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Purpose

This paper aims to investigate the influence of clan culture on gender diversity within the top management teams of Chinese firms.

Design/methodology/approach

This paper analyzes data from Chinese companies listed on the A-share markets from 2003 to 2022.

Findings

We find that stronger clan culture is associated with lower female representation in leadership roles, including positions on the board of directors, supervisory boards and among senior executives. Cross-sectional tests reveal that this negative relationship is more pronounced in state-owned enterprises compared to non-state-owned enterprises. Additionally, we identify mitigating factors: regions with higher economic development and greater foreign cultural influence are less likely to hinder female advancement into top management. Lastly, our analysis of the mechanisms by which clan culture perpetuates gender inequality perceptions underscores its harmful effects on both the demand for and supply of female labor in executive roles.

Originality/value

In recent years, the topic of gender diversity within corporate boardrooms, executive ranks and the workforce at large has garnered considerable attention. Despite extensive research on the determinants of gender diversity and its impact on firm outcomes, the influence of informal institutions, such as culture, on gender diversity within organizations remains an understudied area. This gap is especially pronounced in the context of China, where cultural norms and values deeply influence gender roles and dynamics. Our paper aims to enrich the discourse on gender diversity by exploring the impact of clan culture, a fundamental element of Chinese culture, on the gender diversity of top management teams in Chinese firms.

In recent years, the topic of gender diversity within firm boardrooms, executive ranks, and the workforce at large has garnered considerable attention from scholars, policymakers, and the business community (Labelle, Francoeur, & Lakhal, 2015). This interest is not merely a reflection of societal progress towards gender equality but is underscored by a robust body of literature that attests to the tangible benefits of gender diversity. Studies have consistently shown that gender-diverse boards and management teams contribute positively to firm governance, financial performance, innovation and social responsibility (Adams & Ferreira, 2009; Ahern & Dittmar, 2012; Beji, Yousfi, Loukil, & Omri, 2021; Díaz-García, González-Moreno, & Sáez-Martínez, 2013; Griffin, Li, & Xu, 2021; Joecks, Pull, & Vetter, 2013; Matsa & Miller, 2013; Post & Byron, 2015).

Despite extensive research on the determinants of gender diversity and its impact on firm outcomes, the influence of informal institutions, such as culture, on gender diversity within organizations remains an understudied area. This gap is especially pronounced in the context of China, where cultural norms and values deeply influence gender roles and dynamics (Du, 2016). Our paper aims to enrich the discourse on gender diversity by exploring the impact of clan culture, a fundamental element of Chinese culture, on the gender diversity of top management teams in Chinese firms.

Clan culture, a concept deeply rooted in Chinese history, emphasizes kinship loyalty, familial ties, and collective welfare over individual interests. This cultural framework has traditionally played a significant role in shaping business practices and organizational dynamics in China (Hofstede, 1980; Redding, 2002). Research on clan culture in China (Huang, Ma, & Wang, 2022; Pan, Ning, Ji, & Dai, 2019a, Pan, Weng, Ji, & Dai, 2019b; Zhang, 2020) suggests that it profoundly influences firm governance, financing decisions, and risk taking. While it can promote a sense of belonging and loyalty among employees, it may also reinforce traditional gender roles and hierarchies, especially in family-owned or small- and medium-sized firms that form a significant portion of the Chinese economy.

On one hand, clan culture may lead to lower female representation in top management teams for several reasons. Firstly, the patriarchal nature of traditional clan culture often places men in positions of authority, perpetuating male dominance in leadership roles. Secondly, clan-based networks, which are crucial for career advancement in many Chinese firms, tend to favor men, as these networks are built on long-standing social connections that women are less likely to access due to historical and societal gender role expectations. The emphasis on familial networks and ties in business practices could inadvertently perpetuate gender biases, limiting opportunities for women to ascend to top management positions (Leung & Chan, 2003; Tsui & Farh, 1997). Moreover, the emphasis on familial responsibilities can disproportionately affect women, who are often expected to prioritize family duties over career advancement. This expectation can hinder women's participation in high-commitment leadership roles, limiting their representation in top management teams (Cooke, 2005).

On the other hand, clan culture’s internal cohesion and collective orientation can, under certain conditions, support women’s advancement, especially when female leadership enhances the clan's reputation and serves its broader interests. Thus, clan culture exhibits a dual character: it constrains women through patriarchal traditions, yet it can also facilitate their rise to leadership positions when aligned with collective interests. Overall, the impact of clan culture on female leadership remains uncertain.

Using Chinese firms listed on the A-share market from 2003 to 2022 as research samples, we first explore the impact of clan culture on female representation in top management teams. In line with previous studies (Greif & Tabellini, 2017; Pan et al., 2019a, 2019b; Zhang, 2020), we use city-level genealogy density to assess the influence of clan culture. Specifically, we calculate the number of genealogies per 10,000 residents in the city where the focal firm is incorporated. Our findings indicate that stronger clan culture is associated with fewer female executives within a firm. The effect is economically significant: a one standard deviation increase in our clan culture measure corresponds to a 1.58% decrease in the female executive ratio. Given the mean female executive ratio of 18.6% in our main sample, this represents an 8.49% reduction relative to the sample mean. Our results are robust to several alternative approaches: (1) using different measures of clan culture (e.g. the proportion of the population with the three most common surnames in each Chinese city); (2) applying alternative definitions of top management teams; (3) employing an instrumental variable estimation; (4) considering the influence of other cultural factors (e.g. social trust); (5) incorporating province fixed effects; and (6) clustering standard errors at the city level.

We next document that the negative association between clan culture and female executive representation is more pronounced in state-owned firms (SOEs) compared to non-state-owned firms (non-SOEs). These findings support our hypothesis that rigid hierarchy and male-dominated teams in SOEs exacerbate the negative impact of clan culture on female executive representation. Additionally, we show that this negative relationship is less prominent among firms in regions with higher levels of economic development. This is consistent with our conjecture that better economic conditions provide more opportunities for women, thereby mitigating the negative effects of clan culture. Finally, we find that the negative association between clan culture and female executive representation is weakened for firms located in areas with greater foreign cultural influence. This indicates that cross-cultural influences and inclusive practices from Western contexts can mitigate the adverse effects of traditional cultural norms.

In additional analyses, we examine the transmission mechanisms, revealing that clan culture exacerbates gender inequality notions from both the demand side (firms) and the supply side (women), thereby negatively affecting the recruitment and promotion of female executives. We also document that clan culture also exacerbates the wage gap between female and male executives.

This paper makes several noteworthy contributions to the existing literature and practical understanding of gender diversity in firm leadership, specifically within the context of Chinese firms.

Firstly, this study significantly enriches the existing literature on the determinants of gender diversity within organizations by shedding light on the influence of an informal institution, namely clan culture, on the composition of firm leadership. While prior research has extensively explored the impact of formal institutional mechanisms and organizational policies on gender diversity (Adams & Funk, 2012; Axelsdóttir, Einarsdóttir, & Rafnsdóttir, 2023; Brandth & Bjørkhaug, 2015; Hillman, Shropshire, & Cannella, 2007; Terjesen et al., 2009), the role of informal cultural practices, particularly within the unique socio-economic context of China, has remained relatively underexamined. Two notable studies have begun to explore how cultural factors affect gender diversity in Chinese firms. Du (2016) examines the impact of Confucianism on board gender diversity, finding that Confucian values may hinder the inclusion of women in firm leadership roles. Similarly, Qiu et al. (2023) investigated the role of social trust in female board representation, highlighting how cultural norms surrounding trust can influence gender dynamics at the top levels of Chinese firms. Our research extends this line of inquiry by focusing on a distinct cultural aspect-clan culture. By doing so, we underscore the profound impact that deeply ingrained cultural norms can have on shaping gender dynamics within top management teams, providing new insights into the cultural determinants of female representation in firm leadership.

Secondly, by analyzing the impact of clan culture on gender diversity, this paper contributes to a deeper understanding of clan culture itself. Previous studies have predominantly focused on the implications of clan culture for firm governance, business investing and financing, and risk taking within Chinese firms (Huang et al., 2022; Pan et al., 2019a, 2019b; Zhang, 2020). This paper, however, highlights a previously underexplored dimension of clan culture - its influence on gender diversity. In doing so, it not only broadens the scope of research on clan culture but also illustrates the multifaceted ways in which cultural norms can intersect with and influence firm governance and leadership composition.

Finally, the findings of this study have important practical implications for both policymakers and firm leaders, particularly in the context of global efforts to enhance gender diversity in firm boardrooms. By identifying the suppressive effect of clan culture on female representation in top management positions, this research underscores the necessity of adopting culturally sensitive approaches to promote gender diversity. Recognizing the specific cultural barriers faced by women in different socio-economic and cultural settings is crucial for designing effective interventions. For firms operating in China and similar contexts, this may involve reevaluating recruitment and promotion practices, fostering inclusive networks that extend beyond traditional clan-based connections, and implementing policies that mitigate the adverse effects of cultural norms on gender diversity.

The paper is organized as follows: In Section 2, we review the related literature and present our hypothesis development. In Section 3, we describe our research design, discuss our sample selection procedure, and provide descriptive statistics. Section 4 presents our main empirical results. Section 5 offers additional analyses, and Section 6 concludes.

Clan culture in Chinese society: Clan culture, deeply embedded in the fabric of Chinese society, traces its origins to the Western Zhou Dynasty in the 11th century BC, evolving significantly over millennia. Clans, or tsung tsu, have played a pivotal role as epitomizing social structures, initially reserved for noble families and later expanding to include broader societal groups by the Song Dynasty (960–1279 CE). This expansion was largely influenced by the shift to an imperial examination system and the rise of a gentry class, alongside the philosophical underpinnings provided by Neo-Confucianism, which advocated for the formation and structuring of clan organizations among ordinary people.

Throughout history, clans have served not only as kinship networks but also as critical providers of public goods and social services, functioning at times as substitutes for state mechanisms (Zhang, 2020). They organized around common ancestors, holding properties to support members in need and performing ancestral worship, which was central to their activities.

As shown in Figure 1, the geographical distribution of clans varied across China, with a stronger presence in the southeast and a weaker one in the north and west, reflecting regional variations in clan institutions’ strength and practices. Despite varying sizes and practices, clans shared key characteristics such as living in close-knit communities, owning common properties, and organizing group activities like ancestor worship. The compilation of genealogies was essential, serving to reinforce ties among clan members and promote values of solidarity and loyalty.

Figure 1
A choropleth map shows regions of China shaded by numeric ranges using a multi-color legend from light blue to red.The map shows China divided into multiple administrative regions, each filled with a color corresponding to numeric ranges indicated in the legend on the upper right. The legend is described color wise as follows: the value “0” is represented by light blue, the range “0 to 0.02” is represented by purplish blue, the range “0.02 to 0.04” is represented by pink, the range “0.04 to 0.06” is represented by grey, the range “0.06 to 0.10” is represented by slightly darker blue, the range “0.10 to 0.20” is represented by green, the range “0.20 to 0.30” is represented by orange, the range “0.30 to 0.70” is represented by yellow, the range “0.70 to 2” is represented by purple, and values greater than “2” are represented by red. Large portions of western and northern China appear in light blue and purplish blue, indicating lower values, central regions display mixed colors, including pink, grey, and slightly darker blue, and eastern and southeastern regions contain clusters of green, orange, yellow, purple, and red, indicating higher values. Clear boundary lines separate each region, and southern island areas follow the same color-based classification.

The geographical distribution of clan culture across China. Note: Clan culture is measured by the number of genealogies per 10,000 residents in each city. The map illustrates the geographic distribution of clan culture across China, with a stronger presence in the southeast and weaker presence in the north and west. The color scale in the upper right corner indicates the density of genealogies

Figure 1
A choropleth map shows regions of China shaded by numeric ranges using a multi-color legend from light blue to red.The map shows China divided into multiple administrative regions, each filled with a color corresponding to numeric ranges indicated in the legend on the upper right. The legend is described color wise as follows: the value “0” is represented by light blue, the range “0 to 0.02” is represented by purplish blue, the range “0.02 to 0.04” is represented by pink, the range “0.04 to 0.06” is represented by grey, the range “0.06 to 0.10” is represented by slightly darker blue, the range “0.10 to 0.20” is represented by green, the range “0.20 to 0.30” is represented by orange, the range “0.30 to 0.70” is represented by yellow, the range “0.70 to 2” is represented by purple, and values greater than “2” are represented by red. Large portions of western and northern China appear in light blue and purplish blue, indicating lower values, central regions display mixed colors, including pink, grey, and slightly darker blue, and eastern and southeastern regions contain clusters of green, orange, yellow, purple, and red, indicating higher values. Clear boundary lines separate each region, and southern island areas follow the same color-based classification.

The geographical distribution of clan culture across China. Note: Clan culture is measured by the number of genealogies per 10,000 residents in each city. The map illustrates the geographic distribution of clan culture across China, with a stronger presence in the southeast and weaker presence in the north and west. The color scale in the upper right corner indicates the density of genealogies

Close modal

Although formal clan organizations lost legal status and were largely abolished after the Chinese Communist Party's rise to power in 1949, especially during the Cultural Revolution, the cultural norms, beliefs, and values associated with clans persisted. The economic reforms initiated in 1978 saw a resurgence of clan-related cultural activities, highlighting the enduring influence of clan culture in modern China.

Impact of cultural norms on gender equality in China: China's journey towards gender equality has been complex and multifaceted, evolving significantly over the centuries. From the patriarchal norms of Imperial China to the gender equality efforts initiated in the Communist era, the country has witnessed substantial shifts in the status of women (Andors, 1983). Despite these efforts, the remnants of traditional gender roles persist, influencing the professional landscape. Recent studies, such as those by Sun and Li (2017), indicate that while there has been progress, disparities in leadership representation remain a concern.

Existing explanations of gender disparities in China tend to highlight Confucian ethics, yet other cultural forces, particularly clan culture, also exert a substantial influence. Confucianism is primarily a philosophical and moral system that shapes behavior through values, socialization, and family ethics. Clan culture, in contrast, is rooted in kinship-based organization and is supported by concrete institutions and practices, including clan rules, ancestral halls, lineage councils, and collective rituals (Cohen, 1990; Freedman, 1966). Prior work in sociology and anthropology suggests that clan institutions historically functioned as semi-formal governance structures in rural China, with practical mechanisms for monitoring behavior and enforcing norms—often more directly than broad ideological value systems (Huang, 1985; Freedman, 1966). In this sense, clan culture operates as an institutionalized social system with features distinct from Confucian values alone.

While Confucian culture is often linked to gender inequality through ethical prescriptions (e.g. the Three Obediences and Four Virtues) (Du, 2016), clan culture can reinforce gender hierarchy through material arrangements (e.g. inheritance practices) and social rituals (e.g. women's exclusion from certain forms of ancestral worship) (Watson, 1985; Wolf, 1972). Greif and Tabellini (2017) similarly describe clan-based societies as characterized by strong patriarchy rooted in lineage organization and property transmission rules. By translating ideological expectations into enforceable community practices, clan culture may exert a more tangible and durable influence on gendered power relations.

Consistent with this view, North (1990) distinguishes between formal and informal institutions and argues that informal institutions—embedded in repeated social interactions—often persist and shape behavior more powerfully than abstract ideological norms alone. Clan culture fits this category: its rules and expectations are reinforced through lineage networks and community-based sanctions rather than solely through moral persuasion.

On the one hand, clan culture may lead to lower female representation in top management teams for several reasons.

Firstly, the patriarchal nature of traditional clan culture often places men in positions of authority, perpetuating male dominance in leadership roles. According to social identity theory (Hogg & Abrams, 1988), individuals with similar attributes tend to sympathize with each other, forming stable group preferences. Gender, being a primary marker for dividing group attributes, results in male-dominated executive teams often preferring to promote individuals of the same gender. Consequently, the entry of women into executive positions and their increasing influence in firms are perceived as a challenge to male dominance. This perception makes it difficult for female executive candidates to gain unanimous acceptance from the executive team, thereby suppressing women's ascension to high positions and resulting in fewer female executives in firms.

Secondly, clan-based networks, crucial for career advancement in many Chinese firms, often favor men (Leung & Chan, 2003; Tsui & Farh, 1997). These networks are built on long-standing social connections that women are historically and socially less likely to access due to prevailing gender role expectations. The reliance on familial networks and ties in business practices can inadvertently perpetuate gender biases. This bias limits opportunities for women to ascend to top management positions by reinforcing a gendered division of labor and networking opportunities. Women, often perceived as primarily responsible for domestic roles, find it challenging to penetrate these influential networks, which are instrumental in career advancement within the firm hierarchy. The exclusion from these networks not only hampers women's career progression but also reinforces the gender disparity in leadership positions.

Moreover, the focus on collective welfare and family responsibilities can disproportionately impact women, who are often expected to prioritize family duties over career advancement. In regions where clan culture is strong, men are encouraged to engage in external work, while women take on the primary responsibility for family care. In such areas, women are more likely to see themselves in family roles like wife, mother, and daughter, which can reduce their professional ambitions and their desire to pursue executive roles. As Zhang and Wang (2020) note, women in regions with pronounced clan culture often prioritize family care, leading to less time and investment in their careers. This reduced focus on career development makes it difficult for women to accumulate the human capital needed to compete for high-level executive positions, especially in today’s fast-paced and competitive workplace. Clan culture reinforces traditional gender roles, causing women to invest more in family and less in their careers, ultimately limiting their opportunities for advancement (Du, 2016; Qiu et al., 2023).

On the other hand, clan culture is not only a set of values but also a cohesive, organization-like social structure oriented toward lineage continuity, collective welfare, and group reputation. Precisely because of this collectivist and reputation-sensitive orientation, clan norms can be pragmatically flexible in specific situations: when elevating a capable woman is viewed as advancing the family/clan's longer-term interests—such as succession, continuity, modernization, or legitimacy—women may be able to gain authority by working within existing structures (i.e. “patriarchal bargains”) (Kandiyoti, 1988). Consistent with this logic, evidence from Chinese family firms shows that daughters can become successor-leaders through negotiated processes when their leadership is instrumentally valuable to the controlling family (Xian et al., 2021). In addition, we note (as anecdotal illustrations) that some lineage/hometown associations have appointed female leaders in recent years, suggesting that clan-based organizations can adjust leadership norms when collective interests are salient [1].

Because these restrictive and adaptive mechanisms can operate in opposite directions, we do not impose a directional prediction ex ante. Instead, we state the main hypothesis in null form.

H1.

Clan culture has no association with female executive representation in firms.

To examine the relationship between clan culture and female executive representation, we estimate the following regression model:

(1)

where i and t index firms and years, respectively. The dependent variable FERatioi,t is the measure of female executive representation of firm i in year t. We calculate FERatioi,t as the percentage of females in top management teams including the board of directors, supervisory board members and top executives [2].

Our main variable of interest, Clan, measures the extent to which firms are impacted by clan culture. Following Pan et al. (2019a, 2019b) and Zhang (2020), Clan is measured as the number of genealogies per 10,000 residents compiled in the city where the focal firm is incorporated [3]. Genealogy serves as a fundamental document that chronicles the origins, hereditary lineage, and traditions of a clan, evolving into a key symbol of clan culture (Greif & Tabellini, 2017). In areas where clan culture is deeply rooted, members tend to maintain more genealogical records (Zhang, 2020).

Building on the works of Pan et al. (2019b, 2023) and Qiu et al. (2023), we include control variables at both the firm level and macro level. At the firm level, we control for firm size (Size), solvency (Leverage), profitability (ROA), revenue growth (Growth), the ownership percentage of the largest shareholders (Largest_share_ratio), board size (Board_size), ratio of independent directors (Ind_dir_ratio), and CEO-Chair duality (Dual). At the macro level, we control for regional economic and socio-demographic factors of the province where the focal firm is incorporated, including the logarithm of GDP per capita (Ln_GDP_PC), the share of GDP from the primary industry (First_Ind_GDP), the marketization index (MKT_index), the logarithm of the number of universities (Education), and the logarithm of marriage registrations (Marriage). We also control Confucian culture (Confucianism) to help disentangle the effect of clan culture from broader Confucian norms. Additionally, we control for industry and year fixed effects. Detailed variable definitions are provided in Table 1.

Table 1

Variable definitions

VariableDefinition
Dependent variables
FERatioThe percentage of females in top management teams including board of directors, supervisory board members and top executives
FERatio_managementThe percentage of females in top executives
Wage_diffThe difference between the average salary of male and female executives in the firm, scaled by the average salary of all executives
Independent variables
ClanNumber of genealogies per 10,000 residents in the city where the firm is incorporated
Clan_SurnameProportion of the top three surnames in the city where the firm is incorporated
Instrumental variable
Pop_densityProvincial-level indicators calculated by aligning the areas from the 26th year of the Hongwu period with current administrative districts. Population density is determined by dividing the population by the area, expressed in persons per square kilometer
Control variables
SizeTotal assets (in logarithms)
LeverageThe ratio of total liabilities to total assets
ROAReturn on total assets
GrowthRevenue growth rate
Largest_share_ratioThe ownership percentage of the largest shareholder
Board_sizeNumber of board members (in logarithms)
Ind_dir_ratioProportion of independent directors relative to the total number of board members
DualWhen the chairman and CEO of the two positions concurrently, take the value of 1, otherwise 0
Ln_GDP_PCGross domestic product per capita of the province where the firm is incorporated (in logarithms)
First_Ind_GDPThe GDP of the first industry sector in the province where the firm is incorporated, relative to the total GDP of the province
MKT_indexMarketization index for the province where the firm is incorporated
EducationThe number of universities in the province where the firm is incorporated (in logarithms)
MarriageThe number of marriage registrations in the province where the firm is incorporated (in logarithms)
ConfucianismThe natural logarithm of the number of schools in each city in the Ming and Qing Dynasties
Social_trustFirm trustworthiness at the provincial level, based on the question in the CGSS (2018) questionnaire: “In general, do you agree that the vast majority of people in the society can be trusted?” Responses are coded as follows: “Strongly agree” and “Agree” are assigned a value of 1, while “Neither agree nor disagree”, “Disagree”, and “Strongly disagree” are assigned a value of 0. The average value is then calculated at the province level and matched to firms based on the province where the firm is incorporated
Gender inequality perception variables
LD_GenderPercep1Gender inequality perception measure from the labor demand side perspective. This measure is derived from the CGSS (2018) questionnaire, based on the question: “Do you agree with the statement: Men are inherently more capable than women?” Responses are coded as follows: “Strongly agree” and “Agree” are assigned a value of 1, while “Neither agree nor disagree”, “Disagree”, and “Strongly disagree” are assigned a value of 0. The average value is then calculated at the province level and matched to firms based on the province where the firm is incorporated
LD_GenderPercep2Another gender inequality perception measure from the labor demand side perspective. This measure is derived from the CGSS (2018) questionnaire, based on the question: “Do you agree with the statement: In times of economic depression, female employees should be fired first?” The construction method is identical to that of LD_GenderPercep1
LS_GenderPercep1Gender inequality perception measure from the labor supply side perspective. The first measure is the female labor force participation, which is defined as the ratio of women's average weekly working hours to men's. Using responses to the CGSS (2018) question: “When you have a job, how many hours do you usually work in a week, including overtime?”, we calculate the average weekly working hours separately for women and men, and use their ratio to measure the female labor force participation
LS_GenderPercep2Gender inequality perception measure from the labor supply side perspective. The second measure is the female educational attainment, which is defined as the proportion of women with higher education in the total female population. Using data from the CGSS (2018) questionnaire, we constructed this measure based on responses to the question: “What is your current highest level of education?” Higher education is defined as a college degree or above, and respondents with such qualifications are coded as 1; otherwise, they are coded as 0
Partitioning variables for cross-sectional tests
SOEA dummy variable that equals 1 if the firm is a stated-owned business, and 0 otherwise
High_GDPA dummy variable that equals 1 if the GDP of the province where the firm is incorporated is higher than the annual median GDP of all provinces, and 0 otherwise
OverseaShockA dummy variable that equals 1 if the province where the firm is incorporated historically had an open treaty port, and 0 otherwise

We obtain financial data on the A-share listed firms from the China Stock Market and Accounting Research (CSMAR) database. The sample period for our analysis is from 2003 to 2022. We exclude firms in the financial industry and firms with irregular financial conditions, including those labeled ST and *ST. In addition to financial data, we also collect data on clan culture and Confucian culture from the Chinese Research Data Services Platform (CNRDS) database, the marketability index from the China Sub-Provincial Marketability Index Report (2021), and provincial-level economic and socio-demographic variables from the National Bureau of Statistics of China. After excluding firm-years with missing values of the main dependent and independent variables, our final sample for the baseline analysis consisted of 40,940 firm-year observations. To mitigate the potential influence of extreme observations, we winsorize the top and bottom 1% of all continuous variables.

Table 2 presents the descriptive statistics and correlation matrix pertaining to the primary variables under study. The maximum value of the variable, female executive representation (FERatio), reaches 0.500, while the minimum is observed at 0.000. With an average of 0.186 and a standard deviation of 0.117, these statistics suggest a modest representation of female executives in Chinese firms, alongside discernible variation across individual firms. Turning to the variable representing clan culture (Clan), the observed maximum and minimum values are 6.315 and 0.003, respectively. The mean value stands at 0.713 with a standard deviation of 1.132, pointing to substantial heterogeneity in the influence of clan culture across Chinese corporations. In addition, Clan Culture (Clan) is only modestly correlated with Confucian Culture (Confucianism) (r = 0.196). This pattern supports our conceptual distinction between the two: clan culture is not merely a proxy for Confucian values but reflects a separate, institutionally grounded social system. Comprehensive statistics for additional variables can be found in Table 2 below.

Table 2

Descriptive statistics and correlation matrix

Panel A: Descriptive statistics
VariablesObservationsMeansdminp25p50p75max
FERatio40,9400.1860.1170.0000.0950.1670.2630.500
Clan40,9400.7131.1320.0030.0570.2761.0056.315
Size40,94021.9751.33119.27221.03221.79822.71826.104
Leverage40,9400.4370.2160.0510.2660.4290.5930.999
ROA40,9400.0410.073−0.2840.0140.0400.0760.238
Growth40,9400.1870.472−0.649−0.0240.1160.2863.133
Largest_share_ratio40,94035.51815.2539.43023.42033.16046.03075.010
Board_size40,9402.1370.2061.6091.9462.1972.1972.708
Ind_dir_ratio40,9400.3720.0530.2730.3330.3330.4290.571
Dual40,9400.2720.4450.0000.0000.0001.0001.000
Ln_GDP_PC40,94010.9860.7078.95910.60311.09511.49812.142
First_Ind_GDP40,9406.6705.0910.2313.4005.2009.50022.400
MKT_index40,9409.4481.7804.5878.4909.63810.61012.864
Education40,9404.5970.4032.8904.3694.6734.9205.124
Marriage40,94012.7470.72511.14012.11112.88413.35913.784
Confucianism40,9403.2241.0630.0002.7733.4344.1115.063
Social_trust40,5160.6650.0540.5650.6330.6760.6970.792
LD_GenderPercep140,5160.3470.0630.2610.3000.3230.4110.477
LD_GenderPercep240,5160.0800.0250.0520.0640.0710.0980.139
LS_GenderPercep140,5161.0150.7290.0000.5441.0281.0624.009
LS_GenderPercep240,5160.2020.1080.0320.1090.2400.3040.364
Wage_diff31,9340.2680.406−0.9280.0100.2670.5491.133
Panel B: Correlation matrix
Variables(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)
(1) FERatio1.000         
(2) Clan0.009*1.000        
(3) Size−0.143*−0.062*1.000       
(4) Leverage−0.138*−0.063*0.365*1.000      
(5) ROA0.026*0.046*0.021*−0.410*1.000     
(6) Growth−0.009*0.0020.030*0.032*0.251*1.000    
(7) Largest_share_ratio−0.088*−0.034*0.176*0.029*0.140*0.021*1.000   
(8) Board_size−0.205*−0.027*0.203*0.138*0.0060.0000.047*1.000  
(9) Ind_dir_ratio0.096*0.0010.048*−0.025*−0.005−0.008*0.011*−0.506*1.000 
(10) Dual0.162*0.049*−0.145*−0.160*0.061*0.008−0.079*−0.196*0.127*1.000
(11) Ln_GDP_PC0.247*0.068*0.214*−0.166*0.072*−0.044*−0.089*−0.208*0.159*0.171*
(12) First_Ind_GDP−0.151*−0.048*−0.123*0.111*−0.080*0.016*0.0000.102*−0.086*−0.115*
(13) MKT_index0.219*0.200*0.104*−0.153*0.086*−0.037*−0.086*−0.205*0.125*0.181*
(14) Education0.084*0.195*0.045*−0.100*0.085*−0.016*−0.060*−0.124*0.071*0.107*
(15) Marriage−0.064*0.167*−0.090*−0.011*0.055*0.013*−0.029*−0.019*0.0000.019*
(16) Confucianism0.013*0.196*0.003−0.034*0.040*−0.0070.020*0.009*−0.021*−0.032*
(17) Social_trust−0.042*−0.107*0.024*0.025*−0.008−0.0020.014*0.047*−0.065*−0.081*
(18) LD_GenderPercep1−0.111*0.014*−0.038*0.055*−0.026*0.000−0.0070.049*−0.058*−0.072*
(19) LD_GenderPercep2−0.085*−0.0070.009*0.058*−0.035*0.003−0.0060.060*−0.056*−0.081*
(20) LS_GenderPercep10.020*−0.189*0.042*0.013*−0.036*0.0000.0030.023*0.027*−0.011*
(21) LS_GenderPercep20.106*−0.056*0.057*−0.057*0.021*−0.0040.023*−0.052*0.065*0.079*
(22) Wage_diff0.051*0.043*−0.024*−0.023*0.014*0.012*−0.036*−0.037*0.012*0.018*
Panel B: Correlation matrix
Variables(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)
(1) FERatio            
(2) Clan            
(3) Size            
(4) Leverage            
(5) ROA            
(6) Growth            
(7) Largest_share_ratio            
(8) Board_size            
(9) Ind_dir_ratio            
(10) Dual            
(11) Ln_GDP_PC1.000           
(12) First_Ind_GDP−0.794*1.000          
(13) MKT_index0.812*−0.713*1.000         
(14) Education0.306*−0.204*0.505*1.000        
(15) Marriage−0.294*0.318*0.031*0.733*1.000       
(16) Confucianism0.175*−0.172*0.132*−0.153*−0.223*1.000      
(17) Social_trust0.0050.034*−0.134*−0.246*−0.280*0.205*1.000     
(18) LD_GenderPercep1−0.384*0.583*−0.345*0.114*0.311*−0.156*0.336*1.000    
(19) LD_GenderPercep2−0.230*0.291*−0.321*−0.166*−0.120*−0.142*0.521*0.658*1.000   
(20) LS_GenderPercep10.078*−0.051*−0.155*−0.156*−0.260*−0.090*−0.110*−0.124*−0.075*1.000  
(21) LS_GenderPercep20.473*−0.765*0.402*−0.105*−0.401*−0.038*−0.312*−0.802*−0.400*0.216*1.000 
(22) Wage_diff0.036*−0.020*0.055*0.052*0.030*0.006−0.014*0.011*−0.015*−0.018*−0.0071.000

Note(s): Panel A presents the descriptive statistics for our primary sample of 40,940 firm-year observations over 2003–2022. Panel B reports the correlation matrix of main variables. Variable definitions are provided in Table 1 

We begin our analysis by estimating the effect of clan culture on female executive representation in top management teams using Equation (1). Table 3 presents our baseline results.

Table 3

Test of H1: The relationship between clan culture and female executive representation

VariablesFERatioFERatio
Clan−0.0012**−0.0026***
(−2.477)(−5.196)
Size −0.0155***
 (−30.668)
Leverage −0.0151***
 (−4.660)
ROA 0.0256***
 (2.836)
Growth 0.0034***
 (2.792)
Largest_share_ratio −0.0001*
 (−1.818)
Board_size −0.0477***
 (−14.862)
Ind_dir_ratio 0.0225*
 (1.943)
Dual 0.0196***
 (14.900)
Ln_GDP_PC 0.0054
 (1.436)
First_Ind_GDP −0.0009***
 (−3.396)
MKT_index 0.0013
 (1.606)
Education −0.0046
 (−1.222)
Marriage −0.0019
 (−0.789)
Confucianism −0.0014**
 (−2.552)
Constant0.1279***0.5626***
(21.699)(11.609)
YearYesYes
IndustryYesYes
Observations40,94040,940
Adj. R-squared0.1200.180

Note(s): This table reports the OLS estimation results for Model (1). The dependent variable, FERatio, is measured as the percentage of females in top management teams including board of directors, supervisory board members and top executives. The main variable of interest, Clan, is measured as the number of genealogies per 10,000 residents in the city where the firm is incorporated. Other variable definitions are provided in Table 1. Industry- and year-fixed effects are included in all columns. Coefficient estimates are reported in the row above the t-statistics in parentheses. ***, **, and * denote two-tailed significance at the 0.01, 0.05, and 0.10 levels

As shown in Column (1), the coefficient on Clan is −0.0012 and statistically significant at the 5% level in the specification without control variables. After introducing control variables in Column (2), the estimated coefficient on Clan is −0.0026 and is significant at the 1% level, indicating that as a firm's exposure to clan culture increases, the presence of female executives decreases. The effect of clan culture on female executive representation is also economically significant: a one standard deviation increase in clan culture leads to a 1.58% decrease in the female executive ratio. Given the mean female executive ratio of 18.6% in our main sample, this represents an 8.49% reduction relative to the sample mean.

Turning to firm-level control variables, larger firms (Size), firms with higher leverage ratio (Leverage), firms with higher shareholder concentration (Largest_share_ratio) and firms with more board members (Board_size) hire significantly fewer female executives in their top management teams. In contrast, more profitable firms (ROA), firms with higher revenue growth (Growth), and firms with a higher proportion of independent directors on their boards (Ind_dir_ratio), as well as firms where the CEO also serves as the chairperson of the board (Dual), tend to have a higher proportion of female executives. Consistent with prior literature that Confucian culture reinforces gender hierarchy (Du, 2016), Confucianism is also negatively associated with the female executive ratio [4]. In terms of the macro level, firms located in provinces with more first industry sectors (First_Ind_GDP) exhibit lower female representation in their top management teams. These findings are largely consistent with prior literature (Du, 2016; Qiu et al., 2023).

Overall, the results in Table 3 are consistent with the argument that a predominant clan culture hinders the advancement of female executives, significantly limiting their representation in firm settings.

The above findings are consistent with our baseline hypothesis that clan culture is negatively associated with female executive representation in Chinese firms. However, this analysis may be subject to endogeneity concerns, such as correlated omitted variables. To address these concerns, we employ instrumental variable (IV) estimation. Our chosen instrument is population density (Pop_density). The geographical distribution of population density across China is shown in Figure 2. Conceptually, there is a positive association between population density and clan formation. A dense population inherently suggests a clustering of individuals, which often facilitates the establishment and perpetuation of clans. High population density, driven by the need to compete for and safeguard limited resources, can also promote collaborative behavior, thereby bolstering clan cohesion. Thus, regions with denser populations are hypothesized to exhibit more pronounced clan culture.

Figure 2
A thematic map shows China’s provinces color coded by intensity levels with a legend indicating seven categories.The map shows the outline of China divided into provincial regions, with each province filled using a specific color to represent intensity levels. A legend on the upper right explains the color coding, where “thin” is shown in light grey, “low” in light blue, “normal” in light green, “moderate” in green, “height” in saddle brown, “ultra-high” in red, and “nonedata” in white. Large areas of western and northern China appear in light grey, indicating “thin” levels. Several central and eastern provinces are shaded light blue and light green, representing “low” and “normal” levels. One eastern coastal province is shaded green, indicating a “moderate” level, while an adjacent coastal province is shaded saddle brown, indicating a “height” level. A small neighboring area is shaded red, indicating an “ultra-high” level. Provinces with no available data appear white. Blue boundary lines outline provincial borders, and island groups to the southeast are shown in the same boundary style, showing the geographic structure of China.

The geographical distribution of population density across China. Note: Provincial-level population density is calculated by aligning the administrative regions from the 26th year of the Hongwu reign with current provincial boundaries. It is measured as the total population divided by land area (persons per square kilometer). The map illustrates the spatial distribution of population density across provinces, with colors representing different density levels as shown in the upper right corner

Figure 2
A thematic map shows China’s provinces color coded by intensity levels with a legend indicating seven categories.The map shows the outline of China divided into provincial regions, with each province filled using a specific color to represent intensity levels. A legend on the upper right explains the color coding, where “thin” is shown in light grey, “low” in light blue, “normal” in light green, “moderate” in green, “height” in saddle brown, “ultra-high” in red, and “nonedata” in white. Large areas of western and northern China appear in light grey, indicating “thin” levels. Several central and eastern provinces are shaded light blue and light green, representing “low” and “normal” levels. One eastern coastal province is shaded green, indicating a “moderate” level, while an adjacent coastal province is shaded saddle brown, indicating a “height” level. A small neighboring area is shaded red, indicating an “ultra-high” level. Provinces with no available data appear white. Blue boundary lines outline provincial borders, and island groups to the southeast are shown in the same boundary style, showing the geographic structure of China.

The geographical distribution of population density across China. Note: Provincial-level population density is calculated by aligning the administrative regions from the 26th year of the Hongwu reign with current provincial boundaries. It is measured as the total population divided by land area (persons per square kilometer). The map illustrates the spatial distribution of population density across provinces, with colors representing different density levels as shown in the upper right corner

Close modal

Furthermore, considering exclusivity, it is posited that population density does not directly influence contemporary firm decisions regarding the recruitment and appointment of female executives. Consequently, we contend that population density serves as a suitable instrumental variable. Our measure of population density is derived from the 26th year of the Hongwu period, as detailed in Chinese Population HistoryMing Period (Cao, 2000), aligning with the methodology employed by Wang and Gao (2023).

The outcomes of the 2SLS regressions are presented in Table 4. The first-stage regression (Column (1)) reveals a significant positive correlation between Pop_density and Clan, affirming the validity of our instrument. The second-stage regression (Column (2)) shows that the coefficient estimate on the fitted values of Clan (Clan-hat) is significantly negative, with a value of −0.1321 at the 1% level. This empirical evidence provides further support for our main finding: firm environments deeply entrenched in clan culture are often characterized by a diminished representation of female executives.

Table 4

Instrumental variable test

Variables(1)(2)
ClanFERatio
Pop_density0.0009*** 
(12.605) 
Clan-hat −0.1321***
 (−8.704)
ControlsYesYes
YearYesYes
IndustryYesYes
Observations39,07339,073
Adj. R-squared0.134−1.223
Underidentification test (Kleibergen-Paap rk LM statistic)156.403
Weak identification test (Cragg-Donald Wald F statistic)74.478
Weak identification test (Kleibergen-Paap rk Wald F statistic)158.879

Note(s): This table reports the IV test results based on the 2SLS regressions. Column (1) presents the first stage regression results. The instrumental variable, Pop_density, is a provincial-level measure calculated by first aligning the areas from the 26th year of the Hongwu period with current administrative districts, and then dividing the population of that period by the area, expressed in persons per square kilometer. Column (2) presents the second stage regression results, where Clan-Hat is the predicted value of Clan based on the first stage regression. Variable definitions are provided in Table 1. Industry- and year-fixed effects are included in all columns. Coefficient estimates are reported in the row above the t-statistics in parentheses. ***, **, and * denote two-tailed significance at the 0.01, 0.05, and 0.10 levels

4.3.1 Alternative measure of clan culture

In our primary tests, we measure clan culture by calculating the number of genealogies per 10,000 residents in the city where the focal firm is incorporated. To ensure the robustness of our findings, we also employ an alternative measure of clan culture: the proportion of the population sharing the same surname (Guo & Yao, 2013; Chen & Chen, 2018; Wang et al., 2020). Freedman (1966) notes that families with the same surname in Chinese villages often originate from the same clan. Following Wang et al. (2020), we use data from the 2005 National 1% Population Survey to determine the proportion of the population with the three most common surnames in each Chinese city (Clan_surname). We then use this proportion as an alternative measure of the intensity of clan culture in each region.

Column (1) of Table 5 presents the relevant regression results for Model (1) with Clan replaced by this alternative proxy, Clan_surname. As shown, the regression coefficient on Clan_surname is significantly negative, further supporting our main finding.

Table 5

Robustness checks for H1

Variables(1)(2)(3)(4)(5)
FERatioFERatio_managementFERatioFERatioFERatio
Clan_Surname−0.0397***    
(−3.684)    
Clan −0.0036***−0.0028***−0.0038***−0.0026*
 (−5.031)(−5.595)(−5.855)(−1.726)
Social_trust  −0.0605***  
  (−5.750)  
ControlsYesYesYesYesYes
YearYesYesYesYesYes
IndustryYesYesYesYesYes
ProvinceNoNoNoYesNo
Observations44,07340,94040,51640,94040,940
Adj. R-squared0.1770.0920.1800.1890.180

Note(s): This table reports the OLS estimation results of robustness tests on the impact of clan culture on female executive representation. The dependent variable in Column (1), Column (3), Column (4) and Column (5), FERatio, is measured as the percentage of females in top management teams including board of directors, supervisory board members and top executives. The dependent variable in Column (2), FERatio_management, is measured as the percentage of females in top executives. The independent variable in Column (1), Clan_Surname, is measured as the proportion of the top three surnames in the city where the firm is incorporated. The independent variable in Column (2) to (5), Clan, is measured as the number of genealogies per 10,000 residents in the city where the firm is incorporated. Other variable definitions are provided in Table 1. Industry- and year-fixed effects are included in all columns. Province-fixed effect is included in Column (4). Standard errors are clustered at the city level in Column (5). Coefficient estimates are reported in the row above the t-statistics in parentheses. ***, **, and * denote two-tailed significance at the 0.01, 0.05, and 0.10 levels

4.3.2 Alternative measure of female executive representation

In our main analyses, we measure female executive representation as the percentage of women in top management teams, including the board of directors, supervisory board members, and top executives. Following Qiu et al. (2023), we refine the definition of the top management team to include only top executives (FERatio_management). Column (2) of Table 5 presents the corresponding regression results. As shown, the coefficient of Clan remains significantly negative, confirming our baseline results.

4.3.3 Other cultural factors

Previous studies have shown that social trust can also influence board gender diversity (Qiu et al., 2023). To address the concern that social trust may drive our results, we include a proxy for social trust in our regression as a robustness check.

We construct the variable Social_trust based on the following question in the CGSS (2018) questionnaire: “In general, do you agree that the vast majority of people in the society can be trusted?” Responses are coded as follows: “Strongly agree” and “Agree” are assigned a value of 1, while “Neither agree nor disagree”, “Disagree”, and “Strongly disagree” are assigned a value of 0. The average value is then calculated at the province level and matched to firms based on the province where the firm is incorporated. A higher value indicates a greater level of social trust.

Column (4) of Table 5 presents the estimation results of our baseline model (1) after adding Social_trust as an additional control. As shown, the coefficient of Clan remains significantly negative, suggesting that clan culture is a distinct cultural factor affecting female representation, independent of the influence of social trust.

4.3.4 Incorporating province fixed effects and clustering standard errors at the city level

As demonstrated in Section 2.1, regional variations exist in clan institutions, with a more pronounced presence in the southeast and a relatively weaker one in the north and west. To address potential omitted-variable bias arising from regional heterogeneity, we incorporate province fixed effects into our analysis. Additionally, we cluster standard errors at the city level to account for potential correlation of error terms within cities (Cameron & Miller, 2011).

Columns (4) and Column (5) of Table 5 report the regression results. As shown, the coefficients on Clan remain significantly negative, confirming that our main conclusions are robust to these adjustments.

5.1.1 The nature of business ownership

Firm behavior, particularly in decision-making, is significantly influenced by ownership structures. In the realm of executive recruitment and selection, non-state-owned firms (non-SOEs) tend to offer more progressive opportunities for women compared to state-owned firms (SOEs). This difference largely arises because non-SOEs are market-driven and focus primarily on competence. In non-SOEs, women can overcome cultural biases within clan culture by leveraging their skills and attributes to ascend to executive roles.

In contrast, SOEs typically have executives nominated by the state, many of whom possess strong political ties and state cadre profiles. These nominations are not solely based on optimizing firm benefits but often follow “tenure-based hierarchies” (Pan et al., 2023), reinforcing a rigid promotional structure. Clan culture, which emphasizes “seniority order”, aligns more closely with SOEs’ tenure-based ethos, intensifying its negative impact on female executive representation in these firms. Moreover, the male-dominated executive teams in SOEs (Pan et al., 2023) further impede women’s career progression. While female executives do exist in SOEs, their roles often align more with government policies (Liu & Yang, 2019), potentially diminishing their influence. Consequently, women face greater obstacles in SOEs due to the pervasive clan culture, leading to their sparse representation.

We predict that the negative association between clan culture and female executive representation is more prominent for state-owned firms than for non-state-owned firms. We conducted partitioned sample analyses to test this prediction. Panel A of Table 6 presents these analyses. Columns (1) and (2) tabulate the estimation results of Model (1) for subsamples partitioned by whether the focal firm is a SOE or not. As shown, clan culture is negatively associated with female executive representation for SOE firms (−0.0056, t = −7.382) and non-SOE firms (−0.0028, t = −4.505). Consistent with our prediction, the negative association is more pronounced for SOE firms (χ2 = 7.90). This comparative evaluation highlights that while clan culture negatively affects female executive representation in all firms, its impact is significantly more severe in state-owned firms.

Table 6

Test of H2 – H4: cross-sectional tests

Variables(1)(2)
FERatioFERatio
Panel A: The nature of business ownership
 SOE = 1SOE = 0
Clan−0.0056***−0.0028***
(−7.382)(−4.505)
ControlsYesYes
YearYesYes
IndustryYesYes
Observations17,08123,859
Adj. R-squared0.2100.107
Comparison of Clan coefficient (χ2)7.90***
Panel B: Regional economic development
 High_GDP = 1High_GDP = 0
Clan−0.0031***−0.0054***
(−4.270)(−6.657)
ControlsYesYes
YearYesYes
IndustryYesYes
Observations20,01220,928
Adj. R-squared0.1550.219
Comparison of Clan coefficient (χ2)4.51**
Panel C: External culture exposure
 OverseaShock = 1OverseaShock = 0
Clan−0.0020***−0.0523***
(−3.857)(−9.029)
ControlsYesYes
YearYesYes
IndustryYesYes
Observations32,6478,293
Adj. R-squared0.1580.288
Comparison of Clan coefficient (χ2)75.40***

Note(s): This table reports the OLS estimation results of cross-sectional tests on the impact of clan culture on female executive representation. Panel A presents the results for subsamples partitioned by the nature of business ownership. SOE is a dummy variable that equals 1 if the firm is a stated-owned business, and 0 otherwise. Panel B presents the results for subsamples partitioned by regional economic development. High_GDP is a dummy variable that equals 1 if the GDP of the province where the firm is incorporated is higher than the annual median GDP of all provinces, and 0 otherwise. Panel C presents the results for subsamples partitioned by external culture exposure. OverseaShock is a dummy variable that equals 1 if the province where the firm is incorporated historically had an open treaty port, and 0 otherwise. The dependent variable, FERatio, is measured as the percentage of females in top management teams including board of directors, supervisory board members and top executives. The independent variable, Clan, is measured as the number of genealogies per 10,000 residents in the city where the firm is incorporated. Other variable definitions are provided in Table 1. Industry- and year-fixed effects are included in all columns. Coefficient estimates are reported in the row above the t-statistics in parentheses. ***, **, and * denote two-tailed significance at the 0.01, 0.05, and 0.10 levels

5.1.2 Regional economic development

The trajectory of firm growth is intricately tied to its overarching macro-environment. In regions marked by advanced economic development, the abundance of resources enhances the accessibility of requisite human capital for women, thereby augmenting their likelihood of assuming executive roles. Conversely, in regions characterized by sluggish economic development, women are more susceptible to traditional paradigms, often prioritizing familial responsibilities (Li & Xie, 2016). Consequently, their ambition for upward mobility may be diminished. Therefore, we conjecture that the deleterious influence of clan culture on the representation of female executives can be attenuated in regions exhibiting superior economic development.

We measure regional economic development using the logarithm of the gross domestic product (GDP) of the firm's domiciled province. Panel B of Table 6 presents the results for subsamples partitioned by the median value of GDP for all provinces each year. Columns (1) and (2) show that while clan culture is negatively associated with female executive representation in firms located in both more and less economically developed regions, the negative association is much stronger for firms in regions with slower economic development (−0.0054, t = −6.657) compared to those in regions with superior economic development (−0.0031, t = −4.270).

This split-sample analysis supports our conjecture, suggesting that advanced regional economic development acts as a buffer, tempering the inverse relationship between clan culture and female executive representation. Specifically, in regions with superior economic development, the negative impact of clan culture on female executive representation is less severe, indicating that economic development may mitigate some of the cultural barriers that hinder female executives.

5.1.3 External cultural exposure

Historical evidence shows that isolation and adherence to traditional practices rarely support national development. Today, the Chinese government promotes international openness to stay competitive globally. Increased cross-border investments and human capital mobility bring together diverse cultures (Li, Xu, & Chen, 2021; Wang & Tan, 2022). Research indicates that foreign cultures can influence and change traditional Chinese firm practices (Li et al., 2021; Wang & Tan, 2022).

Western culture, with its focus on individualism, meritocracy, and gender equality, may help mitigate the negative impact of clan culture on female executive representation in Chinese firms. First, Western business practices often emphasize individual performance and competence over seniority and connections. This merit-based approach can help women advance based on their abilities and achievements, counteracting entrenched cultural biases. Second, exposure to Western norms can raise awareness about the importance of gender diversity in leadership and encourage more progressive attitudes towards work-life balance, family responsibilities, and gender roles within the workplace.

We predict that the negative association between clan culture and female executive representation is less pronounced for firms located in areas with greater exposure to foreign culture. To measure the degree of exposure to foreign culture in the region where the firm is located, we consider whether the area was historically forced to open a treaty port. The dummy variable OverseaShock equals 1 if the province where the firm is incorporated historically had an open treaty port, and 0 otherwise.

Panel C of Table 6 presents the results for subsamples partitioned by OverseaShock. Columns (1) and (2) of Panel C show that clan culture is negatively associated with female executive representation in both subsamples. However, the negative relationship is much more pronounced in firms located in areas with less exposure to foreign culture (−0.0523, t = −9.029) compared to firms located in areas with greater exposure to foreign culture (−0.0020, t = −3.857). These results support the idea that external cultural exposure can mitigate the negative relationship between clan culture and female executive representation.

The preceding analysis reveals that clan culture negatively impacts female executive representation in top management teams in China. We argue that this negative impact is driven by the amplification of gender inequality perceptions by clan culture. In this section, we directly test this mechanism. The following Xiong et al. (2018), we used data from the CGSS (2018) survey to measure gender inequality perceptions.

From the labor demand perspective, we construct two gender inequality perception measures to assess male-biased attitudes. The first measure, LD_GenderPercep1, is based on the question in the CGSS (2018) questionnaire: “Do you agree with the statement: Men are inherently more capable than women?” Responses are coded as follows: “Strongly agree” and “Agree” are assigned a value of 1, while “Neither agree nor disagree”, “Disagree”, and “Strongly disagree” are assigned a value of 0. The average value is then calculated at the province level and matched with firms based on the province where the firm is incorporated. A higher value indicates a stronger male-biased attitude. The second measure, LD_GenderPercep2, is based on the question: “Do you agree with the statement: In economic downturns, women should be the first to be laid off?” It is constructed in a similar manner to LD_GenderPercep1.

From the labor supply perspective, we also construct two gender inequality perception measures, LS_GenderPercep1 and LS_GenderPercep2, to assess female gender role perceptions. LS_GenderPercep1 is the female labor force participation, which is defined as the ratio of women's average weekly working hours to men's. Using responses to the CGSS (2018) question, “When you have a job, how many hours do you usually work in a week, including overtime?“, we calculate the average weekly working hours separately for women and men, and use their ratio to measure the female labor force participation. LS_GenderPercep2 is the female educational attainment, which is defined as the proportion of women with higher education in the total female population. Using data from the CGSS (2018) questionnaire, we constructed this measure based on responses to the question: “What is your current highest level of education?” Higher education is defined as a college degree or above, and respondents with such qualifications are coded as 1; otherwise, they are coded as 0.

Table 7 reports the regression results testing the transmission mechanism from both the labor demand and supply perspectives [5]. As shown in Panel A, the regression coefficients of LD_GenderPercep1 and LD_GenderPercep2 on Clan are both significantly positive at the 1% level. In addition, the regression coefficients of Clan×LD_GenderPercep1 and Clan×LD_GenderPercep2 on FERatio were both significantly negative at the 1% level. These indicate that stronger clan culture is associated with more pronounced male-biased attitudes, and as a result, negatively impacts the recruitment of female executives. Similarly, as shown in Panel B, the regression coefficients of LS_GenderPercep1 and LS_GenderPercep2 on Clan are significantly negative, and the regression coefficients of Clan×LS_GenderPercep1 and Clan×LS_GenderPercep2 on FERatio are significantly positive. These findings suggest that while stronger clan culture reinforces traditional female gender role perceptions, higher female labor force participation and educational attainment can mitigate the adverse effects of clan culture on women.

Table 7

Transmission mechanism: impact of clan culture on gender inequality perceptions

Variables(1)(2)(3)(4)
LD_GenderPercep1FERatioLD_GenderPercep2FERatio
Panel A: The labor demand side (male-biased attitudes)
Clan0.0012***0.0066**0.0019***0.0036*
(6.489)(2.170)(24.882)(1.832)
Clan × LD_GenderPercep1 −0.0252***  
 (−3.016)  
LD_GenderPercep1 −0.1206***  
 (−10.536)  
Clan × LD_GenderPercep2   −0.0658***
   (−3.006)
LD_GenderPercep2   −0.2058***
   (−7.944)
ControlsYesYesYesYes
YearYesYesYesYes
IndustryYesYesYesYes
Observations40,51640,51640,51640,516
Adj. R-squared0.3970.1830.2750.182
Panel B: The labor supply side (female gender role perceptions)
Clan−0.0417***−0.0054***−0.0008***−0.0071***
(−24.704)(−4.318)(−3.387)(−6.288)
Clan × LS_GenderPercep1 0.0045***  
 (2.639)  
LS_GenderPercep1 0.0023***  
 (2.651)  
Clan × LS_GenderPercep2   0.0276***
   (4.440)
LS_GenderPercep2   0.0849***
   (8.976)
ControlsYesYesYesYes
YearYesYesYesYes
IndustryYesYesYesYes
Observations40,51640,51640,51640,516
Adj. R-squared0.2420.1800.6970.182

Note(s): This table reports the OLS estimation results on the impact of clan culture on gender inequality perceptions. The dependent variables, LD_GenderPercep1 and LD_GenderPercep2, are measures of gender inequality perceptions assessing male-biased attitudes from the labor demand side. Similarly, LS_GenderPercep1 and LS_GenderPercep2 are measures assessing female gender role perceptions from the labor supply side. The independent variable, Clan, is measured as the number of genealogies per 10,000 residents in the city where the firm is incorporated. Other variable definitions are provided in Table 1. Industry- and year-fixed effects are included in all columns. Coefficient estimates are reported in the row above the t-statistics in parentheses. ***, **, and * denote two-tailed significance at the 0.01, 0.05, and 0.10 levels

Taken together, these results provide robust evidence that clan culture reinforces gender inequality perceptions from both the demand and supply sides, thereby contributing to the underrepresentation of women in top management positions.

In addition to our primary analysis, we also explore whether clan culture contributes to the observed wage differences between male and female executives. To assess this, we construct a new variable, Wage_diff, which captures the wage disparity. Specifically, Wage_diff is measured as the difference between the average salary of male and female executives in the firm, scaled by the average salary of all executives. We then replace the dependent variable FERatio in Model (1) with Wage_diff and re-estimate the model.

The results of this estimation are presented in Table 8 [6]. The coefficient of the variable representing clan culture (Clan) is significantly positive, indicating that clan culture exacerbates the wage disparity between male and female executives. This suggests that in environments where clan culture is prevalent, the existing wage gap between genders is likely to be wider, further disadvantaging female executives in terms of compensation. These findings underscore the importance of considering organizational culture, particularly clan culture, as a factor that can influence and potentially amplify gender-based wage disparities.

Table 8

Impact of clan culture on the wage gap between male and female executives

VariablesWage_diff
Clan0.0092***
(4.191)
ControlsYes
YearYes
IndustryYes
Observations31,934
Adj. R-squared0.015

Note(s): This table reports the OLS estimation results on the impact of clan culture on the wage gap between male and female executives. The dependent variable, Wage_diff, is the difference between the average salary of male and female executives in the firm, scaled by the average salary of all executives. The independent variable, Clan, is measured as the number of genealogies per 10,000 residents in the city where the firm is incorporated. Other variable definitions are provided in Table 1. Industry- and year-fixed effects are included in all columns. Coefficient estimates are reported in the row above the t-statistics in parentheses. ***, **, and * denote two-tailed significance at the 0.01, 0.05, and 0.10 levels

This study delves into the intricate relationship between clan culture and female executive representation in Chinese firms, using a robust dataset of Chinese firms listed on the A-share market from 2003 to 2022. Our findings provide compelling evidence that clan culture significantly impedes the advancement of female executives, reinforcing traditional gender roles and hierarchies.

We first demonstrate that firms with a strong clan culture have lower female executive representation, highlighting the pervasive influence of entrenched cultural norms on organizational behavior. Our results hold true across various robustness tests, including alternative measures of clan culture and female executive representation, as well as through instrumental variable estimation to address potential endogeneity concerns.

Our cross-sectional tests further reveal that the negative association between clan culture and female executive representation is more pronounced in state-owned firms (SOEs) than in non-state-owned firms (non-SOEs), supporting the idea that rigid hierarchies and male-dominated teams in SOEs exacerbate this effect. Additionally, we find that in regions with higher economic development, this negative association is less severe, suggesting that better economic conditions provide more opportunities for women. Moreover, firms located in areas with greater exposure to foreign culture show a reduced negative impact of clan culture on female executive representation, indicating that cross-cultural influences and inclusive practices from Western contexts can mitigate the adverse effects of traditional cultural norms.

Our additional analyses shed light on the mechanisms through which clan culture perpetuates gender inequality. We find that clan culture amplifies male-biased attitudes and reinforces traditional gender role perceptions, both of which hinder the recruitment and promotion of female executives. Furthermore, clan culture contributes to the gender wage gap, exacerbating economic disparities between male and female executives.

In summary, this paper makes significant contributions to the literature on gender diversity in firm leadership, particularly within the context of Chinese firms. It highlights the profound impact of informal cultural institutions, such as clan culture, on organizational dynamics and gender equality. The findings have important implications for policymakers and firm leaders aiming to enhance gender diversity in leadership roles. Adopting culturally sensitive approaches, fostering inclusive networks, and integrating global best practices can help mitigate the adverse effects of traditional cultural norms and promote a more equitable and diverse firm environment.

1.

For instance, the Singapore Chaozhou Longxi Li Clan Association elected its first female president, Li Huimin, after a long history of male leadership. (Link to the website).

2.

We follow Du and Feng (2012) and define top management teams as the board of directors, supervisory board members, and top executives. We also narrow our definition of top management teams to include only board of directors or top executives in the robustness tests, and our results remain qualitatively similar (Section 4.3).

3.

The genealogy data come from “The General Catalog of Chinese Genealogy”, compiled by the Shanghai Library and published in 2008. This project, initiated in 2000 and completed in 2008, aims to support research on Chinese lineage and assist overseas Chinese in tracing their family roots. The catalog includes 52,401 Chinese genealogies written in mainland China or abroad by the end of 2004.

4.

A one-standard-deviation increase in Confucianism is associated with a 0.80 percentage-point decrease in the female executive ratio, equivalent to a 4.30% reduction relative to the mean. Thus, on a standardized basis, the estimated effect of clan culture is approximately twice as large as that of Confucian culture.

5.

The sample size is smaller than that of the baseline regression in Table 3 because the 2018 Chinese General Social Survey (CGSS2018) only conducted research in 29 provinces, municipalities, and autonomous regions in mainland China, excluding Hainan Province, Tibet Autonomous Region, and Xinjiang Uygur Autonomous Region from the survey.

6.

The sample size is smaller than that of the baseline regression in Table 3 for two reasons: first, the mandatory disclosure of executive compensation for Chinese firms only began in 2005; second, some firms do not have any female executives, making it impossible to construct the Wage_diff indicator.

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