Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 21, No. 2, 2025 164 The Impact of Board Composition of Listed Companies on Corporate Performance Wenyu Zhang * School of China Agricultural University, China Agricultural University, Beijing 100083, China * Corresponding author: (Email: zwyuuuuu2022@163.com) Abstract: As a core component of the corporate governance structure, the board of directors is crucial to whether a company can make correct decisions, achieve effective risk management, and create value in a complex and ever -changing market environment. This paper takes A-share listed companies from 2012 to 2022 as research samples and conducts an empirical analysis on board composition. It is found that the diversification of the characteristics of board composition in listed com panies is conducive to improving corporate performance, among which the diversification of age groups and financial backgrounds of the board have the most significant positive impact on corporate performance. The research findings of this paper provide theoretical and empirical evidence for optimizing board composition and enhancing the performance of listed companies. Keywords: Listed Companies; Board Composition; Corporate Performance. 1. Introduction As a core component of the corporate governance structure, the board of directors is not only responsible for formulating the company's strategic direction and supervising the implementation of decisions by the management, but also directly influences the company's operational decisions and resource allocation through the professional backgrounds, decision-making styles, and behavioral patterns of its members. Therefore, whether the board composition is optimized is crucial to a company's ability to make co rrect decisions, achieve effective risk management, and create value in a complex and ever-changing market environment. Meanwhile, as the cornerstone of the capital market, the rationality, professionalism, and independence of the board composition of listed companies have attracted widespread attention from investors, regulatory authorities, and the academic community. Thus, exploring the impact of board composition of listed companies on corporate performance not only holds significant theoretical value b ut also has prominent practical significance. Specifically, this paper takes A-share listed companies from 2012 to 2022 as research samples, conducts an empirical analysis on the board composition, and uncovers the inherent relationship between board composition and corporate performance. It aims to provide a theoretical basis and practical guidance for listed companies to improve their governance structures and enhance governance efficiency. 2. Literature Review The Company Law stipulates that the board of directors is elected by the shareholders' meeting and accountable to it. The shareholders' meeting acts as the principal of the directors, while the directors are agents entrusted to manage the company's affairs. Jensen (1976) [1] views the principal-agent relationship as a contractual one. Due to the separation of operational and decision-making powers in enterprises, only when top management teams achieve greater interest alignment can corporate performance be improved. In terms of previous scholarly research, theoretical studies on the impact of top management team characteristics on corporate performance can be traced back to the 1980s. Hambrick and Mason (1984) [2] first proposed the upper echelons theory, arguing that the personal preferences and characteristics of top management team members influence enterprises' strategic choices at various stages. With the deepening of research, the revised upper echelons theory emphasizes the impact of psychological variables such as cognitive level and values on executives' behaviors, and proposes replacing demographic variables with psychological variables (e.g., cognition and behavioral tendencies) to represent a series of theoretical constructs. Many scholars have discussed and verified the impact of top management team characteristics on corporate development and growth from various perspectives, as these characteristics affect all aspects of corporate operations. Wu Dejun and Huang Dandan (2013)[3], starting from environmental performance, found through an analysis of corporate social responsibility reports that executives' gender and long-term compensation are positively correlated with environmental performance. From the perspective of corporate innovation behaviors, Yang Xuan and Luo Fei (2016) [4] discovered that there is a non -linear "U-shaped" relationship between the average age of executives and corporate innovation behaviors in listed companies on the SME Board. Lu Xin et al. (2017) [5], in their research o n the impact on investment efficiency, concluded that the average age and average tenure of the top management team are positively correlated with investment efficiency. There have also been many in-depth studies on the impact of individual characteristics and preferences of members of corporate management teams on corporate performance, with varying perspectives. From the perspective of age characteristics, Zhu Mingqi and Zhang Fuxiang (2018) [6] found that the older the average age of the top management team, the more conducive it is to increasing R&D investment and, at the same time, to improving corporate performance. In terms of gender structure, Yan Yonghai (2014) [7] found that greater gender diversity in the board of directors can, to a certain extent, promote corporate performance. However, other scholars have drawn different conclusions regarding 165 gender composition. Li Jinglin and Yang Zhen (2019) [8] found that increasing the proportion of female members leads to a decrease in investment in innovative industries, thereby reducing corporate innovation performance. This is because women generally have a risk-averse psychology, so they reduce investment activities to control operational risks. Regarding educational background characteristics, Wen Fang and Hu Yuming (2009) [9], as well as Zhang Junrui et al. (2010) [10], conducted sample studies using data from different periods and types of enterprises. They found that educational level is positively correlated with corporate performance, and the educational level of members has a significant positive impact on R&D investment, among other aspects. Ke Jianglin (2006) [11], however, found that top management teams with greater differences in educat ional backgrounds are more likely to have disagreements during the decision-making process, and such disagreements among team members regarding the company's strategic direction and decisions will be more pronounced. Synthesizing previous studies on how the characteristics of team members affect performance, scholars have not reached a consensus on the relationship between top management team characteristics and corporate performance. Most existing research findings focus on GEM -listed companies in emerging markets to explore the relationship between top management team characteristics and corporate performance, while there are relatively few studies on main board listed companies. This paper attempts to construct an overall diversity index of board members' characteristics to comprehensively examine the impact of the diversity of board composition on corporate performance. 3. Research Design 3.1. Sample Selection and Data Processing Considering data availability and completeness, this paper takes A-share listed companies in China as the research sample, with the observation period set from 2012 to 2022. To ensure the uniformity and reliability of the data, companies were manually screened and excluded, including ST companies with abnormal financial data, financial and insurance companies, and those with incomplete data during the selected period. Ultimately, 1,353 observations from 123 companies were obtained for testing in the empiric al model. Most of the data used in this paper were sourced from the CSMAR database and Wind database, and the main empirical research tools employed were Excel and Stata. 3.2. Variable Definition 3.2.1. Explained Variable Return on Assets (ROA) is a key indicator for measuring the profitability of listed companies. It is closely related to a company’s profitability and asset management efficiency, and reflects a company’s efficiency in generating net profits using its assets. The higher the ROA, the stronger the company’s profitability and the higher the returns from investments. In practical application, ROA can be used to evaluate a company’s profitability, compare the operational efficiency of companies in the same industry, measure a company’s growth potential, and assess the performance of management. This paper selects Return on Assets (ROA) as the proxy variable for measuring the corporate performance of listed companies, so as to determine corporate performance by measuring a company’s profitability. 3.2.2. Explanatory Variable Previous studies on top management team characteristics have mostly focused on age, educational background, gender, and functional background. Therefore, this paper selects age, gender, board members' concurrent positions in other enterprises, educational background, financial background, overseas background, and academic background as indicators for constructing the overall diversity of board members' characteristics, with each indicator summed up with equal weights. Among these, educational background, financial background, overseas background, and academic background are constructed with reference to the Blau index, which avoids an excessive proportion caused by an overrepresentation of a certain group under the same characteristic. The classification criteria for each type of background are based on the definitions in the CSMAR database. The formula for the Blau index is expressed as: 𝐵𝑙𝑎𝑢 = 1 − ∑ 𝑃𝑖 2 𝑃𝑖 2 represents the proportion of members in the i -th category among the total number of board members of the enterprise. The value of Blau ranges between 0 and 1: the closer the value is to 1, the higher the degree of diversity of the board composition in terms of this characteristic; the closer the value is to 0, the lower the degree of diversity of the board composition in terms of this characteristic. Each indicator is summed up with equal weights to obtain the overall diversity composition index: 𝐵𝑜𝑎𝑟𝑑 = 𝐴𝑔𝑒 + 𝐺𝑒𝑛𝑑𝑒𝑟 + 𝐷𝑛𝑢𝑚𝑏𝑒𝑟 + 𝐷𝑒𝑔𝑟𝑒𝑒 + 𝑂𝑣𝑒𝑟𝑠𝑒𝑎 + 𝐴𝑐𝑎 + 𝐹𝑖𝑛 3.2.3. Control Variable Drawing on previous studies, the following firm-level control variables are selected: firm age (Bage), firm market capitalization (Cap), asset-liability ratio (Lev), ownership structure (Share), and management expense ratio (Mer). Detailed definitions of each variable are shown in Table 1: 166 Table 1. Definitions of Variable Indicators Variable Type Variable Name Variable Symbol Description Explained Variable Return on Assets ROA Net profit / average total assets Explanatory Variable Characteristics of Board Members Age Age Standard deviation of ages of board members Gender Gender Proportion of female board members Board Members' Concurrent Positions in Other Enterprises Dnumber Average number of concurrent positions held by board members in other enterprises Educational Background Degree 1 = Secondary technical school or below; 2 = Junior college; 3 = Bachelor's degree; 4 = Master's degree; 5 = Doctoral degree; 6 = Others (academic qualifications published in other forms, such as honorary doctorate, correspondence education, etc.); 7 = MBA/EMBA Overseas Background Oversea 1 = Overseas work experience; 2 = Overseas study experience; 3 = No overseas background Academic Background Aca 1 = Teaching in colleges/universities; 2 = Working in research institutions; 3 = Engaged in research in associations; 4 = No academic research background Financial Background Fin 1 = Regulatory authorities; 2 = Policy banks; 3 = Commercial banks; 4 = Insurance companies; 5 = Securities companies; 6 = Fund management companies; 7 = Securities registration and clearing companies; 8 = Futures companies; 9 = Investment banks; 10 = Trust companies; 11 = Investment management companies; 12 = Exchanges; 98 = Others; 99 = No financial background Control Variable Firm Age Bage Natural logarithm of firm establishment years Market Capitalization Cap Natural logarithm of firm market capitalization Asset-Liability Ratio Lev Total assets / total liabilities Ownership Structure Share Shareholding ratio of the largest shareholder Management Expense Ratio Mer Management expenses / operating income 4. Analysis of the Relationship between Board Composition of Listed Companies and Corporate Performance 4.1. Descriptive Statistics After collecting and processing the data, Stata software was used for data analysis. First, a preliminary data observation was conducted through descriptive statistical analysis, with the results as shown in Table 2. The results indicate that the Return on Assets (ROA) has a minimum value of -1.068, a maximum value of 0.257, and a mean value of 0.037, suggesting significant differences in ROA among sample enterprises and distinct variations in performance levels across different firms. The standard deviation of the diversity of board members' characteristics is relatively large, indicating notable differences in board composition among different companies. The relatively large standard deviation of age reflects significant variations in the ages of directors among listed enterprises. Regarding the number of concurrent positions held by board members in other enterprises, the maximum is 19, the minimum is 0, with a mean of 1.721 and a standard deviation of 1.65 —showing relatively larger differences compared to other indicators, 167 which implies disparities in directors' concurrent positions across companies. Additionally, the relatively large standard deviation of market capitalization indicates differences in scale among listed enterprises. Table 2. Descriptive Statistics Results Variable Number of Observations Mean Standard Deviation Minimum Maximum Roa 1353 0.037 0.055 -1.068 0.257 Board 1353 1.520 0.465 0.471 5.134 Age 1353 7.331 2.450 1.581 16.061 Gender 1353 0.123 0.118 0.000 0.571 Dnumber 1353 1.721 1.650 0.000 19.000 Degree 1353 0.517 0.203 0.000 0.826 Ovesea 1353 0.206 0.210 -0.049 0.667 Aca 1353 0.478 0.191 0.000 0.747 Fin 1353 0.266 0.238 0.000 0.857 Bage 1353 2.690 0.418 0.693 3.664 Cap 1353 5.603 1.530 2.731 10.306 Lev 1353 0.462 0.187 0.057 1.003 Share 1353 0.444 0.161 0.064 0.886 Mer 1353 0.068 0.061 0.002 0.878 4.2. Overall Regression Analysis To avoid multicollinearity, this study conducted a Variance Inflation Factor (VIF) test. Regression analysis was performed only after confirming that there was no multicollinearity issue. Table 3 shows that the mean value of the variance inflation factor (VIF) of the variables is 1.25, indicating that there is no collinearity among the variables. Table 3. Variance Inflation Factor Test Results Variable VIF 1/VIF Cap 1.66 0.602 Lev 1.50 0.666 Share 1.23 0.810 Bage 1.14 0.875 Mer 1.12 0.893 Board 1.06 0.947 Mean VIF 1.29 The results of the Hausman test, as shown in Table 4, indicate that there are systematic differences between the estimated coefficients of the random effects model and those of the fixed effects model. Since the P-value (0.0002) is less than the significance level of 0.05, it is considered more appropriate to use the fixed effects model for regression analysis. Table 4. Hausman Test Results Fixed Random Difference S.E. Board 0.0096787 0.0062015 0.0034773 0.0025181 Bage - 0.0233608 - 0.0080529 -0.0153079 0.0044922 Cap 0.0208993 0.0099848 0.0109145 0.0028917 Lev - 0.1890419 - 0.1583823 -0.0306596 0.0109586 Share 0.0226069 0.0097763 0.0128306 0.0165771 Mer - 0.3008726 - 0.2535412 -0.0473314 0.0237306 Prob>chi2=0.0002 A benchmark regression analysis was conducted on the model, with results as shown in Table 5. The regression results indicate that the independent variable—the diversity index of board members' characteristics—is significant at the 5% level, and a coefficient greater than 0 suggests that there is a positive relationship between the overall diversity of board members' characteristics and corporate performance. A diverse board composition provides enterprises with more professional skills and social experience, enabling them to enhance their information acquisition capabilities and strategic vision in the operation process. Such diversity effectively promotes the return on corporate assets and improves corporate performance. Table 5. Overall Regression Results Variable ROA Board 0.010** (0.031) Bage -0.023*** (0.000) Cap 0.021*** (0.000) Lev -0.189*** (0.000) Share 0.023 (0.029) Mer -0.301*** (0.000) Cons 0.066** (0.011) N 1353 R2 0.139 Note: Standard errors are in parentheses, ***p<0.01, **<0.05, *<0.1 168 4.3. Robustness Test 4.3.1. Exclusion of Special Samples During the Robustness Test, considering that the sudden outbreak of the COVID-19 pandemic during 2020 -2021 caused significant volatility in the global economy and financial markets, and exerted a notable impact on the operations and performance of Chinese listed comp anies, removing data from this period can help us eliminate the interference of these special factors, thereby more accurately evaluating the relationship between the financial background characteristics of board members and corporate performance. After removing the data from 2020-2021, the regression results presented in Table 6 show that the coefficient of the diversity index of board members' characteristics is positive and remains significant. It can thus be concluded that the conclusion is robust. Table 6. Exclusion of Samples from Specific Years Variable ROA ROA* Board 0.010** (0.031) 0.009* (0.076) Bage -0.023*** (0.000) -0.019** (0.011) Cap 0.021*** (0.000) 0.014*** (0.001) Lev -0.189*** (0.000) -0.183*** (0.000) Share 0.023** (0.029) 0.022 (0.363) Mer -0.301*** (0.000) -0.260*** (0.000) Cons 0.066** (0.011) 0.088*** (0.004) N 1353 1107 R2 0.139 0.112 Note: Standard errors are in parentheses, ***p<0.01, **<0.05, *<0.1 4.3.2. Replacement of the Explained Variable Table 7. Replacement of the Explained Variable Variable ROA ROA* Board 0.010** (0.031) 0.992** (0.024) Bage -0.023*** (0.000) -3.066*** (0.000) Cap 0.021*** (0.000) 2.495*** (0.000) Lev -0.189*** (0.000) -15.005*** (0.000) Share 0.023** (0.029) 2.772 (0.188) Mer -0.301*** (0.000) -29.024*** (0.000) Cons 0.066** (0.011) 5.387** (0.034) N 1353 1353 R2 0.139 0.123 Note: Standard errors are in parentheses, ***p<0.01, **<0.05, *<0.1 To ensure the robustness and reliability of the previous regression results, we choose to use ROE (Return on Equity) as the explained variable to replace the original ROA (Return on Assets), thereby providing a different perspective to evaluate corporate performance levels. The regression results, as shown in Table 7, indicate that after replacing the explained variable, the positive promotional effect of the diversity index of board members' characteristics on corporate performance remains unchanged. This confirms that the regression results and conclusions of this paper are relatively reliable. 5. Conclusions, Recommendations and Prospects 5.1. Research Conclusions This paper conducts an empirical study on the comprehensive characteristics of board members (in terms of board composition) and the performance of listed companies by establishing a connection between the diversity index of board members' characteristics and the performance level of listed companies. The results show that the diversity of the compositional characteristics of board members in listed companies is conducive to improving the company's performance level. Additionally, the reliability of the above conclusions can be verified through the Robustness Test. Based on these conclusions and viewpoints, effective measures can be taken to improve the board structure, thereby enhancing the own performance of Chinese listed companies. 5.2. Research Recommendations First, rationally arrange the organization of listed companies' boards of directors. Given the positive effect of the overall characteristic diversity of board members on corporate performance, when selecting and assigning roles to board members, it is necessary to ensure that they possess professional skills and knowledge relevant to the company's business. On this basis, emphasis should be placed on the diversity of members' characteristics to build a diversified board. Focus should be laid on constructing a board structure with a multi-level age composition and diverse integration of financial backgrounds. Regular board meeting s should be held to ensure sufficient communication among members, who can share information and insights, so as to better play a complementary role in business decision -making and responding to internal and external risks. This will help companies better "seize opportunities in the development stage, optimize growth in the growth stage, stabilize capabilities in the mature stage, and pursue transformation in the recession stage." Second, balance the professionalism and backgrounds of board members. In view of the non -linear relationship between the diversity of most single characteristics of board members and performance, listed companies should establish a scientific evaluation and incentive mechanism for board members, objectively assess their contributions, and promptly track and monitor the alignment between industry trends and the capabilities of board members. They should not blindly strive to expand the diversity of board composition. Instead, in terms of factors such as gender, educational background, and functional background, they should align with the most urgent development needs of the enterprise and industry at the current stage, and balance the professionalism and backgrounds of board members. By establishing a multi -level talent pool for the enterprise, the company can maximize the advantages of its human resources, thereby facilitating adjustments to the board composition and providing reserve support for improving corporate performance. 169 Second, balance the professionalism and backgrounds of board members. In view of the non -linear relationship between the diversity of most single characteristics of board members and performance, listed companies should establish a scientific evaluation and incentive mechanism for board members, objectively assess their contributions, and promptly track and monitor the alignment between industry trends and the capabilities of board members. They should not blindly strive to expand the diversity of board composition. Instead, in terms of factors such as gender, educational background, and functional background, they should align with the most urgent development needs of the enterprise and industry at the current stage, and balance the professionalism and backgrounds of board members. By establishing a multi -level talent pool for the enterprise, the company can maximize the advantages of its human resources, thereby facilitating adjustments to the board composition and providing reserve support for improving corporate performance. 5.3. Future Prospects First, as fiduciaries of shareholders, directors are responsible for managing and supervising the company's operations. A rational board structure can ensure that the board's decisions align with the best interests of shareholders and effectively protect shareholders' rights and interests. Additionally, obtaining more and more accurate measurements of board structure characteristics can better rationally guarantee the company's stable operation and healthy growth. For future research, focus can be placed on samples of listed companies in different industries to verify the more direct and obvious effects and mechanisms of board composition in specific industries. This will provide guidance for the establishment, management, and operation of boards of directors across various industries. References [1] Jensen Michael C. Theory of the firm: Managerial behavior, agencycosts and ownership structure [J]. Journal of Financial Economics, 1976(4):305-360. [2] Donald C. Hambrick; Phyllis A. Mason. Upper Echelons: The Organization as a Reflection of Its Top Managers [J]. The Academy of Management Review, 1984(2). [3] Wu Dejun, Huang Dandan. Top management characteristics and corporate environmental performance [J]. Journal of Zhongnan University of Economics and Law, 2013, (05): 109- 114. [4] Yang Xuan, Luo Fei. A study on the relationship between top management team characteristics and corporate innovatio n behavior of small and medium-sized board listed companies [J]. Collected Essays on Finance and Economics, 2016, (05): 87- 95. [5] Lu Xin, Zhang Lele, Li Huimin, Ding Yanping. Top management team background characteristics and investmen t efficiency: A study based on the moderating effect of executiv e incentives [J]. Journal of Audit & Economics, 2017, 32 (02): 66-77. [6] Zhu Mingqi, Zhang Fuxiang. Top management team, corporate innovation and corporate performance: An empirical study based on the mediating role of corporate innovation [J]. Friends of Accounting, 2018(22). [7] Yan Yonghai. Board gender diversity and corporate financial performance: Empirical evidence from small and medium - sized board listed enterprises [J]. Friends of Accounting, 2014(18):33-37. [8] Li Jinglin, Yang Zhen. Board gender diversity, corporate social responsibility and corporate technological innovation: An empirical study based on Chinese listed enterprises [J]. Science of Science and Management of S&T, 2019, 40(05):34-51. [9] Wen Fang, Hu Yuming. Top management personal characteristics and R&D investment in Chinese listed enterprises [J]. Management Review, 2009, 21(11):84-91+128. [10] Zhang Junrui, Wang Peng, Jia Zongwu, Zeng Zhen. A study on the impact of independent director background on corporate value: Empirical evidence from small and medium-sized enterprise board listed companies [J]. Journal of Statistics and Information Forum, 2010, 25(06):63-70. [11] Ke Jianglin, Sun Jianmin, Zhang Biwu. Reasons for turnover of top management team members in Chinese listed companies : An explanation and empirical study based on demographic characteristic gaps [J]. Economic Management Journal, 2006, (23):55-60.