains additional keywords that are considered relevant to applying these digital technologies [35]. Finally, the variable measuring the whole process of firm digital transformation is generated by counting the frequency of all the keywords reported by the firm.

Table 1. Summary of digital transformation variables.

Variable	Obs.	Mean	SD	Min	Med	Max
Sum of Words	16,205	40.97	61.27	0	18	351
Concept of DT	16,205	14.71	21.21	1	7	123.96
AI	16,205	4.07	10.03	0	1	67
Blockchain	16,205	0.33	1.34	0	0	10
Cloud Computing	16,205	1.70	5.37	0	0	37
Big Data	16,205	5.28	12.17	0	1	77
Internet of Things	16,205	2.77	7.85	0	0	54
Industry 4.0	16,205	3.99	9.23	0	1	61
Digital Application	16,205	5.44	10.57	0	1	64

provides summary statistics of the eight digital transformation categories mentioned above. The concept of digital transformation is the most frequently discussed, with an average of 15.25 mentions per report. Among specific technologies, digital applications and big data stand out as the most prominent, with averages of 5.9 and 5.73 mentions per report, respectively, followed closely by AI and Industry 4.0. Blockchain and cloud computing, while important, receive comparatively less attention. The high standard deviations across all variables suggest significant variation in the extent to which these technologies are discussed, potentially due to differences in industry focus or the maturity of digital transformation initiatives.

CEO compensation refers to the total value of pay and benefits provided to a company’s Chief Executive Officer. This variable sums up the CEO’s base salary, bonuses, stock options, restricted stock units (RSUs), long-term incentive plans (LTIPs), benefits, severance pay, and any other monetary or non-monetary compensation they may receive. The monetary unit used is one million Chinese yuan.

3.2.3. Moderating Variables

To examine potential moderating effects, several variables were included, similar to the ones used as controls. Firm size was measured as the natural logarithm of total assets (lnTA). State-ownership (SOE) indicated whether a firm is state-owned (1) or non-state-owned (0). CEO age (CEO_age) was included as a continuous variable representing the CEO’s age from their birth year to the relevant year. CEO gender (CEO_gender) was generated as a dichotomous variable indicating whether the CEO is female (1) or not (0).

3.2.4. Control Variables

Following standard practice established in the literature [44,47,51,52,53], a set of control variables was used to address possible confounding factors: Tobin’s Q ratio is a measure of a company’s market value relative to its asset replacement cost (TobinsQ); leverage is measured as the ratio between debt and total assets (Leverage); return on assets is the ratio of net income to total assets (ROA); return on equity is the ratio of net income to shareholders’ equity (ROE); tenure of the firm is the total years of the firm being listed (Listing_tenure); a dichotomous variable was generated, with 1 indicating that the CEO also serves as board chair and 0 otherwise (Duality); and the ratio of independent directors on the board suggesting the firm’s board independence (Indirratio).

3.3. Econometric Specification

Following the literature [30,54], a firm-year two-way fixed effect model was used, utilizing panel data and control variables to enable the treatment of unobserved firm heterogeneity. Using a fixed effect model helps control for unobserved time-invariant differences between firms, while clustering standard errors at the firm level accounts for potential heteroskedasticity. Lagged independent variables are used to address reverse causality concerns. The baseline model regression equation is proposed as follows:

$${\mathrm{E}\mathrm{S}\mathrm{G}\_\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e}}_{\mathrm{i},\mathrm{t}}={\mathsf{\alpha }}_0+{\mathsf{\beta }}_1{\mathrm{I}\mathrm{V}}_{\mathrm{i},\mathrm{t}}+{\mathsf{\beta }}_2{\mathrm{I}\mathrm{V}}_{\mathrm{i},\mathrm{t}}\times \mathrm{M}+\sum {{\mathsf{\beta }}_{\mathrm{k}}\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{s}}_{\mathrm{k},\mathrm{i},\mathrm{t}}+{\mathsf{\mu }}_{\mathrm{i}}+{\mathsf{\gamma }}_{\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i},\mathrm{t}}$$

(1)

where $\mathrm{E}\mathrm{S}\mathrm{G}\_\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e}$ is the explained variable; IV is the explanatory variable(s), either digital transformation measure, CEO compensation, or their interaction; $\mathrm{i}$ represents firm $\mathrm{i}$; $\mathrm{t}$ represents year $\mathrm{t}$; $\mathrm{k}$ represents control variable k; M is the moderating interaction for the relevant hypothesis if it exists, and it is the interaction between the moderator and the independent variable; $\mathsf{\mu }$ is the fixed effect of individual firms; $\mathsf{\gamma }$ is the fixed effect of the year, used to control other non-observable factors that do not change over time; and $\mathsf{\epsilon }$ is the random error term. To ensure that multicollinearity does not affect the reliability of the regression coefficients, the Variance Inflation Factor (VIF) was calculated for each of the variables. All VIF values were below 2, indicating minimal multicollinearity. This suggests that each predictor provides unique information, and the regression model’s estimates are reliable.

4. Results

4.1. Descriptive Statistics

As showed in

Table 2. Descriptive statistics of the key variables.

Variable	Obs.	Mean	SD	Min	Med	Max
ESG Rating	16,205	6	0.79	4.26	5.96	8.25
DT_freq	16,205	2.92	1.35	0	2.94	5.86
CEO_compensation	16,205	1.20	1.16	0.09	0.85	7.18
lnTA	16,205	22.37	1.38	20.02	22.14	27.12
SOE	16,205	0.35	0.48	0	0	1
TobinsQ	16,205	1.90	1.76	0.08	1.40	10.09
CEO_age	16,205	48.35	7.35	30	49	66
CEO_gender	16,205	0.08	0.27	0	0	1
Leverage	16,205	149.74	330.61	−1109.92	81.21	2031.34
ROE	16,205	5.41	16.33	−85.28	7.23	41.89
ROA	16,205	3.84	7.39	−27.82	3.92	23.81
Indirratio	16,205	0.38	0.06	0.11	0.36	1
Duality	16,205	0.34	0.47	0	0	1
Listing_tenure	16,205	11.01	8.34	0.43	9.09	29.03

, the mean ESG rating is 6, with scores ranging from 3.14 to 9.61. CEO compensation is shown in millions of Chinese yuan and averages 1.25 but varies from 0.001 to 54.97, reflecting divergent pay practices. The average firm size, measured by lnTA, is 22.38 (around CNY 5 billion in assets), ranging from 18.28 to 31.17. Tobin’s Q averages 1.93, suggesting higher market valuations than asset costs on average, though values span 0.02 to 33.23. The mean age of firm CEOs is 48.35 years, ranging from 23 to 78 years old. Roughly 35% of firms are state-owned enterprises. The majority of the sample firm CEOs are male, with only 8% being female.

4.2. Digital Transformation and ESG Performance

Table 3. Digital transformation and ESG performance.

	ESGRating
	(1)	(2)	(3)
L.DT_freq		0.05822 ***	−0.47712 ***
		(0.00609)	(0.07912)
lnTA	0.14518 ***	0.13419 ***	0.06155 ***
	(0.00810)	(0.00810)	(0.01350)
SOE	0.04641 *	0.05383 **	0.06892 *
	(0.02508)	(0.02479)	(0.04055)
L.DT_freq x lnTA			0.02405 ***
			(0.00359)
L.DT_freq x SOE			−0.00476
			(0.01108)
CEO_age	0.00302 **	0.00293 **	0.00285 **
	(0.00136)	(0.00135)	(0.00135)
CEO_gender	−0.06341 *	−0.07107 **	−0.06897 *
	(0.03575)	(0.03533)	(0.03537)
TobinsQ	0.00921 **	0.01000 ***	0.00877 **
	(0.00361)	(0.00360)	(0.00360)
Leverage	−0.00003	−0.00003	−0.00003
	(0.00024)	(0.00024)	(0.00024)
ROE	0.00005 **	0.00005 **	0.00005 **
	(0.00002)	(0.00002)	(0.00002)
ROA	0.00121 **	0.00120**	0.00118 **
	(0.00060)	(0.00060)	(0.00059)
Indirratio	0.33347 ***	0.28583 **	0.28128 **
	(0.09647)	(0.09621)	(0.09608)
Duality	−0.04715 **	−0.05097 **	−0.05116 **
	(0.02289)	(0.02262)	(0.02265)
Listing_tenure	−0.01926 ***	−0.01835 ***	−0.01882 ***
	(0.00137)	(0.00136)	(0.00136)
Industry Fixed Effect	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes
N	16,205	16,205	16,205
R2	0.44756	0.45226	0.45347
Adjusted R2	0.44671	0.45138	0.45252

Notes: (1) * significant at 10%, ** significant at 5%, *** significant at 1%; (2) L. means one year lagged; (3) standard errors are in parenthesis.

presents the regression results for the main effect of digital transformation on ESG performance (H1a) and the moderating effects of firm size (H1b) and state ownership (H1c). Column 1 shows the regression results of the control variables. Column 2 shows the effect of firm digital transformation on ESG rating, controlling for various factors. Column 3 introduces interaction terms to examine the moderating roles of firm size and state ownership, respectively.

In hypothesis H1a, we hypothesize that higher levels of digital transformation are positively associated with better ESG performance which predicts a positive association between digital transformation and ESG performance. The result presented in Column 2 offers supporting evidence for this hypothesis. The coefficient for the firm digital transformation measure is positive and statistically significant at the 1% level.

In hypothesis H1b, we hypothesize that larger firms have a stronger positive relationship between digital transformation and ESG performance, which proposes that the positive relationship between digital transformation and ESG performance is more pronounced for larger firms. Column 3 examines this hypothesis by incorporating an interaction term between digital transformation and firm size measures, which is positive and significant at the 1% level. This result supports H1b.

In hypothesis H1c, we hypothesize that state-owned enterprises (SOEs) exhibit a stronger relationship between digital transformation and ESG performance than non-SOEs, predicting that the positive relationship between digital transformation and ESG performance is stronger for state-owned enterprises than non-SOEs. Column 3 also investigates this hypothesis by incorporating an interaction term between digital transformation and SOE measures, which is negative but not significant. Hence, H1c is not supported.

4.3. CEO Compensation and ESG Performance

Table 4. Compensation and ESG performance.

	ESG Rating
	(1)	(2)	(3)
CEO_compensation		0.01969 ***	−0.04123
		(0.00412)	(0.02597)
CEO_age	0.00302 **	0.00283 **	0.00133
	(0.00136)	(0.00136)	(0.00149)
CEO_gender	−0.06341 *	−0.06400 *	−0.02966
	(0.03575)	(0.03564)	(0.04065)
CEO_compensation x CEO_age			0.00129 **
			(0.00052)
CEO_compensation x CEO_gender			−0.02766 *
			(0.01565)
lnTA	0.14518 ***	0.13655 ***	0.13631 ***
	(0.00810)	(0.00828)	(0.00828)
SOE	0.04641 *	0.04918 **	0.04810 *
	(0.02508)	(0.02501)	(0.02501)
TobinsQ	0.00921 **	0.00829 **	0.00837 **
	(0.00361)	(0.00361)	(0.00361)
Leverage	−0.00003	−0.00002	−0.00002
	(0.00024)	(0.00024)	(0.00024)
ROE	0.00005 **	0.00005 **	0.00005 **
	(0.00002)	(0.00002)	(0.00002)
ROA	0.00121 **	0.00102 *	0.00103 *
	(0.00060)	(0.00060)	(0.00060)
Indirratio	0.32271 ***	0.33472 ***	0.33440 ***
	(0.09634)	(0.09640)	(0.09639)
Duality	−0.04715 **	−0.04757 **	−0.04839 **
	(0.02289)	(0.02282)	(0.02282)
Listing_tenure	−0.01926 ***	−0.01909 ***	−0.01912 ***
	(0.00137)	(0.00136)	(0.00136)
Industry Fixed Effect	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes
N	16,205	16,205	16,205
R2	0.44756	0.44882	0.44912
Adjusted R2	0.44671	0.44793	0.44817

Notes: (1) * significant at 10%, ** significant at 5%, *** significant at 1%; (2) standard errors are in parenthesis.

presents the regression results for the main effect of CEO compensation on ESG performance (H2a) and the moderating effects of CEO age (H2b) and CEO gender (H2c). Column 1 shows the regression results of the control variables. Column 2 shows the direct effect of CEO compensation on ESG performance, controlling for various factors. Column 3 introduces interaction terms to examine the moderating roles of CEO age and gender, respectively.

In hypothesis H2a, we hypothesize that higher CEO compensation is positively associated with better ESG performance, which predicts a positive relationship between CEO compensation and ESG performance. However, the result in Column 2 provides full support for this hypothesis since the coefficient for CEO compensation is positive and significant at the 1% level.

In hypothesis H2b, we hypothesize that the effect of CEO compensation on ESG performance varies with CEO age, such that the effect of CEO compensation on ESG performance is stronger for younger CEOs. H2b proposes that the positive effect of CEO compensation on ESG performance differs and is stronger for younger CEOs. Column 3 shows the result by introducing an interaction term between CEO compensation and CEO age. The coefficient is positive and significant at the 5% level, which contrasts with H2b. This indicates that the positive relationship between CEO compensation and ESG performance is more pronounced for older than younger CEOs.

In hypothesis H2c, we hypothesize that the effect of CEO compensation on ESG performance differs between male and female CEOs, such that the effect of CEO compensation on ESG performance is stronger for female CEOs. H2c predicts that the positive effect of CEO compensation on ESG performance is stronger for female CEOs. Column 3 also shows the result by including an interaction term between CEO compensation and CEO gender. The interaction term is negative and significant at the 10% level, providing no support for H2c. This suggests that the effect of CEO compensation on ESG performance differs significantly between male and female CEOs, but the effect of CEO compensation on ESG performance is stronger for males.

The gender of the CEO also impacts the relationship between digital transformation and ESG performance. This study finds that male CEOs are more proactive in linking digital transformation with ESG performance. This may be related to the risk preferences and strategic decision-making styles of male CEOs. However, future research can further explore the underlying mechanisms of gender differences, such as by analyzing the leadership styles and decision-making processes of CEOs of different genders.

4.4. The Joint Effect of Digital Transformation and CEO Compensation on ESG Performance

Table 5. Digital transformation, CEO compensation, and ESG performance.

	ESG Rating
	(1)	(2)	(3)
L.DT_freq		0.05822 ***	0.05118 ***
		(0.00609)	(0.00674)
CEO_compensation			0.00042
			(0.00926)
L.DT_freq x CEO_compensation			0.00531 **
			(0.00240)
CEO_age	0.00255 *	0.00293 **	0.00276 **
	(0.00138)	(0.00135)	(0.00134)
CEO_gender	−0.06113 *	−0.07107 **	−0.07048 **
	(0.03633)	(0.03533)	(0.03524)
lnTA	0.12146 ***	0.13419 ***	0.12627 ***
	(0.00803)	(0.00810)	(0.00828)
SOE	−0.07082 ***	0.05383 **	0.05551 **
	(0.02406)	(0.02479)	(0.02473)
TobinsQ	0.01142 ***	0.01000 ***	0.00929 ***
	(0.00363)	(0.00360)	(0.00360)
Leverage	−0.00002	−0.00003	−0.00003
	(0.00025)	(0.00024)	(0.00024)
ROE	0.00006 **	0.00005 **	0.00005 **
	(0.00002)	(0.00002)	(0.00002)
ROA	0.00192 ***	0.00120 **	0.00104 *
	(0.00060)	(0.00060)	(0.00060)
Indirratio	0.33162 ***	0.31721 ***	(0.09614)
	(0.09706)	(0.09621)	(0.09706)
Duality	−0.00672	−0.05097 **	−0.05149 **
	(0.02308)	(0.02262)	(0.02256)
Listing_tenure	−0.01837 ***	−0.01835 ***	−0.01824 ***
	(0.00136)	(0.00136)	(0.00135)
Industry Fixed Effect	Yes	Yes	Yes
Year Fixed Effect	Yes	Yes	Yes
Obs	16,205	16,205	16,205
R2	0.43866	0.45226	0.45349
Adjusted R2	0.43783	0.45138	0.45254

Notes: (1) * significant at 10%, ** significant at 5%, *** significant at 1%; (2) L. means one year lagged; (3) standard errors are in parenthesis.

shows the regression outcomes for the joint effect of digital transformation and CEO compensation on ESG performance. In hypothesis H3, we hypothesize that the interaction between digital transformation and CEO compensation positively affects ESG performance, such that the effect of digital transformation is stronger for firms with higher CEO compensation. H3 predicts that firm digital transformation and CEO compensation can reinforce each other in strengthening firm ESG performance. The results in Table 5, as shown in Column 3, provide support for this hypothesis. The coefficient for the interaction term between firm digital transformation and CEO compensation is positive and significant at the 5% level, suggesting a synergetic effect.

5. Robustness Test

Given the potential endogeneity concerns between a firm’s digital transformation and its ESG performance—stemming from issues such as omitted variables and reverse causality (i.e., firms with higher ESG ratings may be more inclined to pursue digital transformation to more effectively convey their ESG information to stakeholders)—this study employs an instrumental variables approach to mitigate these biases and assess the robustness of the findings. We use the local government marketization index in the region where the sample enterprises are located as an instrumental variable, similar to Lu et al., who used the regional digitalization level as an IV [9].

Table 6. Robustness test of the relationship between digital transformation and ESG performance using marketization index as an instrumental variable.

	ESG Ratings
DT_freq	0.68889 ***
	(0.13048)
lnTA	0.01437
	(0.02383)
SOE	0.13884 ***
	(0.02415)
CEO_age	0.00150
	(0.00112)
CEO_gender	−0.14989 ***
	(0.03373)
TobinsQ	0.03247 ***
	(0.00489)
Leverage	0.00026
	(0.00045)
ROE	0.00005
	(0.00005)
ROA	0.00726 ***
	(0.00097)
Indirratio	−0.03182
	(0.14453)
Duality	−0.09383 ***
	(0.01961)
Listing_tenure	−0.00659 ***
	(0.00246)
Industry Fixed Effect	Yes
Year Fixed Effect	Yes
Obs	16205

Notes: (1) *** significant at 1%; (2) standard errors are in parenthesis.

presents the results of the instrumental variables test, indicating that the regression coefficient for digital transformation is 0.68889, which is statistically significant at the 1% level. This finding underscores the robustness and reliability of the study’s conclusions.

6. Discussion and Conclusions

6.1. Discussion

This study investigates the effects of digital transformation and CEO compensation on the ESG performance of Chinese listed companies. It analyses a comprehensive dataset built from financial data, scores given by ranking agencies, and a matrix built from a word-counting technique containing 16,205 firm-year observations from 2018 to 2022. The evidence supports the hypothesis and the research question, finding a positive impact of digital transformation and CEO compensation on ESG performance and moderating effects from firm size, state ownership, CEO age, industry, and region.

The results show that higher levels of digital transformation, mainly focusing on the overall concept of digital transformation, are positively associated with better ESG performance. This relationship is stronger for larger firms, and state-owned compared to non-SOE enterprises show mixed results regarding different digital transformation measurements, suggesting that firm size plays a crucial role in the effectiveness of digital transformation initiatives in promoting ESG performance and that state ownership can have a mixed influence on company sustainable efforts, but the concept itself positively influences it. These findings are consistent with the literature on digital transformation and ESG performance, highlighting digital technologies’ importance in driving sustainability efforts [9,32,52].

The findings suggest that while firm size is a critical determinant in the success of digital transformation efforts, state ownership introduces complexities that can either enhance or detract from a company’s sustainable development initiatives. Given the varying impacts of digital transformation on ESG performance across different firm sizes and ownership structures, policymakers should take these characteristics into account. For instance, larger firms could be provided with enhanced incentives for digital transformation to boost their ESG performance. For SOEs, given their mixed results in leveraging digital transformation for ESG performance, policymakers should prioritize institutional reforms to reduce bureaucratic inefficiencies while enhancing resource allocation for digital initiatives. For instance, policymakers could integrate ESG metrics into SOEs’ performance evaluation frameworks, coupled with targeted funding for digital infrastructure.

Large firms have significant advantages in digital transformation and ESG performance. With abundant resources, large firms can more easily invest in advanced digital technologies such as artificial intelligence and big data analytics, thereby enhancing their ESG performance. For example, large firms can establish intelligent supply chain management systems to optimize resource utilization efficiency and reduce their environmental footprint. Moreover, large firms typically face greater stakeholder pressure, which prompts them to place greater emphasis on ESG performance.

The age of the CEO significantly moderates the relationship between digital transformation and ESG performance. This study finds that older CEOs are more inclined to link digital transformation with ESG performance, possibly due to their richer industry experience and strategic vision. Older CEOs may be better able to recognize the long-term value of digital transformation for the firm and drive the firm to achieve sustainable development goals through incentive mechanisms.

The gender of the CEO also impacts the relationship between digital transformation and ESG performance. This study finds that male CEOs are more proactive in linking digital transformation with ESG performance. This may be related to the risk preferences and strategic decision-making styles of male CEOs. However, future research should further explore the underlying mechanisms of gender differences, such as by analyzing the leadership styles and decision-making processes of CEOs of different genders.

The findings suggest that while firm size is a critical determinant in the success of digital transformation efforts, state ownership introduces complexities that can either enhance or detract from a company’s sustainable development initiatives. Given the varying impacts of digital transformation on ESG performance across different firm sizes and ownership structures, policymakers should take these characteristics into account. For instance, larger firms could be provided with enhanced incentives for digital transformation to boost their ESG performance.

CEO compensation was found to be positively associated with better ESG performance, and this effect was more pronounced for older CEOs. In addition, the effect of CEO compensation on ESG performance is stronger for male CEOs. These results align with the growing body of research on the relationship between executive compensation and ESG performance, which suggests that aligning CEO pay with sustainability objectives can improve ESG outcomes [3].

6.2. Conclusions

This study contributes to the growing literature on the determinants of ESG performance, particularly in the context of extensive and diverse markets such as China. By highlighting the roles of digital transformation and CEO compensation, as well as the moderating effects of firm characteristics and CEO attributes, valuable insight is provided for policymakers, investors, and corporate decision-makers seeking to promote sustainability. The positive impact of digital transformation and CEO compensation on ESG performance highlights the potential economic benefits of investing in these areas.

Moreover, the moderating effects of firm size and state ownership observed in this study can inform policy decisions and managerial strategies. Policymakers could use these insights to develop targeted initiatives that encourage large firms and SOEs to prioritize digital transformation and align CEO compensation with ESG goals, thereby contributing to China’s overall sustainability objectives. At the firm level, managers can leverage the findings of this study to optimize their digital transformation strategies and CEO compensation structures, leading to improved sustainability performance and long-term economic success.

This study has several more practical implications. First, it underscores the importance of digital transformation in driving ESG performance, especially for larger firms and state-owned enterprises. Companies should consider investing in digital technologies and initiatives to enhance sustainability. Second, the findings suggest that aligning CEO compensation with ESG objectives can effectively improve ESG performance, particularly for older CEOs. Boards and compensation committees should consider incorporating ESG metrics into executive compensation schemes to incentivize top management to prioritize sustainability goals.

For theoretical implications, this study reveals the interactive effects of digital transformation and CEO compensation in ESG governance, thereby expanding the cross-application of upper echelons theory and stakeholder theory. It also proposes a “digital-incentive synergy” framework, offering a new perspective for ESG governance in emerging markets. For enterprises, it is recommended to construct a governance system that links digital capability assessment, ESG target setting, and compensation incentives. For policymakers, there is a call to introduce tax incentives that link digital transformation with ESG, such as subsidies for green digital equipment.

Although this study provides valuable insights into the impact of digital transformation and CEO compensation on ESG performance, there are some limitations. First, the data sample of this study is limited to Chinese listed companies, and the time span is relatively short (2018–2022), which may restrict the generalizability of the research findings. Future studies may consider expanding the sample scope to include companies from different countries and regions to verify the robustness of these findings.

Second, this study uses word frequency analysis to measure digital transformation, a method that, while common in academic research, may have some subjectivity. Future studies could consider employing more sophisticated text analysis methods, such as Natural Language Processing (NLP), to more accurately capture the essence of digital transformation.

In addition, this study mainly focuses on firm size and CEO characteristics as moderating factors, but future research could further explore other potential moderating factors, such as the degree of industry competition and market environment. These factors may significantly influence the relationship between digital transformation and ESG performance under different circumstances.

Lastly, the cross-sectional design of this study limits the inference of causal relationships. Future studies could adopt a longitudinal research design to track the long-term changes of companies in terms of digital transformation and ESG performance to more accurately assess the dynamic relationship between these variables.