The Impact of Firm Digital Transformation on Environmental, Social, and Governance Performance: Evidence from China

2.1 Firm DT and ESG Performance

In the past, the development of firms often relied on the theories of maximizing profits and maximizing shareholder value as action guidelines, with a single goal as the direction of firms’ management (Freeman, 2010). However, according to stakeholder theory, firms need to consider the shareholders’ interests. Additionally, they should balance and pay attention to the disparate demands of multiple stakeholders, taking into account aspects such as employees, customers, suppliers, society, and the environment in business decision-making (Parvaresh & Amini, 2024). In addition, with the gradual improvement of the modern firms’ system, the demand for the working class to safeguard their authorities and interests continues to rise. Moreover, in recent years, governments of countries have successively implemented a series of laws and regulations to curb corporate misconduct, thus raising new demands for corporations to achieve community responsibility. The conception of corporate social responsibility (CSR) has been an inevitability in history.

Nowadays, on account of frequent global extreme weather, continuous trade frictions, and severe environmental protection situations, the ESG concept is increasingly receiving attention from various stakeholders of firm, prompting managers to no longer blindly pursue economic returns and shareholder priority profit distribution methods. Instead, they use a long-term vision to seek a model that is more in line with the conception of sustainable development, abandoning the original “profit first” thinking, forcing firms to undergo transformation and upgrading. However, it must be pointed out that implementing ESG activities usually requires financial investment, including expenses for equipment updates, process improvements, and other aspects (Hoang, 2018). Specifically in environmental activities such as reducing carbon emissions and using renewable energy, significant investments may be required, and it may take some time to achieve positive returns, examined by Mahmoudi et al. (2021). Conversely, Taliento et al. (2019) found that the benefits brought by ESG activities are often difficult to quantify directly, and this uncertainty makes it difficult for firms to make a clear economic evaluation of the costs and benefits of carrying out ESG activities, leading to some firms hesitating.

Studies by Li et al. (2020) have shown that after DT, the support of digital technology can help firms more efficiently enhance their green image, customer reputation, and product quality, thereby bringing profit growth to the firm (Sepetis et al., 2024). At the same time, DT can also trigger shifts in organization structure, internal management, and other governance respects to firms, reduce the expected costs of ESG activities, and even change their own profit models (Wang et al. 2022). While reducing firm costs, it can create more employment opportunities for society, thereby promoting sustainable economic growth. Based on the above analysis and literature experience, this article believes that DT is beneficial for promoting firm ESG performance. Therefore, this article proposes a hypothesis:

H1: The process of DT positively influences the ESG performance of the firm.

2.2 Mechanism Analysis

In this section, this article explores how various factors can affect the relationship between a corporate DT and its ESG performance, focusing on three primary elements independently.

2.2.3 Technological Innovation

This article believes that encouraging technological innovation can improve the degree of DT of firms, thereby enhancing their ESG performance. Many industry practices and empirical studies have revealed a stable positive transmission mechanism between DT, technological innovation capabilities, and ESG performance.

According to Dąbrowska et al. (2022), DT is capable of promoting the improvement of technological innovation level in these three aspects. At first, increase investment in research and development. By implementing DT, firms can enhance their research and development capabilities. DT significantly enhances their technological innovation capabilities, investment, and quality, thereby improving the overall level of technological innovation in firms (Yang et al., 2023). Second, improve operational efficiency. DT can promote technological innovation in firms by optimizing the allocation of innovative elements, reducing firm costs, and other means (Su et al., 2023). By leveraging digital strategies and technological means, firms can accelerate the operation speed of manufacturing processes, promote process improvement, and strengthen the compressive strength of supply chains and industrial structures (Rezaee & Pilevari, 2022). They can optimize information acquisition and product development through new technologies and platforms and enhance their innovation capabilities (Ben Arfi & Hikkerova, 2021). Third, improve the level of human capital. DT enhances employees’ ability to access valuable external knowledge and information resources, providing them with opportunities for self-learning and growth. Bansal et al. (2023) found that it helps employees improve their personal human capital level, thereby promoting technological innovation in the firm.

The technological innovation becomes a key player in influencing the ESG performance of firms undergoing DT through several mechanisms. To begin with, technological innovation enables firms to lower energy usage and decrease emissions of pollutants during their production processes, which in turn bolsters their environmental stewardship and performance (Yurdakul & Kazan, 2020). Next, it contributes to the enhancement of product quality, safety, and dependability, which amplifies the firms’ accountability to their customers, workforce, and the broader community (Yuan & Cao, 2022). Finally, technological innovation is instrumental in advancing the quality of information exposure and transparency of corporations, which helps to refine their internal governance structures (Karim et al., 2022). Based on this, the hypothesis is put forward in this article:

H4: DT can improve the ESG performance of firms by improving their technological innovation level.

Through this article framework, as depicted in Figure 1, all hypotheses are summarized. First, this article tested the direct effect of DT on corporate ESG performance. Second, this article attempts to investigate the relationship between underlying mechanisms and firm digital transformation (FDT). Then, this article applies empirical analysis to explore the quantitative relationships.

Figure 1

Research framework.

3.1 Data and Sample

This study employs the information from all A-share quoted companies on the Shanghai and Shenzhen Stock Exchanges between 2006 and 2022. It utilizes Python web scraping technology to measure the DT degree within these companies and investigate its influence on their ESG performance. To ensure an accurate assessment of DT impact on companies, this study excludes certain types of firms: those in the financial sector, firms designated with *ST or ST (which means Special Treatment), and firms with accounting or financial reporting issues.

The methodology for quantifying the frequency of DT within firms is based on the article by Wu et al. (2021). The control variables are primarily derived from the superior firms’ annual reports. The final sample comprises an unbalanced panel consisting of 27,119 firm-year observations spanning from 2006 to 2022.

3.2 Variables

3.3 Empirical Model

This fixed effect model is created based on the aforementioned theoretical analysis, with the aim of researching the correlation between Firms DT and ESG performance:

The subscript variables i and t refer to firm i in year t. ESG _it refers to the ESG performance firm i in year t. The independent variable FDT _it serves as the proxy for DT, as elaborated in the preceding description. Controls _it encompasses the control variables at the level of the company, including Firm Scale, Firm Return On Assets, Firm Age, Size Leverage, Cash Holdings, Ownership of the biggest shareholder, Board Size, Percentage of Independent Directors, and Dual Role, employed to mitigate the influence of factors that could impact total factor productivity at the micro level of the firm. Additionally, this study incorporates fixed effects for firms ∑Firm and year ∑Year, along with the random error term ε _it (Qi et al. (2024)).

4.1 Descriptive Statistics

In order for the precision of the data, the data is processed as follows: (1) Excluding special processing firms (ST, * ST). (2) Exclude firms with severe data gaps. (3) Excluding the more specialized financial and insurance industries. (4) For the purpose of eliminating the impact of outliers on estimation results, the total continuous variables were subjected to 1 and 99% quantile truncation. Table 2 displays the descriptive statistics of the major variables. The mean ESG score for firms reaches approximately 4.21, with a standard deviation of around 0.983, suggesting that the ESG performance of most companies is notably commendable. The mean level of FDT stands at about 12.56, with a standard deviation of roughly 33.05, indicating varying levels of DT among Chinese listed firms. The descriptive statistics of control variables corresponds closely to former research studies in the field.

4.2 Baseline Result

Tables 3 and 4 present the Impact of FDT on ESG performance. The univariate regression outcomes are displayed in the first column, controlling solely for corporate fixed effects as well as year-fixed effects. Subsequently, column (2) introduces control variables at the firm level to address potential omitted variable bias. It is discovered that the regression coefficient for firm ESG performance on total factor productivity is significant statistically at the level of 1%. Economically speaking, a 1% increase in DT corresponds to a 0.037-unit rise in ESG performance. This suggests that enhancing the extent of DT is capable of positively impacting corporate ESG performance, supporting the core conclusion. It can be inferred that ESG advantages effectively enhance firms’ total factor productivity, thereby validating hypothesis H1. According to the results of the collinearity experiment table, there is no collinearity phenomenon in this study.

4.3 Robustness Test

In order for the robustness of our discoveries, a series of robustness tests were implemented. First, this article replaced the independent variable by introducing dummy variables based on available data. Specifically, this article created the dummy firm digital transformation (DFDT) dummy variable to identify firms implementing DT. The value of this is 1 for companies with non-zero FDT values. The regression outcomes are shown in Table 5, the first column.

Second, this article replaced the dependent variable by substituting the ESG performance data from Huazheng Firms with ESG data sourced from Bloomberg Consulting in the robustness tests for regression. The Bloomberg corporate ESG data, rated on a scale of 0–100, encompasses three aspects: environmental (Env), social responsibility (Soc), along with corporate governance (Gov) (Antolín-López & Ortiz-De-Mandojana, 2023). The regression outcomes are expressed in Table 5, columns (2)–(5). Despite the replacement of the dependent variable and regression across different dimensions, the direction and statistical significance of FDT remained consistent with the initial results.

Following these replacements, the results indicate that FDT continues to positively impact firm ESG performance. Through these adjustments, our core conclusion remains robust and reliable, affirming that DT significantly enhances firms’ ESG performance. It is worth noting that the data show that the environment (Env) is significant at the 1% level, social responsibility (Soc) is significant at the 5% level, and corporate governance (Gov) is significant at the 10% level. According to the analysis in this article, the occurrence of this result may be caused by the following factors.

First, the inherent differences in various indicators may vary. Different ESG components may be influenced by different internal and external factors within the enterprise. Environmental indicators (Env) are often influenced by stricter regulations and policies, such as emission standards and environmental requirements, which may make changes in environmental indicators have a more direct and significant impact on business performance. In contrast, the influencing factors of social responsibility (Soc) and corporate governance (Gov) may be more complex and diverse, leading to differences in statistical significance.

Second, the data quality and availability of various indicators also vary. The environmental data publicly disclosed by firms is often more detailed and standardized than social responsibility and governance data, because environmental information disclosure is often mandatory by laws and regulations. In this case, the quality and reliability of environmental data are relatively high, which may lead to a stronger significance of its statistical test results.

4.4 Mechanism Discussions

For the purpose of coping with the financial constraint effect of FDT, this research uses the CSMAR China Listed Firm Management Dilemma Research Database to obtain the KZ financial constraint index^[1] of A-share superior firms and uses its logarithmic processed data (FC-KZ) for testing. The specific inspection outcomes are displayed in Table 6. Additionally, it is indicated that the DT role in enlarging corporate financing and eliminating corporate financial constraints to improve ESG performance (Yang & Han, 2023) is supported by H2 in this paper. Therefore, this article finds that financial constraint is one of the underlying mechanisms of the main effect. Hypothesis H2 in this article is valid.

For the purpose of dealing with the impact of FDT on information transparency, this study utilized the comprehensive index of internal control information from DiBo Data Consulting. The analysis was conducted on the logarithmically transformed data (IC), and the outcomes are shown in Table 7. The discoveries in Table 7 indicate that the corporate DT significantly enhances the disclosure of internal control information (Wang et al., 2023). This signifies that FDT contributes to increased transparency of internal information, mitigates information asymmetry, encourages firms to genuinely and effectively uphold their social responsibilities, consequently enhancing firms’ ESG performance (Wang & Hou, 2024). As a result, hypothesis H3 posited in this study is supported.

In examining the influence of firm DT on technological innovation, this study leveraged insights from prior literature and accessed pertinent patent classification numbers of A-share quoted companies from China Research Data Service Platform. These data were cross-referenced with the patent classification numbers in the Green Patent List issued by the World Intellectual Property Organization to determine the count of applications for green invention patents as well as green utility model patents among listed firms. The logarithmically transformed data (ENV) was used for analysis, as detailed in Table 8. In Table 8, it is indicated that a remarkable enhancement in green technology creation results from the corporate DT. This underscores that the corporate DT fosters green technology innovation, encouraging firms to shoulder greater environmental responsibilities and thereby paving the way for improved ESG performance (Zhang & Liu, 2023). Consequently, hypothesis H4 posited in this study is upheld.

5.1 Heterogeneity Analysis Based on Firm Size

Lu et al. (2024) point out that the company size plays an irreplaceable part in impacting its capability of effectively enhancing ESG performance. This study utilizes total assets as a metric to gauge firm size, as per available data. Firms are categorized based on total assets, with the lowest 30% classified as small firms, those between 30 and 70% as medium-sized firms, and the top 30% as big companies. Subsequently, the model (1) estimates were recalibrated based on firm size categories. The regression outcomes in Table 9 reveal that the influence of DT on ESG performance differs across firm sizes. Specifically, the DT coefficients reach 0.0135 for small companies, 0.0336 for medium-sized companies, and 0.0502 for large companies. The significance levels vary, with DT being significant at the 10% level for small firms, 5% level for medium-sized firms, and 1% level for large firms. This suggests that as firm size increases, the impact of DT on ESG performance becomes more pronounced.

Based on the above data and existing literature case analysis, this article speculates that large firms have significant advantages in funding, technology, personnel, and other aspects, which can provide sufficient support for innovation activities (Liubkina et al., 2019). Compared to large firms, although small and medium-sized firms have a stronger willingness to innovate, their R&D investment is generally lower due to the above factors (Carfora et al., 2021). Firms can alleviate financial constraints through DT and help establish a good social responsibility image (Wang & Yan, 2023). According to Wu et al. (2023), by improving information control capabilities, information is capable of being improved and processed in time and effectively, lessening the degree of information asymmetry. By improving employee benefits, attracting more innovative talents to join, and enhancing the degree of technical innovation (Biea et al., 2023). Ultimately, the progression of ESG performance is achieved.

5.2 Heterogeneity Analysis Based on Region

Table 10 presents an analysis based on the distinct features of disparate regions in China, namely the eastern, central, and western regions. The influence of corporate DT on enhancing ESG performance might change across regions due to variations in regional economic progress and institutional environments. The analysis reveals that the ESG regression coefficient for firms in the eastern region is obviously positive at the level of 1%, significant at the 10% level in the central region, and not prominent in the western region. This article posits that the corporate DT in the western region does not significantly impact ESG performance. This can be ascribed to some elements. First of all, the western region faces relative inadequacies in infrastructure and resource support compared to the eastern and central regions, constraining the pace and quality of DT and subsequently affecting ESG performance. The eastern and central regions, being more economically developed with better infrastructure and resource support, facilitate firms in undertaking DT and enhancing ESG performance. Second, the western region experiences a scarcity of high-quality talent, particularly in the digital domain, hindering firms from effectively driving DT and resulting in insignificant ESG performance. In contrast, the eastern and central regions boast more abundant talent reserves, with a greater presence of high-quality professionals engaging in DT efforts, thereby bolstering ESG performance. Furthermore, the western region’s relatively underdeveloped nature, coupled with limited market demand and a lack of incentive for firms to pursue DT, impacts ESG performance. Conversely, the eastern and central regions exhibit robust market demand, compelling firms to intensify their DT efforts to enhance ESG performance.

In conclusion, central and eastern areas hold advantages over the western areas in terms of infrastructure, talent availability, and market demand, fostering a conducive environment for firms to engage in DT and thereby elevate their ESG performance.