HUMAN CAPITAL, GENDER AND ENTREPRENEURIAL SUCCESS: EMPIRICAL
EVIDENCE FROM CHINA AND GERMANY
Nina Rosenbusch, Friedrich Schiller University Jena, Germany
Andreas Rauch, Rotterdam School of Management, Erasmus University, The Netherlands
Simon C. Parker, University of Western Ontario, Canada
Jens M. Unger, Justus Liebig University Giessen, Germany
ABSTRACT
Entrepreneurship scholars have frequently emphasized that gender differences exist with respect
to accumulated human capital of entrepreneurs and entrepreneurial success. At the same time,
human capital of entrepreneurs influences the success of their firms. Gender differences may not
only occur with regarding human capital itself, but also regarding the relationship between
human capital and entrepreneurial success. In this paper, we aim to detect whether gender
differences in entrepreneurship depend on the cultural context. To derive our hypotheses we
combine social role theory and the resource-based view of the firm. Drawing on a sample of
German and Chinese entrepreneurs we find that gender gaps in human capital differ depending
on the national culture. In addition, we reveal that different human capital related factors
determine the success of women- as compared to men-owned businesses.
INTRODUCTION
Entrepreneurial activities by women have attracted a considerable amount of interest among
policy-makers who have recognized the potential of female entrepreneurship for increasing
economic growth and job creation. Although the gender gap in entrepreneurship has narrowed
during the past decades, the share of female entrepreneurs engaged in venture creating activities
is still comparatively low in many countries (Delmar & Davidsson, 2000; Reynolds, Carter,
Gartner, & Greene, 2004; Arenius & Minniti, 2005; Bosma, & Harding, 2007; Parker, 2009).
Researchers have addressed gender differences in entrepreneurship with respect to venture
creation, growth aspirations (Cliff, 1998), innovation (Strohmeyer & Tonoyan, 2005), and new
venture performance in terms of survival (Kalleberg, & Leicht, 1991), growth (e.g., Alsos,
1
Isakson, & Ljunggren, 2006; Coleman, 2007; Kalleberg, & Leicht, 1991) and profitability
(Coleman, 2007; Watson, 2002). A prominent explanation for gender differences in
entrepreneurial performance is that women have fewer resources as compared to male
entrepreneurs and, therefore, lack important prerequisites to achieve success (e.g., Lerner, Brush,
& Hisrich, 1997). This resource gap may be a result of different role expectations and associated
career paths that influence human as well as financial capital. However, such differences in the
professional careers of men and women due to role expectations may largely depend on the
cultural context and, subsequently, on the participation of men and women in the work force in
general. As a consequence, gender differences in human capital and entrepreneurial success may
not exist universally, but depend on the cultural context. In addition, social role expectations may
have a crucial impact as to how men- and women-led businesses benefit from their founders’
human capital.
In order to detect how social role expectations influence gender differences in human capital as
well as its impact on firm performance we study small business in China and (Western)
Germany. A comparison of these two countries is very useful for studying gender differences
due to several reasons. First, (Western) Germany and China differ significantly regarding
masculinity and other cultural dimensions (Hofstede, 1980). Cultural values, in turn, influence
social role expectations. Furthermore, economic and institutional conditions have an impact on
social role expectations. China is a country in transition, whereas Germany is an established
social market economy. Average household incomes are much lower in China, which forces
women into paid employment. The participation rate of women in the workforce has traditionally
been much higher in China than in (Western) Germany. For the above-stated reasons it can be
expected that social roles associated with women differ significantly between the two countries.
Within the scope of this study, we apply social role theory and the resource-based view of the
firm to explain how human capital of the founder determines the success of entrepreneurial firms
owned by men and women. In so doing, we aim to make three contributions to entrepreneurship
research. First, we intend to reveal whether gender differences with respect to entrepreneurs’
human capital depend on the cultural context. In particular, we study entrepreneurs in Germany
and China – two countries that do not only differ regarding masculinity and other cultural
2
dimensions (Hofstede, 1980), but also regarding the role women play in the economic system.
Further, we aim to demonstrate whether men and women benefit from the same or different sets
of human capital-related factors. Lastly, we examine whether these findings apply universally.
Our results are of considerable importance for policy-makers in different countries who intend to
support male and female entrepreneurship in customized programs.
The paper is organized as follows. First, we present theoretical arguments derived from social
role theory, human capital theory and the resource-based view of the firm to derive our
hypotheses. In the following methods section we describe the sample of German and Chinese
entrepreneurs and the operationalization of variables. Results are discussed with reference to
their contribution to the existing literature and policy implications.
THEORETICAL BACKGROUND AND HYPOTHESES
Gender Differences in Human Capital
Previous research has shown that the proportion of female entrepreneurs is low compared to
male entrepreneurs (Delmar & Davidsson, 2000; Reynolds, Carter, Gartner, & Greene, 2004;
Arenius & Minniti, 2005; Bosma, & Harding, 2007). Moreover, women-owned business
ventures have a lower propensity than men-owned ventures to grow and be successful (Welter, et
al. 2003). A prominent explanation for such gender differences is that compared to male
entrepreneurs female entrepreneurs lack critical human and financial resources to start and run a
business successfully (e.g., Lerner, Brush, & Hisrich, 1997). Within the scope of this study we
focus on gender differences in human capital levels of entrepreneurs and their impact on
entrepreneurial performance. Thereby, we adopt a human capital definition provided by Becker
(1964). We consider human capital as the skills and knowledge an entrepreneur acquires during
his life, e.g., through schooling, work experience, and training. Empirical research shows that
human capital of founders is an important resource for entrepreneurial firms (Unger, Rauch,
Frese, Rosenbusch, & Steinmetz, 2008).
A considerable amount of research has examined gender differences in human capital of
entrepreneurs. However, empirical evidence on this issue is mixed. A number of studies report
that female entrepreneurs have less valuable work, managerial and self-employment experience
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(e.g., Boden & Nucci, 2000; Hisrich & Brush, 1983; Watkins & Watkins, 1983; Kalleberg &
Leicht, 1991). Other studies find that female entrepreneurs have similar amounts or even more
education than male entrepreneurs (e.g., Cowling & Taylor, 2001; Birley et al. 1987).
Inconsistencies in empirical results on gender gaps in human capital may be at least partially
attributable to the focus on different types of human capital, as well as to different cultural
settings that influence human capital endowments of male and female entrepreneurs.
In this study, we use social role theory to explain gender differences in human capital in different
cultural settings. Social role theory assumes that expectations in society assign different roles to
women and men (Eagly, 1987). Thus, in many cultures, women are expected to fulfill a domestic
role, while men are expected to fulfill career-related roles. Such social role expectancies affect
various behaviors, such as educational or occupational choices. Human capital theory
distinguishes between general and specific human capital (Becker, 1964). General human capital
refers to general knowledge and skills acquired for example through education and work
experience. By contrast, specific human capital is defined as knowledge and skills which are
specific to a task. In the case of entrepreneurs, specific human capital refers to knowledge and
skills that are useful for establishing and running a business. Gender differences in human capital
as well as cultural influences on gender differences in human capital may depend on the type of
knowledge and skills. One reason for this phenomenon is that many western and transition
countries have reformed their educational system in favor of girls and women although role
expectancies in the labor market have not seriously changed. Hence, it is necessary to distinguish
between general and specific human capital.
General Human Capital
In this study, the number of years spent in the educational system reflects the general human
capital of an entrepreneur. In Germany, the proportion of girls that obtain advanced degrees in
schools has risen constantly since the reform of the educational system in the 1970s. According
to the Federal Statistical Office [Statistisches Bundesamt], today slightly more girls than boys
earn school degrees permitting entrance to a university; and the share of female students in the
German university system reached 48 percent in the academic year 2006/2007. In China, access
of women to school education has also greatly improved over the past few decades. Gender
4
discrimination in education still exists, but mainly refers to girls and women in rural areas
(Baden & Green, 1994). Because we study Chinese entrepreneurs in urban regions in Eastern
China, we assume that gender discrimination in education is not a severe problem for female
entrepreneurs. In view of these considerations we do not expect major gender differences in
terms of general human capital in the two countries studied.
Specific Human Capital
We do, however, expect greater gender differences in specific human capital, i.e. industryspecific work experience and managerial experience. Male entrepreneurs may have more
industry-specific experiences as compared to female entrepreneurs because they do not fulfill a
domestic role and, are therefore, more likely to invest more time in developing work and
industry specific experiences. Moreover, men are more likely to attain management positions,
because management experiences are related to male role expectations. Although role
expectations have changed significantly during the past century in favor of gender equality at
work, women are still disadvantaged in terms of career development in many countries. Women
often interrupt their careers to fulfill their domestic role as mothers. Such career interruptions
result in significantly less accumulated time in employment, and, thus, less work and industry as
well as managerial experience. Therefore, we assume that
Hypothesis 1: Female entrepreneurs have a significantly lower degree of specific human capital
than male entrepreneurs.
This line of reasoning can be extended with regard to cross-country differences, because role
expectations are developed in a specific cultural context. As a result, for example, the prevalence
rate of female entrepreneurs varies between countries (Bosma & Harding, 2007). China is a
country that has a socialistic market economy which has been allowing women to actively
participate in economic activities. The participation rate of women in the workforce is
significantly higher than in Western countries (Bu & McKeen, 2000). According to a study by
Bu & McKeen (2000), Chinese women value their occupational role more than Canadian
women. The promotion of the one-child policy and the necessity for women to increase the
households’ income foster Chinese women’s participation in the workforce. Accordingly,
5
Chinese women are able to develop experiences (e.g., industry and managerial experiences) that
are related to the entrepreneurial role. By contrast, Germany is a coordinated market economy
where women are not necessarily expected to work. Role expectations in the society and high
average household incomes allow women to fulfill a domestic role. Especially in the Western
part of Germany where this study was carried out, role expectations in favor of women fulfilling
a domestic role have predominated. As a consequence, a significantly lower portion of women
have been participating in the workforce as compared to East Germany, a part of the country that
underwent a transition from a socialist to a market economy. German women are less likely to
gain specific human capital during dependent employment. We can, thus, assume that compared
to male entrepreneurs (West) German women are even more disadvantaged regarding the
acquisition of specific human capital than Chinese women because role expectancies should be
more pronounced in Germany as compared to China. Therefore, we propose that:
Hypothesis 2: The gender difference in specific human capital is significantly lower in China
than in Germany.
Gender Differences in the Relationship between Human Capital and Entrepreneurial
Success in Different Cultural Contexts
Human capital theory was originally developed to explain income differentials between
employees (Becker, 1964). In his seminal work, Becker (1964) argued that investments in human
capital influence the structure and the distribution of personal income (Becker, 1964). While the
traditional human capital approach focused on employees rather than entrepreneurs,
entrepreneurship scholars have studied the influence of human capital on firm survival and
success (e.g., Brüderl, Preisendörfer, & Ziegler, 1992; Bates, 1985, 1990). Due to its
idiosyncratic and socially complex nature, human capital embodied in knowledge and skills of
founders is rare, difficult to trade, imitate and substitute and, thus, fulfils several of the criteria
for sources of competitive advantage mentioned by the resource-based view (Barney, 1991; Amit
& Schoemaker, 1993; Hatch, & Dyer, 2004). The most important question is, however, whether
and how founders’ human capital can be utilized to create value in entrepreneurial firms.
Entrepreneurs often play a dominant role in their business, especially when they are starting
small. A high degree of human capital has several advantages for the founded business: First,
6
individuals with a broader general knowledge base have a better ability to effectively scan their
environment and identify opportunities (e.g., Davidsson, & Honig, 2003; Ucbasaran, Westhead,
Wright, & Binks, 2003; Shepherd, & DeTienne, 2005; Ucbasaran, Westhead, & Wright, 2008) –
the core task of an entrepreneur and the prerequisite for entrepreneurial growth (Shane &
Venkataraman, 2000). At the same time, entrepreneurs with a high degree of human capital are
capable of successfully exploiting opportunities. Human capital of founders increases their
productivity resulting in higher firm profits which can be used to finance strategies for further
growth (Bates, 1985). For the above-stated reasons, entrepreneurial firms should benefit from
their founder’s human capital.
Gender studies in entrepreneurship research have frequently demonstrated that businesses run by
women under-perform firms run by male entrepreneurs in terms of economic success (see Rosa,
Carter, & Hamilton, 1996 and Parker, 2009 (chapter 6) for a literature review). There has been an
ongoing discussion on the causes for performance differentials between women and men
businesses. Systematic differences between male and female entrepreneurs exist for example
regarding the size of business start-ups (Du Rietz & Henrekson, 2000), growth aspirations (Cliff,
1998) and industry choice (Du Rietz & Henrekson, 2000). Empirical evidence on gender
differences regarding human capital is mixed. Despite the large body of research on gender
differences in human capital the different performance effects of human capital for businesses
run by women and men remain unclear (Brush, Carter, Gatewood, Greene, & Hart, 2004). A
notable exception is a study by Kalleberg & Leicht (1991) who examine the effect of different
human capital-related variables on entrepreneurial success of male and female business owners.
From a resource-based view (Barney, 1991), a unique set of different resources at founding is
critical for new venture survival and economic success. Female entrepreneurs are somewhat
disadvantaged when it comes to providing financial capital to their business. Women usually
have income losses when they interrupt their career in order to take care of their children.
Furthermore, differences in pay structure between men and women constrain women’s
opportunities to accumulate financial capital for starting a business. For example, according to
the German Institute for Employment Research (2009) [Institut für Arbeitsmarkt- und
Berufsforschung], female full-time employees earn 24 % less than male full-time employees
7
(IAB, 2009). As a consequence of such wage inequalities, female entrepreneurs have less starting
capital on average than men (Brush 1992; Verheul & Thurik, 2001). Women also make less use
of external financing (Greene, Brush, Hart, & Saparito, 1999). Chandler and Hanks (1998)
demonstrate that financial and human capital are substitutable, i.e. that the same economic
performance can be achieved with high (low) levels of financial and low (high) levels of human
capital. Financial institutions such as banks or venture capital firms take the human capital of
business owners into account when making decisions about providing financial capital. Human
capital serves as a signal to potential employees and lenders and can, thus, enhances
entrepreneurial growth indirectly through an easier access to other human resources and a
decrease in capital constraints (Parker, & van Praag, 2006; Backes-Gellner, & Werner, 2007).
For example, venture capitalists apply management skills and experience as criteria for assessing
the performance potential of firms (Zacharakis & Meyer, 2000). Because women are
disadvantaged regarding the accumulation of financial assets as well as the access to externally
provided financial and other resources we argue that human capital is a more important resource
for female than for male business owners. Substitution of financial capital through human capital
is crucial for women due to the above-stated disadvantages compared to male entrepreneurs. In
addition, a recent study suggests that human capital increases growth expectancies of female
entrepreneurs but does not affect growth expectancies of male entrepreneurs (Manolova, Carter,
Manev, & Gyoshev, 2007). We assume that women entrepreneurs benefit more from a higher
level of knowledge and skills than men. Thus, we hypothesize that the strength of the
relationship human capital and entrepreneurial growth depends on the business owner’s gender.
This applies to both types of human capital because general and task-specific knowledge and
skills can be useful as (partial) substitutes for financial and other constraints women are facing
due to role expectations in the society.
Hypothesis 3: The relationship between general human capital and entrepreneurial success is
stronger for female than for male entrepreneurs.
Hypothesis 4: The relationship between specific human capital and entrepreneurial success is
stronger for female than for male entrepreneurs.
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Since role expectations are developed in a society and, therefore, largely depend on the cultural
context (Eagly, 1987), we assume that gender differences in human capital-success relationships
are associated with the national culture. The arguments developed here are similar to the
arguments justifying hypothesis 2. Due to its socialistic economy, Chinese women actively
participate in the economy in China. Thus, role expectations in China do not necessarily assign a
domestic role to females. In contrast, in the (West) German economy, many women fulfill a
domestic role and do not actively participate in the economy to a high degree as they do in
China. Since female entrepreneurs violate role expectations by choosing the entrepreneurial role
in Germany, female entrepreneurs need to create legitimacy in order to be successful. Human
capital creates legitimacy because it indicates that the entrepreneur is capable of running a
business successfully (Aldrich, 1990). Thus, it serves as a positive signal to resources providers
such as lenders and venture capitalists, customers, suppliers, employees and other stakeholders
that may have an influence on firm success (Parker & van Praag, 2006; Backes-Gellner &
Werner, 2007). Such positive signaling should be especially useful for female entrepreneurs in a
society that associates women with a domestic role. Social structures also influence gender wage
inequality. Such inequalities still exist in many countries, but they have been declining in recent
years (IAB, 2009). The results of a study recently presented by the Institute for Employment
Research (2009) [Institut für Arbeitsmarkt- und Berufsforschung] indicate that German women
are still disadvantaged regarding the access to higher-paid jobs. As a result of the remaining
social structures in favor of domestic roles for women, Germany was the only European country
where the wage inequality between men and women could not be decreased within the past 15
years (IAB, 2009). In Germany, female entrepreneurs do not only violate role expectations, they
have also considerable disadvantages concerning the accumulation of start-up capital. Thus,
female entrepreneurs are forced to develop more legitimacy than male entrepreneurs in
Germany, while this effect is less prevalent in China as an economy where women actively
participate in the workforce. Therefore, we hypothesize that:
Hypothesis 5: The gender difference in the relationship between general human capital and
entrepreneurial success is lower in China than in Germany.
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Hypothesis 6: The gender difference in the relationship between specific human capital and
entrepreneurial success is lower in China than in Germany.
METHODS
Sample
In order to test our hypotheses, we use data collected in a larger project on entrepreneurship in
China and Germany funded by the German National Science Foundation. This study compared
two samples of business owners/managers from China and Germany. The data were collected in
2004 and 2005. In order to ensure that the samples are comparable, the participants were selected
by using three criteria: First, the participant had to be the owner and active manager of the
business (Stewart & Roth, 2001). A required ownership share of at least 10 percent ensures that
the participants have a significant interest in the business. Second, the enterprise had to have at
least one employee. We introduced this criterion because there is a qualitative difference
between business owners who work alone and owners who have employees (Cowling, Taylor &
Mitchell, 2004). The employment of other people is associated with changes in self-perception,
responsibilities and managerial requirements (Frese & de Kruif, 2000). Third, the participant’s
enterprise had to belong to one of four different industries: car and machinery components
manufacturing, software development, hotel and catering, and building and construction. We
introduced this criterion to ensure that we have comparable enterprises sampled in the two
countries.
We used Yellow Pages and lists provided by the Chinese local government and the German
Chamber of Commerce to identify business owners. We contacted potential participants in four
provinces (Hubei, Hunan, Jiangsu, and Zheijang) and two municipalities (Chongqing and
Shanghai) in Eastern China and one federal state (Hesse) in Germany. We phoned randomly
selected participants in order to ask for participation in our study. People who agreed to
participate were interviewed and asked to fill out a questionnaire. The Chinese sample consists
of 298 business owners; the response rate was 65%. The German sample was drawn in the
Rhine-Main area and consists of 290 business owners; the response rate was 42 percent. Among
the 298 Chinese participants were 36 women; that equals 12.1 percent. With a share of 19.0
10
percent women were slightly more represented in the German sample. These relatively low
shares of women in both sub-samples reflect the gender gap in entrepreneurial activities which
was shown in previous studies (e.g., Sternberg, Brixy, & Hundt, 2007; Bosma, Acs, Autio,
Coduras, & Levie, 2009). Because a number of participants did not answer to all questions asked
in the questionnaire, the sample size is somewhat reduced in the regressions. Exact numbers can
be found in the respective tables.
Measures
Human Capital. In line with Becker (1964), we distinguish between general and specific human
capital. General human capital is not directly related to the specific tasks of entrepreneurs, but
may be useful for the exploration and exploitation of opportunities as well as the everyday tasks
of running a business. Entrepreneurship researchers have applied different measures to assess
general human capital. Although we acknowledge that direct measures of knowledge such as
have several advantages (Unger et al. 2008), we used the number of years in education as a
proxy for general human capital of business owners (Brüderl, Preisendörfer, & Ziegler, 1992).
Specific human capital in the entrepreneurial context describes knowledge and skills that directly
relate to the tasks of an entrepreneur. Because the entrepreneur needs to fulfil a number of tasks
when operating her/his business, several different types of specific human capital can be
distinguished. Due to the high relevance of leadership and management skills, managerial
experience is an especially important type of task-specific human capital. Thus, we included a
categorial variable assessing the level of previous managerial experience. The categories include
no managerial experience (0), experience in lower management positions (1), experience in
middle management positions (2), and experience in upper management positions (3). Industry
experience can help entrepreneurs to identify opportunities, interact with customers and
employers and scan the competitive environment. We use the number of years an entrepreneur
has been working in the industry in which he set up the business as an indicator for industry
experience.
Entrepreneurial Success. Measuring entrepreneurial success has been a challenge for
entrepreneurship researchers. A variety of measures has been used in the past, often without
11
justification (Brush & Vanderwerf, 1992; Murphy, Trailer & Hill, 1996). In general, the
performance of firms is a multi-dimensional construct (Cook, Crook, & Shook, 2005) with
survival being the minimal criterion. One dimension of firm performance which is of high
relevance for entrepreneurial firms is growth. High growth enables firms to overcome liabilities
of smallness (Stinchcombe, 1965) and reach increased profitability levels in the long run. In
addition, small firm growth and the resulting job creation is a desirable outcome from a
macroeconomic perspective. Thus, we considered the growth dimension of entrepreneurial
success within the scope of this work. More precisely, we use the employment growth rate for
measuring entrepreneurial success. To account for skewness we calculated the difference
between the natural logarithm of the number of employees in 2003 and 2001.
Control Variables. The age of the firm may have a significant impact on firm performance due to
liabilities of newness (Freeman, Carroll, & Hannan, 1983) that constrain a firm’s potential to
succeed. Thus, we included firm age calculated as the number of years between the firm’s
founding and 2001. Because industry characteristics may also determine firm performance to a
significant extent (Porter, 1980), we include industry dummies to account for inter-industry
differences in entrepreneurial success.
RESULTS
To test our first three hypotheses we performed Mann-Whitney-U-Tests for the number of years
spent in education and industry experience as well as the ordinal-scaled variable managerial
experience. Table 1 depicts the results of the different tests to compare means.
--------------------------------------------Table 1
---------------------------------------------
The results show that female entrepreneurs are not disadvantaged regarding levels of general
human capital. We hypothesized that women acquire less specific human capital than males due
to role expectations (hypothesis 1). We found that women have indeed significantly less
managerial experience (Z = 4.096, p < .01). However, the other measure of specific human
12
capital –industry experience – did not show a significant gender difference. Thus, we find only
moderate support for hypothesis 1. In hypothesis 2 we argued that gender differences in specific
human capital are more severe in Germany than in China due to different role expectations and
participation rates of women in the workforce. Our data support this hypothesis in terms of
gender differences in managerial experience. Whereas we observed a significant difference
between female and male entrepreneurs in Germany, we do not find significant gender
differences in managerial experience for Chinese entrepreneurs. Again, there are no significant
effects for industry experience.
Hypothesis 3 and 4 assumed that the relationship between human capital and success is stronger
for female than for male entrepreneurs. To test these hypotheses we performed separate
regression analyses for women- and men-owned businesses. Table 2 depicts the regression
results. Model 1 includes firm age and industry dummies as controls. In model 2, we add
measures of general and specific human capital.
--------------------------------------------Table 2
---------------------------------------------
For both male and female entrepreneurs, general human capital, i.e. the number of years spent in
education, did not have a significant influence on entrepreneurial success. In addition, we did not
observe a significant difference between the coefficients for the two groups (Z = .264, p > .10)1.
Hypothesis 3 is, therefore, not supported. Hypothesis 4 assumed that the relationship between
specific human capital and success is stronger for female as compared to male entrepreneurs.
Our analyses showed that industry experience has a negative impact on entrepreneurial success
in both, men- and women-owned businesses. The negative effect is stronger for women-owned
businesses (Z = 2.232, p < .05). Thus, the gender effect is significant, but not in the hypothesized
direction. However, Hypothesis 4 was supported for management experience; managerial
experience had a significantly positive effect on the performance of women-owned businesses,
1
The Z-Value refers to the difference between the regression coefficients for women- and men-owned businesses
(Paternoster, Brame, Mazerolle, & Piquero, 1998).
13
but did not influence the success of businesses owned by men. The difference between the two
regression coefficients was significant (Z = 2.376, p < .01).
--------------------------------------------Table 3
---------------------------------------------
Hypotheses 5 and 6 proposed cross-country differences in the relationship between general and
specific human capital and entrepreneurial success. In order to test such cross-country
differences, we performed moderated regression analyses where gender is the moderator of the
human capital-success relationship separately for both countries (Table 3). Whereas we observed
a significant moderating effect of gender on the relationship between human capital and
entrepreneurial success in German firms (p = .011), our data did not show a significant gender
effect in China (p = .695). More specifically, this cultural effect refers to specific human capital.
The gender effect regarding the benefits of specific human capital, i.e. industry and managerial
experience, is prevalent in Germany, but does not occur in China. A Chow test indicates that the
results of the two regressions for the Chinese and the German sub-sample differ significantly (F
= 5.773, p < .01). In Germany, the relationship between specific human capital and
entrepreneurial success is stronger for women-owned businesses.
DISCUSSION AND IMPLICATIONS
Our analyses revealed that gender differences exist with respect to human capital itself, but also
regarding the impact of human capital on entrepreneurial success. We used social role theory to
explain these differences. Role expectations are important contextual factors which influence
gender differences in entrepreneurship. Such role expectations are embedded in the cultural
context. We, thus, proposed that gender differences do not apply universally but depend on the
national culture. Our findings largely support this proposition. We found that gender differences
are more prevalent in Germany than in China. This result indicates that gender differences are
more common in a context where women are expected to take a domestic role.
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More precisely, we found that gender differences do not exist for general human capital. On one
hand, that means that female entrepreneurs in Germany and China are not disadvantaged
regarding the level of general human capital in terms of education. Both countries underwent
reforms of the educational systems that allowed girls and women to obtain an education equal to
that of men. Shares of female students in school and university education have risen dramatically
over the past decades. However, one needs to keep in mind that gender gaps in education still
exist in rural China (Baden & Green, 1994). Therefore, studies in rural China could lead to
different results with respect to gender differences in education. In the German context, regional
variations in the education systems of the federal states should not result in gender differences.
Our data on general human capital can, thus, be expected to be representative for the whole
country. Although our findings demonstrate that female entrepreneurs in urban China and
Germany are not disadvantaged in the acquisition of general human capital in the educational
system, this result may not occur in other countries, e.g., in developing countries (Glick, 2008).
Similar studies in other national contexts may, thus, provide further insights. Moreover, we
hypothesized that general human capital may be more useful for women than for men because
female entrepreneurs benefit more from increased legitimacy through human capital due to role
expectations in the society to the disadvantage of women engaging in entrepreneurial activities.
This notion is not supported by the data. General human capital does not affect entrepreneurial
success in both, men- and women-owned businesses. One reason for this finding may be that
lenders, venture capitalists, customers and suppliers do not regard education as an indicator for
entrepreneurial capabilities. Furthermore, general human capital may indeed not be of the same
relevance for entrepreneurial success as specific human capital.
Task-specific human capital is only partially affected by gender differences. The results for
specific human capital depend on its type. Comparisons between male and female business
owners showed that there is no gender difference in industry experience. Surprisingly, we found
that industry experience is detrimental for entrepreneurial success across women- and menowned businesses. A higher level of industry experience should increase the entrepreneur’s
ability to deal with customers and suppliers, and to generate knowledge about movements of
competitors. However, a work background with experiences in diverse industries may be
beneficial in terms of opportunity recognition. Diversity of work experience enables
15
entrepreneurs to scan a broader environment including more than one industry. The combination
of knowledge about different industries may lead to new ideas that result in the creation and
exploitation of opportunities. Thus, it may be the diverse experience in several industries that
makes entrepreneurs and their businesses successful. Previous studies on the relationship
between industry experience and entrepreneurial success found inconsistent results. In a gender
study, Kalleberg & Leicht (1991) demonstrate that industry experience does not have significant
effects on business survival and success in both, men- and women-owned firms.
The most important difference between male and female entrepreneurs occurred for managerial
experience. First, women have significantly less managerial experience than men. However, this
applies only to the German context. We attribute this finding to different role expectations in the
two countries and a greater participation rate of women in the workforce in China. Even more
interesting than gender difference in managerial experience is the gender effect in the
relationship between managerial experience of entrepreneurs and the success of their firms.
German women benefit most from managerial experience. Because female entrepreneurs in
Germany violate the role expectations of the society they need to rely on specific human capital
to increase their legitimacy. Managerial experience then serves as a signal to stakeholders of the
firm, such as lenders, employees, customers and suppliers that entrepreneurs have to deal with
when aiming at successfully running a business.
A limitation of our study is the focus on only two countries which decreases the generalizability
of results on our cross-country hypotheses. More research in other cultural contexts could
provide useful insights on how role expectations affect human capital and its implications for
entrepreneurial success in men- and women-owned businesses. This line of research provides
several contributions to academic research as well as practical implications. Our results suggest
that human capital does not necessarily lead to entrepreneurial success. In fact, the impact on
success not only depends on the type of human capital, but also gender and cultural context can
explain inconsistencies in research results (Unger et al., 2008). For disadvantaged sub-groups,
human capital seems to be more important than for the whole population of business owners.
This may not only apply to female entrepreneurs in certain cultural contexts, but also to other
disadvantaged groups such as ethnical minorities. Entrepreneurs who need to build up legitimacy
16
benefit from human capital to an above-average degree. In addition, human capital can substitute
a lack of financial capital (Chandler & Hanks, 1998) which female entrepreneurs are often faced
with when starting a business.
Our results offer the opportunity to derive practical implications for (nascent) entrepreneurs,
business owners, resource providers and policy-makers. Women who have the intention to start a
business at a later stage of their lives should aim at gaining managerial experience. This is often
not an easy task especially in a society that mainly relates them to a domestic role and where
disadvantages for women in dependent employment exist. Although gender equality is a
contractual principle of the European Union, women in Germany and many other countries are
still disadvantaged regarding the filling of management positions with decision power (European
Commission, 2007). That makes it difficult for women to gain important managerial experience
before starting a business. Policy-makers should, therefore, put more effort to promote gender
equality throughout the economic system. An attempt by the German government to promote
parental leave for fathers is a first step in this regard. In addition, entrepreneurship support
programs customized for women should include training that provide women with task-specific
human capital instead of purely focusing on financial support.
17
TABLES
Table 1: Descriptive Statistics of Female and Male Entrepreneurs and Results of Mann-Whitney U-Test
- Overall Sample Female Entrepreneurs
Male Entrepreneurs
Z-Value
p-Value
N
Mean
SD
N
Mean
SD
Years in Education
68
16.066
4.959
383
15.194
5.065
.990
.322
Industry Experience
73
11.658
11.806
389
11.356
11.104
.032
.974
Managerial Experience
78
1.385
1.176
409
1.976
1.059
4.096
.000
Z-Value
p-Value
-
Chinese Subsample -
Female Entrepreneurs
Male Entrepreneurs
N
Mean
SD
N
Mean
SD
Years in Education
25
15.840
6.944
183
14.090
6.276
.773
.439
Industry Experience
27
3.278
4.805
173
5.272
6.386
1.530
.126
Managerial Experience
30
1.800
1.243
196
2.102
1.128
1.261
.207
18
-
German Subsample -
Female Entrepreneurs
Male Entrepreneurs
Z-Value
p-Value
N
Mean
SD
N
Mean
SD
Years in Education
43
16.198
3.411
203
16.172
3.400
.153
.879
Industry Experience
46
16.576
11.950
216
16.229
11.673
.308
.758
Managerial Experience
48
1.125
1.064
213
1.859
0.980
4.302
.000
19
Table 2: Results of Regression Analyses on the Relationship between Human Capital
and Entrepreneurial Success in Women- and Men-owned Businesses
Women-Owned Businesses
Men-Owned Businesses
Model 1
Model 2
Software Industry
.286
.140
.144**
.095
Hospitality Industry
.067
-.066
-.031
-.067
Car and Machinery
Components Industry
.237
.307***
.276***
Firm Age
-.256
-.216***
-.128**
.320*
-.011
Model 1
Model 2
Years in Education
-.045
.004
Industry Experience
-.609***
-.286***
.348**
Managerial Experience
-.005
F-Value
1.802
8.577
11.579
19.783
Adjusted R²
0.074
0.375
.130
.193
Significance of R²
Change (p-Value)
.150
.001
.000
.000
37
37
236
236
N
* p < .10
** p < .05
*** p < .01
Dependent variable: employment growth rate
20
Table 3: Results of Moderated Regression Analyses on the Relationship between Human Capital and Entrepreneurial Success in
Chinese and German Businesses
All Businesses
Software Industry
Hospitality Industry
Car and Machinery Industry
Firm Age
Years in Education
Industry Experience
Managerial Experience
Gender
Years in Education x Gender
Industry Experience x Gender
Managerial Exp. x Gender
F-Value
Adjusted R²
Significance of R² Change
N
* p < .10
** p < .05
.103*
-.069
.268***
-.121**
-.004
-.322***
.056
.008
26.424
.220
.000
261
Chinese Businesses
.096
-.093
.262***
-.106**
.200
.050
-.416**
.081
-.244
-.402**
.520***
.003
-.288**
.162
-.146
.085
.063
-.248***
.205**
31.077
.246
.003
261
9.579
.111
.000
119
*** p < .01
Dependent variable: employment growth rate
21
.006
-.294**
.152
-.148
.337
-.333
-.380
.378*
-.289
.465
.145
10.062
.098
.695
119
German Businesses
.228***
.031
.133*
-.079
-.098
-.268***
.108
-.016
10.901
.139
.000
142
.228***
.017
.130*
-.072
.091
.298
-.480**
.211**
-.224
-.627***
.683***
14.711
.176
.011
142
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