How ESG and Digitalization Drive High-Quality Enterprise Development: Evidence from China

Abstract

The ESG performance of enterprises is congruent with contemporary development concepts and plays a pivotal role in promoting enterprises to achieve high-quality development. The present study commences with an evaluation of the high-quality development of firms across multiple dimensions. It then undertakes an empirical investigation into the impact of ESG performance on the high-quality development of firms. This study utilises data from Chinese A-share listed firms from 2010 to 2023. The findings indicate that ESG performance has the capacity to encourage firms to advance towards high-quality development. Digital transformation is identified as a significant factor that positively moderates the facilitating effect of ESG performance on firms. The mechanism of action of ESG performance involves enhancing supply chain stability and alleviating financing constraints. Furthermore, evidence suggests that ESG performance tends to be heterogeneous in its contribution to the high-quality development of enterprises, with more significant facilitating effects for state-owned enterprises and firms in regions with favourable business environments. The present study offers theoretical and practical empirical support for the establishment of an ESG system that is suitable for China’s national conditions and that will promote high-quality firm development.

1. Introduction

As the world’s second-largest economy, China has achieved remarkable economic growth over the past thirty years. However, this period of growth has coincided with the emergence of significant structural and ecological challenges. The economic growth model, which is heavily reliant on a substantial input of factors, has given rise to a series of structural problems. These include industrial low-end lock, a paucity of technological innovation, regional development imbalance, and the widening of the income gap, which have had deleterious effects on the sustainability of China’s economic development [1,2]. The overall quality of China’s economic development has become increasingly fragile. In order to effect a change in this situation, the report of the 20th National Congress of the CPC proposed a new economic development policy, namely to comprehensively turn down the road of high-quality economic development. Evidently, the advancement of macroeconomics towards a state of high quality is contingent upon the parallel development of micro-entities. In this sense, the report identifies the enhancement of enterprise micro-operations as a pivotal practical concern in the context of China’s ongoing economic transformation [3].

The concept of the high-quality development of enterprises is predicated on the continuous enhancement of their core competitiveness and comprehensive strength, whilst pursuing sustainable development. The objective is to achieve stable, healthy, and long-term development. The concept of the high-quality development of enterprises is manifested at the microlevel, signifying a novel paradigm of enterprise development that adapts to the stage of high-quality economic development in China and represents an expansion and extension of high-quality economic development. However, the specific content of the high-quality development of enterprises remains a subject of debate within the academic community. The extant literature on the subject typically selects a single indicator for the purpose of measuring the high-quality development of enterprises. The most widely recognised indicators include the total factor productivity (TFP) of firms [4], the level of research and development innovation [5], and the economic value added of enterprises [6].

Nevertheless, the advanced development of enterprises is characterised by its comprehensive, integrated, and dynamic nature, and therefore, a single indicator is insufficient for comprehensively reflecting its development characteristics. For instance, although the TFP indicator can reflect technological efficiency improvements, it is difficult to capture the carbon reduction effects of green transformation; although R&D investment intensity can characterise innovation momentum, it cannot identify the commercial conversion efficiency of innovative achievements; and although economic value added can measure the ability to create value, it lacks consideration for financial stability [7]. Constructing indicators based on the presence or absence of certain behaviours ultimately forms a dimensionless indicator with low comparability. Consequently, this article employs the entropy weight method to construct multidimensional comprehensive indicators for measuring the high-quality development of enterprises from four dimensions: innovative development, efficient development, green development, and stable development.

In recent years, the concept of environmental, social, and governance (ESG) has gained significant traction in developed countries, where it has been adopted as a sustainable investment system and a novel corporate governance standard within the capital market. In the People’s Republic of China, the ESG is currently in its infancy; however, the pace of ESG-related institutional system construction is also accelerating. In 2018, the China Securities Regulatory Commission issued a revised version of the “Code of Corporate Governance for Listed Companies”, which, for the first time, explicitly required listed companies to disclose information on environmental, social, and governance aspects. In 2019, the Fund Industry Association released the “Research Report on ESG Evaluation System of Chinese Listed Companies”, further promoting the development of the ESG system.

The contribution of ESG performance to the high-quality development of enterprises has been demonstrated by a large body of research. Wong et al. (2021) [8] conducted empirical research using sample data from 53 countries and found that ESG performance can promote the high-quality development of enterprises. The promotion of high-quality development by ESG performance can be attributed to three main factors. Firstly, from the perspective of stakeholders, ESG performance strengthens the connection between enterprises and supply chain stakeholders, improves the stability of enterprise supply chains, and subsequently promotes the high-quality development of enterprises [9]. Secondly, in terms of the capital market, the favourable evaluation of corporate ESG responsibility has significantly increased market attention, released more positive signals, improved the company’s image, enabled the company to obtain excess profits, and thus promoted the high-quality development of the enterprise [10]. Thirdly, from the perspective of enterprises, good ESG performance can help improve operational efficiency, enhance the authenticity of financial information, broaden financing channels, alleviate financing constraints, and promote the high-quality development of enterprises [11].

The digital transformation of enterprises is predicated on novel digital means such as mobile Internet, embedded devices, and artificial intelligence. These innovations have been demonstrated to enhance the efficiency of production, input, and output by facilitating enhanced data mobility and industrial intelligence. Consequently, this has been shown to promote the high-quality development of enterprises [12]. Furthermore, as digitalisation gradually permeates business operations, it has become a practical technological foundation for fulfilling ESG responsibilities. A substantial body of research has demonstrated that digital transformation can effectively collaborate with corporate ESG practices, thereby significantly enhancing the value creation effect of ESG initiatives [13,14,15]. Digital technology facilitates the recording and tracking of ESG information disclosure. Consequently, digital transformation has the potential to enhance enterprises’ capacity to collect information, thereby reducing information asymmetries. It can also improve the effectiveness of corporate governance, environmental protection initiatives, and regional economic gap, profoundly empower enterprise business activities and economic decisions, and promote the high-quality development of enterprises [16,17,18,19,20].

A review of the extant literature reveals a substantial body of research in academic circles concerning the impact of ESG performance and digitalisation on high-quality development. The majority of studies concur that ESG performance and digital transformation can assist companies in achieving high-quality development. Nevertheless, the relationship between ESG performance, digital transformation, and high-quality development has not received significant attention from the academic community, particularly the paucity of research on the moderating role of digital transformation on the impact of ESG performance on the high-quality development of enterprises.

This article employs panel data from Chinese A-share listed companies in Shanghai and Shenzhen from 2010 to 2023 to assess the high-quality development of enterprises from multiple dimensions. Through a combination of theoretical analysis and empirical testing, this study seeks to address the following research question: Specifically, it seeks to ascertain whether the adoption of enhanced ESG practices within enterprises can contribute to the promotion of high-quality development. Furthermore, this study seeks to determine whether digital transformation exerts a moderating effect on the relationship between firms’ ESG performance and high-quality development and attempts to elucidate the underlying mechanisms and pathways through which these phenomena occur. This study also explores the heterogeneity of assistance. The answers to these questions will provide empirical support for the construction of an ESG system with Chinese characteristics in theory, as well as new ideas for promoting the high-quality development of enterprises in practice.

In comparison with the extant literature on this subject, the article’s contributions can be summarised as follows: firstly, it employs stakeholder theory and signal transmission theory to explore the impact of corporate ESG practices on the high-quality development of enterprises. This contributes to the expansion of research on the realisation path of the high-quality development of enterprises, as well as to the literature on ESG and enterprise production and operation. The selection of an exhaustive index of the high-quality development of enterprises, encompassing four dimensions of innovation, efficiency, green, and stability, along with the inclusion of single-dimensional indicators, such as TFP and R&D innovation, ensures the objectivity and credibility of the conclusions presented in this article. Secondly, this article elucidates the mechanism of ESG in promoting high-quality development through two channels, financing constraints and supply chain stability, thereby unveiling the long-term value creation logic of corporate ESG practices. Moreover, the extant literature has explored the role of corporate ESG performance in alleviating financing constraints and improving supply chain stability. However, no further analysis has been conducted from the perspective of high-quality development. This article serves as a valuable addition to the existing body of knowledge in this field. Thirdly, the integration of enterprise digitisation and ESG performance into a unified framework system for high-quality development provides a theoretical explanation of how enterprises can promote environmental, social, and governance changes through digitisation, achieve win–win economic, social, and ecological benefits, and ultimately promote high-quality development. The theoretical mechanisms involved are examined in detail from different dimensions, revealing the important role of enterprise digitization in promoting high-quality development. In summary, this article makes three contributions. Firstly, it employs stakeholder theory to construct multidimensional indicators to measure the high-quality development of enterprises, thereby ensuring objective conclusions. Secondly, it clarifies the mechanism by which ESG promotes high-quality development through financing constraints and supply chain stability, thus supplementing existing research. Thirdly, it integrates digitalisation and ESG, thereby revealing the promoting role of digitalisation from multiple dimensions.

2. Literature Review

2.1. Research on the High-Quality Development of Enterprises

The implementation of a novel development concept, predicated upon prioritising quality, and the promotion of changes in quality, efficiency, and motivation are essential for achieving high-quality development. Enterprises, as the primary agents of high-quality development, are driven to achieve this goal and attain competitive advantages to ensure a prosperous future. The extant research on the high-quality development of enterprises principally encompasses two aspects: external driving factors and internal implementation paths. In terms of external driving factors, firstly, it is evident that the government’s policy formulation, in its capacity as the system’s creator and custodian, will exert a pivotal influence on the pursuit of high-quality development among enterprises. The empirical literature has highlighted that government policies, such as environmental regulation [21], green credit policies [22], and low-carbon city pilot policies, have the potential to promote the high-quality development of enterprises [23]. Secondly, the market is not only the lifeline of enterprises but also a guide for their development. The enhancement of the business environment in the market [24] will enhance the efficiency of resource allocation for enterprises, thereby significantly promoting their high-quality development. Furthermore, with the comprehensive promotion of digitisation, the digital economy has become the primary economic form after the agricultural economy and industrial economy. It has been noted by numerous scholars that the construction of digital infrastructure and the development of the digital economy represent significant drivers for the high-quality development of enterprises [25,26,27].

2.2. Research on Corporate ESG Practices

The predominant school of thought within the domain of traditional corporate governance theories is that of shareholder primacy. In pursuit of profit maximisation, enterprises simultaneously achieve the maximisation of social welfare. Friedman (1970) thus proposed that enterprises should prioritise profit maximisation as their social responsibility [28]. However, in reality, enterprises engender a multitude of external issues in the course of production and operation, including social inequality, environmental pollution, and illegal behaviour [28]. These issues not only compromise the interests of stakeholders within the enterprise but also inflict welfare losses on society at large. In response to these challenges, Carroll (1991) advanced the Pyramid Theory, which posits that corporate social responsibility should encompass not only economic responsibility but also environmental, legal, ethical, philanthropic, and internal governance responsibilities [29]. This theoretical framework underscores a shift towards a more holistic approach to corporate governance, emphasising the maximisation of stakeholder interests within the enterprise. However, it should be noted that enhancing ESG practices within enterprises frequently necessitates substantial investments of human, material, and financial resources. Moreover, considerable controversy persists regarding the potential for such practices to generate significant economic returns for the company. Consequently, a substantial volume of research has been dedicated to investigating the correlation between corporate ESG practices and corporate performance, financing costs, and corporate risks. With regard to corporate performance, some scholars believe that strengthening ESG practices can help companies gain the trust and support of stakeholders, thereby improving their financial performance and market value [30].

It has been argued by certain scholars that companies with superior environmental, social, and governance (ESG) performance have the capacity to generate greater moral capital, thereby enabling them to garner support from stakeholders even in the aftermath of crisis events, cultivate trust to withstand crises, and safeguard shareholder rights [31]. In terms of financing costs, Chen et al. (2023) indicated that corporate ESG practices are conducive to reducing the financing costs of enterprises [32], and there is also much literature that has tested the reduction in equity capital costs and debt capital costs by corporate ESG practices [33,34]. In terms of corporate risk, due to the fact that ESG practices encourage companies to pay attention to stakeholders and regulate their behaviour, it has been demonstrated that these practices can significantly reduce the risk of litigation for companies [35].

A review of the existing literature reveals that, firstly, the majority of extant research on the internal implementation path of the high-quality development of firms is from the perspective of corporate governance and management strategies, with few studies exploring the role of ESG practices in promoting the high-quality development of enterprises; Secondly, extant research on corporate ESG practices also focuses more on short-term economic impacts, such as increasing market value, alleviating financing constraints, and reducing corporate risks. The strategy of enhancing ESG practices in enterprises is predicated on the abandonment of short-sightedness in favour of a focus on long-term development, a course of action that is conducive to the long-term high-quality development of enterprises. This article therefore examines the role of ESG practices in promoting the high-quality development of enterprises. This study contributes to the exploration and research of the path to achieving the high-quality development of enterprises, and also enriches the study of the long-term sustainability impact brought by the ESG practices of enterprises. This study signifies a significant theoretical and practical contribution to the field.

3. Theoretical Analysis and Research Hypotheses

3.1. ESG Practice and High-Quality Development of Enterprises

The ESG practices of enterprises primarily encompass three aspects: participation in environmental governance, the assumption of social responsibility, and the enhancement of corporate governance. Specifically, with regard to the participation in environmental governance, enterprises are required to perform the following: Firstly, as per stakeholder theory and signal transmission theory, certain enterprises actively engage in pollution prevention and control, energy conservation, and emission reduction, thereby showcasing a responsible corporate image to the public. This behaviour is likely to elicit a positive response from the public, government, and financial institutions, thus promoting the sustainable development of enterprises. Secondly, enterprises’ participation in environmental governance can facilitate effective communication with stakeholders, thereby fostering trust and support among them. This, in turn, can lead to the creation of shared value between enterprises and stakeholders, thereby enhancing the core competitiveness of enterprises. Consequently, enterprises that actively engage in environmental governance can contribute to the advancement of their own development.

In terms of social responsibility, the following observations can be made. Firstly, the prioritisation of the rights and interests of stakeholders is likely to garner their support. Enterprises concentrate on safeguarding the interests of employees, establishing favourable working environments and ensuring safe production conditions for them, and fostering their professional growth. This approach fosters a sense of ownership and responsibility among employees, enhancing their work enthusiasm and contributing to enhanced production efficiency [36]. Furthermore, enterprises should prioritise safeguarding the interests of creditors, thereby fostering good corporate credit and facilitating capital acquisition, thus alleviating financing constraints and enhancing financial performance [37]. Additionally, emphasising the protection of human rights, upholding social justice, and fostering a fair, competitive social environment will garner support from vulnerable groups. The primary focus of this study is on the protection of suppliers’ and customers’ interests at all points in the industrial chain, with the ultimate aim of achieving mutual benefit and win–win outcomes for all stakeholders. This approach is expected to contribute to enhanced supply chain safety, improved product and service quality, the rejection of counterfeit and substandard products, better alignment with customer needs, and the acquisition of a substantial and stable customer base. Secondly, from the perspective of the corporate social responsibility insurance mechanism, while actively assuming social responsibility, enterprises will generate a certain amount of moral capital, which enables them to gain the support of stakeholders and build trust to resist crises even after experiencing crisis events [38]. Consequently, enterprises that assume social responsibility can contribute to the promotion of high-quality development.

It is imperative to enhance the corporate governance framework. The agency theory posits that effective internal governance within a corporate entity can serve to mitigate agency costs, curtail opportunistic and myopic conduct on the part of managerial personnel, and thereby enable the establishment of long-term investment preferences. This, in turn, can facilitate the pursuit of sustainable and high-quality development. Concurrently, robust corporate governance can serve to ameliorate information asymmetries between enterprises and their external stakeholders, engender greater transparency with regard to enterprise information, curtail the cost of the external supervision of internal personnel, optimise the efficacy of external supervision mechanisms, and ensure the alignment of the behaviour of enterprise operators with the interests of shareholders and other stakeholders. Consequently, the proactive enhancement of corporate governance can facilitate the advancement of enterprises towards a higher level of development.

In summary, the corporate practices of environmental, social, and governance (ESG) issues principally encompass three aspects: environmental governance, social responsibility, and corporate governance. In the context of environmental governance, enterprises are able to demonstrate a responsible image through a range of practices, including pollution prevention and control, energy conservation, and emission reduction. These practices are underpinned by stakeholder theory and signal transmission theory and are met with approval by multiple stakeholders, thereby promoting sustainable development. Furthermore, they are able to engage in communication with relevant stakeholders with a view to foster trust and enhance competitiveness. In terms of social responsibility, enterprises can improve production efficiency, alleviate financing constraints, ensure supply chain security, and accumulate moral capital to resist crises by safeguarding the interests of employees, creditors, and others. In the context of corporate governance, agency theory posits that effective governance can lead to a reduction in agency costs, the enhancement of information transparency, and the promotion of the high-quality development of enterprises. In light of the aforementioned discussion, the following hypothesis is proposed:

H1. 

The enhancement of ESG practices within enterprises can contribute to the promotion of high-quality development.

3.2. ESG Practices, Financing Constraints, and the High-Quality Development of Enterprises

The existence of substantial financial resources is an indispensable condition for the high-quality development of firms. However, due to the strict risk management mechanisms of financial institutions and the information asymmetry present in the capital market, many enterprises encounter difficulties in obtaining sufficient financial support. Consequently, financing constraints have emerged as a pivotal challenge impeding the high-quality development of enterprises.

Digital transformation has enhanced the quality, authenticity, and timeliness of ESG information disclosure, thereby empowering stakeholders to comprehensively grasp corporate information and alleviate financing constraints. The advent of digital technology has effectively dismantled the constraints imposed by time and geographical boundaries on business operations, thereby facilitating enterprises to respond expeditiously to market fluctuations. The digital transformation of enterprises has enhanced the methods and means by which investors obtain corporate information, promoted the transparency and standardisation of ESG performance information disclosure, and retained more long-term investors [39].

Concurrently, the digital transformation of enterprises has rendered the manifestation of ESG cultivating corporate reputation advantages more intelligent and standardised. In the process of alleviating corporate financing constraints through ESG performance, digital transformation has strengthened the authenticity of corporate ESG information, thereby increasing the trust of the non-financial and financial information of enterprises. This, in turn, has resulted in the favour of creditors and customers, leading to a reduction in corporate financing costs and the enhancement of corporate financing capabilities. The alleviation of financing constraints will further promote the realisation of the high-quality development of enterprises. Firstly, the alleviation of financing constraints ensures that enterprises can obtain a large amount of funds for the introduction of production technology and professional equipment, thereby ensuring the innovative and efficient development of enterprises. Secondly, the alleviation of financing constraints ensures that enterprises have sufficient financial reserves, making the selection and production processing of raw materials more refined and professional, thereby ensuring the improvement of product and service quality [40]. Finally, the alleviation of financing constraints will also promote enterprises to hire high-quality, high-level, and sophisticated professionals with more generous salaries, improve their production and management levels, and ensure their sustainable and high-quality development [41].

In summary, sufficient financial resources are essential for the high-quality development of enterprises, but financing constraints have become key challenges due to strict risk control by financial institutions and information asymmetry in the capital market. Digital transformation has been demonstrated to enhance the quality, authenticity, and timeliness of ESG information disclosure, strengthen stakeholders’ grasp of corporate information, and alleviate financing constraints. The preceding discussion gives rise to the following hypothesis:

H2. 

Digital transformation exerts a positive moderating effect on the alleviation of financing constraints on the ESG performance of enterprises, thereby promoting the high-quality development of enterprises.

3.3. ESG Practices, Stability of the Supply Chain, and the High-Quality Development of Enterprises

The stability of the supply chain mainly refers to the stability of the upstream suppliers and downstream customers of the enterprise, reflecting the safety and stability of the enterprise from raw material supply to production and processing, and then to marketing and sales. It can be said that the stability of the supply chain is an important foundation for enterprises to achieve high-quality development.

Strengthening ESG practices can help companies build long-term, secure, and stable supply chains. Firstly, according to stakeholder theory, on the one hand, strengthening ESG practices in enterprises can change their product direction, improve the quality of their products and services, and provide more and better green products based on the needs of different customers. Therefore, enterprises will also gain more favour and support from customers. On the other hand, strengthening ESG practices by enterprises not only considers the interests of suppliers but also ensures their own credit and social reputation, which is conducive to establishing long-term stable cooperative relationships between enterprises and suppliers. On the other hand, according to the theory of signal transmission, companies strengthen their ESG practices, disclose ESG information reports, and improve the transparency of corporate information, thereby enabling customers and suppliers to obtain internal information more clearly and comprehensively, reducing the risk of cooperation.

The promotion of supply chain stability through ESG performance is facilitated by digital technology, which enables enterprises to manage customer relationships more intelligently and conveniently. This, in turn, improves the accuracy of ESG information reporting and disclosure, thereby enhancing supply chain stability. Concurrently, the function of digital technology connecting network nodes and resources can assist enterprises in integrating into a sharing alliance of complementary capabilities, resource sharing, and value co-creation. By leveraging the network of customers and business partners, enterprises can foster relationships that enhance supply chain stability [42]. For example, Amazon employs machine learning algorithms to analyse historical sales data, meteorological information, traffic data, and other multi-source data in order to predict regional demand fluctuations in advance and guide suppliers in making dynamic adjustments to production capacity and inventory. In the context of the 2022 West Coast port strike in the United States, the utilisation of the AI real-time re-planning of logistics routes resulted in a 35% reduction in delivery delays, thereby ensuring the maintenance of supply chain continuity.

The enhancement of supply chain stability is instrumental in facilitating the high-quality development of enterprises. The theory of transaction costs posits that the costs incurred by enterprises in conducting business primarily encompass the expenses associated with information retrieval within the market, the costs of negotiating transactions, the costs of decision-making and contract execution, the costs of supervising execution, and the costs of contract breach that are shouldered by one party. Consequently, enhancing supply chain stability fosters the establishment of long-term cooperative and mutually trusting relationships between suppliers and customers, thereby significantly reducing transaction costs and contributing to the realisation of high-quality enterprise development. Secondly, the relative stability of the enterprise supply chain helps to reduce operational and financial risks and enhance the enterprise’s ability to resist risks [43]. When there are fluctuations in the raw material market and product market, enterprises can jointly cope with market risks with upstream and downstream enterprises. When a company faces a liquidity crisis, it can alleviate financial constraints through commercial financing and supply chain financing from upstream and downstream enterprises. Finally, the stability of the supply chain will promote communication and cooperation between enterprises, suppliers, and customers, which not only helps enterprises grasp the situation of the upstream raw material supply market but also helps enterprises grasp the customer demand, development prospects, and product upgrading trends of the downstream product market [44], thereby ensuring that enterprises can achieve high-quality development that keeps pace with the times and is sustainable.

In conclusion, supply chain stability is an important foundation for the high-quality development of enterprises. Strengthening ESG practices can be based on stakeholder and signalling theories by improving product and service offerings, safeguarding supplier interests, enhancing information transparency, and building a stable supply chain. Digital technology helps with intelligent management and information disclosure, enhances supply chain stability, reduces transaction costs, resists risks, promotes communication, and drives the high-quality development of enterprises. This article puts forward the following hypothesis:

H3. 

Digital transformation exerts a positive moderating effect on enhancing ESG performance and supply chain stability, thus fostering enterprises’ high-quality development.

4. Research Design

4.1. Sample Selection and Data Sources

The present article employs the panel data of Chinese A-share listed companies from 2010 to 2023 as the research sample and processes the sample as follows: The financial industry sample companies are excluded in accordance with the industry classification guidelines of the China Securities Regulatory Commission’s “Guidelines for Industry Classification of Listed Companies” (revised in 2012). Companies with a listing period of less than three years are excluded. Companies that were ST or *ST during the sample period are excluded. In order to eliminate the influence of extreme values, this paper truncated the continuous variables by 1% and finally obtained a total of 30,014 annual observations from enterprises. The relevant data of the listed companies in this article are all derived from the CSMAR database. The ESG rating data are from the Huazheng ESG rating agency, and the enterprise patent data are from the China Research Data Service Platform (CNRDS).

4.2. Model Design and Indicator Selection

In order to study the impact of strengthening ESG practices on the high-quality development of enterprises, this article sets the following benchmark regression model:

$${HQD}_{i,t+1}={\beta }_0+{\beta }_1{ESG}_{i,t}+{\beta }_j{Controls}_{i,t}+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(1)

$${TFP}_{i,t+1}={\beta }_0+{\beta }_1{ESG}_{i,t}+{\beta }_j{Controls}_{i,t}+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(2)

$${Lnpatent}_{i,t+1}={\beta }_0+{\beta }_1{ESG}_{i,t}+{\beta }_j{Controls}_{i,t}+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(3)

The dependent variable, HQD, is the comprehensive index of the high-quality development of enterprises constructed using the entropy weight method. TFP and Lnpatent are the TFP of enterprises and the number of patent applications of enterprises, respectively. The core explanatory variable ESG is the ESG rating index of Huazheng enterprises, Controls is the control variable, λ is the individual fixed effect, μ is the time fixed effect, ε is the random error term, and the parameter ${\beta }_1$ reflects the supportive effect of strengthening ESG practices on the high-quality development of enterprises. In addition, in order to make the statistical inference results more robust, this article also used robust standard errors to estimate the regression model.

4.3. Variable Measurement and Data Sources

(1)

The high-quality development of enterprises: In extant empirical research, there is an absence of a unifying measurement form for the high-quality development of enterprises. The existing literature research has both selected single indicators and constructed comprehensive indicators to measure the high-quality development of enterprises. The selection of widely recognised indicators includes the TFP of enterprises [1] and the innovation level of research and development [3]. However, given the multifaceted nature of enterprise development, characterised by integration, complexity, and dynamism, numerous scholars have employed the entropy weight method to construct multidimensional comprehensive indicators to measure the high-quality development of enterprises. This study employs a combination of the two single indicators of enterprise TFP and R&D innovation, along with the comprehensive index of enterprise high-quality development constructed through the entropy weight method as a proxy variable to measure the high-quality development of enterprises.

(2)

Enterprise total factor productivity (TFP_LP): In the extant literature, two semi-parametric methods, OP [45] and LP [46], are frequently employed to measure the TFP. While the OP method has been shown to effectively circumvent the challenges posed by simultaneity bias and sample selection bias, it necessitates that the real investment of the enterprise must exceed 0, resulting in the loss of a substantial number of enterprise samples during the estimation process. The LP method, on the other hand, utilises intermediate inputs as proxy variables, thereby effectively addressing the issue of sample loss and enhancing the accuracy of estimation results. Consequently, this article employs the TFP_LP of enterprises measured by the LP method in the benchmark model as a single-dimensional proxy variable to assess the high-quality development of enterprises for empirical testing.

(3)

Enterprise innovation (Lnpatent): The present study employs the logarithmic data of invention patents, utility model patents, and design patent applications as a single-dimensional proxy variable to measure the high-quality development of enterprises for empirical testing.

(4)

The comprehensive index of the high-quality development of enterprises (HQD) is a composite metric that encapsulates the comprehensive performance of enterprises in their pursuit of high-quality development. The measurement of the high-quality development level of enterprises is conducted by referring to the approach of Zhang et al. (2024) [2]. The high-quality development level of enterprises is measured from four aspects: innovative development, efficient development, green development, and stable development. As illustrated in

Table 1. High-quality development index of enterprises.

Major Indexes	Minor Indexes	Variable	Definition	Effect
High-quality development	Innovation-driven development	R & d capabilities	Number of enterprise patent applications	+
	Efficient development	Productivity	Total factor productivity	+
	Green development	Environmental compliance	Number of environmental penalties	−
		Green governance	Environmental protection investment	+
	Steady development	Credit risk	Number of violations punished	−
		Operational risk	Dibo internal control index	+

, this article utilises the number of enterprise patent applications and the TFP calculated by the LP method to assess the innovation and efficient development level of enterprises. It employs enterprise environmental penalties and environmental investment data to measure the level of the green development of enterprises separately. It also uses the corporate violation penalty data provided by the China Securities Regulatory Commission website and the DiBo internal control index to measure the steady development level of the enterprise. Finally, this article constructs a multidimensional comprehensive index HQD using the entropy weight method to measure the high-quality development of enterprises.

(5)

Corporate ESG performance: In the benchmark model, the present article employs the Huazheng ESG rating as the core explanatory variable. The scale utilised for the Huazhong ESG rating ranges from 1 to 9, with 1 representing the lowest possible score and 9 representing the highest. The annual ESG rating of a company is determined by averaging the scores obtained four times a year. Huazheng ESG rating was selected due to its extensive coverage of Chinese A-share listed companies (2010–2023) and its alignment with the Chinese policy context. This is evident in the incorporation of localised indicators, such as environmental penalties and social responsibility performance. However, Huazhong Securities’ ratings focus on policy compliance, which may result in ESG innovation practices being underestimated.

(6)

Enterprise digital transformation: Digital transformation is defined as the process by which enterprises enhance their value proposition to customers through the integration of modern technology and communication methods [47]. It is utilised as a moderating variable in this article. The present article draws on the approach of Wu et al. [1] and uses the natural logarithm of the sum of word frequencies in five dimensions of company annual report text information as a measure of digital transformation (Digit) for enterprises. The frequency of words related to enterprise digital transformation is then classified into the following categories: “artificial intelligence technology”, “big data technology”, “cloud computing technology”, “blockchain technology”, and “digital technology application”. The frequency of feature words in each category is then calculated, and the sum of these frequencies is added. Finally, logarithmic processing is performed to obtain the quantitative indicators of enterprise digital transformation. The digitalization process uses the text keyword counting method from the annual report, as Chinese enterprises’ digitalization practices often use text disclosure technology applications (such as AI and big data), which can dynamically capture the degree of technological penetration. However, text analysis relies on keyword presets and carries the risk of semantic bias. It also does not cover non-annual report data, such as that from supply chain digital platforms.

(7)

Control variables: In order to enhance the research accuracy, this article aligns with the methodologies employed by Wu et al. (2024) and Yu et al. (2024) [1,3], incorporating additional control variables that may influence the high-quality development of enterprises within the model. These control variables encompass enterprise size (Size), return on equity (Roe), enterprise age (Age), the total asset turnover ratio (Tat), the asset liability ratio (Lev), the fixed asset ratio (Fix), and net cash flow from operating activities (CF). Furthermore, this article incorporates individual and time fixed effects into the model in order to control for unobservable variables that do not vary with individuals and time.

The definitions of the primary variables aforementioned are delineated in

Table 2. Variable definition.

Name	Symbol	Definition
Enterprise high-quality development index	HQD	Construction of entropy weight method
Total factor productivity	TFP_LP	Total factor productivity calculated by LP method
Enterprise innovation	Lnpatent	Ln (invention, utility model, and design patent application + 1)
ESG performance	ESG	Huazheng ESG quarterly rating, taking the average
Enterprise size	Size	Ln (total assets of the enterprise)
Return on equity	ROE	Net profit/total owner’s equity
Enterprise age	Age	Ln (year − year of company listing + 1)
Total asset turnover	Tat	Total operating revenue/assets
Asset liability ratio	Lev	Total liabilities/total assets
Fixed asset ratio	Fix	Net fixed assets/total assets
Cash flow	CF	Net cash flows from operating activities/total assets

.

5. Empirical Result Analysis

5.1. Statistical Description Results

The descriptive statistical results of the primary variables in this article are displayed in

Table 3. Descriptive statistics.

Variable	Obs	Mean	SD	Min	Median	Max
HQD	30,014	0.073	0.069	0.007	0.071	0.348
TFP_LP	30,014	8.346	1.041	4.599	8.236	13.106
Lnpatent	30,014	2.149	1.534	0.000	2.079	8.843
ESG	30,014	4.092	0.975	1.000	4.000	8.000
Size	30,014	22.203	1.301	18.284	22.002	27.468
Lev	30,014	0.419	0.205	0.027	0.410	2.186
ROE	30,014	0.045	0.204	−2.506	0.066	0.764
Age	30,014	2.928	0.325	1.099	2.944	3.664
Tat	30,014	0.621	0.394	0.003	0.536	2.696
Fix	30,014	0.208	0.146	0.001	0.181	0.756
CF	30,014	0.047	0.068	−0.289	0.045	0.266

Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

. The mean of the core explanatory variable ESG is 4.092, with a standard deviation of 0.975, indicating that the majority of companies’ ESG ratings are concentrated between CCC AND BB, and a significant number of companies have begun to pay attention to and gradually carry out ESG-related practices. The mean and median of the comprehensive index of high-quality development (HQD) for enterprises are 0.073 and 0.071, respectively, with a standard deviation of 0.069, indicating that there are significant differences in the comprehensive index of high-quality development among different listed companies, providing a certain basis for this study. In the control variables, the mean and median of enterprise size (Size) are 22.203 and 22.002, respectively, with a maximum value of 27.468 and a minimum value of 18.284, indicating that the majority of the enterprise sample consists of medium-to-large enterprises. Furthermore, the descriptive statistical outcomes of the variables selected in this article are consistent with existing research and are within a reasonable range; therefore, they will not be repeated here.

5.2. Correlation Analysis

In order to ensure the reliability of the research results in this article, it is necessary to first check whether there is multicollinearity between the variables before carrying out the regression analysis. For this purpose, we examined the Pearson correlation coefficients between the variables, as shown in

Table 4. The correlation matrix.

	HQD	TFP_LP	Lnpatent	ESG	Size	Lev	ROE	Age	Tat	Fix	CF
HQD	1
TFP_LP	0.3 ***	1
Lnpatent	0.9 ***	0.4 ***	1
ESG	0.2 ***	0.2 ***	0.2 ***	1
Size	0.3 ***	0.8 ***	0.4 ***	0.2 ***	1
Lev	0.1 ***	0.4 ***	0.1 ***	−0.1 ***	0.4 ***	1
ROE	0.1 ***	0.1 ***	0.1 ***	0.2 ***	0.1 ***	−0.2 ***	1
Age	0.1 ***	0.2 ***	0.1 ***	−0.1 ***	0.2 ***	0.2 ***	−0.1 ***	1
Tat	0.0 ***	0.3 ***	0.0 ***	0.0 ***	0.1 ***	0.2 ***	0.1 ***	0.0 ***	1
Fix	−0.0 ***	−0.1 ***	−0.1 ***	−0.0 ***	0.1 ***	0.1 ***	−0.0 ***	−0.0	0.0 ***	1
CF	0.0 ***	0.1 ***	0.0 ***	0.1 ***	0.1 ***	−0.2 ***	0.3 ***	0.0 ***	0.1 ***	0.2 ***	1

Notes: *** indicates significance at the 1% level. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

. The correlation coefficients between ESG and the variables HQD, TFP_LP, and Lnpatent are significant at the 1% level, suggesting a notable relationship between ESG ratings and the quality development of companies. Finally, the correlation coefficients between the control variables selected in this article and HQD, TFP_LP, and Lnpatent are all significant at the 10% level, indicating that the control scalar used in this article is appropriate. In addition, the absolute values of the correlation coefficients between the control variables are all less than 0.5, which, to some extent, eliminates the possibility of multicollinearity in the main regression of this article.

5.3. Regression Results of the Benchmark Model

Table 5. Benchmark regression results.

	(1)	(2)	(3)	(4)	(5)	(6)
	HQD	HQD	TFP_LP	TFP_LP	Lnpatent	Lnpatent
ESG	0.00472 ***	0.00269 ***	0.04877 ***	0.00657 ***	0.10118 ***	0.05696 ***
	(9.2747)	(5.2572)	(13.8914)	(4.2124)	(13.7542)	(7.8714)
Size		0.02548 ***		0.61429 ***		0.55927 ***
		(27.6914)		(218.9946)		(42.9720)
Lev		−0.00489		0.06812 ***		−0.16848 ***
		(−1.3599)		(6.2127)		(−3.3119)
ROE		0.00527 **		0.12268 ***		0.06199 **
		(2.4114)		(18.4123)		(2.0053)
Age		−0.00544		−0.01540		−0.12524
		(−0.8457)		(−0.7855)		(−1.3766)
Tat		−0.00151		1.24615 ***		0.01952
		(−0.8247)		(222.5164)		(0.7511)
Fix		0.00278		−1.36572 ***		0.13357 *
		(0.5351)		(−86.2566)		(1.8182)
CF		0.01310 **		0.23346 ***		0.13407 ***
		(2.0312)		(11.8747)		(4.4698)
Constant	0.18684 ***	−0.35200 ***	8.15381 ***	−5.80911 ***	1.73533 ***	−10.10540 ***
	(88.6310)	(−13.2924)	(561.2209)	(−71.9477)	(56.9984)	(−26.9751)
Firm	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
N	30,014	30,014	30,014	30,014	30,014	30,014
Adj. R2	0.676	0.686	0.876	0.977	0.751	0.769

Notes: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; t-statistics are shown in parentheses. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

presents the regression results of the benchmark model under discussion in this article. Columns (1), (3), and (5) represent the regression results after adding only the core explanatory variable ESG and controlling for individual fixed effects and time fixed effects. Columns (2), (4), and (6) are the regression results after adding control variables to the model. As shown in Table 5, the coefficients of the core explanatory variables are significantly positive at the 1% level, which validates the core conclusion of this article. The findings indicate that enhancing ESG practices in enterprises can facilitate high-quality development, thereby validating hypothesis H1. Furthermore, the regression coefficient of return on equity (ROE) is found to be significantly positive, indicating that high-ROE enterprises achieve high-quality development through technology premium capture (increased R&D conversion rate), asset allocation optimisation, and other means. Furthermore, the regression coefficient of net cash flow from operating activities (CF) is also significantly positive, because enterprises with a higher net cash flow from operating activities have sufficient cash flow to ensure the continuity of long-term investments, such as research and development investments, which are conducive to the high-quality development of the enterprise. The hypothesis H1 has been verified.

5.4. The Regulatory Role of Digital Transformation in Enhancing ESG Performance and Promoting the High-Quality Development of Enterprises

The existing literature suggests that digital transformation can empower ESG supply chain management and improve the quality of corporate information disclosure. Consequently, this article hypothesises that digital transformation will positively regulate the ESG performance of enterprises and enhance their high-quality development. The subsequent investigation, presented in

Table 6. Digital transformation, ESG performance, and the high-quality development of enterprises.

	(1)	(2)	(3)
	HQD	TFP_LP	Lnpatent
ESG	0.0020 ***	0.0088 ***	0.0510 ***
	(3.644)	(5.264)	(6.608)
ESG × DIGI	0.0089 ***	0.0270 ***	0.0747 **
	(3.950)	(3.938)	(2.343)
DIGI	0.0554 ***	0.1486 ***	0.4394 ***
	(5.982)	(5.259)	(3.349)
Size	0.0252 ***	0.6150 ***	0.5570 ***
	(27.367)	(219.191)	(42.776)
Lev	−0.0047	0.0674 ***	−0.1665 ***
	(−1.298)	(6.149)	(−3.274)
ROE	0.0051 **	0.1231 ***	0.0605 *
	(2.319)	(18.486)	(1.958)
Age	−0.0054	−0.0156	−0.1246
	(−0.833)	(−0.797)	(−1.370)
Tat	−0.0012	1.2454 ***	0.0217
	(−0.674)	(222.488)	(0.835)
Fix	−0.0002	−1.3589 ***	0.1115
	(−0.039)	(−85.683)	(1.515)
CF	−0.0128 **	0.2326 ***	−0.1316
	(−1.988)	(11.839)	(−1.444)
Constant	−0.3405 ***	−5.8363 ***	−10.0188 ***
	(−12.854)	(−72.234)	(−26.714)
Firm	Y	Y	Y
Year	Y	Y	Y
N	30,014	30,014	30,014
Adj. R2	0.687	0.977	0.769

Notes: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; t-statistics are shown in parentheses. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

, undertakes an in-depth examination of the interplay between ESG performance and the high-quality development of enterprises, utilising a novel interaction term between ESG and digital transformation within the benchmark model. The findings indicate that the coefficient of ESG × DIGI is significantly positive, suggesting that digital transformation positively moderates the relationship between ESG performance and the high-quality development of enterprises. When the degree of the digital transformation of enterprises is high, the impact of ESG performance on high-quality development is more significant.

5.5. Mechanism Analysis

The following article employs an empirical approach to assess the channels through which companies can enhance their ESG practices to facilitate high-quality development. The article constructs a moderation effect model as outlined below:

$$M_{i,t+1}={\beta }_0+{\beta }_1{ESG}_{i,t}+{\beta }_j{Controls}_{i,t}+{\lambda }_i+{\mu }_t+{\epsilon }_{i,t}$$

(4)

The dependent variable $M_{i,t+1}$ is the mechanism variable of the action channel, while the other variables remain consistent with the baseline regression model.

The present article commences by conducting an examination of the mechanism through which ESG performance exerts its influence on the high-quality development of enterprises, with a view of establishing an empirical foundation for the subsequent testing process. The present study adopts the approach of Li et al. (2024) and commences from the dynamic perspective of changes in supply chain relationships [16]. Proxy variables for supply chain stability (Stable) are constructed by taking the average of the number of appearances of the top five suppliers in the previous year, divided by five, and the number of appearances of the top five customers in the previous year, divided by five. Concurrently, this article draws on the research ideas of Kaplan and Zingales (1997) to construct the KZ index as a mechanism variable to verify the channel of action [47]. The KZ index is employed as a mechanism variable to verify the channel of action [46]. The KZ index is positively correlated with the degree of financing constraints faced by the enterprise. This article replaces the dependent variables in the benchmark model with supply chain stability (Stable) and financing constraints (KZ). The empirical results presented in columns (1) and (2) of

Table 7. Inspection of regulating mechanisms.

	(1)	(2)	(3)	(4)
	Stable	KZ	Stable	KZ
ESG	0.00539 ***	−0.04195 ***	0.00569 ***	−0.03239 ***
	(11.7652)	(−5.4707)	(11.6440)	(−3.9536)
ESG × DIGI			0.00353 ***	−0.11345 ***
			(4.7499)	(−3.3215)
DIGI			0.01258	0.45085 ***
			(1.5145)	(3.1891)
Size	−0.00957 ***	−0.44594 ***	−0.00958 ***	−0.44565 ***
	(−11.6147)	(−32.0540)	(−11.6116)	(−32.0048)
Lev	−0.02266 ***	6.28215 ***	−0.02277 ***	6.27880 ***
	(−7.0365)	(115.5512)	(−7.0696)	(115.4896)
ROE	0.00394 **	−0.42814 ***	0.00392 **	−0.42825 ***
	(2.0116)	(−13.1068)	(2.0011)	(−13.1111)
Age	−0.03070 ***	1.23257 ***	−0.03072 ***	1.23270 ***
	(−5.3302)	(12.8629)	(−5.3328)	(12.8665)
TAT	−0.00708 ***	0.32365 ***	−0.00713 ***	0.32187 ***
	(−4.3035)	(11.6263)	(−4.3347)	(11.5619)
Fix	0.02549 ***	2.72298 ***	0.02560 ***	2.73124 ***
	(5.4802)	(34.7695)	(5.4906)	(34.8004)
CF	−0.00441	−13.33182 ***	−0.00452	−13.33565 ***
	(−0.7643)	(−1.4 × 102)	(−0.7818)	(−1.4 × 102)
Constant	−3.54152 ***	5.10020 ***	−3.54235 ***	5.05626 ***
	(−1.5 × 102)	(12.8404)	(−1.5 × 102)	(12.7110)
Firm	Y	Y	Y	Y
Year	Y	Y	Y	Y
N	30,014	30,014	30,014	30,014
Adj. R2	0.972	0.868	0.972	0.868

Notes: **, and *** indicate significance at the 5%, and 1% levels, respectively; t-statistics are shown in parentheses. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

demonstrate that ESG performance can enhance the high-quality development of enterprises by promoting supply chain stability and reducing financing constraints. This provides a solid foundation for further research, particularly in examining the moderating effect of digital transformation on the ESG performance of enterprises and their high-quality development.

Drawing upon the theoretical underpinnings delineated in this article, it is posited that digital transformation may serve to positively regulate the ESG performance of enterprises, thereby promoting their high-quality development through two distinct mechanisms. The impact of alleviating financing constraints and improving supply chain stability on the high-quality development of enterprises has been the subject of study by previous researchers, and there are clear conclusions that are not the focus of this article. The present study focuses on the moderating effect of digital transformation on the impact of corporate ESG performance on mechanism variables, with a particular emphasis on the enhancement of supply chain stability and the alleviation of financing constraints. The prevailing focus in contemporary research is on the underlying mechanisms of these issues. The present article introduces the interaction term between ESG and corporate digital transformation in model (4), and the empirical results are shown in columns (3) and (4) of Table 7. The regression coefficient of the interaction term (ESG × DIGI) in column (3) is significantly positive, indicating that as the digitalisation level of enterprises increases, the role of ESG performance in improving supply chain stability becomes more significant. The interaction term in column (4) of Table 7 is significantly negative, indicating that as the digitalization level of enterprises increases, ESG performance has a more significant impact on alleviating financing constraints. In summary, the hypotheses H2 and H3 proposed in this article have been validated, namely that digital transformation has a positive moderating effect on the ESG performance of enterprises, improving supply chain stability and alleviating financing constraints, thereby enhancing enterprise value. The hypotheses H2 and H3 have been verified.

5.6. Robustness Test

Firstly, endogenous issues: Despite the fact that the benchmark model selects control variables from a number of perspectives, there is still a possibility of endogeneity issues being caused by omitted variables or reverse causality, resulting in biassed estimates. In order to alleviate the above problems, this article draws on Wang Bo’s approach and uses the industry annual average as the instrumental variable for ESG rating. The ESG rating of a company has been shown to have a strong correlation with the ESG performance of its industry, thus meeting the requirements of instrumental variable correlation. Concurrently, the ESG performance of the industry does not directly impact the enterprise value of a company, thereby satisfying the requirements for instrumental variable exogeneity.

Table 8. Instrumental variable test.

	(1)	(2)	(3)	(4)
	ESG	HQD	TFP_LP	Lnpatent
ESG		0.00032 ***	0.00084 ***	0.06425 **
		(4.1595)	(3.1375)	(2.2550)
IV	0.81210 ***
	(42.5624)
Size	0.25984 ***	0.02629 ***	0.61630 ***	0.55729 ***
	(24.4829)	(24.7679)	(190.4570)	(37.1339)
Lev	−0.93654 ***	−0.00791 *	0.06069 ***	−0.16117 ***
	(−22.5397)	(−1.9311)	(4.8629)	(−2.7846)
ROE	0.03602	0.00536 **	0.12290 ***	0.06177 **
	(1.4130)	(2.4504)	(18.4312)	(1.9975)
Age	−0.34300 ***	−0.00632	−0.01757	−0.12311
	(−4.5725)	(−0.9781)	(−0.8921)	(−1.3479)
TAT	0.02285	−0.00149	1.24622 ***	0.01945
	(1.0664)	(−0.8088)	(222.4222)	(0.7484)
Fix	−0.10546 *	0.00253	−1.36633 ***	0.13417 *
	(−1.7408)	(0.4867)	(−86.2168)	(1.8255)
CF	−0.24935 ***	−0.01394 **	0.23140 ***	−0.13204
	(−3.3154)	(−2.1523)	(11.7232)	(−1.4424)
Firm	Y	Y	Y	Y
Year	Y	Y	Y	Y
LM statistic	153.246
F statistics	155.251
N	30,014	30,014	30,014	30,014

Notes: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; t-statistics are shown in parentheses. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

presents the regression outcomes attained via the two-stage least squares method with instrumental variables. The first estimation result of column (1) shows that the coefficient of instrumental variable IV is significantly positive at the 1% level, indicating that the selected instrumental variable in this article meets the correlation condition, and the LM statistic is 153.246, which rejects the null hypothesis of the insufficient identification of instrumental variables. The F statistic, which is 155.251, is greater than the critical value of 16.38 at the 10% level, indicating that there is no problem of weak instrumental variables. The second paragraph of columns (2)–(4) shows that the ESG coefficients are all positive at a significance level of at least 5%. This finding lends further credence to the core conclusion that companies strengthen their ESG practices to help achieve high-quality development, a conclusion that remains robust despite the presence of endogeneity issues.

Secondly, the dynamic GMM test: As illustrated in

Table 9. Dynamic GMM test.

	(1)	(2)	(3)
	HQD	TFP_LP	Lnpatent
ESG	0.0021 ***	0.0030 ***	0.0400 ***
	(3.787)	(4.814)	(5.146)
L.HQD	0.2045 ***
	(28.857)
L2.HQD	0.0351
	(0.193)
L.TFP_LP		0.2105 ***
		(43.124)
L2.TFP_LP		−0.0599
		(−0.368)
L.Lnpatent			0.2761 ***
			(38.451)
L2.Lnpatent			0.0461
			(0.555)
Size	0.0184 ***	0.5302 ***	0.3923 ***
	(17.242)	(137.720)	(25.097)
Lev	−0.0087 **	0.0640 ***	−0.1458 **
	(−2.154)	(5.194)	(−2.509)
ROE	0.0059 ***	0.1248 ***	0.0836 ***
	(2.774)	(18.952)	(2.717)
Age	−0.0140	−0.0592 **	−0.1770
	(−1.508)	(−2.083)	(−1.323)
TAT	0.0016	1.1291 ***	0.0955 ***
	(0.775)	(160.867)	(3.271)
Fix	−0.0065	−1.1462 ***	−0.0424
	(−1.084)	(−61.908)	(−0.493)
CF	−0.0176 **	0.2035 ***	−0.2400 **
	(−2.503)	(9.498)	(−2.376)
Constant	−0.2098 ***	−5.0191 ***	−6.8005 ***
	(−5.931)	(−45.963)	(−13.290)
Firm	Y	Y	Y
Year	Y	Y	Y
N	22,055	22,055	22,055
AR (2)	0.385	0.428	0.421
Hansen	0.105	0.104	0.108

Notes: **, and *** indicate significance at the 5%, and 1% levels, respectively; t-statistics are shown in parentheses. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

, L.HQD, L.TFP_LP, and L.Lnpatent denote high-quality development variables lagged by one period, while L2.HQD, L2.TFP_LP, and L2.Lnpatent represent high-quality development variables lagged by two periods. The regression coefficients of ESG variables are found to be significantly positive. The values of AR (2) in Table 4 are 0.385, 0.428, and 0.421, respectively, indicating that the null hypothesis that there is no autocorrelation in the second-order difference in the perturbation term cannot be rejected. Furthermore, the p-values of Hansen’s test are all greater than 0.1 and less than 0.25, indicating that the null hypothesis of the validity of instrumental variables cannot be rejected and that there is no problem of excessive instrumental variables. The findings of the research, following the implementation of GMM testing, indicate that ESG performance has the capacity to exert a positive influence on the high-quality development of enterprises.

Thirdly, the replacement of the dependent variable: The present article employs the generalised moment estimation method to measure the total factor productivity (TFP_GMM) of enterprises and the ratio of logarithmized data of invention patents (Lninnpatent) as replacement variables for the indicators of efficient and innovative development in Table 1. A new comprehensive indicator of the high-quality development of enterprises (HQD2) is constructed using the entropy weight method for robustness testing; meanwhile, TFP_GMM and Lninnpatent were also used as replacement variables for the single-dimensional proxy variables TFP_LP and Lnpatent for robustness testing. The robustness test results of replacing the dependent variable are shown in

Table 10. Replacement of explanatory variables.

	(1)	(2)	(3)
	HQD2	TFP_GMM	Lninnpatent
ESG	0.00263 ***	0.00773 ***	0.05897 ***
	(6.0014)	(5.4852)	(6.6379)
Size	0.02390 ***	0.81547 ***	0.63660 ***
	(30.2793)	(321.6672)	(39.8432)
Lev	−0.00430	0.05775 ***	−0.20807 ***
	(−1.3942)	(5.8285)	(−3.3317)
ROE	0.00515 ***	0.11421 ***	0.09862 ***
	(2.7476)	(18.9660)	(2.5985)
Age	−0.00341	0.00109	−0.18771 *
	(−0.6186)	(0.0615)	(−1.6806)
TAT	−0.00021	1.25952 ***	0.06278 **
	(−0.1329)	(248.8473)	(1.9681)
Fix	0.00558	−0.30800 ***	0.21243 **
	(1.2521)	(−21.5237)	(2.3554)
CF	−0.01272 **	0.22956 ***	−0.20124 *
	(−2.2988)	(12.9195)	(−1.7970)
Constant	−0.36382 ***	−8.27354 ***	−10.06835 ***
	(−16.0118)	(−1.1 × 102)	(−21.8921)
Firm	Y	Y	Y
Year	Y	Y	Y
N	30,014	30,014	30,014
Adj. R2	0.713	0.987	0.753

Notes: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; t-statistics are shown in parentheses. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

. The coefficients of the core explanatory variables are significantly positive at the 1% level, indicating that strengthening ESG practices still has a significant supportive effect on the realisation of the high-quality development of enterprises. This finding serves to reinforce the core conclusion of this article, thereby ensuring its robustness and credibility.

Fourthly, ESG ratings are heavily dependent on non-financial information voluntarily disclosed by companies; however, such data are frequently unaudited and are often not up to date. For instance, certain key indicators (e.g., crude steel production) in Baosteel’s ESG report were not fully disclosed, which had a detrimental effect on the accuracy of the rating. It is imperative that Huazheng clearly delineates the scope and temporal parameters of the data source, whilst implementing a third-party authentication mechanism to mitigate reliance on a solitary disclosure channel. Therefore, the replacement of explanatory variables is to be conducted, with robustness testing being performed using ESG rating data (ESG2) from Bloomberg Consulting. The robustness test for replacing core explanatory variables is shown in

Table 11. Replacement of explained variables.

	(1)	(2)	(3)
	HQD	TFP_LP	Lnpatent
ESG2	0.0002 ***	0.0019 ***	0.0047 **
	(4.265)	(4.656)	(2.307)
Size	0.0213 ***	0.6051 ***	0.5381 ***
	(13.080)	(125.412)	(22.221)
Lev	−0.0051	0.1007 ***	−0.2730 ***
	(−0.767)	(5.163)	(−2.787)
ROE	0.0064	0.1448 ***	0.0777
	(1.557)	(11.973)	(1.280)
Age	−0.0135	0.1141 ***	−0.2295
	(−1.322)	(3.763)	(−1.508)
TAT	−0.0004	1.1746 ***	0.0546
	(−0.126)	(127.809)	(1.184)
Fix	−0.0086	−1.2118 ***	0.0278
	(−0.930)	(−44.446)	(0.203)
CF	−0.0154	0.3544 ***	−0.1253
	(−1.389)	(10.786)	(−0.760)
Constant	−0.2199 ***	−6.0166 ***	−9.2058 ***
	(−4.822)	(−44.586)	(−13.592)
Firm	Y	Y	Y
Year	Y	Y	Y
N	10,687	10,687	10,687
Adj. R2	0.726	0.979	0.817

Notes: **, and *** indicate significance at the 5%, and 1% levels, respectively; t-statistics are shown in parentheses. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

. The coefficients of the core explanatory variables that have been replaced with Bloomberg’s ESG rating data are significantly positive at the 1% level, indicating that the core conclusion of this article is still robust and credible.

6. Heterogeneity Analysis

In accordance with the empirical investigation conducted in the preceding section, the enhancement of ESG practices has been demonstrated to facilitate the attainment of high-quality development for enterprises. This is achieved through mechanisms that alleviate financing constraints and enhance supply chain stability. This section will conduct heterogeneity tests on the aforementioned supportive effects from two perspectives: the nature of internal property rights and the external business environment. The following observations can be made.

6.1. Heterogeneity of Internal Property Rights Nature

The responsibilities, positioning, and goals of the different types of enterprises are not uniform, and therefore, the internal nature of enterprises can cause heterogeneity in the assistance effect. From the perspective of the property rights nature of enterprises, compared to the flexible capital operation and opportunistic preferences of private enterprises, state-owned enterprises, due to their special positioning, shoulder the mission entrusted by the state and society. Consequently, the enhancement of corporate ESG practices exhibits heterogeneity in its role in promoting the high-quality development of enterprises with divergent property rights. To investigate this heterogeneity, this study employed grouped regression analysis on state-owned enterprises and private enterprises. The regression results are presented in

Table 12. Heterogeneity test results of enterprise nature.

	(1)	(2)	(3)	(4)	(5)	(6)
	HQD	HQD	TFP_LP	TFP_LP	Lnpatent	Lnpatent
	Nonstate-Owned	State-Owned	Nonstate-Owned	State-Owned	Nonstate-Owned	State-Owned
ESG	0.0012	0.0028 ***	0.0041	0.0050 **	0.0231 *	0.0592 ***
	(1.288)	(4.398)	(1.508)	(2.576)	(1.775)	(6.566)
Size	0.0263 ***	0.0239 ***	0.6158 ***	0.6148 ***	0.5744 ***	0.5494 ***
	(15.366)	(20.667)	(124.126)	(174.768)	(24.008)	(33.515)
Lev	0.0075	−0.0070	0.0864 ***	0.0553 ***	0.1380	−0.2066 ***
	(1.097)	(−1.553)	(4.348)	(4.048)	(1.440)	(−3.247)
ROE	−0.0005	0.0046 *	0.1492 ***	0.1076 ***	0.0309	0.0258
	(−0.110)	(1.740)	(11.747)	(13.383)	(0.504)	(0.690)
Age	0.0255 **	−0.0125	−0.0171	−0.0285	0.1818	−0.0182
	(2.179)	(−1.516)	(−0.503)	(−1.142)	(1.112)	(−0.157)
TAT	0.0066 **	−0.0058 **	1.1212 ***	1.3292 ***	0.0883 **	−0.0148
	(2.214)	(−2.364)	(130.101)	(178.718)	(2.126)	(−0.427)
Fix	−0.0056	0.0092	−1.0735 ***	−1.4984 ***	−0.0894	0.3044 ***
	(−0.630)	(1.393)	(−41.478)	(−74.513)	(−0.716)	(3.249)
CF	−0.0157	−0.0119	0.2470 ***	0.2045 ***	−0.2510	−0.0530
	(−1.380)	(−1.480)	(7.464)	(8.407)	(−1.573)	(−0.468)
Constant	−0.4730 ***	−0.2933 ***	−5.8246 ***	−5.7946 ***	−11.4922 ***	−10.1623 ***
	(−9.302)	(−8.795)	(−39.483)	(−57.213)	(−16.153)	(−21.535)
Firm	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
p-value	0.031 **		0.000 ***		0.000 ***
N	9588	19,690	9588	19,690	9588	19,690
Adj. R2	0.722	0.676	0.982	0.972	0.821	0.738

Notes: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; t-statistics are shown in parentheses. “p-values” were used to test for differences in coefficients by bootstrap sampling 1000 times. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

. The findings indicate that enhancing ESG practices in state-owned enterprises offers a more substantial endorsement for high-quality development in comparison to private enterprises. Furthermore, this study employed Fisher’s combination test to analyse the disparities between the two groups. Empirical p-values obtained through self-sampling 500 times showed that the differences between the groups were significantly different from zero, at least at the 5% level. The potential reasons for these results are discussed as follows: firstly, state-owned enterprises, in accordance with their inherent social public mission, demonstrate a proactive response to national policy calls and are able to accurately identify social public needs; secondly, within the context of stringent internal governance norms and external regulatory requirements, state-owned enterprises can effectively fulfil their corporate social responsibility, thereby reducing the burden of pseudo-social responsibility. Consequently, state-owned enterprises can more effectively promote their high-quality development by implementing ESG practices in an effective manner.

6.2. Heterogeneity of External Business Environment

In addition to the heterogeneity of property rights within a company, the business environment in the region where the company is located also has a critical impact on its high-quality development. Therefore, there is also a certain degree of heterogeneity in the external business environment for companies to strengthen their ESG practices in order to promote high-quality development. In order to examine the heterogeneity of the external business environment, this article selects the marketization degree index of different provinces in China to reflect the degree of marketization in each region. According to the median of the above index by industry and year, the entire sample was divided into a high-marketization group and a low-marketization group, and then grouped regression was conducted. The regression results are shown in

Table 13. Heterogeneity test results of the external business environment.

	(1)	(2)	(3)	(4)	(5)	(6)
	HQD	HQD	TFP_LP	TFP_LP	Lnpatent	Lnpatent
	L_marketization	H_marketization	L_marketization	H_marketization	L_marketization	H_marketization
ESG	0.0018 ***	0.0037 ***	0.0035 ***	0.0950 ***	0.0470 ***	0.0687 ***
	(3.210)	(3.134)	(0.672)	(4.807)	(5.829)	(4.232)
Size	0.0264 ***	0.0302 ***	0.6068 ***	0.6196 ***	0.5816 ***	0.6018 ***
	(25.911)	(12.119)	(201.854)	(77.491)	(40.154)	(17.440)
Lev	−0.0088 **	0.0093	0.0909 ***	−0.0181	−0.1185 **	−0.1192
	(−2.224)	(0.990)	(7.802)	(−0.601)	(−2.111)	(−0.917)
ROE	0.0035	0.0045	0.1221 ***	0.1237 ***	0.0370	0.0808
	(1.421)	(0.941)	(16.732)	(8.146)	(1.052)	(1.233)
Age	0.0014	−0.0451 ***	−0.0173	−0.0334	−0.0124	−1.0224 ***
	(0.193)	(−2.856)	(−0.814)	(−0.660)	(−0.121)	(−4.674)
TAT	−0.0010	0.0024	1.2649 ***	1.1636 ***	0.0515 *	−0.0263
	(−0.489)	(0.599)	(202.713)	(88.850)	(1.713)	(−0.465)
Fix	−0.0065	0.0148	−1.4001 ***	−1.1700 ***	0.1299	−0.1959
	(−1.130)	(1.116)	(−83.006)	(−27.523)	(1.598)	(−1.068)
CF	−0.0170 **	−0.0009	0.2323 ***	0.1849 ***	−0.1574	0.0287
	(−2.397)	(−0.061)	(11.052)	(3.861)	(−1.555)	(0.139)
Constant	−0.3785 ***	−0.3826 ***	−5.6661 ***	−5.8029 ***	−10.8057 ***	−8.8477 ***
	(−13.052)	(−5.388)	(−66.102)	(−25.494)	(−26.161)	(−9.006)
Firm	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
p-value	0.001 ***		0.000 ***		0.000 ***
N	23,778	6172	23,778	6172	23,778	6172
Adj. R2	0.690	0.715	0.976	0.976	0.766	0.806

Notes: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively; t-statistics are shown in parentheses. “p-values” were used to test for differences in coefficients by bootstrap sampling 1000 times. Sources: Panel data from CSMAR and CNRDS; ESG ratings from Huazheng ESG.

. In regions with high marketization construction, the strengthening of corporate ESG practices provides relatively stronger support for the high-quality development of enterprises, and empirical p-values obtained through self-sampling 500 times indicate that inter-group differences are significantly different from zero, at least at the 10% level. This article believes that the possible reasons for the above results are as follows: the higher the degree of marketization construction in the region, the more complete the economic development, the lower the transaction costs of enterprises, the faster the information transmission, and the more accurate and transparent the ESG-related activities carried out by enterprises can convey positive signals to stakeholders, thereby obtaining corresponding reciprocal support, which will further help enterprises achieve high-quality development.

7. Discussion

At the level of individual researchers, extant research has principally concentrated on the impact mechanism of ESG on the high-quality development of enterprises. In addition, future research directions in this field are relatively diverse. Firstly, further research can be conducted to construct an ESG indicator evaluation system that is tailored to China’s national conditions and in line with the high-quality development goals of Chinese enterprises. This would improve the top-level design of ESG. The establishment of a unified and authoritative ESG evaluation system would be conducive to enhancing academic standards and supporting government departments in formulating pertinent legal policies. Secondly, improvements can be made to the measurement methods for the high-quality development of enterprises, with the aim of creating a unified and authoritative quantitative method for the high-quality development of enterprises. This would broaden the evaluation dimensions of companies, enable companies to conduct quantitative self-evaluation, and assist government departments in judging the development level and high-quality transformation process of companies. Finally, existing research has focused primarily on the direct impact of ESG factors on the high-quality development of enterprises, while further research is needed on the interaction and joint influence of ESG factors with other factors such as company strategy, organisational culture, human resource management, etc. Future research endeavours should explore the integration of ESG factors with other internal and external factors of the company to collectively promote high-quality development.

In summary, future research should seek to further refine our understanding of the impact mechanism of ESG on the high-quality development of enterprises. It should also expand the scope of ESG’s influence on company development and explore ways to combine ESG factors with other internal and external factors of the company to collectively promote the company’s high-quality development. Moreover, the enhancement of ESG performance necessitates the consideration of cost issues, which were not incorporated within the research framework of this article. Addressing these issues is imperative for future research endeavours.

8. Conclusions and Policy Implications

In light of the mounting global consensus on ESG concepts, the enhancement of ESG practices by enterprises is poised to serve as a pivotal catalyst for achieving high-quality development. This article employs a sample of Chinese A-share listed companies from 2010 to 2020 to empirically assess the high-quality development of enterprises across multiple dimensions. The findings of this study suggest that ESG performance has the potential to significantly enhance the high-quality development of enterprises. Furthermore, this study indicates that digital transformation can positively regulate the role of ESG performance in promoting the high-quality development of enterprises, with the mechanism of action being to enhance supply chain stability and alleviate financing constraints. The impact of ESG performance on the high-quality development of enterprises exhibits heterogeneity, with its assistance effect being more pronounced for state-owned enterprises and enterprises operating in regions characterised by superior business environments.

In light of the aforementioned research conclusions, this article puts forward the following policy recommendations.

Firstly, companies should strengthen their ESG concepts and proactively engage in ESG practices. Enterprises should integrate ESG concepts with their business development strategies, implementing them into their operational behaviour. They should also actively carry out environmental governance, better fulfil social responsibilities, and improve corporate governance efficiency. In doing so, enterprises should prioritise the maximisation of stakeholder interests, fostering mutually beneficial relationships and contributing to the advancement of stakeholders.

Secondly, the promotion of ESG practices within state-owned enterprises is crucial, leveraging their role as exemplars in this domain. For state-owned enterprises that have dual goals of economic benefits and social development, and shoulder more national missions and responsibilities, it is vital that they fully play their exemplary role, actively carry out ESG practices to help state-owned enterprises achieve innovative, efficient, green, and stable high-quality development, and contribute to the comprehensive promotion of China’s ecological civilisation construction and green low-carbon development.

Thirdly, it is imperative to continuously enhance the construction of the regional business environment and promote the rapid development of the marketisation process. In regions where marketisation processes are more advanced and business environments are more conducive, the economic development level of the region is comparatively high, and the transaction costs of enterprises are relatively low. This is conducive to the active implementation of ESG practices in enterprises and provides robust external support for the development of an ESG system with Chinese characteristics.

Finally, it is imperative to promote the gradual improvement of the corporate ESG information disclosure system and the standardisation of corporate ESG performance evaluation. In the context of China, the disclosure of ESG information by listed companies is predominantly voluntary and does not stipulate mandatory standards for disclosure content. This has resulted in a lack of consistent standards and the issue of “greenwashing”, which has consequently become a significant challenge in evaluating the performance of corporate ESG practices. In order to address these challenges, the government should implement a gradual improvement of the corporate ESG information disclosure system to ensure the authenticity and measurability of corporate ESG practices. Conversely, the heterogeneity of rating agencies’ positions, industry standards, and data sources leads to significant variations in ESG ratings, complicating the establishment of a uniform evaluation framework. This has the potential to mislead stakeholders, including investors, the general public, suppliers, and customers, and hinder the ability to ascertain the authenticity of corporate ESG practices. In order to address this challenge, it is essential that the government promotes the standardisation of ESG performance evaluation for enterprises. By doing so, it will be possible to truly better promote value co-creation between enterprises and stakeholders and thus promote the realization of the high-quality development of enterprises.

This study acknowledges that, although ESG practices generally promote high-quality development, high cost measures such as emissions reduction may indeed squeeze short-term profitability. It is recommended that future research incorporate cost–benefit analysis in order to explore how long-term ESG benefits (e.g., reputation enhancement and policy support) offset short-term costs. This would allow for a more comprehensive revelation of the trade-off mechanism and the real role of ESG in corporate development. While the article focuses on the Chinese context in accordance with data and policy logic, it can briefly explore the implications of research findings for other emerging markets. For instance, companies in Southeast Asia, Latin America, and other regions may face similar balance issues between policy promotion and market adaptation in ESG practices and digital transformation but with differences in regulatory strictness, stakeholder demands, or mechanisms of action. This may be considered a future research direction, with the potential to enhance the generalizability of conclusions through cross-regional comparisons and to assist readers in evaluating the broader applicability of the conclusions.