Exploring the Role of Top Management Team Diversity and Absorptive Capacity in the Relationship Between Corporate Environmental, Social, and Governance Performance and Firm Value

Abstract

Environmental, social, and governance (ESG) performance is a key indicator of a firm’s long-term value and competitiveness. This study combined internal management dynamics (TMT diversity and absorptive capacity) and external social responsibility (ESG) to provide a more holistic perspective that explores the relationship between ESG performance and corporate value at multiple levels. In this study, Chinese A-share listed companies from 2011 to 2022 were selected and analyzed using a quantitative approach. The findings are as follows: (1) There is a positive correlation between ESG performance and firm value. (2) This relationship is particularly accentuated within non-high-polluting industries, the eastern and middle region, and non-state-owned firms. (3) The age, gender, financial background, and absorptive capacity of TMTs significantly moderate the relationship between corporate ESG performance and firm value. These findings will help business leaders and policymakers understand how effective management and responsibility practices can drive long-term business success and social impact. These findings not only help academics deepen their theoretical constructs but also provide operational guidance for business practices.

1. Introduction

The increasing importance of environmental, social, and governance (ESG) factors signifies a substantial shift in the various roles firms play in social and natural environments [1,2]. Firms are no longer solely focused on economic benefits; instead, they increasingly prioritize environmental impacts, societal contributions, and governance transparency. Thus, ESG performance has become an important indicator for assessing the level of corporate sustainability [3]. A company’s ESG performance is of interest to external stakeholders, especially investors and regulators. In today’s world, where investors are increasingly exploring sustainable investment, excellent ESG performance is an assured way to attract more investment and improve the market performance of a company’s stock. An increasing number of scholars have provided empirical evidence supporting the positive impact of ESG initiatives on innovation, corporate reputation, and company performance [4,5,6,7]. However, no consistent findings have been obtained [7,8,9,10]. Hence, the current study aims to enhance our understanding of the relationship between ESG factors and the top management team (TMT) of a firm. It also seeks to examine the way these elements collectively influence firm value.

Country factors are important in explaining ESG performance [11,12]. Contrary to Western countries, China has strongly emphasized sustainable development since the earliest stages of its economic and social development, although ESG has developed relatively late in the country [13]. China’s normative frameworks, cultural values, and business conditions differ greatly from those of Western nations, and these distinctions significantly influence the local understanding and implementation of corporate social responsibility (CSR) [14]. In China, CSR practices are frequently associated with government policies [15], social expectations [3], and cultural influences [16], thereby emphasizing the harmonious symbiosis and long-term development of all aspects of business and society. Thus, the examination of the relationship between ESG performance and firm value can be meaningfully informed by considering the case of China’s economic growth and policy directions.

The structure and function of the management team are key to an organization’s success. A diverse management team brings a broader range of perspectives and innovative thinking, which helps the business make more effective decisions in its socially responsible practices. The absorptive capacity of a company is critical to the sustainability of its business [17]. Examining these internal dynamics can help us understand how management decisions affect a company’s response to external pressures and opportunities. ESG performance is one way in which a company responds to external environmental and social demands. By examining how ESG performance affects firm value, we can assess the economic returns of adopting these social responsibility measures and understand how firms can improve their market competitiveness by improving their social and environmental performance. Examining how TMT diversification and absorptive capacity moderate the impact of ESG performance on firm value can reveal the interaction between internal management strategies and external social responsibility. This integrated perspective can help us identify key drivers for improving corporate performance and achieving sustainable growth. Therefore, this study combines management dynamics and social responsibility to provide a comprehensive perspective on how companies can improve their performance and social impact by optimizing their internal management and implementing social responsibility practices.

The top-level perspective is based on the theory of corporate behavior, which states that managers’ strategic decisions are influenced by human cognitive limitations, which can significantly affect firm performance [18]. This theoretical framework emphasizes the human weaknesses inherent in managers’ decision-making processes, such as limited information-processing abilities and subjective biases, and how these shape corporate strategy and ultimately affect firm performance. It has been shown that diversity is a key factor in a TMT’s ability to assess situations and make optimal strategic decisions [18] and can improve a team’s ability to solve complex problems. Specifically, different diversity variables have different impacts on business outcomes [19].

Absorptive capacity is an important organizational capability [20] that describes a firm’s ability to identify, acquire, integrate, and utilize external knowledge to enhance its competitive advantage [21]. This concept is particularly important in the context of ESG. Limitations on the ability to judge the potential of new knowledge stem not only from the cognitive and competence boundaries produced by search and expectation but also from the use of stakeholder values as assessment criteria [22]. They emphasize the inherent limitations that firms must overcome when valuing new knowledge and highlight the need to more openly and holistically consider the potential of new knowledge to better leverage it to drive firms’ innovation and growth. Absorptive capacity is one of the most important factors for better understanding how firms can enhance their ESG performance by strategically utilizing their resources and capabilities; ultimately, it translates into economic value.

As the world’s second-largest economy, China has a unique economic structure, policy orientation, and cultural background that have had a profound impact on the practice of ESG. This study used China as the research background to explore the impact of ESG on corporate value and create a multifaceted impact on this research area.

2. Literature Review and Hypothesis Development

First, the literature has already proved that national factors have an important impact on social performance [11]. This study expands the geographical scope of ESG research and provides an emerging market perspective in the Chinese context. Second, it innovatively combines executive team diversity with ESG, revealing the key role of this moderating effect, which is a factor that has been overlooked in previous research [23]. Third, while other studies exist on absorptive capacity as a mediating variable [24] and as a moderating variable [25], there is a gap in the research on the impact of ESG on corporate performance. Fourth, the rigor of the empirical research methods provides a robust analytical framework for global ESG research. It also takes into account the heterogeneity of industries, regions, and market competition. Finally, it provides important insights for formulating corporate strategies with Chinese characteristics and provides policy recommendations on how global companies can improve their ESG performance and optimize the composition of their executive teams.

2.1. ESG Performance and Firm Value

Resource-based theory (RBT) represents a central tenet within the discipline of strategic management that explains how firms gain competitive advantages by utilizing and allocating their resources [26]. Firms’ efforts in environmental and social responsibility help shape their unique skills and competencies, which provide distinct advantages over their competition [7,13]. Stakeholder theory [27] asserts that firms should be accountable not only to shareholders but also to a broader array of stakeholders. These stakeholders include employees, customers, suppliers, communities, government entities, and the environment, and their interests and needs must be acknowledged in corporate decision-making processes [27]. Ahsan et al. [14] posited that considering the interests of all stakeholders enhances a firm’s value and creates a win–win situation for both the company and its diverse stakeholder groups. Similar to financial metrics for assessing a company’s performance for its shareholders, ESG metrics serve to evaluate a company’s performance and stance on various issues that are crucial to a broader group of stakeholders [28]. These metrics provide insights into environmental sustainability, social responsibility, and governance practices, thereby offering a comprehensive view of a company’s impacts and practices beyond financial results. The implementation of ESG practices is of paramount importance in meeting the needs of stakeholders and has become a significant component of the corporate approach to achieving environmentally and socially relevant goals [29]. Serafeim and Grewal [30] suggested that nonfinancial information can be a valuable predictor of a company’s expected future financial performance [30,31]. This characteristic underscores the importance of integrating ESG factors and other nonfinancial indicators into business analyses and decision-making processes.

A company’s ESG performance is a significant nonfinancial indicator of its long-term success and potential to attract investment. Firstly, a company’s ESG ratings provide insights into its level of engagement in environmental responsibility and social well-being. An excellent rating serves as evidence of a company’s endeavor to diminish information asymmetry and promote market stability. Secondly, a company that focuses on social responsibility and environmental protection not only contributes to a favorable brand image but also signals stronger growth potential. Such firms can better meet asset managers’ needs for stable long-term returns [9]. In essence, responsible firms are more likely to achieve sustained success and profitability. Corporate reputation has been shown to be a vital factor in improving financial performance [7,32]. Firms with a high ESG performance can improve their corporate reputation and thereby attract more investors, customers, and talent [33]. In this way, firms can improve their overall performance.

ESG is a critical factor that influences a firm’s risk, performance, and value [9]. Firms’ disclosure of ESG information results in several positive outcomes [15]. Examples include reducing the cost of equity capital [34], firms’ downside risk [35], financing risk [36,37], and share price volatility [38]. A positive ESG performance reduces systemic risk, improves a firm’s resilience to shocks [39], and leads to better risk management capabilities [15]. Friede et al. [8] concluded that most studies have reported a non-negative relationship between ESG and financial performance, with most results exhibiting a positive correlation. Consequently, we propose the following hypothesis:

H1: 

Corporate ESG performance positively influences firm value.

2.2. Moderating Effect of Top Management Team

From the perspective of top managers, the foundations of their decision-making processes are deeply rooted in the theory of corporate behavior [40]. This theory provides insights into the fact that managers’ decisions are not always based on purely rational pursuits but are heavily influenced by the inherent cognitive limitations and behavioral tendencies of human beings [18]. In conclusion, the decisions made by managers are frequently influenced by their inherent information-processing abilities, experiential habits, and psychological biases. Consequently, these decisions and actions have a direct impact on business performance [41]. Owing to the challenges of parsing and assessing the complex psychological states and actual behaviors of top executives, organizational demographics have become the primary methodology for early top-level research [18]. This approach provides a more objective and accessible way to study the diversity and decision-making processes of TMTs.

Wiersema and Bantel [42] found a robust correlation between the cognitive dispositions of top executives, as reflected by the demographic characteristics of the team, and the team’s ability to drive the company’s strategy. The higher the board diversity, the lower the volatility, and the better the firm performance [43]. A TMT with a younger average age is more inclined to adopt and implement strategic changes [42], and rejuvenated leaders are more likely to lead their firms down the path of strategic renewal. Nielsen [18] conducted a theoretical review of TMT diversity and posited that with the slow but steady growth of TMT numbers, gender may become an important attribute for future research. Firms with higher gender diversity tend to have better decision-making capabilities [44]. Gender diversity in TMTs can be effective in improving voluntary carbon disclosure and its quality, and increased transparency and accountability will motivate and support a low-carbon transition in the global economy [45]. Additionally, top executives with financial backgrounds often have a deep understanding of financial metrics and market dynamics, which may influence their assessment and decision-making regarding ESG investments. They are typically proficient in risk assessment and management [46], which helps firms identify and mitigate potential financial risks when implementing ESG strategies. In summary, it cannot be ignored that the financial background of firms’ TMTs influences the relationship between ESG practices and firm value. By combining financial expertise with ESG strategies, firms can achieve their sustainability goals more effectively and gain a competitive advantage in the marketplace. Therefore, we propose the following hypotheses:

H2: 

TMTs moderate the relationship between ESG performance and firm value.

H2-1: 

The older average age of TMT members weakens the positive impact of ESG performance on firm value.

H2-2: 

Female TMT members enhance the positive impact of ESG performance on firm value.

H2-3: 

TMT members with financial backgrounds enhance the positive impact of ESG performance on firm value.

2.3. Absorptive Capacity

Absorptive capacity refers not only to an organization’s acquisition and absorption of information but also to its ability to effectively use that information [20]. Camisón and Forés [47] proposed that absorptive capacity can be applied to different units of analysis and various fields of study, such as organizational learning [48,49], strategic management [50], and innovation management [51,52]. Absorptive capacity has a moderating effect and can translate the implementation of ESG initiatives into sustained competitive advantages for firms [53]. Zahra et al. (2008) emphasized the relationship between absorptive capacity regulation, international venture capital, and firm profitability and revenue growth [54]. Engelen et al. (2014) focused on absorptive capacity as a moderator of the relationship between entrepreneurial orientation and firm performance, particularly the benefits of improving the application of entrepreneurial strategies [55]. Firms with high absorptive capacity can adapt to environmental changes by absorbing and assimilating external knowledge [56] and advancing eco-friendly production and practices [25,57] to show the fastest and most comprehensive performance improvement [58]. By contrast, low levels of absorptive capacity reflect an organization’s inability to use external knowledge effectively because of internal resource constraints [52]. A lack of absorptive capacity is a stumbling block preventing firms from improving and innovating. Therefore, we propose the following hypothesis:

H3: 

Absorptive capacity positively moderates the relationship between ESG performance and firm value.

Testing these hypotheses not only enhances existing theoretical frameworks but also offers valuable insights for practical applications, particularly in the context of the growing emphasis on sustainability in global business.

3. Data and Model Specification

3.1. Data Sources and Samples

This study uses a quantitative research methodology to investigate the relationship between corporate ESG performance and firm value while exploring the moderating effects of individual TMT characteristics and absorptive capacity. We used data from the Sino-Securities Index (SNSI) ESG rating system, which is more in line with China’s national conditions and a better source of data than other ESG rating systems [33]. Additional financial data were sourced from the China Stock Market and Accounting Research (CSMAR) database. Specifically, the sample for this study starts in 2011 and excludes financial firms; ST, *ST, and delisted firms; and firms with missing data. All continuous variables are deflated at the 1% and 99% levels. This rigorous screening process provides a solid foundation for studying the relationship between corporate ESG performance and firm value [7]. The final sample consists of 26,227 observations from 3856 Chinese A-share listed companies over 12 years from 2011 to 2022.

3.2. Variable Measurement

3.2.1. Dependent Variable

The existing literature uses Tobin’s Q to measure firm value [7,13,59]. As described by Elamer and Boulhaga [7], Tobin’s Q is a widely recognized financial indicator for assessing firm value options. Therefore, we used Tobin’s Q as the dependent variable to measure firm value; it is calculated as the ratio of the total market value of a firm’s equity and debt to its total assets. Tobin’s Q focuses not only on the company’s existing material assets but also on the market’s expectations of the company’s future potential and performance. This dual focus ensures comprehensive and in-depth assessment results.

3.2.2. Independent Variable

We used the Huazheng ESG data, which includes indicators related to China’s current stage of development [33], with nine grades scored from AAA to C, with the highest being 9 and the lowest being 1. This system has been extensively used in Chinese ESG research [13,15,33,60]. A better ESG performance is indicated by higher scores, which increase with rank.

3.2.3. Moderating Variables

Based on the proposed hypotheses, this study employed the characteristics of TMTs, i.e., age, gender, and financial background, as moderating variables, along with absorptive capacity. The individual characteristics of TMT members, i.e., their age, gender, and professional background, determine how they interpret market and internal data and influence strategic decisions. This study established the average age, number of female members, and financial background of TMTs in the sample firms and measured absorptive capacity based on the intensity of R&D spending, which is defined as the ratio of annual R&D expenditures to operating revenues [24].

3.2.4. Control Variables

In our study, we drew on the prior literature [3,7,24,33,59] and employed control variables similar to those used by other researchers. These variables synthesize a set of firm-level characteristics that may affect firm value. Specifically, we controlled for the logarithm of total assets (Size), leverage (Lev), tangible assets as a percentage of total assets (Tang), firm growth rate (Growth), logarithm of institutional investor shareholding (Institution), logarithm of the number of years on the stock market (ListAge), logarithm of the percentage of shares held by the first largest shareholder (Top1), CEO and chairman duality (Dual), and logarithm of the number of directors (Board). All the variables are defined in

Table 1. Variable measurements.

Variable	Abbreviation	Description
Dependent variable
Firm value	Tobin’s Q (TQ)	The ratio of the total market value of the firm’s equity and debt to its total assets
Independent variable
ESG performance	ESG	The logarithm of company’s composite ESG score
Moderating variable
TMT age	TMTage	The average age of TMT
Female membership	TMTfemale	The ratio of females in TMT to total TMT
Financial background	TMTfinback	Financial background (e.g., regulator, bank, securities, futures, investment firm, and trust) of TMT member
Absorptive capacity	AC	The ratio of annual R&D spending to operating income
Control variables
Firm size	Size	The logarithm of total assets for the year
Financial leverage	Lev	Total liabilities at year end divided by total assets at year end
Ratio of tangible assets	Tang	The ratio of the sum of assets and inventories to total assets
Company growth	Growth	Revenue growth rate
Institutional ownership	Inst	The logarithm of the total number of shares held by institutional investors divided by the total number of share capital
Number of years listed	ListAge	The logarithm of the sum of the current year minus the listed year plus 1
Shareholding ratio of the largest shareholder	Τop1	The logarithm of the number of shares held by the largest shareholder divided by the total number of shares
Duality	Dual	The chairman of the board and the general manager are the same person = 1; otherwise = 0
Board size	Βoard	The logarithm of the total number of board of directors

.

3.3. Model Specification

3.3.1. Model of Benchmark Regression

Based on the aforementioned hypotheses, this study proposes a benchmark regression model to examine the relationship between corporate ESG performance and firm value (H1):

$${TobinQ}_{i,t}={\beta }_0+{\beta }_1{ESG}_{i,t}+\sum {Control}_{i,t}+{Company}_i+{Year}_t+{\epsilon }_{i,t}$$

(1)

In Equation (1), subscript i denotes the firm, and t denotes the year. TobinQ_i,t is the model’s dependent variable and quantifies firm value. ESG_i,t is the ESG performance and is the primary explanatory variable. β is the regression coefficient; if the coefficient β₁ is significantly greater than 0, it supports the proposed H1. Control is the control variable. The model includes the fixed effects of the year and company to account for the possible impacts of time and individuals. ε_i,t is a random disturbance term.

3.3.2. Moderation Regression Model

A moderating effect model was developed for analysis to examine whether the moderating variables, namely, TMT diversity and corporate absorptive capacity, moderate the influence of ESG performance on firm value.

$$\begin{gathered} {TobinQ}_{i,t}={\beta }_0+{\beta }_1{ESG}_{i,t}+{\beta }_2{TMTage}_{i,t}+{\beta }_3{ESG\times TMTage}_{i,t}+ \\ {\beta }_4{TMTfemale}_{i,t}+{\beta }_5{ESG\times TMTfemale}_{i,t}+{\beta }_6{TMTfinback}_{i,t}+ \\ {\beta }_7{ESG*TMTfinback}_{i,t}+\sum {Control}_{i,t}+{ Company}_i+{Year}_t+{\epsilon }_{i,t} \end{gathered}$$

(2)

$$\begin{array}{cc}\hfill {TobinQ}_{i,t}={\beta }_0+& {\beta }_1{ESG}_{i,t}+{\beta }_8{Absorptivecapacity}_{i,t}\hfill \\ & +{\beta }_9{ESG\times Absorptivecapacity}_{i,t}+\sum {Control}_{i,t}\hfill \\ & +{Company}_i+{Year}_t+{\epsilon }_{i,t}\hfill \end{array}$$

(3)

In Equations (2) and (3), i and t denote the firm and year, respectively. TobinQ_i,t stands for firm value, ESG_i,t stands for ESG performance, and Control is the control variable. Company is the individual company fixed effect, and Year is the year fixed effect. ε_i,t is the random perturbation term. The interaction terms include ESG * TMTage, ESG * TMTfemale, ESG * TMTfinback, and ESG * Absorptive capacity.

This chapter describes the data sources, sample selection, and variable definitions, and develops baseline regression models and moderated effects models. The representativeness of the sample and the accuracy of the analysis are ensured.

4. Empirical Findings

4.1. Characteristic Statistics

Table 2. Characteristic statistics.

Variable	N	Min	Max	Mean	p50	SD
TobinQ	26,227	0.800	15.61	1.900	1.580	1.060
ESG	26,227	52.61	85.50	73.71	73.82	4.560
TMTage	26,227	40.69	57.79	49.53	49.59	3.180
TMTfemale	26,227	0	0.560	0.190	0.180	0.110
TMTfinback	26,227	0	1	0.600	1	0.490
AC	26,227	0	0.440	0.040	0.030	0.050
Size	26,227	19.63	26.45	22.28	22.06	1.290
Lev	26,227	0.0300	0.910	0.410	0.400	0.190
Tang	26,227	0	0.850	0.350	0.330	0.160
Growth	26,227	−0.660	4.020	0.160	0.110	0.350
Inst	26,227	0.100	121.8	43.87	45.35	25.87
Listage	26,227	0	3.400	2.020	2.080	0.830
Top1	26,227	8.020	75.78	34.35	32.19	14.81
Board	26,227	1.610	2.710	2.120	2.200	0.190
Dual	26,227	0	1	0.300	0	0.460

shows that TobinQ exhibits some variation in firm value, with a mean value of 1.900, standard deviation of 1.06, maximum value of 15.61, and minimum value of 0.80. The key explanatory variable ESG mean of 73.71 is moderately near the median of 73.82, indicating a relatively even distribution with little variation. The moderator variable TMTage has mean and standard deviation values of 49.53 and 3.18, respectively. These values indicate a significant difference between the samples. Similarly, the moderator variable TMTfemale has minimum, maximum, mean, and standard deviation values of 0, 0.56, 0.19, and 0.11, respectively. Moreover, the moderator variable TMTfinback has minimum, maximum, mean, and standard deviation values of 0, 1, 0.6, and 0.49, respectively, thereby indicating some variation between the samples. The moderator variable Absorptive capacity has mean and standard deviation values of 0.04 and 0.05, respectively, indicating little variation between the samples.

4.2. Correlation and Multicollinearity Test

The correlation coefficients between the model variables are presented in

Table 3. Correlation coefficients.

	TobinQ	ESG	TMTage	TMTfemale	TMTfinback	AC	Size	Lev	Growth	Board	Dual	ListAge	Inst	Top1	Tang
TobinQ	1
ESG	−0.022 ***	1
TMTage	−0.109 ***	0.087 ***	1
TMTfemale	0.087 ***	−0.012 **	−0.242 ***	1
TMTfinback	−0.017 ***	0.007	−0.023 ***	−0.074 ***	1
AC	0.277 ***	0.026 ***	−0.160 ***	0.092 ***	−0.090 ***	1
Size	−0.335 ***	0.184 ***	0.384 ***	−0.203 ***	0.093 ***	−0.272 ***	1
Lev	−0.316 ***	−0.032 ***	0.164 ***	−0.134 ***	0.076 ***	−0.322 ***	0.557 ***	1
Growth	0.098 ***	−0.00500	−0.083 ***	−0.005	0.046 ***	−0.016 ***	0.032 ***	0.036 ***	1
Board	−0.115 ***	0.022 ***	0.207 ***	−0.181 ***	0.107 ***	−0.146 ***	0.274 ***	0.152 ***	−0.010	1
Dual	0.096 ***	−0.019 ***	−0.179 ***	0.143 ***	−0.039 ***	0.175 ***	−0.205 ***	−0.144 ***	0.030 ***	−0.193 ***	1
ListAge	−0.100 ***	−0.015 **	0.329 ***	−0.120 ***	0.054 ***	−0.253 ***	0.481 ***	0.357 ***	−0.100 ***	0.183 ***	−0.249 ***	1
Inst	−0.032 ***	0.096 ***	0.289 ***	−0.172 ***	0.108 ***	−0.227 ***	0.449 ***	0.216 ***	0.033 ***	0.250 ***	−0.195 ***	0.182 ***	1
Top1	−0.092 ***	0.074 ***	0.121 ***	−0.058 ***	0.025 ***	−0.193 ***	0.183 ***	0.043 ***	−0.013 **	0.023 ***	−0.047 ***	−0.071 ***	0.490 ***	1
Tang	−0.142 ***	−0.032 ***	0.146 ***	−0.158 ***	0.013 **	−0.311 ***	0.171 ***	0.282 ***	−0.030 ***	0.130 ***	−0.103 ***	0.195 ***	0.156 ***	0.108 ***	1

***, p < 0.01; **, p < 0.05; * p < 0.1.

. The correlation coefficient between ESG and TobinQ is −0.022, which initially contradicts our hypothesis. Considering the influence of other variables, we suspect that the other variables might have contributed to the bias in the results. Consequently, further regression analysis must be conducted to obtain a more thorough understanding of the underlying relationships. Accordingly, we performed a variance inflation factor (VIF) test to further investigate the issue of multicollinearity across the major variables. The results show no covariance issue; the maximum and minimum VIF values are 2.25 and 1.03, respectively.

4.3. Baseline Regression Results

Before performing the panel data regressions, we conducted a Hausman test to determine which effects model to use. Prob > chi² = 0.0000, which is less than 0.05, indicating that the model passes the fixed effects test and that it benefits significantly from the difference between the fixed and random effects [61].

The impact of corporate ESG performance on firm value was regressed, and the findings are presented in

Table 4. Corporate ESG performance and firm value.

	(1)
Variables	TQ
ESG	0.006 ***
	(4.55)
Size	−0.462 ***
	(−17.95)
Lev	−0.010
	(−0.12)
Growth	0.125 ***
	(7.55)
Board	−0.084
	(−1.44)
Dual	−0.012
	(−0.60)
ListAge	0.608 ***
	(20.85)
Inst	0.015 ***
	(17.67)
Top1	−0.010 ***
	(−7.50)
Tang	0.147 *
	(1.87)
Constant	10.209 ***
	(16.55)
Observations	26,227
Adjusted R-squared	0.283
Number of id	3856
Year	YES
Industry	YES

Robust t-statistics in parentheses. ***, p < 0.01; **, p < 0.05; * p < 0.1.

. A positive correlation exists between ESG and TobinQ (β = 0.006, p < 0.01), thereby supporting H1, which is consistent with the findings of Chen et al. [39]. The effect of the control variables on firm value is consistent with the findings of previous research [62,63].

4.4. Endogeneity

4.4.1. Two-Stage Least Squares Regression

Corporate ESG performance also influences corporate decision-making and performance. In other words, companies with larger market capitalization might be able to invest more in ESG initiatives and thereby have better ESG results. Therefore, to reduce the reverse causality issue, this study used the two-stage least squares method and endogeneity test, using the mean value of firms’ ESG performance (ESG_IV) as an instrumental variable [64]. The results are shown in

Table 5. Endogeneity test results based on two-stage least squares regression.

	(1)	(2)
Variables	ESG	TQ
ESG_IV1	0.979 ***
	(139.20)
ESG		0.018 ***
		(9.74)
Size	0.234 ***	−0.310 ***
	(9.34)	(−44.81)
Lev	−1.329 ***	−0.659 ***
	(−9.45)	(−17.11)
Growth	−0.141 **	0.306 ***
	(−2.42)	(19.39)
Board	−0.083	−0.145 ***
	(−0.73)	(−4.76)
Dual	−0.002	0.080 ***
	(−0.04)	(6.39)
ListAge	−0.076 **	0.161 ***
	(−2.49)	(19.53)
Inst	0.000	0.009 ***
	(0.44)	(32.89)
Top1	−0.001	−0.005 ***
	(−0.50)	(−12.31)
Tang	−0.232	−0.169 ***
	(−1.53)	(−4.14)
Constant	−2.770 ***	7.375 ***
	(−4.07)	(40.73)
Observations	26,227	26,227
Adjusted R-squared	0.506	0.328
Year	YES	YES
Industry	YES	YES

t-statistics in parentheses. ***, p < 0.01; **, p < 0.05; *, p < 0.1.

. Column (1) displays the first-stage regression results. The instrumental variable (ESG_IV) is significantly correlated with ESG (β = 0.979, p < 0.01), and the F-statistic is much larger than the critical value of 10, which refutes the original hypothesis of a weak instrumental variable and passes the test. Column (2) shows the second-stage regression findings. The coefficient of ESG remains positive (β = 0.018, p < 0.01), which is consistent with the results of our benchmark regression. It is plausible that the instrumental variables satisfy the correlation with the endogenous explanatory variables and are uncorrelated with the error term [62].

4.4.2. Propensity Score Matching

To reduce the endogeneity issue resulting from selection bias in the control variables [33], we used propensity score matching (PSM) in classifying corporate ESG performance into two groups using the median of ESG. We designated firms in the high ESG performance group = 1 if their ESG performance is above the median of 73.82; otherwise, we assigned them to the low ESG performance group = 0. The sample was matched using 1:1 nearest neighbor matching in a logistic regression to categorize the firms into control and treatment groups. The impact of ESG_PSM on company value (TQ) remains significant at the 1% level (

Table 6. Endogeneity test results based on propensity score matching.

Variables	TQ
ESG_PSM	0.070 ***
	(5.66)
Size	−0.314 ***
	(−33.77)
Lev	−0.703 ***
	(−15.85)
Growth	0.330 ***
	(14.01)
Board	−0.135 ***
	(−3.63)
Dual	0.076 ***
	(5.01)
ListAge	0.162 ***
	(16.77)
Inst	0.009 ***
	(25.31)
Top1	−0.005 ***
	(−8.52)
Tang	−0.187 ***
	(−4.08)
Constant	9.159 ***
	(30.55)
Adjusted R-squared	0.330
Observations	19,304
Year	YES
Industry	YES

Standard errors in parentheses. ***, p < 0.01; **, p < 0.05; *, p < 0.1.

), demonstrating the validity and reliability of the findings.

4.5. Moderating Effect

Table 7. Moderating effect.

Variables	TQ	TQ	TQ	TQ
ESG	0.007 ***	0.007 ***	0.006 ***	0.006 ***
	(4.76)	(4.68)	(4.10)	(4.56)
ESG * TMTage	−0.001 **
	(−2.20)
TMTage	0.011 **
	(2.48)
ESG * TMTfemale		0.029 ***
		(2.61)
TMTfemale		0.082
		(0.76)
ESG * TMTfinback			0.007 ***
			(3.20)
TMTfinback			0.005
			(0.31)
ESG * AC				0.086 **
				(2.16)
AC				−0.827 **
				(−2.11)
Control	YES	YES	YES	YES
Constant	10.143 ***	10.175 ***	10.226 ***	9.840 ***
	(16.61)	(16.45)	(16.48)	(15.46)
Observations	26,227	26,227	26,227	26,227
Adjusted R-squared	0.284	0.284	0.284	0.284
Number of id	3856	3856	3856	3856
Year	YES	YES	YES	YES
Industry	YES	YES	YES	YES

Robust t-statistics in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

presents the results of model (2), focusing on the moderating effects of TMT diversity and absorptive capacity and introducing ESG * TMTage, ESG * TMTfemale, ESG * TMTfinback, and ESG * Absorptive capacity as the interaction terms. The results show that the interaction term ESG * TMTage negatively affects firm value (β = −0.001, p < 0.05) and that an older TMT age attenuates the positive effect of ESG on TobinQ, consistent with the findings of Tanikawa et al. [65]. The interaction terms ESG * TMTfemale (β = 0.029, p < 0.01) and ESG * TMTfinback (β = 0.007, p < 0.01) positively affect TobinQ, thus suggesting that female executives and executives with financial backgrounds enhance the positive effect of ESG performance on firm value, corroborating the findings of Adams and Ferreira [66]. Meanwhile, absorptive capacity amplifies the beneficial effects of ESG and ΤobinQ (β = 0.086, p < 0.05). H2-1, H2-2, H2-3, and H2-4 are confirmed.

4.6. Robustness Tests

We utilized alternative evaluation mechanisms to conduct a comprehensive stability assessment of corporate ESG performance. This alternative measurement strategy was structured to guarantee that the outcomes of our evaluation of corporate sustainability practices are robust and credible. Specifically, we used ROA as a proxy variable for TobinQ [60]. The results presented in

Table 8. Robustness test.

	(1)	(2)	(3)
Variables	ROA	TQ	TQ
ESG	0.000 ***	0.006 ***
	(3.69)	(4.61)
ESG_final			0.008 ***
			(6.10)
Control	YES	YES	YES
Constant	−0.205 ***	9.845 ***	5.358 ***
	(−4.50)	(13.37)	(41.34)
Observations	26,227	26,219	26,227
Number of id	3856	3855	3856
Adjusted R-squared	0.243	0.284
Year FE	YES	YES	YES
Province	NO	YES	NO
Industry	YES	YES	YES

***, p < 0.01; **, p < 0.05; *, p < 0.1.

(1) remain consistent. These results confirm the robustness of the initial findings.

We also employed a multilevel fixed effects model to account for the influence of province, industry, and year-fixed effects. Other omitted variables at the provincial and industrial levels may have effects that vary over time [3]. Accordingly, province-fixed effects were incorporated into the model. The results shown in Table 8 (2) remain unchanged.

We again performed GLM regressions after decentering the data (ESG_final). Decentering provides an easy means of controlling for individual characteristics and time trends, resulting in more reliable and interpretable analytical results. The results in Table 8 (3) are consistent with the baseline regression.

This chapter presents the findings of the regression analysis, which corroborate the assertion that ESG performance has a beneficial effect on firm value. Meanwhile, TMT diversity and absorptive capacity exert a significant moderating influence on the relationship between the impact of ESG performance on firm value. The results of the robustness tests corroborate the findings of the underlying analysis, thereby underscoring the necessity for firms to optimize their ESG strategies by their specific industry and regional characteristics.

5. Heterogeneity Analysis

5.1. Industry Division

Businesses operating in high-polluting industries are confronted with a greater degree of uncertainty, are more prone to causing environmental issues, and are responsible for releasing a greater quantity of carbon than their counterparts in low-polluting industries. Different industries have different impacts on ESG performance [14,33]. Based on the listed companies by industry classification form and according to the similarity of the business activities [24], the study sample was categorized into firms from high-polluting and non-high-polluting industries to further test the existence of any differences in the impact of ESG performance on firm value in different industries. The results are shown in Group A of

Table 9. Heterogeneity analysis.

	Group A: Industry Division		Group B: Regional			Group C: Property Rights
	Non-Heavy	Heavy	East	Mid	West	State-Owned	Non-State-Owned
Variables	TQ	TQ	TQ	TQ	TQ	TQ	TQ
ESG	0.008 ***	0.004	0.007 ***	0.010 **	0.003	0.009 ***	−0.000
	(4.82)	(1.49)	(3.99)	(2.47)	(0.76)	(4.86)	(−0.15)
Control	YES	YES	YES	YES	YES	YES	YES
Observations	8725	7502	19,352	2911	3955	16,970	8700
Adjusted R-squared	0.292	0.270	0.298	0.248	0.257	0.321	0.240
Number of id	2883	1093	2940	383	551	2965	1021
Year	YES	YES	YES	YES	YES	YES	YES
Industry	YES	YES	YES	YES	YES	YES	YES

Robust t-statistics in parentheses. ***, p < 0.01; **, p < 0.05; *, p < 0.1.

. The coefficient of the impact of ESG performance on firm value in non-high-polluting industries is 0.008, which is significant at the 1% level. That is, firms in non-high-polluting industries are more likely to gain a competitive advantage by improving their ESG performance compared with firms in high-polluting industries. This significant variability across industries suggests that the benefits of ESG performance for firm value are site-specific, with varying implications for policies and strategies [24].

5.2. Regional Distribution

Additionally, the provinces from which the sample was collected are classified into three geographical regions: eastern, central, and western. The results are presented in Group B of Table 9. The regression coefficients of ESG on TobinQ are 0.007 and 0.010 for the eastern and central regions, respectively, with positive effects at the 1% and 5% levels. Compared with the western regions, the eastern and central regions demonstrate a more pronounced impact of corporate ESG performance on firm value. This finding is consistent with the conclusions in the literature [13]. In conclusion, the influence of ESG performance on firm value obviously has regional disparity, with the impact being more pronounced for firms in regions with higher economic levels [13].

5.3. Property Rights Heterogeneity

This study tested for heterogeneity by dividing the total sample into subsamples based on firm attributes (state-owned or non-state-owned firms). The results in Group C of Table 9 indicate that it can be seen that the ESG performance of non-state-owned firms has a more significant effect on firm value (β = 0.009, p < 0.01). The findings suggest that non-state-owned firms are more significantly affected by ESG performance compared to state-owned firms [63]. Additionally, this effect notably enhances firm value.

This chapter further examines the diversity of the influence of ESG performance on firm value by examining distinct subgroups across industries, regions, and levels of market competition. The detailed segmentation analysis enables the identification of how the impact of ESG performance on firm value varies across different environments, thereby providing more granular insights.

6. Discussion

From a theoretical standpoint, this study expands the boundaries of research in the ESG domain by focusing on the impact of ESG strategies on organizational performance. This study reveals the mechanisms through which ESG strategies affect firm value and offers insights into the relationship between ESG strategies and TMTs. Furthermore, this study addresses the gap in the research on the relationship between TMT diversification and ESG. This study also takes into account the heterogeneity of industries, regions, and firm attributes. This is important for the construction and improvement of the innovation theory of Chinese listed companies [61].

In terms of managerial implications, this study’s results demonstrate that the four dimensions of TMT members’ age, gender, financial background, and absorptive capacity significantly moderate the impact of corporate strategy (ESG strategy) on implementation effectiveness (firm value). Younger TMTs are more likely to encourage their firms to adopt novel strategic updates, indicating a proclivity for change and foresight. The presence of female executives not only enriches teams’ perspectives but also enhances their sensitivity to and understanding of diversity issues; meanwhile, the presence of female members on the board of directors improves firm performance and positively impacts firm value [67,68]. In addition, executives with financial backgrounds are instrumental in identifying and mitigating potential financial risks when implementing ESG strategies [46]. TMTs’ absorptive capacity is an important organizational capability that plays a carrier role in firms’ access to and application of market information. It not only facilitates the integration of new knowledge but also accelerates firms’ responsiveness to market changes. These findings emphasize the importance of building a diverse TMT with complementary competencies to ensure the success of firms’ strategies. After an in-depth study, it was found that companies operating in non-heavy areas, companies located in economically developed regions in the eastern or central part of China, and non-state-owned firms seem to be more likely to seize the first opportunity and gain a competitive advantage in the market by continuously optimizing their ESG performance. This phenomenon suggests that, in the context of the current economic transformation and green development, companies should emphasize improving ESG performance as an effective way to enhance competitiveness. On this basis, enterprises can not only realize sustainable development but also promote the healthy and orderly development of the whole industry and contribute to the high-quality growth of the economy.

The limitations of this study include the following. First, ESG is included in three dimensions, and this study is only concerned with comprehensive ESG scores. Future research can thoroughly explore these three dimensions to offer a more nuanced reference for both theoretical studies and corporate management practices. Second, CSR is subdivided into corporate responsibility to shareholders, employees, suppliers, consumers, and customers, as well as the environment and society [61]. In future studies, stakeholders can be categorized and then examined in terms of the different categories. Third, this study uses a single research method. Subsequent studies should consider introducing experimental methods, questionnaires, etc., and using a combination of primary and secondary data for different research topics to innovate the research methodology and enhance the robustness of the findings. Fourth, this study develops an analysis based on three theories, which may make the focus of the study relatively diffuse. We will consider a more focused approach to a single theoretical framework in subsequent studies to gain a deeper understanding of the specific applications and implications of the theory in corporate ESG practices. Future research should study the dimensions of diversity and their interactions to more accurately capture the mechanism of diversity in TMTs and organizational outcomes.

As a consequence of the deepening of globalization and the increasing frequency of international exchanges, Chinese enterprises are gradually absorbing and integrating advanced international ESG concepts, combining them with local realities, and exploring social responsibility with Chinese characteristics. This approach will not only help boost the international competitiveness of enterprises but also play a crucial role in advancing the achievement of global sustainable development goals.

7. Conclusions

Based on resource base theory, firm behavior theory, and stakeholder theory, this study combined internal management dynamics (TMT diversity and absorptive capacity) and external social responsibility (ESG) to explore the relationship between ESG performance and firm value in a multidimensional manner using a comprehensive dataset of Chinese A-share listed entities for the period from 2011 to 2022. The findings emphasize the positive correlation between ESG performance and firm value, providing evidence that TMT diversification and corporate absorptive capacity play a key role in the relationship between firms’ ESG and firm performance. Specifically, this study demonstrates that TMT age, gender, and financial background significantly moderate the relationship between ESG performance and firm value. Moreover, firm absorptive capacity significantly and positively moderates the relationship between ESG performance and firm value. In addition, this study gains a deeper understanding of the generalization and applicability of TMT diversity and absorptive capacity in the impact of ESG performance on firm value.

To add to its rigor, this study also analyzes heterogeneity by industry, region, and firm attributes, all of which indicate significant differences in results across subgroups. Through this research, we aim to contribute to the ongoing discourse on incorporating ESG considerations into investing decision-making processes and the subsequent impact on shareholder value creation. Expanding on this context, by employing robust econometric methodologies, the study seeks to identify the extent to which ESG-related initiatives and their outcomes influence the market’s perception of a firm’s value. This exploration is particularly relevant in light of the increasing recognition of ESG criteria as pivotal components in assessing corporate sustainability and long-term financial performance. The results will furnish stakeholders with crucial evidence regarding the significance of environmental, social, and governance integration in the Chinese stock market, encompassing investors, company management, and policymakers. The findings indicate a positive correlation between corporate ESG performance and firm value. In other words, the better the corporate ESG performance, the higher the market and investor-assessed values. This further emphasizes how crucial TMT diversity and absorptive capacity are when formulating strategic plans.