The Impact of Board Governance on Firm Risk among China’s A-Share Market-Listed Companies from 2010 to 2019

Abstract

This paper selects firm downside risk and firm upside risk as proxy variables of enterprise risk, and the proportion of independent directors as a proxy variable of board governance. Using the panel data of Chinese listed companies from 2010 to 2019, a multiple linear regression model is established to empirically study the impact of supervisory function and advisory function of board governance on the downside risk and the upside risk, to test whether the two functions of the board of directors play a role in the enterprise risk management (ERM). The internal mechanism and boundary conditions of board governance that affect firm risk are also explored in this paper. It is found that the sample enterprises pay more attention to the board‘s supervisory function. At the same time, they reduce the firm’s overall risk by reducing the downside risk and the upside risk while performing this function. We also identify that boards are more likely to use meetings to communicate and strategize to prevent upside risks than to identify and control downside risks. Finally, boards are negatively affected by CEO duality in performing their oversight functions.

1. Introduction

The global financial crisis of 2008 reflected the growing dynamism and complexity of markets and raised questions about the importance of implementing comprehensive risk management. Differing from traditional risk management, enterprise risk management (ERM) is a new management paradigm which regards all the risks of an enterprise as a whole and integrates them into the enterprise strategy for management, so as to improve the enterprise’s overall awareness of risks and promote the improvement of operational and strategic decisions. Hoyt and Liebenberg [1] pointed out that effective enterprise risk management can increase the performance of enterprises by reducing the cash volatility and external capital cost of enterprises and increasing the synergy between different risk management activities of enterprises. Roggi et al. [2] further pointed out that effective risk management not only reduces exposure to downside risks, but also increases exposure to upside returns.

ERM emphasizes the integration of internal control and strategic objectives in order to achieve the objectives of the enterprise. At the same time, enterprises can increase their value through effective risk management and governance, because risk management is related to and dependent on corporate governance [3]. As an effective control mechanism of corporate governance, the board of directors is held responsible by shareholders for the effectiveness of enterprise risk management [4,5] and has two major functions, namely supervision and consultation [6]. Moreover, the board of directors can use an effective ERM framework to ensure that the management can actively identify and analyze risks in order to make reliable decisions [7]. Therefore, board governance plays a pivotal role in enterprise risk management.

However, most of the existing literature related to board governance and risk studies focuses on the supervisory function of the board, ignoring its advisory function. Turel [6] argued that the board of directors has both advisory and supervisory functions, and the two have different roles. At the same time, firm risk, as a reactive index of EMR, is used to measure the result of an EMR. In terms of the selection of proxy variables, most studies use idiosyncratic risk, system risk or overall risk, and the conclusions are inconsistent. Therefore, previous studies could not distinguish whether the advisory function and the supervisory function of the board of directors played a role.

Second, in China, at the regulatory level, there are no normative documents specifically on EMR [8], only the Guidelines on Comprehensive Risk Management for Central Enterprises issued by the State-owned Assets Supervision and Administration Commission in 2006 and the Basic Norms for Enterprise Internal Control issued by Five Ministries and Commissions in 2008. At the same time, the existing literature on the impact of board governance on risk management mainly focuses on developed markets, while domestic research is relatively lacking. Therefore, it is necessary to test whether the governance practices of developed countries can also work in emerging countries.

Finally, China, as a developing country among emerging markets, has potential economic growth and lucrative investment opportunities, and is playing an increasingly important role in the global economy. Using the data of Chinese listed companies to study the impact of board governance on corporate risk taking is helpful to test the validity of agency theory and resource dependence theory in the emerging market environment.

Based on this, this paper uses the panel data of China listed companies from 2010 to 2019 to carry out the following research: (1) establishing the impact of board of directors performing their supervisory duties on firm downside risk; (2) examining the impact of the board of directors performing their consulting duties on the upside risk of the firm; (3) establishing whether board meetings, as a way of reflecting the efforts of the board of directors and providing communication opportunities for directors, mediate the impact of board governance on corporate risk taking; (4) studying whether CEO duality will weaken the governance level of the board of directors, thus weakening the impact of board governance on corporate risk taking.

The main contributions of this paper are as follows:

(1)

Different from previous studies, this paper selects firm downside risk and upside risk as proxy variables for corporate risk taking, and, at the same time, the supervisory and consulting functions of the board of directors, respectively, to test the impact of board governance on corporate downside risk and upside risk, so as to test whether the two functions of the board of directors play a role. The study found that the sample companies paid more attention to the supervisory function of the board of directors than to the advisory function.

(2)

There is a lack of studies on the mechanism of board governance on corporate risk taking in the existing literature. This paper takes board meeting as an intermediary variable to verify whether the supervisory and advisory functions of the board of directors have an impact on the downside risk and the upside risk. The study found that boards were more likely to use meetings to communicate and strategize to prevent upside risks than to identify and control downside risks.

(3)

This paper also tests whether the impact of the two functions of board governance on the downside risk and the upside risk is affected by the duality of the CEO. It is found that although the board of directors may be negatively affected by CEO duality when performing supervisory functions, it should pay more attention to the impact of CEO duality on the performance of consulting functions.

This article is outlined as follows: the Section 1 introduces the research motivations and implications. The Section 2 introduces the research on board governance and firm performance or risk, The Section 3 provides the theoretical basis for board governance and enterprise risk, followed by the research hypothesis. The Section 4 explains the sample selection, data sources and method used in this paper. The Section 5 shows the results and the Section 6 draws the conclusion and discusses the results.

2. Literature Review

Effective EMR can increase enterprise performance by reducing cash volatility and increasing synergies between different risk management activities of enterprises [1]. Dang and Nguyen [9] also pointed out that internal corporate governance can reduce cash risk by overseeing a firm’s daily operations. As an important mechanism of corporate governance, boards play a pivotal role in risk management and have been widely studied by the academic community.

Baysinger and Butler [10] found that enterprises with more outside directors have good financial performance. Abidin et al. [11] found that the independence of the board of directors has a positive impact on corporate financial performance. Chu et al. [12] even found that independent directors could reduce earnings management and information risks associated with the enterprise, so they became a consideration for banks to set loan interest rates for the enterprise. However, Wu et al. [13] found that the independence of the board has a negative impact on corporate performance. Ng et al. [14] also showed that the increase in the number of independent directors on the board of directors significantly reduces the financial performance of enterprises. A study on the relationship between board independence and corporate financial performance by using the cross-sectional data of China’s A-share market-listed companies shows that the positive effect of independent directors on corporate performance has not been explored fully [15]. Li and Yang [16] combined board capital to test the interactive effect of board independence and board capital on corporate performance. The research results show that board independence and board capital can indirectly improve corporate operating efficiency through interactive effects.

According to agency theory, independent directors can evaluate management activities more objectively and restrain unnecessary risks more effectively. However, the research on the relationship between independent directors and enterprise risk has produced inconsistent results. Borokhovich et al. [17] found that with the addition of outside directors to the board of directors, enterprises would increase the use of interest rate derivatives, thus increasing corporate risk. Similarly, Pathan [18] showed that an enterprise with more independent directors seems to be more willing to engage in more risky activities, so it is more susceptible to credit risk and bankruptcy. Recently, Dang and Nguyen [9] found that strong boards, proxied by board size and board independence, are positively related to future stock price crash risk. However, Beasley [19] shows that with the increase in the number of independent directors on the board of directors, the enterprise is less likely to commit financial fraud. Elloumi and Gueyie [20] compared the board structure of financially struggling enterprises and financially healthy enterprises and found that the boards of financially struggling enterprises had fewer independent directors. Zheng [21] showed that independent directors can significantly improve the ability of enterprises to take risks. Liu and Sun [22] also found that, compared with other independent directors, independent directors with legal expertise can significantly reduce the overall risk and systemic risk of enterprises. In addition, Nguyen [23,24] argued that, as the secondary committee of the board of directors, the audit committee assumed a lot of supervision responsibility, and indicated that independent directors can improve the level of supervision of the board. He provided evidence that smaller audit committees with more independent members can improve bank stability by reducing risk [23], and that audit committee effectiveness, proxied by the audit committee index, which includes nine characteristics of audit committees, can reduce bank risk-taking through increasing bank efficiency [24]. Recently, Nguyen and Dang [25] also investigated the relationship between a bank’s risk governance structure and its risk management effectiveness and found that the proportion of independent directors in the audit committee was positively correlated with the effectiveness of risk management. This indicates that independent directors can effectively reduce enterprise risks. Dionne and Triki [26], however, showed that independent directors have no significant relationship with corporate risk.

The reasons for the inconsistent results of the above studies may be as follows: (1) different samples and different years of data selection; (2) most studies start from the supervisory function of the board of directors, ignoring the role of the advisory function of the board of directors in corporate risk management; and (3) in the selection of proxy variables of enterprise risk, the basic focus is on some special risks, total risks or systemic risks, ignoring the impact of the two functions of the board of directors on the downside risk and the upside risk, respectively. Therefore, in order to further understand the impact of board governance on EMR, it is necessary to study the impact of the two functions of the board of directors, respectively, on the upside risk and the downside risk of the enterprise, and clarify the mechanisms through which the two functions act on enterprise risk management and are affected by these mechanisms.

According to agency theory, independent directors can evaluate management activities more objectively and restrain unnecessary risks more effectively. According to the resource dependence theory, the rich experience of outside directors can provide important heterogeneous resources for enterprises, thus helping the board of directors to improve their decision-making ability. Therefore, this paper selects the proportion of independent directors of the board of directors as the proxy variable of board governance to study the influence mechanism of the supervisory function and advisory function of the board of directors on the downside risk and the upside risk, respectively.

3. Theoretical Background and Research Hypothesis

3.1. Board Governance and Corporate Downside Risk

Downside risk is the extent to which the value of an asset may fall below a particular target and is associated with losses. According to agency theory, agents cannot always act in the best interests of the principal. They may pursue their own interests at the expense of the interests of shareholders, so there is a conflict of interest between shareholders and managers. In terms of the supervisory function of the board, Amran et al. [27] stated that the board performs various supervisory tasks to eliminate agency costs, align the interests of shareholders and management, appoint and dismiss managers, and monitor the behavior of the CEO. Aebi et al. [28] demonstrated that banks with chief risk officers performed significantly better during the global financial crisis. It is precisely because the chief risk officer reports directly to the board rather than the CEO that the interaction between risk management and corporate governance is enhanced, which improves the risk environment faced by the company. Elamer [29] also pointed out that many financial institutions fail to fully integrate risk management practices into corporate governance, leading to large-scale economic crises at the global level. Gupta et al. [30] further pointed out that a poor governance system includes the board’s weak control over management and poor risk management practices. Therefore, the supervisory function of the board of directors plays a pivotal role in corporate governance and risk management.

Jackling and Joan [31] pointed out that in the case of conflicts of interest between shareholders and managers, boards with a larger proportion of independent directors are more likely to take independent supervisory actions. At the same time, in order to maintain their “expert” reputation, independent directors will not only take effective regulatory measures to reduce agency costs between managers and shareholders [32,33] and will objectively evaluate management activities and adopt more effective methods to curb unnecessary risks. In fact, outside directors are seen as good supervisors because their careers are not related to the CEO of the company, and therefore they do not have to worry about their future pay and position while making decisions that are unfavorable to the CEO [26]. Beasley et al. [34] also pointed out that because independent directors have no personal interests in the enterprise, they can make fair judgments without being dominated by fear and preference. Based on this, the first hypothesis is proposed:

 Hypothesis 1.

When the board of directors performs its supervisory function, improving the level of board governance (the increase in the number of independent directors) is conducive to reducing the downside risk of the enterprise.

3.2. Board Governance and Corporate Upside Risk

Upside risk is the extent to which asset values may exceed a predetermined benchmark, and is related to investment returns. According to the resource dependence theory, the board of directors should be composed of a wide range of diverse members, so that the board of directors has unique capabilities and can effectively implement its functions. In terms of the advisory function of the board, Zahra and Pearce [35] pointed out that directors belong to multiple organizations, suppliers and customers, and have industry and governance experience. Therefore, they can bring knowledge, skills and capital that executives do not have to the organization, which is conducive to improving the quality of the decision-making of top managers [6]. Hillman and Dalziel [36] also pointed out that board capital is an indicator to measure an enterprise’s ability to obtain resources. It can provide consultation, suggestions and utilize some external tangible resources.

Pfeffer [37] pointed out that the composition of the board of directors is not random, but a reasonable response to the external environment of the enterprise. When the enterprise needs and depends on the external environment more, the proportion of external directors in the board will be larger. Since ERM emphasizes the integration of internal control and strategic objectives, the board of directors needs to identify the potential opportunities and threats facing the enterprise under the constantly changing environment, and make appropriate strategic decisions for the enterprise to achieve the enterprise’s objectives. On the other hand, independent directors are more sensitive to the external environment and have keen insights, which is conducive to the formulation of strategies and the effective allocation of resources. In addition, independent directors serve in multiple companies at the same time, and these companies may span multiple industries. Booth and Deli [38] pointed out that multi-serving directors have rich social networks. Therefore, independent directors have rich business experience and connections, which can provide operators with knowledge and resources they cannot get, and help enterprises to connect with competitive environment [21]. It can also help enterprises to increase their value [39]. Harris and Shimizu [40] also pointed out that having multiple appointed directors has a positive impact on a company’s performance. Moreover, the internal directors’ excessive familiarity with the enterprise’s operation mode can cause path dependence, while the addition of independent directors can break this path dependence and provide unique investment suggestions for the enterprise [21]. To sum up, independent directors can bring different experience and professional knowledge to the board of directors, so as to improve decision-making ability, improve decision-making efficiency and achieve performance objectives. Based on this, the second hypothesis is proposed:

 Hypothesis 2.

When the board of directors performs its advisory function, improving the level of board governance (the increase in the number of independent directors) helps to increase the upside risk of the enterprise.

3.3. The Mediating Role of Board Meetings

According to agency theory, the supervisory effect of board meetings will largely determine the effectiveness of corporate governance [41], and the number of board meetings can improve the performance of corporate governance and reflect the effectiveness of supervision [42]. For example, increasing the number of board meetings helps to reduce the chance of fraudulent activities [43] and helps to detect managerial incompetence in a timely manner [44]. At the same time, more board meetings also help to encourage directors to act more on behalf of shareholders’ wishes [45]. When performing its supervisory function, the main purpose of the board of directors is to ensure the effectiveness of internal control and ensure that risks are identified and controlled [6], so as to reduce unnecessary risks. The number of board meetings can not only reflect the effectiveness of supervision, but also help to restrain the opportunistic behavior and moral hazards of the management. Therefore, board governance can realize its supervisory function through board meetings, thus reducing corporate downside risks.

Jackling and Johl [31] pointed out that another aspect of resource dependence theory related to corporate governance is the intensity of board activities, which is usually measured by the frequency of board meetings. The frequency of board meetings can play a positive role in bridging the external environment and corporate governance, and can have a positive impact on a company’s performance. In addition, the number of board meetings can not only reflect the diligence of the board, but also provide more time for directors to communicate and formulate strategies [46]. Finally, the number of board meetings can improve the participation of the board of directors in the corporate strategy and ensure the scientific implementation of the strategy, so as to improve the business performance of the company [41]. When performing its consulting function, the board of directors mainly makes strategic plans and provides suggestions to senior executives [6], so as to ensure the effective implementation of strategies. Board meetings can not only provide a platform for directors to communicate, but also help directors to promote the correct implementation of strategic plans by senior executives. Therefore, board governance can fulfill its advisory function through board meetings, thus increasing the upside risk of the enterprise. To sum up, the third hypothesis is proposed:

 Hypothesis 3a

. When the board of directors performs its supervisory function, improving the level of board governance will reduce the downside risk of the enterprise by increasing the frequency of board meetings.

 Hypothesis 3b.

When the board of directors performs its advisory function, improving the level of board governance will increase the upside risk of the firm by increasing the frequency of board meetings.

3.4. The Moderating Effect of CEO Duality

The supervisory function of the board of directors is to control managers and protect the interests of shareholders from being infringed. The chairman of the board of directors is responsible for managing the board of directors and supervising and evaluating management activities, while the CEO is responsible for implementing the company’s policies and managing the company. Agency theory states that it is often impossible for principals to ensure that agents always act in the best interests of principals, so the independence of the board needs to be guaranteed. As the CEO enjoys the most power in the management team, he is regarded as the designer and planner of the long-term strategy of the enterprise [47]. The CEO makes key investment and financing decisions that affect the risk and value of the business [48]. Therefore, if the CEO serves as the chairman of the board of directors at the same time, the power of the CEO will be enhanced and the independence of the board of directors will be reduced. Finally, the supervision of the board of directors will be weakened, which will lead to the weak supervision of the board of directors over the managers [49] and will not help to restrain the selfish behaviors of the managers [41]. Studies have shown that the CEO, as the chairman of the board of directors, will use economic temptation to attract other directors, thereby weakening the board of directors’ supervision ability, thus increase the CEO’s management ability.

The advisory function of the board of directors is to provide suggestions to senior executives and approve strategic plans put forward by the senior management team. If the CEO, who has the most power in the management team, also serves as the chairman of the board, the board of directors will increase its dependence on him [16], thus weakening the advisory function of the directors. At the same time, CEO duality may weaken the independence of the board of directors, which is confirmed by [49]—that is, the CEO concurrently serving as the chairman of the board will cause the board of directors to hire fewer independent directors. Because independent directors can bring unique knowledge, skills and social relations to the enterprise, CEO duality prevent the board of directors having the capital to achieve the implementation of the enterprise’s strategic goals, and ultimately harm the enterprise’s performance. Some studies have shown that when the CEO serves as the chairman of the board of directors at the same time, the independence of the board of directors cannot be truly guaranteed, and the existence of independent directors may be just a symbol rather than playing an actual role [50]. To sum up, the fourth hypothesis is proposed:

 Hypothesis 4a.

When the board of directors is performing its supervisory function, CEO duality will inhibit the impact of board governance on corporate downside risk.

 Hypothesis 4b.

When the board of directors performs its advisory function, CEO duality will inhibit the impact of board governance on the upside risk of the firm.

4. Research Design

4.1. Sample Selection and Data Sources

ERM emphasizes the integration of enterprise strategy into risk management. This study on the relationship between the two responsibilities of board governance and the downside and upside risks of the enterprise responds to the need for ERM. After the global economic crisis in 2008, global enterprises paid more attention to the implementation of ERM, and promoted the improvement of international supervision efforts. Many countries issued normative documents for ERM. In China, there are only guidance documents issued by the State-owned Assets Supervision and Administration Commission (SASAC) on the Overall Risk Management of Central Enterprises in 2006.

Therefore, to understand whether the guidance document can guide firms to achieve EMR after the financial crisis, this paper selected the data of A-share market-listed non-financial companies in China from 2010 to 2019 for research. Due to the particularity of the financial industry, samples from the financial industry was excluded from the study, and because of the close connection between the real estate industry and the financial industry, the samples from the real estate industry were also excluded. After that, ST and ST* enterprises were excluded, and the enterprises with missing values were excluded. Finally, after 1% winsorization of the samples, 1407 sample enterprises and 10,184 sample observed values remained for examination. Among them, the sample data were mainly from the CSMAR database and RESSET database.

4.2. Main Variables and Models

4.2.1. Dependent Variable

In this paper, the dependent variable was corporate risk taking. Based on the practices of [51,52], firm downside risk and firm upside risk variables were selected as proxy variables.

(1) Measurement of downside risk. Downside risk refers to the potential loss of an enterprise, which was measured by means of two methods in this paper. The first method used value at risk (VaR) to measure downside risk, and the second method used CVaR (condition VaR) to measure downside risk, which was used as a robustness test.

VaR refers to the potential losses of enterprises in a specific period of time within a certain confidence interval, and is calculated by using the parameter method of VaR value. The VaR value parameter method assumes that the daily stock returns of an enterprise are normally distributed. Therefore, the annual VaR value of a single company could be obtained by calculating the mean (x) and standard deviation (σ) of the annual daily stock returns. Considering the assumption of a normal curve, this paper used the worst 5% of points on the curve to obtain VaR = 1.645σ at the 95% confidence level. The daily stock return was calculated as the logarithm of the ratio of the stock price of the day to the previous day. The calculation formula is as follows:

$${Ret}_{it}=\ln \frac{p_t}{p_{t-1}}$$

(1)

where Ret_it is the daily stock return of enterprise i in year t, P_t is the closing price of stock on day t, and p_t−1 is the closing price of stock on day t−1.

Like VaR, CVaR also represents the expected loss of an enterprise, but it takes into account the loss exceeding VaR [53] and has better performance when used to measure the downside risk [54]. According to [52], CVaR is the average loss that occurs under the worst scenario over a given time period. Thus, the annual CVaR value of a single company is less than the average annual daily stock return of VaR.

(2) Measurement of upside risk. Upside risk refers to the potential earnings of the enterprise in a specific period of time, which is opposite to the downside risk. It is in the right tail of the normal curve, measured by UP (upside risk) and CuP (condition upside risk). Using the quantile of the best return in a company’s history, as [50] did, UP equals the best return at the 95th percentile at the 95% confidence level, and CuP equals the average annual daily stock return above UP. Again, CuP was used for robustness testing.

4.2.2. Dependent Variable

The independent variable in this paper was the board governance. According to the practices of [55], the proportion of independent boards (Bind) was used as its proxy variable.

In addition to independent variables, this paper selected some control variables that have a significant impact on enterprise risk based on previous studies [8,29,48,56], including: board size (Bsize), as measured by the number of sitting directors on the board; company size (Fsize), measured as the natural logarithm of the total number of employees in a business; leverage, measured by total liabilities/total assets; current ratio (Liquidity), current assets/current liabilities; return on assets (ROA), measured by the net income/total assets; board ownership, expressed as the percentage of company shares owned by directors; market-to-book ratio (MTB), calculated as (book value of debt + market value of equity)/book value of assets; and capital expenditure intensity (Cap), expressed as capex/total assets. Finally, this paper controlled both the annual fixed effect and the industry fixed effect. See

Table 1. Variable definition and measurement.

Variable Type	Variable Name		Variable Symbol	Measurement
Dependent variable	Firm Risk (Frisk)	Downside risk	VaR	1.645 σ (95% confidence level based on normal distribution)
			CVaR	The average of the worst 5% of actual returns (over 95% VaR)
		Upside risk	UP	The best return in the 95th percentile of actual returns
			CuP	The average of the best 5% (over 95%) of actual returns
Independent variable	Proportion of independent directors		Bind	Number of independent directors/number of board members
Mediating variable	Board meeting		Bmeeting	Environmental management system certification score
Moderating variable	CEO duality		Cduily	Dummy variable, if the CEO is also the chairman of the board of directors, the value is 1, otherwise 0.
Control variable	Board size		Bsize	Number of board members
	Firm size		Fsize	The natural logarithm of the total number of employees in the firm
	Leverage ratio		Leverage	Total liabilities/total assets
	Return on assets		ROA	Net income/total assets
	Current ratio		Liquidity	Current assets/current liabilities
	Board shareholding ratio		Bownership	Percentage of shares held by directors
	Market-To-Book		MTB	(Book value of debt + market value of equity)/book value of Total assets
	Intensity of capital		Cap	Capital expenditure/total assets
	Year		Year	Year dummy variable
	Industry		Ind	Industry dummy variable

for the specific description of each variable.

4.2.3. Dependent Variable

In order to verify Hypothesis 1 and Hypothesis 2, the following regression equation is used:

Frisk_it = β₀ + β₁Bind_it + β₂Bsize_it + β₃Fsize_it + β₄Leverage_it + β₅ROA_it + β₆Liquidity_it +
β₇Bownership_it + β₈MTB_it + β₉Cap_it + ε_it

(2)

In order to verify Hypothesis 3, using the three-stage method, the regression equation is as follows:

Bmeeting_it = β₁Bind_it + β₂Bsize_it + β₃Fsize_it + β₄Leverage_it + β₅ROA_it + β₆Liquidity_it +
β₇Bownershi_it + β₈MTB_it + β₉Cap_it + ε_it

(3)

Frisk_it = β₀ + β1Bind_it + β₂Bsize_it + β₃Bmeeting_it + β₄Fsize_it + β₅Leverage_it + β₆ROA_it +
β₇Liquidity_it + β₈Bownership_it + β₉MTB_it + β₁₀Cap_it + ε_it

(4)

In order to verify Hypothesis 4, the regression equation is as follows:

Frisk_it = β₀ + β₁Bind_it + β₂Cduily_it + β₃Bind × Cduily_it + β₄Bsize_it + β₅Fsize_it + β₆Leverage_it +
β₇ROA_it + β₈Liquidity_it + β₉Bownership_it + β₁₀MTB_it + β₁₁Cap_it + ε_it

(5)

In addition, in order to control the heterogeneity between years and different industries, Equations (2)–(5) include both year and industry dummy variables. The pool ordinary least squares method (OLS) was used to verify the equation, and the standard errors are clustered by firm to control heteroscedasticity and intra-firm correlation in the residuals.

5. Analysis of Empirical Results

5.1. Descriptive Statistical Analysis

Table 2. Descriptive analysis.

Variable	N	Mean	SD	Min	Median	Max
VaR	10,184	0.047	0.015	0.0132	0.044	0.116
UR	10,184	0.046	0.019	0.013	0.041	0.096
Bind	10,184	0.374	0.057	0.182	0.333	0.8
Bmeeting	10,184	9.563	3.864	2	9	49
Cduily	10,184	0.757	0.429	0	1	1
Bsize	10,184	8.765	1.778	3	9	18
Fsize	10,184	8.401	0.972	1.386	8.653	9.449
MTB	10,184	2.698	1.924	0.889	2.068	14.872
Bownership	10,184	0.093	0.174	0	0.0001	0.892
Leverage	10,184	0.447	0.199	0.057	0.442	0.954
Liquidity	10,184	2.087	1.730	0.249	1.533	14.166
ROA	10,184	0.026	0.034	−0.146	0.019	0.159
Cap	10,184	0.061	0.078	−0.127	0.037	0.443

shows the results of descriptive statistical analysis of the samples. It can be seen from the table that the average value of VaR and UR is 4.7% and 4.56% at the 95% confidence level, which is significantly lower than the values reported by [52] (7.8% for VaR and 9.03% for UR). The value of downside risk VaR is close to the value (4.75%) reported by [57] for the data of Taiwan companies. This shows that Chinese companies as a whole have managed the downside risks relatively well, but at the same time suppressed the upside risks. The mean value of Bind, a proxy variable for board governance, is 37.4%, which is less than the requirements of the Sarbanes-Oxley Act in the United States for the board of directors of listed companies, but higher than the 33.3% value reported by [42]. There is also a big difference between the minimum value of 18.2% and the maximum value of 80%, indicating that Chinese companies are making efforts to improve governance, but there are big differences among companies. The average number of board meetings annually was 9.574, higher than the 8.546 reported by [58] for UK data. The mean of CEO duality (Cduily) was 75.9%. This is significantly higher than the 4.6% reported by [42].

As for the control variable, the mean value of board size (Bsize) is 8.794, close to the value of 8.8 reported by [50]. The mean value of firm size (Fsize) is 8.414, while the maximum value and minimum value are 1.386 and 9.449, respectively. This shows that there is a significant difference in size between the sample firms. The mean value of the market-to-book ratio (MTB) is 2.68 and the minimum, mean and maximum values are 0, 9.6% and 89.2%, respectively, which are significantly higher than those reported by [59] (0, 1.1% and 42.7). The reason for the inconsistent results is that the sample observations were selected in different years. The leverage and liquidity ratios of the company are 43.8 percent and 2.079 percent, respectively, worse than those reported by [52] (35 percent for leverage and 4.66 percent for liquidity). The average return on assets (ROA) is 2.7%, which is lower than the 4.78% reported by [58]. This indicates that the overall profit level of the sample enterprises is still low after the financial crisis. Moreover, based on the maximum value (15.9%) and the minimum value (−14.6%) of ROA, the performance of the sample enterprises varies greatly. Finally, the average capital expenditure intensity (Cap) of 6.5% is slightly higher than the 5.6% reported by the [48].

5.2. Correlation Analysis

Pearson correlation coefficients among variables are shown in

Table 3. Correlation analysis.

	VaR	UR	Bind	Bmeeting	Cduily	Bsize	Fsize	MTB	Bownership
VaR	1
UR	0.921 ***	1
Bind	−0.016 *	−0.009	1
Bmeeting	0.048 ***	0.051 ***	0.045 ***	1
Cduily	−0.061 ***	−0.049 ***	−0.116 ***	−0.012	1
Bsize	−0.093 ***	−0.080 ***	−0.441 ***	−0.012	0.172 ***	1
Fsize	−0.01	−0.009	0.001	0.013	0.026 ***	0.055 ***	1
MTB	0.367 ***	0.333 ***	0.014	−0.031 ***	−0.111 ***	−0.138 ***	−0.038 ***	1
Bownership	0.116 ***	0.093 ***	0.046 ***	0.009	−0.244 ***	−0.172 ***	−0.053 ***	0.223 ***	1
Leverage	−0.053 ***	−0.028 ***	0.007	0.188 ***	0.114 ***	0.150 ***	0.037 ***	−0.372 ***	−0.288 ***
Liquidity	0.080 ***	0.055 ***	0.009	−0.132 ***	−0.099 ***	−0.125 ***	−0.034 ***	0.342 ***	0.297 ***
ROA	−0.073 ***	−0.055 ***	−0.032 ***	−0.070 ***	−0.036 ***	0.012	0.014	0.173 ***	0.141 ***
Cap	−0.039 ***	−0.030 ***	−0.019 **	0.040 ***	−0.035 ***	0.070 ***	−0.010	−0.043 ***	0.057 ***
		Leverage		Liquidity		ROA		Cap
Leverage		1
Liquidity		−0.684 ***		1
ROA		−0.338 ***		0.238 ***		1
Cap		0.038 ***		−0.117 ***		0.009		1

*, ** and *** represent significance levels of 10%, 5% and 1%, respectively.

. As can be seen from Table 3, downside risk (VaR) and upside risk (UR) are significantly positively correlated at the 1% level, and the correlation coefficient reaches 0.921, confirming the view that high return is associated with high risk [60]. The proportion of independent directors (Bind) has a significant negative correlation with VaR at the level of 10%, while the relationship with UR is negative but not significant. However, this result does not control other variables, so it needs to be treated with caution. It can also be seen from Table 3 that the proportion of independent directors (Bind) is significantly positively correlated with the frequency of board meetings (Bmeeting), and significantly negatively correlated with CEO duality.

In addition, the correlation coefficient between the respective variables is less than 0.7, and the mean variance inflation factor (VIF) is 1.17 (see

Table 4. VIF for variables.

	VIF	1/VIF
Bind	1.34	0.744
Bmeeting	1.10	0.913
Cduily	1.10	0.906
Bsize	1.48	0.678
Fsize	2.06	0.486
MTB	1.69	0.591
Bownership	1.27	0.786
Leverage	2.64	0.379
Liquidity	2.06	0.485
ROA	1.25	0.799
Cap	1.14	0.876

), less than 3. This indicates that there is no multiple linear relationship between variables, and multiple linear regression analysis can be carried out.

5.3. Main Effect Regression Analysis

Table 5. Main effect regression results.

	(1)	(2)	(3)	(4)
	VaR	VaR	UR	UR
Bind	−0.008 ***	−0.018 ***	−0.007 **	−0.018 ***
	(−2.73)	(−6.81)	(−2.44)	(−6.13)
Bsize		−0.0006 ***		−0.0006 ***
		(−6.76)		(−5.5)
Fsize		0.00005		0.00007
		(0.44)		(0.45)
MTB		0.002 ***		0.002 ***
		(18.31)		(20.17)
Bownership		0.008 ***		0.007 ***
		(8.27)		(6.34)
Leverage		0.005 ***		0.009 ***
		(4.93)		(6.68)
Liquidity		0.0003 **		0.0002 *
		(2.42)		(1.75)
ROA		−0.028 ***		−0.017 ***
		(−6.77)		(−3.26)
Cap		−0.004 ***		−0.004 **
		(−2.80)		(−2.02)
_cons	0.052 ***	0.053 ***	0.051 ***	0.048 ***
	(37.42)	(26.25)	(29.36)	(19.08)
Year	YES	YES	YES	YES
Ind	YES	YES	YES	YES
N	10,184	10,184	10,184	10,184
R2	0.466	0.533	0.411	0.469

Note: The T value is in parentheses; *, ** and *** represent significance levels of 10%, 5% and 1%, respectively.

shows the pooled least square regression results of Formula (2). The independent director ratio (Bind) is the proxy variable of board governance, while downside risk (VaR) and upside risk (UR) are the proxy variables of enterprise risk. Columns (1) to (4) of Table 5 all contain the annual fixed effects and industry fixed effects, and the R-Square is greater than 0.4, indicating a good fit. As can be seen from Table 5, independent directors can not only significantly reduce the company’s downside risk, but also significantly reduce the company’s upside risk, which indicates that the sample enterprises only pay attention to internal control and do not incorporate strategy into the ERM, so they only pay attention to the supervisory function of the board of directors and ignore the advisory function. After joining the board of directors, an independent director is helpful to the improvement of the supervisory function of the board of directors, but its unique consulting advantage has not been brought into play.

Specifically, it can be seen from column (1) that the coefficient of the board governance level (Bind) was −0.008, which, although significant at the 1% level, was still relatively small; meanwhile, column (2) shows that after the addition of control variables, the coefficient increased to −0.018 and was still significant at the 1% level. The results support Hypothesis 1—that is, when the board of directors performs its supervisory function, improving the level of board governance helps to reduce the downside risk of the firm. This result is consistent with the results of [52,57]. The coefficients of Bind in columns (3) and (4) are significantly negative at the 5% and 1% levels, respectively, which is counter-intuitive but consistent with the results of [52], which reject Hypothesis 2. The reason for this result may be that the board of directors of the sample enterprises only paid attention to the supervisory function while ignoring the consulting function when performing their functions, thus failing to make full use of the rich social capital and unique insights of independent directors.

As for control variables, the coefficient of board size (Bsize) in columns (2) and (4), although only −0.0006, is significant at the 1% level, indicating again that the board of directors of the sample company has a good supervisory function while ignoring its consulting function. The estimated coefficients of leverage in column (2) and (4) are 0.005 and 0.009, respectively, and are significant at the 1% level. This result is consistent with [58]—that is, the higher the leverage ratio, the higher the operational risk. The estimated coefficient of return on assets (ROA) in column (2) is −0.028 and significant at the 1% level, which is consistent with [4]—that is, companies with a higher return on assets have less downside risk. The coefficient of firm size (Fsize) is positive, but not significant. The coefficient of the liquidity ratio is significantly positive, which indicates that excessive occupation of current assets will affect the capital turnover efficiency of the company, thus increasing the risk of the enterprise.

5.4. Mediating Effect Test

Table 6. Intermediary effect test.

	(1)	(2)	(3)	(4)	(5)	(6)
	VaR	Bmeeting	VaR	UR	Bmeeting	UR
Bind	−0.018 ***	2.325 *	−0.018 ***	−0.018 ***	2.325 *	−0.019 ***
	(−6.81)	(1.65)	(−6.9)	(−6.13)	(1.65)	(−6.26)
Bmeeting			0.0001 ***			0.0002 ***
			(3.06)			(4.04)
Bsize	−0.0006 ***	−0.016	−0.0006 ***	−0.0006 ***	−0.016	−0.0006 ***
	(−6.76)	(−0.25)	(−6.23)	(−5.5)	(−0.25)	(−5.38)
Fsize	0.00005	0.045	0.00005	0.00007	0.045	0.00006
	(0.44)	(0.77)	(0.39)	(0.45)	(0.77)	(0.4)
MTB	0.002 ***	0.030	0.002 ***	0.002 ***	0.030	0.002 ***
	(18.31)	(1.03)	(18.31)	(20.17)	(1.03)	(20.17)
Bownership	0.008 ***	1.295 ***	0.007 ***	0.007 ***	1.295 ***	0.007 ***
	(8.27)	(3.5)	(8.09)	(6.34)	(3.5)	(6.13)
Leverage	0.005 ***	4.119 ***	0.005 ***	0.009 ***	4.119 ***	0.008 ***
	(4.93)	(8.2)	(4.45)	(6.68)	(8.2)	(6.25)
Liquidity	0.0003 **	−0.016	0.0003 **	0.0002 *	−0.016	0.0003 *
	(2.42)	(−0.37)	(2.44)	(1.75)	(−0.37)	(1.78)
ROA	−0.028 ***	−0.407	−0.028 ***	−0.017 ***	−0.407	−0.017 ***
	(−6.77)	(−0.17)	(−6.74)	(−3.26)	(−0.17)	(−3.24)
Cap	−0.004 ***	2.232 ***	−0.005 ***	−0.004 **	2.232 ***	−0.005 **
	(−2.80)	(3.1)	(−2.99)	(−2.02)	(3.1)	(−2.24)
_cons	0.053 ***	5.748 ***	0.052 ***	0.048 ***	5.748 ***	0.047 ***
	(26.25)	(4.52)	(25.52)	(19.08)	(4.52)	(18.38)
Year	YES	YES	YES	YES	YES	YES
Ind	YES	YES	YES	YES	YES	YES
N	10,184	10,184	10,184	10,184	10,184	10,184
R2	0.533	0.069	0.534	0.470	0.069	0.471
Sobel-Z	2.53 **			3.70 **
Goodman-P	0.013			0.0002
Intermediary effect	−0.031			−0.096
Bootstrap (BC)	[0.0000577, 00006591]			[0.0000803, 0.0008328]

*, ** and *** represent significance levels of 10%, 5% and 1%, respectively.

shows the verification results of Equations (2)–(4). It can be seen from columns (2) and (4) in the table that the Bind coefficient is significantly positive at the 10% level, indicating that when the board of directors performs its functions, the increase in the number of independent directors will increase the number of board meetings. This result is consistent with [61]. However, from the positive coefficient of Bmeeting in column (3) and (6), the increase in the number of board meetings did not reduce the company’s downside risk, but increased the company’s upside risk. Moreover, although the coefficients of Bind and Bmeeting are both significant, their symbols are inconsistent, and the mediating effect is also negative. Therefore, this conclusion does not support Hypotheses 2a and 2b. The reason for this result may be that the board of directors of the sample companies paid more attention to its supervisory function, but instead of identifying risks and restraining the incompetent behaviors of the management through meetings, they paid more attention to communicating and formulating strategies through meetings. This result indicates that the sample firms do not integrate internal controls and strategies to implement ERM.

5.5. Moderating Effect Test

Table 7. Moderation effect test.

	(1)	(2)
	VaR	UR
Bind	−0.024 ***	−0.027 ***
	(−5.58)	(−5.52)
Cduily	−0.004 **	−0.005 **
	(−2.22)	(−2.23)
Bind*Cduily	0.009 *	0.011**
	(1.81)	(2.03)
Bsize	−0.006 ***	−0.006 ***
	(−6.09)	(−5.35)
Fsize	0.00006	0.00007
	(0.45)	(0.46)
MTB	0.002 ***	0.002 ***
	(18.28)	(20.14)
Bownership	0.007 ***	0.007 ***
	(7.81)	(5.97)
Leverage	0.005 ***	0.009 ***
	(4.96)	(6.88)
Liquidity	0.0003 **	0.0003 *
	(2.4)	(1.73)
ROA	−0.028 ***	−0.017 ***
	(−6.77)	(−3.24)
Cap	−0.004 ***	−0.004 ***
	(−2.91)	(−2.09)
_cons	0.056 ***	0.051 ***
	(22.36)	(17.27)
YEAR	YES	YES
Ind	YES	YES
N	10,184	10,184
R2	0.534	0.470

*, ** and *** represent significance levels of 10%, 5% and 1%, respectively.

shows the pooled least square regression results of Formula (5). As can be seen from the table, the coefficient of CEO duality and independent director interaction (Bind × Cduily) is significantly positive at the 5% level, which confirms that CEO duality mentioned in the previous theory can affect the relationship between board governance and enterprise risk. Specifically, the coefficients of CEO duality (Cduily) in column (1) and (2) are −0.004 and −0.005, respectively. Although the coefficients are small, they are both significant at the 5% level, indicating that the CEO duality will reduce the upside and downside risks of the company, which is accordance with the assumption that managers are risk averse in agency theory. In column (1), the coefficient of Bind*Cduily is 0.009, indicating that CEO duality will reduce the supervisory function of independent directors, thus weakening the ability of independent directors to reduce downside risks. This conclusion supports Hypothesis 3a—that is, when the board of directors performs its supervisory function, CEO duality will inhibit the impact of board governance on corporate downside risk. In column (2), the coefficient of Bind*Cduily is 0.011 and significant at the 5% level, indicating that when the CEO serves as the chairman of the board, they will become very confident due to the increase in power [62]. Thus, they could ignore the advisory function of the independent directors and affect the independence of the independent directors, which weakens the board’s supervisory function. So, Hypothesis 3b is not supported.

5.6. RobustnessTest

5.6.1. Endogeneity Test

Although the main effect regression results show that the increase in the number of independent directors helps to reduce the company’s downside risk when the board of directors performs its supervisory function, this result may have the endogenous problem of reverse causality—that is, the increase in the company’s downside risk will lead the board to appoint more independent directors. Therefore, in order to solve this endogeneity problem, on the basis of main effect regression, the next period of data on enterprise risk variables are used to conduct regression again. The regression results can be seen from

Table 8. Robustness test.

Endogeneity Test			Changing the Measurement of Enterprise Risk
	(1)	(2)	(3)	(4)	(5)
	VaRt+1	URt+1	SD	CVaR	CuR
Bind	−0.015 ***	−0.014 ***	−0.011 ***	−0.022 ***	−0.025 ***
	(−5.86)	(−4.68)	(−6.81)	(−6.12)	(−6.5)
Bsize	−0.0006 ***	−0.0007 ***	−0.0004 ***	−0.0008 ***	−0.0008 ***
	(−6.79)	(−6.04)	(−6.34)	(−6.46)	(−5.55)
Fsize	0.000	0.000	0.00003	0.0000	0.0000
	(0.06)	(0.05)	(0.44)	(0.04)	(0.02)
MTB	0.001 ***	0.001 ***	0.001 ***	0.002 ***	0.003 ***
	(13.12)	(11.37)	(18.31)	(16.48)	(16.60)
Bownership	0.004 ***	0.004 ***	0.005 ***	0.010 ***	0.010 ***
	(4.81)	(3.44)	(8.27)	(8.73)	(6.81)
Leverage	0.003 ***	0.005 ***	0.003 ***	0.005 ***	0.009 ***
	(2.57)	(3.39)	(4.39)	(3.93)	(5.76)
Liquidity	0.0001	0.0001	0.0002 **	0.0004 ***	0.0006 ***
	(1.44)	(0.76)	(2.42)	(2.64)	(2.89)
ROA	−0.055 ***	−0.055 ***	−0.017 ***	−0.047 ***	−0.024 ***
	(−14.84)	(−11.13)	(−6.77)	(−8.79)	(−3.60)
Cap	−0.003 **	−0.002	−0.003 ***	−0.004 *	−0.007 ***
	(−1.98)	(−0.97)	(−2.8)	(−1.93)	(−2.78)
_cons	0.050 ***	0.046	0.032 ***	0.075 ***	0.071 ***
	(25.44)	(17.84)	(26.25)	(27.91)	(22.5)
Year	YES	YES	YES	YES	YES
Ind	YES	YES	YES	YES	YES
N	8456	8456	10,184	10,184	10,184
R2	0.627	0.536	0.533	0.496	0.289

*, ** and *** represent significance levels of 10%, 5% and 1%, respectively.

in column (1) and (2). This result also supports Hypothesis 1 but not Hypothesis 2. Therefore, this result is still robust after considering endogeneity. Specifically, the coefficient of Bind in column (1) and (2) is significantly negative at the level of 1%, indicating once again that the board pays more attention to its regulatory responsibilities and improves its governance level by increasing the proportion of independent directors, which only reduces the downside risk of the enterprise while restraining the upside risk of the enterprise.

5.6.2. Changing the Measurement of Enterprise Risk

Although VaR value can prevent the enterprise’s downside risk, it cannot prevent a small part of the loss exceeding the VaR value. Therefore, the conditional VaR value (CVaR) as the proxy variable of an enterprise’s downside risk has better performance. Similarly, the CuR is used as the proxy variable for the corporate upside risk. At the same time, in order to further test whether the board of directors performs its supervisory function and reduces the firm’s total risk, the standard deviation (SD) of individual stock return is used as the proxy variable for the total risk. Then, the regression analysis is carried out again by using Equation (2), and the annual fixed effect and industry fixed effect are controlled. The standard errors are clustered by firm to control heteroscedasticity and intra-firm correlation in the residuals. The regression results can be seen from Table 8 in column (3) to (5). These results show that the increase in the number of independent directors will reduce the overall risk, downside risk and upside risk of enterprises. Hypothesis 1 is again supported.

6. Conclusions and Discussion

After the global financial crisis, enterprises now pay more attention to the implementation of ERM, which emphasizes the integration of internal control and strategic objectives, and the board of directors, as an important mechanism of corporate governance, plays a supervisory and advisory role in the ERM. In order to understand whether Chinese enterprises have implemented ERM according to relevant domestic guidance documents, this paper selects enterprise downside risk and enterprise upside risk as proxy variables of enterprise risk, and the proportion of independent directors as proxy variables of board governance, and uses panel data of China listed companies from 2010 to 2019. Based on agency theory and resource dependence theory, this paper empirically studies the effects of the supervisory function and advisory function of the board of directors on downward risk and upward risk, respectively.

In Table 4, we can see that the coefficients of Bind in columns (3) and (4) are negative, which indicates that the increase in board governance not only reduces the downside risk but also the upside risk. This conclusion is consistent with the findings of [52]. Therefore, Hypothesis 1 is supported in this paper, while Hypothesis 2 is not. The conclusion shows that only the supervisory function is paid sufficient attention and plays a role in the two functions of the board of directors of the sample enterprises. Therefore, when the board of directors increases its governance level by appointing independent directors, it not only reduces the downside risk but also restrains the upside risk of the enterprise. In addition, sample enterprises do not pay much attention to the advisory function of the board of directors, so they do not make full use of the social capital and keen insights of independent directors to help them develop effective strategies to prevent abnormal returns.

In Table 6, we can see that the coefficients of Bind and Bmeeting in columns (3) and (6) are opposite to each other, which indicates that the analysis results of the mediating effects do not support Hypotheses 3a and 3b. The reasons for this are as follows: the board of directors of the sample enterprise performs its supervisory duties not by identifying risks and suppressing the incompetent behaviors of the management through meetings, but also by setting up a risk management committee to help it perform its supervisory duties and improve its ability to monitor risks. This was confirmed by Agarwal et al. [63]. As can be seen from the results in Table 6, the increase in the frequency of board meetings will increase both the downside and upside risks of the enterprise. This result indicates that the sample enterprises may pay more attention to the use of meetings to communicate and formulate strategies, but fail to integrate strategies and internal controls to implement comprehensive risk management.

In Table 6, we can see that the coefficient of Bind*Cduily is significant and opposite to Bind’s coefficient, which indicates that the analysis on the moderating effect supports Hypothesis 4a—that is, when the board of directors performs its supervisory function, CEO duality will inhibit the impact of board governance on the corporate downside risk. Hypothesis 4b is not supported. First of all, the sample enterprises did not pay attention to the advisory function of the board of directors; secondly, the increase in CEO power will cause the CEO to ignore the opinions of independent directors and affect the independence of independent directors. Finally, it is worth noting that the Cduily coefficient is significantly negative—that is, the CEO duality will reduce both the downside risk and the upside risk of the enterprise. This conclusion is consistent with the assumption of managers’ risk aversion in agency theory. Thus, boards performing their advisory functions may be more susceptible to CEO duality than those performing their supervisory functions.

6.1. Implications for Theory

Firstly, based on agency theory and resource dependence theory, this paper expounds the impact of board governance on enterprise risk from the dual perspectives of consultation and supervision, and enriches the research on the impact of board governance. The existing research mainly focuses on the impact of supervisory function on risk management based on agency theory [22,23,41]. Thus, many inconsistent conclusions while considering the impact of board governance on firm risk were obtained. Turel and Bart [6] pointed out that boards have two major functions, namely supervision and consultation. However, few scholars have considered the impact of boards on risk management by combining their supervisory and advisory functions. Based on agency theory and resource dependence theory, Zheng [21] examined the impact of board size on enterprise risk-taking from the perspective of boards’ advisory and supervisory functions, but ignored the impact of different functions on different risks. This paper emphasizes that both supervisory and advisory functions should be considered when considering the governance mechanism of board of directors. Different functions have different roles in ERM simultaneously.

Secondly, in this paper, the application of risk management in board governance is discussed by integrating the upside and downside risk of enterprises. Previous studies still focus on total risk or idiosyncratic risk in the selection of proxy variables for firm risk [8,9,17]. However, ERM emphasizes the combination of strategy and internal control, so it is necessary to distinguish the upside risk and the downside risk in the selection of proxy variables for enterprise risk, so as to verify the effective implementation of ERM. Ali [48] used the upside risk and the downside risk as proxy variables of enterprise risk, and examined the impact of board governance on the upside risk and the downside risk, respectively, but only considered the supervisory function of the board, ignoring the advisory function. This paper emphasizes that the two functions of the board have different effects on the upside risk and the downside risk, respectively.

Thirdly, this paper also explores the internal mechanism of boards’ influence on enterprise risk. Although many scholars have studied the impact of board meetings on enterprise risk, many were based on the perspective of the board’s supervisory function [43,44,45]. Based on the theory of resource dependence, Ning [47] discussed the influence of board advisory function on corporate performance, but did not consider the firm risk. Therefore, the existing literature does not combine the two functions of the board to consider the impact of board meetings on enterprise risk. This paper explores whether boards perform their supervisory and advisory duties through board meetings and finds that board meetings, as an important mechanism of board governance, do not play a real role. However, we also find that boards are more likely to use meetings to communicate and strategize to capture upside risks than to identify and control downside risks.

Finally, boundary conditions of board governance that affect firm risk are explored in this paper. Although many scholars have studied the impact of CEO duality on independence of the board, many were based on agency theory and did not combine the two functions of the board [47,48,49]. Zheng [21] studied the impact of CEO duality on corporate risk based on the dual perspective of the two functions of the board, but did not consider both the upside risk and the downside risk. This paper explores whether boards are influenced by CEO duality in performing their duties and finds that boards are negatively affected by CEO duality in performing their oversight functions.

6.2. Practical Implications

First, enterprises should fully realize the importance of the two functions of the board of directors. In order to better implement ERM, enterprises should give full play to their supervisory function to reduce downside risks, while taking into account their advisory function to increase upside risks. The board of directors should take into account its two functions when performing its governance function. At the same time, board of directors can pay attention to balancing the two functions based on the characteristics of their industry.

Second, enterprises should regard board meetings as an important mechanism of board governance and give full play to its role. The board of directors should make full use of board meetings to perform its two main functions. The board should not only fully discuss the formulation of strategies in the meeting while performing its advisory function, but also to identify and control some agency problems and unnecessary risks while performing its oversight functions.

Finally, enterprises should treat CEO duality rationally. According to agency theory, managers are risk averse, CEO duality may impede the performance of board functions, whether supervisory or advisory. Thus, companies with a CEO who also serves as the chairman of the board need to create incentives to encourage directors to perform their respective duties.

6.3. Limitations and Suggestions for Future Research

First, in terms of sample selection, although the financial industry and the real estate industry are excluded from the sample, the characteristics of the remaining industries may affect the role of the two functions of the board of directors. For example, enterprises with intense industry competition or rapid product updates may require the board of directors to perform its advisory function more, while enterprises with less intense industry competition may prefer the board of directors to perform its supervisory function. Therefore, future studies can study the impact of the two functions of the board of directors on corporate risk taking in different industries.

Second, although this paper verifies that board meetings do not mediate the impact of board governance on corporate downside risks, and proposes that the board of directors is more willing to use meetings to communicate and formulate strategies, it does not conduct further tests. Future research could further validate this conclusion by examining board meeting minutes and examining whether the board relies on its own secondary committee, the Risk Management Committee, to perform the supervisory function.

Finally, the governance level of the board of directors is also affected by other secondary committees set up by the board of directors, such as the audit committee. Taking the proportion of independent directors in the board of directors as the proxy variable in this paper cannot fully capture the governance level of the board of directors. Therefore, future studies may consider using comprehensive governance index as the proxy variable of governance level to obtain more accurate results.