The Impact of Top Management Team Heterogeneity on Environmental, Social, and Governance Performance and Corporate Green Innovation: Evidence from Chinese Manufacturing Companies

Abstract

In the context of global climate change and resource scarcity, corporate environmental, social, and governance (ESG) performance, as well as corporate green innovation, have emerged as pivotal drivers for fostering sustainable development. The heterogeneity of the top management team (TMT) significantly influences the direction and effectiveness of both ESG performance and corporate green innovation. Drawing on upper echelon theory, information decision-making theory, and social categorization theory, this paper conducts an empirical study using a sample of 314 manufacturing enterprises and employs multiple linear regression analysis to uncover the impact of TMT heterogeneity on corporate green innovation and the mediating role of ESG performance. The findings from this research suggest that TMT heterogeneity exerts a notable positive influence on green innovation (including green technological innovation and green product innovation), and that ESG performance plays a partial mediating role between TMT heterogeneity and green innovation. This research enriches the theoretical foundation of corporate green innovation from the perspective of TMT heterogeneity and offers pertinent suggestions for enterprises to advance their green innovation development.

1. Introduction

As industrialization accelerates and the population continues to grow, the global ecological environment is confronted with a grave threat, and climate change and environmentally sustainable development have become the most urgent issues that social development must deal with [1]. As important participants in socioeconomic activities, enterprises must assume the social responsibility of reducing pollution and saving resources [2]. Green innovation is a crucial approach to alleviating the contradiction between economic growth and environmental pollution [3], and it is also a practical way to enhance enterprises’ green competitiveness [4]. By introducing environmentally friendly technologies, optimizing production processes, and developing green products, green innovation helps enterprises reduce costs and environmental resource burdens while creating new market opportunities, providing differentiated products, and satisfying consumers’ demands for environmentally friendly and healthy products, thus attaining a mutually beneficial scenario where both economic and social gains are realized [5,6]. Due to its significance in coordinating environmental and economic development for enterprises, green innovation has received widespread attention from all sectors of society.

In the increasingly complex and volatile global economic environment, the expertise of a single decision-maker within an enterprise might not be sufficient to meet the demands of sustainable corporate development. Moreover, the capabilities of an enterprise’s innovation and strategic decisions are significantly influenced by the heterogeneity of the top management team (TMT) [7], i.e., their differences in terms of age, gender, educational level, professional experience, and thinking patterns [8]. In line with this, based on upper echelon theory, heterogeneity implies the possession of different cognitive frameworks by the members. Heterogeneity, in turn, helps the enterprise to identify the potential risks exist in the innovation process more accurately, seize innovation opportunities [9], and enhance risk resistance capabilities [10]. In addition, according to information decision-making theory, a heterogeneous TMT possesses a greater number of resources and information sources. Accordingly, the enterprise is able to formulate comprehensive and innovative strategic decisions when faced with a complex business environment [11]. As maintained by Horbach and Jacob, the influence of TMT characteristics on green innovation needs to be considered [12].

In recent years, an increasing global attention had been paid to sustainable development and social responsibility. Moreover, ESG performance is considered an important yardstick for measuring the comprehensive performance of enterprises. Accordingly, it has been widely noted and considered by enterprises, society, and academia [13]. According to the ‘2023 China Sustainable Bond Market Report’, released by the Climate Bonds Initiative (CBI) and Industrial Bank Economic Research Consulting Co., Ltd., a total of 940 billion yuan worth of green bonds was issued by China in both domestic and offshore markets in 2023. Also, as the world’s largest green bond issuer for two consecutive years, China has significantly attracted both domestic and international investors. Amidst the backdrop of green sustainable development, funds injected into the ESG sector have also been growing steadily, which is an indication of a long-term upward trend [14]. In line with this, ESG is recognized as a mainstream economic activity by an increasing number of companies [15]. Consequently, they integrate the principles of ESG into their corporate strategies and operational management. Such companies also strive for balanced development across the environmental, social, and governance dimensions. Notably, the diversity of perspectives and the abundance of resources brought about by TMT heterogeneity contribute to the organic unification of ESG performance [11]. This, in turn, plays a positive role in practicing green development concepts and attracting external technical talents and innovative investments. Importantly, the latter is crucial for accelerating the green innovation process within companies [16].

Hence, drawing on upper echelon theory, information decision-making theory, and social categorization theory, the present study aimed to construct a relationship model among TMT heterogeneity, ESG performance, and corporate green innovation. Moreover, ESG performance was used as the intermediary variable. Accordingly, the mechanism through which TMT heterogeneity influences corporate green innovation was investigated. As the result, the pathways and conditions for promoting green innovation were further determined by enhancing the level of TMT heterogeneity. The obtained results are expected to provide valuable guidance and insights for enterprises to improve their ESG performance and advance their green innovation practices.

The subsequent sections of this paper are organized as follows. In Section 2, the theoretical analysis, the hypotheses, and the conceptual model are employed, proposed, and constructed, respectively. Section 3 presents the design of the questionnaire. The collected sample data are also processed to provide support for the empirical research. Section 4 discusses the application of SPSS 27.0 software to analyze and test the obtained data and verify the research hypotheses. Finally, drawing upon the outcomes of the empirical tests, the findings are summarized and explained in Section 5.

2. Literature Review and Hypotheses Development

2.1. Top Management Team (TMT) Heterogeneity and ESG Performance

According to the upper echelon theory proposed by Hambrick and Mason [17], a corporate’s strategic decisions and behavioral patterns are significantly influenced by the compositional attributes of the TMT. This, in turn, further impacts organizational performance. The TMT heterogeneity refers to differences among the members in such individual attributes as race, tenure, professional background, and work experience [18,19]. With regards to information processing and upper echelon theory, the cognition of a TMT is deeply influenced by its heterogeneity. This heterogeneity prevents team members from acquiring and integrating the internal and external information resources through a single approach. In so doing, as the capabilities of the team’s information processing and decision-making are enhanced, and the enterprise is led towards new strategic directions and action plans [20].

Heterogeneity also creates diverse knowledge, experiences, and cognitive perspectives [21]. This helps the enterprise to better cope with complex and ever-changing market demands and environments [11]. Moreover, it enhances the overall cognitive capabilities of the team. Notably, heterogeneous cognitive experiences play an important role in shaping and updating the entire enterprise’s routines [22]. In line with this, a heterogeneous TMT can more comprehensively understand and process information and facilitate the exchange and collision of different viewpoints. As a consequence, the team can stimulate innovative thinking and enhance the enterprise’s innovation capabilities [23]. This capability not only helps enterprises adapt to environmental changes, as well as seize market opportunities, it also promotes business model innovation and, accordingly, provides a competitive advantage for the enterprise [24].

Similarly, ESG serves as a vital factor in building competitive advantages, stimulating innovation, and seizing market opportunities. However, it needs to be noted that it is also deeply constrained and influenced by the enterprise’s own management capabilities [25]. Considering decision-making and strategic planning, TMT also plays a crucial role in fostering sustainable development [26]. For example, Wang and Dass [27] equated TMT heterogeneity to the different knowledge, experiences, and cognitive habits of the team members. According to them, heterogeneity helps the executive team avoid falling into set thinking and collective bias when acquiring and processing information. Accordingly, the team can make more scientific and comprehensive decisions, which improves ESG performance. In another study, Gao Yuan et al. [11] found the potential of TMT heterogeneity in mitigating the marginal impact of digitization on corporate governance performance. According to the study, this is achieved by alleviating information asymmetry and agency costs, which leads to harmonious integration of the enterprise’s ESG performance. Drawing on the aforementioned analysis, the following hypothesis is proposed:

Hypothesis 1. 

Top management team (TMT) heterogeneity exerts a positive influence on ESG performance.

2.2. ESG Performance and Corporate Green Innovation

As sustainable and green development gain importance, increasingly more enterprises are incorporating ESG indicators into their strategic planning and operational management [28]. ESG performance is a holistic indicator of assessing an enterprise’s performance in environmental, social, and governance aspects. It promotes environmental protection, social responsibilities, and corporate organizational structure and governance. ESG performance also incorporates green transformation and collaborative development within an enterprise [28]. In addition, an enterprise’s degree of sustainable development can be assessed by its ESG performance [29], the optimization of which can bolster the ability to explore and implement innovative activities. Thus, the value creation, green innovation, and financial performance of an enterprise can be promoted [30,31]. It is also instrumental in guiding the implementation of green and innovative development, prioritizing energy-saving and emission-reduction technologies, researching green innovation and development, and driving the green transformation of products and services [32].

While green innovation serves as the core driving force in moving towards a low-carbon economy and achieving sustainable development, ESG performance is a pivotal factor in measuring a company’s performance in terms of sustainable development [33]. In line with this, Meng et al. [34] demonstrated that ESG performance provides political and financial guarantees for the green innovation of an enterprise. According to them, it also ensures the smooth and continuous implementation and improvement of green innovations through promoting values, alleviating financing constraints, and influencing stakeholders’ behavior. Furthermore, according to Ren et al. [35], improving an enterprise’s ESG performance can positively impact its decisions regarding innovative investment. They also showed that it can favorably influence external supervision evaluations and access to government subsidies, which results in significant promotion of green technological innovations.

A study by Zhou Fangzhao and Pan Wanying [36] corroborated that good ESG performance often corresponded with enterprises’ inclinations to invest in green technological innovation. This, in turn, was observed to help them attract more investors and partners willing to focus on sustainable development. Such contributions by the stakeholders provide necessary financial and resource support and promote a virtuous cycle of green technological innovation. Moreover, significant ESG performance can convey favorable signals to the external world about the enterprise’s environmental, social, and governance aspects. So, the enterprise is publicly perceived as bearing more social responsibilities, which, accordingly, establishes a reliable brand image and reputation [37]. In another study, the public was observed by Yu Liufang and Tang Mengting [38] to be more willing to pay enterprises with a good social reputation. This inclination both reduces the market risk of innovative products and leads enterprises to be more active in green product innovation. Drawing from the preceding analysis, the following hypotheses were derived:

Hypothesis 2a. 

ESG performance positively impacts corporate green innovation.

Hypothesis 2b. 

ESG performance positively impacts corporate green technological innovation.

Hypothesis 2c. 

ESG performance positively impacts corporate green product innovation.

2.3. Top Management Team (TMT) Heterogeneity and Corporate Green Innovation

Green innovation aims at promoting sustainable development. It involves the application of innovative thinking and technological means to innovative activities in product design, product processes, management models, etc. [39]. The aim of green innovation is to reduce environmental pollution and resource waste, to meet social needs, and to promote sustainable economic development [40]. Based on the literature, despite their significant differences, different types of green innovation exhibit common features in developing corporate economic performance [41,42]. Through green technological innovation, enterprises can develop more energy-efficient and effective technologies and processes. Therefore, the consumption of raw materials and energy is reduced, costs are lowered, and negative impacts on the environment are minimized. This, in turn, is mutually beneficial in attaining both economic and environmental advantages [43,44]. While pursuing economic benefits, green product innovation is a model through which enterprises develop environmentally friendly products to achieve sustainable development [45]. This helps enterprises to meet their consumers’ green demands and enhance their competitiveness in the market, but at the same time, it also contributes to reduction of operating costs and improvement of the corporate’s profitability [46]. Moreover, the priority of most market entities is an increase in their economic gains. Therefore, if a green innovation strategy is capable of providing more economic benefits than those of competitors, it is more likely to be adopted [47]. In line with this, Zhao Jinguo et al. [48] focused on green innovation from two aspects of green product innovation and green technological innovation.

Emphasizing the TMT, upper echelon theory provides an internal analytical perspective on developing an enterprise. It considers an enterprise as the primary decision-making entity. The theory also looks at an enterprise as an accountable party with regards to their performance, bearing the heavy responsibility of sustainable corporate development [2]. Based on previous studies, a heterogeneous TMT exhibits significant differences in terms of cognitive foundations, values, etc. This is to say that, a highly heterogeneous executive team can approach problems from different perspectives and, accordingly, can have an influence on corporate strategic choices, green innovation, and green performance [49,50]. Wang Xingyu and Xing Yun [51] demonstrated that a TMT with diverse professional backgrounds can acquire information from various fields. When information and knowledge are shared within the team, this helps the enterprise discover new opportunities with regards to green innovation and, as the result, generate more green innovation outcomes. Furthermore, according to Li Dongwei and Wu Jing [52], a TMT with rich working experience has broader perspectives, fewer thinking limitations, and stronger inclusivity and is able to propose more forward-looking strategies, which promotes green technological innovation.

Existing research has shown that a heterogeneous TMT differs in its members’ functional backgrounds, which leads to variation in their thinking patterns. That is, greater emphasis is often placed on green technological innovation with those executives who are experienced in engineering, research, and development, while those engaged in production, marketing, etc. may focus more on green product innovation [53]. For example, Qi Liyun et al. [54] proved that TMT heterogeneity contributes to formulating more comprehensive and higher-quality environmental strategies. Such strategies were found to encourage an increase in investment in environmental protection and green development, thereby promoting green technological innovation. Zhao Na et al. [55] also showed that the adoption of external knowledge facilitated green product innovation. A heterogeneous TMT often possesses broader social networks and resources. Consequently, it can integrate knowledge structures and information resources from different domains, which in turn, provides strong support for enterprises’ green product innovation. Taking into account the prior analysis, the following hypotheses were suggested:

Hypothesis 3a. 

Top management team (TMT) heterogeneity positively impacts corporate green innovation.

Hypothesis 3b. 

Top management team (TMT) heterogeneity positively impacts corporate green technological innovation.

Hypothesis 3c. 

Top management team (TMT) heterogeneity positively impacts corporate green product innovation.

2.4. Mediator Effect of ESG Performance

Based on upper echelon theory, both the innate features and the acquired experiences of the TMT jointly shape their members’ cognitive patterns and values. This, consequently, influences corporate behavioral decisions and strategic choices [56]. Moreover, the same issue can be approached differently by a highly heterogeneous TMT. This is because such a team has access to a richer array of decision-making resources and information. Diversity can also help mitigate biases within decision-making processes, as well as foster a more scientific approach to implementing ESG decisions [57]. According to Bilal et al. [58], ESG can promote green innovation through enhancing corporate social responsibility and government procurement. The heterogeneity of a TMT is also reflected in the different experiences, knowledge reserves, and viewpoints possessed by the team members. This heterogeneity helps enterprises to consider ESG factors more comprehensively. They are also able to adopt a broader perspective in terms of analyzing the market environment and resource conditions required for implementing green innovation activities. Moreover, they can mitigate potential risks associated with green technological and green product innovations [59].

TMT heterogeneity implies that the team members come from different personal backgrounds. This is particularly true for those coming from environmental protection fields. These members can bolster ESG performance by causing an enterprise to place greater emphasis on issues such as environmental conservation and social responsibility [60]. In addition, in a study by Tuo et al. [61], enterprises with favorable ESG performance were observed to send positive signals to investors. Thus, they were able to broaden external funding sources for their green technological innovation projects and, accordingly, ensure the smooth progress of green technological innovation. TMT heterogeneity exerts a profound influence on corporate ESG performance [11], which can encourage research and development, promote green product innovation, form competitive advantages, and secure higher product premiums [62]. Building upon the previous analysis, the following hypothesis were introduced:

Hypothesis 4a. 

ESG performance acts as a mediator between top management team (TMT) heterogeneity and corporate green innovation.

Hypothesis 4b. 

ESG performance acts as a mediator between top management team (TMT) heterogeneity and corporate green technological innovation.

Hypothesis 4c. 

ESG performance acts as a mediator between top management team (TMT) heterogeneity and corporate green product innovation.

Figure 1 shows the theoretical framework of this paper, which is grounded on the aforementioned assumptions.

3. Research Methods

3.1. Sample Source and Data Collection

The manufacturing industry occupies a dominant position in the national economy. It is also characterized by substantial energy consumption and pollution. These features have resulted in significant attention being paid to this industry by all social sectors. Currently, due to considerable resource and environmental pressures, manufacturing enterprises urgently need to enhance their resource utilization efficiency and develop a circular economy through green innovation [63]. Therefore, the samples analyzed in the present study were selected from among such enterprises. Spanning four months, the data were collected through online and offline questionnaires from mid-April 2024 until the end of August 2024. Middle and senior management personnel were asked to fill out the questionnaires. The subjects were selected from among those who were familiar with the diverse characteristics of TMT internal members and corporate green innovation. Online collection of the data was primarily achieved using questionnaire software (such as wenjuanxing), webchat, and email. Offline data collection involved directly visiting and distributing the questionnaires to the subjects. Out of a total of 436 questionnaires that were dispensed, 338 completed questionnaires were returned. Subsequently, based on rigorous criteria, 24 invalid questionnaires were excluded due to item discrepancies, logical inconsistencies, and missing answers. Therefore, for an effective response rate of 72.1%, a total of 314 valid questionnaires were included in the analysis. The main characteristics of the sampled enterprises are outlined in

Table 1. Basic information regarding the investigated manufacturing enterprises.

Item	Characteristic	Frequency	%
Enterprise age	Under 5 years	59	18.8
	6 to 10 years	140	44.6
	11 to 15 years	61	19.4
	16 to 20 years	31	9.9
	More than 20 years	23	7.3
Enterprise scale	Under 50 people	69	21.9
	From 51 to 100 people	108	34.4
	From 101 to 150 people	90	28.7
	From 151 to 200 people	33	10.5
	More than 200 people	14	4.5
Industry	Electronic and information technology industry	12	3.8
	Biomedical industry	13	4.1
	Equipment manufacturing industry	39	12.4
	New energy industry	44	14
	Textile industry	28	8.9
	Food manufacturing	52	16.6
	Chemical manufacturing	31	9.9
	Automobile and spare parts manufacturing	51	16.2
	Rubber and plastics manufacturing industry	21	6.7
	Furniture manufacturing	6	1.9
	Petroleum and coal processing industry	9	2.9
	Other	8	2.6
	Total	314	100

.

Given the significant difference between the number of the returned questionnaires and the total number of distributed questionnaires, a T-test was conducted on the 314 valid and 98 unreturned questionnaires. This was to ensure the reliability of the study. The results showed no significant difference between such indicators as the size and the number of operating years of the enterprises, which corroborated the representativeness of the sample data, i.e., there is no non-response bias. Additionally, the items were arranged randomly. The questionnaire also remained anonymous to reduce psychological pressure on the respondents. However, since each questionnaire was completed by a single individual, there may still be a risk of homology bias. Therefore, the Harman single-factor method was applied. The results revealed the loading of the first principal component to be 39.528%, i.e., falling below the threshold of 40%. Accordingly, the homology bias can be argued to be within a controllable range, and thus not affect the research conclusions.

3.2. Variable Measurement and Questionnaire Development

To ensure the dependability and accuracy of this research, well-established and validated scales were used for the relevant variables (TMT heterogeneity, ESG performance, green technological innovation, green product innovation). With regards to the items, language adjustments were made to better suit the needs of the research. After developing the initial draft of the questionnaire, it was piloted on a small scale. To confirm the precision and practicality of the questionnaire, opinions were sought from experts, scholars, and middle to senior managers. Subsequently, based on the results of the pilot survey and expert feedback, final revisions were made to the questionnaire. A five-point Likert scale, spanning from “strongly disagree” to “strongly agree”, corresponding to scores of 1 to 5, was also adopted. The test items are displayed in Table 2.

The independent variable was defined as top management team (TMT) heterogeneity. The present study primarily deals with the interpretation of TMT proposed by Hambrick and Mason [17]. They define TMT as a management team composed of the general manager, deputy general managers, and other senior executives of equivalent ranks within a company. TMT heterogeneity is reflected in the different demographic characteristics of the team members. Current research on TMT heterogeneity mainly focuses on such aspects as members’ age distribution, professional background, tenure, and working experience [64]. Using five items to measure TMT heterogeneity, the present study mainly refers to the research scales of Hu Baoliang et al. [65] and Talke et al. [66].

The mediating variable was defined as ESG performance. Corporate ESG performance encompasses achievements in three major areas: environment, social responsibility, and internal governance. Examining ESG performance can further assess the sustainability of enterprises’ operations and whether it aligns with societal values [38]. This paper primarily draws on the studies carried out by Wang et al. [67] and Mai et al. [68]. Thus, the items include profit generation through environmentally friendly means, improvement of employees’ job satisfaction, emphasis on efficient internal governance, and other the related content. In total, six items are utilized to assess ESG performance.

The dependent variable was defined as green innovation. Based on a study by Zhao Jinguo et al. [48], green innovation is divided into green technological innovation and green product innovation. As the core driving force of green innovation activities, the former promotes greening of products and services through technological innovations. It also serves as a pivotal approach in attaining green innovation [69]. On the other hand, the latter is the direct embodiment of green innovation activities. By developing new products which are environmentally friendly, utilizing resources efficiently, and prioritizing product recyclability, companies can intuitively demonstrate their green innovation achievements to the market and consumers [55]. With regards to the green technological innovation, this study mainly draws upon research carried out by Zhao Jinguo et al. [48] and Li Jieyi et al. [70]. So, four items were used for measuring the performance of enterprises in terms of resource consumption, material recycling, and other aspects. Considering green product innovation, this study is mainly based on the scales designed by Zhao Jinguo et al. [48] and Ghen et al. [71], with a focus on the performance of enterprises in terms of product pollution, product design, and other aspects, also using four items for measurement.

Regarding control variables, enterprises of different sizes exhibit different resource acquisition, market position, and technological capabilities. These differences may directly influence their ESG performance and green innovation activities. Moreover, larger enterprises are typically better at attracting and retaining executives from diverse backgrounds and possess more funds to support green innovation [72]. Enterprises that have been established for longer may accumulate more experience and resources. They also possess a deeper understanding of and capacity to address social responsibilities and environmental issues. Therefore, such enterprises are expected to be more proactive in conducting green innovation activities [2]. In order to guarantee the constancy of the findings and to prevent biased conclusions due to instabilities in individual variables, the scale and the age of the enterprises were used as the control variables. Furthermore, in order to minimize numerical bias as much as possible, natural logarithms were used to transform the obtained values.

Table 2. Specific measurement items on the sample enterprise questionnaire.

Major	Code	Sub-Factor	Reference
TMT	TMT1	Age varies widely between members of the top management team in the enterprise
	TMT2	The tenure of members in the top management team varies greatly within this enterprise
	TMT3	The education level of the top management team members varies widely in enterprises	Hu Baoliang et al. [65]; Talke et al. [66]
	TMT4	The educational professional background of the top management team members varies greatly within the enterprise
	TMT5	The specialties of the top management team members vary greatly in the enterprise
ESG	ESG1	The enterprise actively promotes the concept of environmental protection
	ESG2	The enterprise makes profits in a green way
	ESG3	The enterprise takes an active role in engaging with societal welfare endeavors
	ESG4	The enterprise focuses on and constantly improves its employees’ job satisfaction	Wang et al. [67]; Mai et al. [68]
	ESG5	The enterprise’s business philosophy is about sustainable development
	ESG6	The company values efficient internal governance
GTI	GTI1	In the production process, the enterprise strives to improve the utilization rate of natural resources
	GTI2	In the production process, the enterprise will process the scraps to achieve recycling and reuse	Zhao Jinguo et al. [48]; Li Jieyi et al. [70]
	GTI3	The enterprise is committed to technology upgrading to promote regeneration and recycling of resources
	GTI4	In the production process, the enterprise will reduce the loss of materials as much as possible
GPI	GPI1	In the design of new products, the enterprise tends to choose materials with the least pollution and the lowest resource consumption
	GPI2	In new product design, the enterprise will think about the future recyclability of products	Zhao Jinguo et al. [48]; Ghen et al. [71]
	GPI3	In the design of new products, the enterprise strives to create green products with low pollution and low energy consumption
	GPI4	In order to drive green development, the enterprise is willing to increase investment in product innovation and design

Note: TMT = top management team heterogeneity; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation.

Table 2. Specific measurement items on the sample enterprise questionnaire.

Major	Code	Sub-Factor	Reference
TMT	TMT1	Age varies widely between members of the top management team in the enterprise
	TMT2	The tenure of members in the top management team varies greatly within this enterprise
	TMT3	The education level of the top management team members varies widely in enterprises	Hu Baoliang et al. [65]; Talke et al. [66]
	TMT4	The educational professional background of the top management team members varies greatly within the enterprise
	TMT5	The specialties of the top management team members vary greatly in the enterprise
ESG	ESG1	The enterprise actively promotes the concept of environmental protection
	ESG2	The enterprise makes profits in a green way
	ESG3	The enterprise takes an active role in engaging with societal welfare endeavors
	ESG4	The enterprise focuses on and constantly improves its employees’ job satisfaction	Wang et al. [67]; Mai et al. [68]
	ESG5	The enterprise’s business philosophy is about sustainable development
	ESG6	The company values efficient internal governance
GTI	GTI1	In the production process, the enterprise strives to improve the utilization rate of natural resources
	GTI2	In the production process, the enterprise will process the scraps to achieve recycling and reuse	Zhao Jinguo et al. [48]; Li Jieyi et al. [70]
	GTI3	The enterprise is committed to technology upgrading to promote regeneration and recycling of resources
	GTI4	In the production process, the enterprise will reduce the loss of materials as much as possible
GPI	GPI1	In the design of new products, the enterprise tends to choose materials with the least pollution and the lowest resource consumption
	GPI2	In new product design, the enterprise will think about the future recyclability of products	Zhao Jinguo et al. [48]; Ghen et al. [71]
	GPI3	In the design of new products, the enterprise strives to create green products with low pollution and low energy consumption
	GPI4	In order to drive green development, the enterprise is willing to increase investment in product innovation and design

Note: TMT = top management team heterogeneity; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation.

3.3. Reliability and Validity Test

To assess the dependability and accuracy of the utilized scales, this article employed SPSS 27.0 software to process and test the data obtained from the valid questionnaires. The particular findings are displayed in

Table 3. Results of the variable reliability and validity tests.

Variate	Item	Load	Cronbach’s α	KMO	AVE	CR
TMT	TMT1	0.833	0.889	0.888	0.694	0.919
	TMT2	0.821
	TMT3	0.835
	TMT4	0.839
	TMT5	0.836
ESG	ESG1	0.826	0.908	0.917	0.685	0.929
	ESG2	0.813
	ESG3	0.834
	ESG4	0.822
	ESG5	0.831
	ESG6	0.839
GTI	GTI1	0.841	0.880	0.837	0.736	0.918
	GTI2	0.864
	GTI3	0.859
	GTI4	0.867
GPI	GPI1	0.846	0.870	0.829	0.720	0.911
	GPI2	0.857
	GPI3	0.868
	GPI4	0.823

Note: TMT = top management team heterogeneity; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation.

. The empirical results indicate that the KMO values for all variables are above 0.8, meeting the standard values of greater than or close to 0.7 and had a p-value of 0.000 in Bartlett’s Test of Sphericity, indicating a notable relationship between the matrix of original variable correlations and the identity matrix, making it suitable for factor analysis. According to the criteria proposed by Nunnally [73], the Cronbach’s α coefficients for all variables in this study span from 0.870 to 0.908, while the composite reliability (CR) values fall within the range of 0.911 to 0.929, surpassing the standard value of 0.7, passing the internal consistency test, and indicating that the scales are at a good level of reliability. Additionally, referring to the provisions of Fornell and Larcker [74], the standardized factor loadings for each scale item lie between 0.813 and 0.868, while the average variance extracted (AVE) values fall between 0.685 and 0. 736. All these values surpass the required minimum of 0.5, signifying that the convergent validity of each scale is highly satisfactory. Therefore, it can be concluded that the questionnaire employed in this study possesses strong reliability and validity.

4. Analysis and Results

4.1. Correlation Analysis

This paper presents the results of Pearson correlation analysis and mean analysis, both of which were performed using SPSS 27.0, and the detailed findings are outlined in

Table 4. Correlation coefficient of sample variables of manufacturing enterprises.

Variate	MV	SD	1	2	3	4	5	6
1. Enterprise age	0.78	0.47	1
2. Enterprise scale	0.77	0.49	−0.031	1
3. TMT dimension data	3.33	0.98	0.024	0.005	1
4. ESG dimension data	3.34	0.97	0.094	−0.056	0.406 ***	1
5. GTI dimension data	3.42	1.01	0.027	−0.032	0.370 ***	0.415 ***	1
6. GPI dimension data	3.38	0.99	0.013	0.001	0.367 ***	0.440 ***	0.447 ***	1

Note: *** is p < 0.001; MV= mean value, SD = standard deviation; ES = enterprise size; TMT = top management team heterogeneity; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation.

. There are significant positive correlations between TMT heterogeneity and ESG performance (r = 0.406, p < 0.001), green technological innovation (r = 0.370, p < 0.001), and green product innovation (r = 0.367, p < 0.001). In this paper, the findings offer preliminary backing for the hypotheses introduced, warranting further testing.

4.2. Hypothesis Testing and Analysis

The research hypotheses were tested by multiple linear regression using SPSS 27.0 software. The results are presented in

Table 5. Regression analysis of the independent variables on the mediating and dependent variables.

	ESG		GI		GTI		GPI
Variate	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8
constant	3.279	1.970	3.389	2.151	3.427	2.168	3.352	2.135
EA	0.187	0.168	0.041	0.022	0.055	0.036	−0.027	0.009
ES	−0.105	−0.110	−0.031	−0.036	−0.065	−0.069	−0.002	−0.002
TMT		0.404 ***		0.433 ***		0.370 ***		0.367 ***
R2	0.012	0.175	0.001	0.188	0.002	0.138	0.000	0.135
Adjusted R2	0.005	0.167	−0.006	0.181	−0.005	0.130	−0.006	0.126
F	1.820	21.848 ***	0.135	23.988 ***	0.260	16.607 ***	0.027	16.100 ***

Note: *** is p < 0.001; EA = enterprise age; ES = enterprise size; TMT = top management team heterogeneity; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation; GI = green innovation.

. In Models 1, 3, 5, and 7, the independent variables exclusively encompass the control variables (namely, the size and the age of enterprise), with each model separately investigating their relationship with the dependent variables (ESG performance, green innovation, green technological innovation, and green product innovation, respectively). The results suggest no significant relationships between the control variables and each dependent variable. This in turn means that the findings were not influenced by the control variables. Moreover, Models 2, 4, 6, and 8 incorporated the independent variable (TMT) into the regression models based on Models 1, 3, 5, and 7, respectively. The aim was to assess the influence of TMT heterogeneity on ESG performance, green innovation, green technological innovation, and green product innovation. The obtained results are an indication of the significantly positive effect of heterogeneity on ESG performance (β = 0.404, p < 0.001), green innovation (β = 0.433, p < 0.001), green technological innovation (β = 0.370, p < 0.001), and green product innovation (β = 0.367, p < 0.001). Hence, H1a, H3a, H3b, and H3c are verified.

The relationships between ESG performance and green innovation, green technological innovation, and green product innovation were also examined through multiple linear regression. As can be seen in

Table 6. Regression analysis of the mediation variables on the dependent variables.

	GI		GTI		GPI
Variate	Model 9	Model 10	Model 11	Model 12	Model 13	Model 14
constant	3.389	1.929	3.427	1.995	3.352	1.863
EA	0.041	−0.042	0.055	−0.027	0.027	−0.058
ES	−0.031	0.016	−0.065	−0.019	0.002	0.050
ESG		0.505 ***		0.416 ***		0.444 ***
R2	0.001	0.253	0.002	0.173	0.000	0.195
Adjusted R2	−0.006	0.246	−0.005	0.165	−0.006	0.187
F	0.135	34.972 ***	0.260	21.553 ***	0.027	24.982 ***

Note: *** is p < 0.001; EA = enterprise age; ES = enterprise size; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation; GI = green innovation.

, the empirical results indicate that ESG performance has a significantly positive influence on green innovation (β = 0.505, p < 0.001), green technological innovation (β = 0.416, p < 0.001), and green product innovation (β = 0.444, p < 0.001). Hence, H2a, H2b, and H2c are verified.

As proposed by Baron and Kenny [75], the mediation effect test approach was initially applied to examine the effect of an independent variable (TMT heterogeneity) on dependent variables (green innovation, green technological innovation, and green product innovation). Subsequently, the impact of the independent variable (TMT heterogeneity) on the mediator variable (ESG performance) was analyzed. This was followed by assessing the influence of the mediator variable (ESG performance) on the dependent variables (green innovation, green technological innovation, green product innovation). Finally, to assess shifts in the impact of the independent variable on the dependent variables, both the independent variable (TMT heterogeneity) and the mediator variable (ESG performance) were included within the regression model. Based on the obtained results, it is evident that TMT heterogeneity exerts a notably positive influence on green innovation, green technological innovation, and green product innovation. Therefore, a significantly positive correlation between the independent variable and the dependent variables is observed in the mediation effect test. These results suggest that, while the D-W value stands at 2.078 (close to 2), the VIF value is 1.000, i.e., falling below the critical threshold of 3. Therefore, no autocorrelation or multicollinearity is observed among the variables. Also, as can be seen in

Table 7. Regression analysis of the independent variables on the mediation variables.

	Pearl River Delta
Variate	ESG
	Standardized beta	VIF
TMT	0.406 ***	1.000
R2	0.164
Adjusted R2	0.162
F	61.398 ***

Note: *** is p < 0.001; TMT = top management team heterogeneity; ESG = ESG performance.

, the regression coefficient between TMT heterogeneity and ESG performance is β = 0.406 (p < 0.001), suggesting a significantly positive association between the two. Therefore, this fulfills the requirement of a significant impact of the independent variable on the mediator variable in the mediation effect test.

As indicated by Models 16, 18, and 20 (

Table 8. Test of the mediation effect.

	GI		GTI		GPI
Variate	Model 15	Model 16	Model 17	Model 18	Model 19	Model 20
EA	−0.042	−0.036	−0.027	−0.020	−0.058	−0.052
ES	0.016	0.002	−0.019	−0.033	0.050	0.037
IV
TMT		0.275 ***		0.242 ***		0.225 ***
ESG	0.505 ***	0.393 ***	0.416 ***	0.317 ***	0.444 ***	0.352 ***
R2	0.253	0.316	0.173	0.221	0.195	0.237
Adjusted R2	0.246	0.307	0.165	0.211	0.187	0.227
F	34.972 ***	35.672 ***	21.553 ***	21.971 ***	24.982 ***	23.987 ***

Note: *** is p < 0.001; EA = enterprise age; ES = enterprise size; IV = independent variable; TMT = top management team heterogeneity; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation; GI = green innovation.

), the comparison of Model 16 with Model 4 shows a reduction in the regression coefficient of TMT heterogeneity on green innovation from β = 0.433 (p < 0.001) to β = 0.275 (p < 0.001). This means that ESG performance acts as a partial mediator in the relationship between TMT heterogeneity and green innovation, which accordingly verifies H4a. Similarly, comparison of Model 18 with Model 6 demonstrates a decrease in the regression coefficient of TMT heterogeneity on green technological innovation from β = 0.370 ( p < 0.001) to β = 0.242 (p < 0.001). In the same manner, this is an indication of the function of ESG performance as a partial mediator in the relationship between TMT heterogeneity and green technological innovation. Therefore, H4b is verified. Comparison of Model 20 with Model 8 also reveals a decline in the regression coefficient of TMT heterogeneity on green product innovation from β = 0.367 (p < 0.001) to β = 0.225 (p < 0.001). This implies that ESG performance functions as a partial mediator in the relationship between TMT heterogeneity and green product innovation. Hence, H4c is verified.

To further test the robustness of the research conclusions, the Bootstrap method was employed for validation. Accordingly, with a non-parametric estimation confidence interval of 95%, the number of Bootstrap samples was set to 5000. According to Preacher and Hayes [76], for the indirect effect, when the Boot confidence interval does not include 0 between its upper and lower limits, the mediation effect is significant; on the other hand, involving 0 is an indication of an insignificant mediation effect. Therefore, when the mediation effect is significant, the Boot confidence interval is tested for the direct effect. Moreover, if the Boot confidence interval of the direct effect does not include 0 between its upper and lower limits, the direct effect is suggested to be significant and play a partial mediation role; if it includes 0, the direct effect is not significant and plays a full mediation role. As shown in

Table 9. Bootstrap test results of mediating effects (Bootstrap = 5000).

IV	DV	MV	Indirect Effect			Direct Effect			Total Effect
			BootLLCI	BootULCI	Effect Ratio (%)	BootLLCI	BootULCI	Effect Ratio (%)	BootLLCI	BootULCI
TMT	GI	ESG	0.0917	0.1881	36.6	0.1572	0.3234	63.4	0.293	0.458
TMT	GTI	ESG	0.0816	0.1922	34.6	0.1468	0.3549	65.4	0.282	0.487
TMT	GPI	ESG	0.0894	0.2010	38.7	0.1205	0.3341	61.3	0.269	0.466

Note: IV = independent variable; DV = dependent variable; MV = mediating variable; TMT = top management team heterogeneity; ESG = ESG performance; GTI = green technology innovation; GPI = green product innovation; GI = green innovation.

, the Boot confidence intervals of both the indirect effects of all pathways and the direct effects do not contain 0. Accordingly, this indicates that ESG performance plays a partial mediating role between TMT heterogeneity and green innovation (including green technological innovation and green product innovation). Hence, this corroborates the strong robustness of the research conclusions.

5. Conclusions

5.1. Discussion

In the present study, empirical evidence was obtained from 314 valid questionnaires distributed among manufacturing enterprises. The data were used to analyze the influence of TMT heterogeneity on the corporate green innovation, mediated by ESG performance.

Firstly, TMT heterogeneity can be argued to positively influence ESG performance. As a result, diverse and new perspectives can be injected into the enterprise [21]. This, in turn, assists enterprises in making more comprehensive and thorough considerations when formulating ESG strategies. It also provides a wider range of information and opinions, which helps mitigate blindness and bias in the process of decision-making [27]. By optimizing ESG performance, the diversified input leads to more scientific and rational decisions. This ensures that enterprises act more responsibly. In conclusion, in order to achieve sustainable development, enterprises are recommended to fully harness the advantages of TMT heterogeneity to drive their ESG performance.

Secondly, TMT heterogeneity positively influences green innovation. In case of problems, a heterogeneous TMT often proposes unique insights and solutions. This cognitive diversity breaks through traditional thinking constraints and accordingly generates more novel and feasible ideas to promote green innovation. According to information decision theory, the experience and knowledge accumulated by TMT members complement each other, forming a synergistic effect [77]. In green innovation projects, this complementary experience assists enterprises in identifying market opportunities more quickly. They can also avoid risks and, as a result, accelerate innovation process [52]. Hence, enterprises can effectively utilize the advantages of executive team heterogeneity and drive greater achievements in green innovation.

Lastly, the intermediary role of ESG performance in the relationship between TMT heterogeneity and green innovation was investigated. ESG performance was found to serve as a partial mediator between the two. Similarly, it also functions as a partial mediator between TMT heterogeneity and both green technological innovations and green product innovations. This mediating effect indicates that the extent to which TMT heterogeneity fully impacts green innovation hinges on the corporate ESG performance level. Enterprises with good ESG performance enjoy a more beneficial influence of TMT heterogeneity on green innovation. Therefore, the mediating role of ESG performance between TMT heterogeneity and green innovation cannot be overlooked.

5.2. Influence

In the present study, the interplay between TMT heterogeneity, ESG performance, and green innovation was theoretically and practically investigated. Accordingly, a novel approach was presented for fostering green innovation within manufacturing enterprises. Therefore, the findings of the study hold both academic and practical significance, which is discussed below.

With regards to the academic significance, TMT heterogeneity is an important research topic in the fields of organizational behavior and management. Therefore, its impact on corporate development has always been the focus of academic attention. However, previous studies have primarily investigated the impact of TMT heterogeneity on strategic decision-making and corporate performance. This is to say that the role of ESG performance and green innovation has been overlooked. Therefore, taking green innovation as the research object, this study not only broadens the research boundaries of TMT heterogeneity, but also deepens understanding of the driving factors behind corporate green innovation. Moreover, as a key measure in assessing enterprises’ comprehensive performance, ESG performance plays a vital role in their sustainable development [29]. Therefore, it is necessary to explore the influence of TMT heterogeneity on ESG performance, as well as the mediating role of ESG performance in the relationship between TMT heterogeneity and corporate green innovation. By so doing, we can better understand the bridging function of ESG performance in corporate strategic decision-making and innovation. In line with this, the findings from the present study reveal that TMT heterogeneity influences corporate ESG performance and green innovation. This is mainly done through such mechanisms as team decision-making, resource allocation, and innovation. This not only provides a new perspective for studying the consequences of TMT heterogeneity but also enriches the antecedent variables of ESG performance and green innovation.

Considering the practical significance of the research, increasing emphasis on environmental protection and sustainable development from all sectors of society has extensively promoted green innovation as a significant trend in corporate development. Therefore, the present study examined the mechanism which describes the influence of TMT heterogeneity on corporate green innovation. Moreover, the intermediary role played by ESG performance was also investigated. Accordingly, the findings from this study provide invaluable theoretical guidance for enterprises to develop their green innovation endeavors. Furthermore, policy makers and business managers are able to formulate more scientific and reasonable green innovation strategies. Also, to attain a harmonious blend of economic, social, and environmental benefits, they can base such strategies on the characteristics of the TMT and ESG performance.

Hence, policy makers and business managers are required to initially recognize the significant role of TMT heterogeneity in promoting ESG performance and green innovation. Thus, an increase in the level of TMT heterogeneity can achieve improvements in both ESG performance and green innovation. Moreover, when forming the TMT, diversified selection criteria need to be established. Such criteria are required to fully consider differences in members’ age, educational background, professional experience, etc. This is to say that they should not merely focus on candidates with a single background or set of experiences. In the same manner, policy makers are recommended to encourage enterprises to build a diversified TMT through tax incentives, subsidies, or the formulation of relevant policies. Furthermore, based on social categorization theory, attention needs to be paid to controlling TMT heterogeneity within a reasonable range. This is because unreasonable heterogeneity may lead to communication barriers and decision-making conflicts within the organization [77]. Therefore, enterprises are strongly advised to set up efficient systems that encourage the communication of information and the exchange of viewpoints among the team members. They can also ensure the members’ prompt understanding of each other’s viewpoints and progress through holding regular team meetings, setting up cross-departmental communication platforms, and adopting other means. As a consequence, they can jointly promote green innovation and ESG performance. In addition, business managers are also expected to promote and popularize green concepts. For example, training sessions can be organized to raise the environmental awareness of senior executives and, accordingly, the team members’ environmental awareness. Green innovation activities can also be more emphasized. Meanwhile, policy makers may consider establishing corresponding environmental protection funds. These financial means can support TMT members in learning about environmental protection. They can also enhance their professional knowledge and skills in green fields. Enterprises are also required to internally foster an inclusive cultural atmosphere. They also need to formulate incentives to encourage team members to share different skills and insights. Since heterogeneity leads to collisions of different viewpoints, this can stimulate the enterprise’s innovative vitality. Enterprises should also actively take advantage of and encourage their team members to propose innovative green technologies and products. Hence, they can drive the enterprise to make breakthroughs in green innovation.

Policy makers and business managers should also prioritize enhancement of ESG performance. In this regard, business managers should integrate the concept of ESG into their strategic planning and daily operations. In addition to considering economic benefits, they are also expected to assess the project’s environmental impact, social contributions, and corporate governance compliance when making investment decisions. Accordingly, they can make sure that their decisions align with the requirements of sustainable development. On the other hand, policy makers can encourage financial institutions such as banks to introduce green credit products and to provide low-interest loans to eligible enterprises. They can also support issuing green bonds to broaden the enterprises’ financing channels and accordingly, improving their ESG performance. Furthermore, business managers need to set clear ESG goals and assign responsibilities accordingly. Differentiated incentive measures should also be implemented based on the contribution and performance of TMT members. Such measures include acknowledgement and promotion of executives who demonstrate significant achievements in ESG management. Policy makers are also advised to shift away from traditional assessment systems which merely focus on financial indicators. This is to say that non-financial indicators such as green innovation achievements and ESG performance need to be incorporated into performance evaluation systems. Accordingly, to motivate prioritization of ESG performance, outstanding enterprises need to be recognized and rewarded. Finally, business managers should establish an ESG performance monitoring system to collect and analyze the relevant data and information. As a result, their performance can be better understood. Moreover, areas which need improvements in ESG aspects can also be detected, which provides a basis for formulating improvement measures. Policy makers should reinforce supervision of ESG information disclosure by enterprises. Thus, enterprises are strongly advised to be asked to regularly publish detailed ESG reports on their green innovation achievements, social responsibility fulfillment, and the sophistication of their corporate governance structures.

5.3. Research Limitations and Future Perspectives

Despite the academic and practical significance of the findings, the study is still limited in a number of aspects. This is mainly due to the variety of subjective and objective factors involved. Firstly, this study fails to consider endogeneity issues, such as the presence of two key factors in this study that may influence the findings: ESG funds and monetary expansion. (1) In terms of the increasing popularity of ESG funds, as ESG investments become more popular [78], not only does TMT diversity increase, but also green innovation, thus creating a mechanistic correlation. (2) Monetary expansion has led to increased liquidity, especially during the COVID-19 pandemic, when central banks in both developed and emerging market economies expanded their monetary base, which prevented asset prices from falling and boosted corporate performance [79]. Thus, excess liquidity may promote green innovation due to the lower cost of capital and TMT diversity due to amplified ESG flows as a result of monetary expansion, a variable whose potential impact on the findings has also not been fully considered. These two factors may have interfered with the main findings of the thesis but were not explored in the study. Future research should explore in more depth how these factors influence the findings and attempt to employ a more rigorous research design to strip away these potential endogenous effects. Secondly, since the study’s samples involve manufacturing enterprises in China, the conclusions and implications might not be extended universally to other regions and industries, which requires further empirical verification. Therefore, to test the universality of the research conclusions, future research is recommended to expand the scope and the number of samples. Thirdly, the sample data were all collected synchronously and cross-sectionally. Consequently, the relationships between the variables may be temporary rather than long-term and stable. Thus, considering the dynamics and variations of ESG performance and green innovation, future research could use dynamic longitudinal data to provide more solid and comprehensive evidence for the related fields. Fourthly, TMT heterogeneity is treated as an overall variable in the present study, i.e., it is not dissected into its dimensions. So, TMT heterogeneity could be more finely divided into such aspects as age heterogeneity, educational level heterogeneity, and tenure heterogeneity in future studies. In so doing, researchers can delve deeper into the ways these dimensions separately and collectively influence ESG performance and green innovation.