Investigating gender dynamics on a Dutch
crowdfund platform:
Closing the female entrepreneurship and investor gap?
University of Amsterdam
MSc. Business Administration
Entrepreneurship & Innovation Track
Name: Mick Gromotka Student number: 10669132
First Supervisor: Dhr. Dr. G. T. Vinig Second Supervisor: ?
Statement of originality
This document is written by Student Mick Gromotka who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Contents: 1.0 Abstract ... 5 2.0 Introduction ... 6 3.0 Literature review ... 10 3.1 Crowdfunding ... 10
3.1.1 From crowdsourcing to crowdfunding ... 10
3.1.2 Definition of Crowdfunding ... 11
3.1.3 Industry development ... 12
3.1.5 Research streams ... 15
3.2 Relevant research gender differences ... 20
3.2.1 Gender differences in Entrepreneurship ... 20
3.2.2 Female Investment and funding success ... 22
3.2.3 Homophily ... 24
3.2.5 Team formation ... 25
3.3 Gender related crowdfunding research ... 26
4.0 Methodology ... 28
4.1 Research approach ... 28
4.2 Data collection ... 28
4.3 Data preparation ... 29
5.0 Analysis / Results ... 32
5.1 Descriptive statistics dataset ... 32
5.2 Differences in Entrepreneurs ... 33
5.2.1 Entrepreneurial participation per gender per category ... 33
5.2.2 Gender and funding success ... 35
5.2.3 (Fe)male success rates ... 36
5.2.4 Success premium ... 39
5.3 Gender and investors ... 40
5.3.1 Investor participation per category per gender ... 41
5.3.2 Investors and team composition ... 43
5.4 Donation/Loan gender differences ... 44
6.0 Discussion ... 47
6.1 Gender and Entrepreneurship ... 47
6.3 Gender and investors ... 49
6.4 Donation/loan-based crowdfunding behavior ... 51
6.5 Limitations and future research ... 52
7.0 Conclusion ... 54 8.0 Reference list ... 56 Appendices ... 62
1.0 Abstract
This research investigates gender differences on a Dutch crowdfund platform. In particular we look if crowdfunding has the potential to free the entrepreneurship and capital markets by serving as a tool for both female entrepreneurs and female investors to participate more fully. We found that female entrepreneurs are slightly more active compared to the traditional markets. The success rate of female entrepreneurs exceeds that of their male counterparts and is statistically significant in some categories. Single female entrepreneurs set their funding goals lower then man in every category, but at the same time they were also found to be more successful in every category; indicating that female entrepreneurs could possibly ask for more capital when starting a campaign. There was a high number of female investors on this platform (55%), and we found that female investors, across all categories, significantly invest more (by number of investors) in projects that were led by a female entrepreneur. At last we found that male investors invested a significant higher amount (almost twice the amount of female investors) compared to female investors.
2.0 Introduction
In recent years there has been a notable global trend in the economic sector going on. The number of women as workers participating in the labor market increased significantly. A large percentage of these women began working as an entrepreneur. Because of this significant growth in the group of mainly small independent entrepreneurs, numerous researchers were prompted to examine the issue of gender and entrepreneurship, although most of the research has taken off recently (Carter & Bennett, 2006). Many studies focused primarily on the cause of the aforementioned growth, while in more recent research the focus shifted more towards the differences between male and female entrepreneurship.
The more recent studies put more emphasis on general issues related to leadership within businesses run by women. One of the main findings is that women who start a business can be identified as a group that has struggled to attract funding. Female entrepreneurs repeatedly encounter different barriers when creating a new venture or searching for financing. Since the economic crisis in 2008, getting a loan for your new venture has become increasingly difficult (Sannajust, 2014). Therefore entrepreneurs around the world have been looking for new ways to attract financing. In the past few years, a new form off financing called crowdfunding has been of help to thousands of entrepreneurs worldwide: Crowdfunding. Crowdfunding is asking a crowd of people, typically via the Internet, to help raise funding for a specific cause or project. The project owner can either receive a donation, or reward a certain end product for the money exchanged. Other alternatives are giving equity or debt to investors. Where traditionally most investors are found in the friends and family circle, the nature of crowdfunding platforms enables entrepreneurs to reach an undefined large network of potential investors. Since literature indicates that female entrepreneurs may face higher financing barriers than men it is interesting to investigate whether these conditions change with this new form of financing (Coleman & Robb, 2009).
Women make up about one third of all entrepreneurs in the Netherlands, and more than 85% works independently. Even today the industries in which woman are active, differ from male entrepreneurs. The largest number of female led businesses can be found in the personal services sector in the following branches: Information & communication, consultancy & research, education & culture and sport & recreation (KvK, rapport startersprofiel 2014). The difference is even larger on the investor side. In terms of access to networks and capital in our society (Europe, Netherlands) men and women still seem to operate in separate business networks. The implications for female entrepreneurs are alarming: Almost 95% of venture capital partners and 95% of informal investors in the Netherlands are men.(Kaufman Foundation, 2011; DELL, 2013; Europese Commissie OECD). Women investors and entrepreneurs are clearly not operating at the same rates as men do.
Another problem is that investors and female entrepreneurs barely meet, while venture capitalists and angel investors heavily rely on trusted relationships (Kaufman Foundation, 2011). Often investors meet entrepreneurs at an early stage; this creates trust between the investor and the entrepreneur, and therefore creates a perception of reduced risk. A trusted business relationship is the primary reason for investors to do an investment in a startup. Entrepreneurs who do not naturally operate in each other’s networks will consequently have a disadvantage. The growth of female entrepreneurs is therefore limited because they don’t seem to have access to (male) capital. On the other hand, investors limit their opportunities because they do not have access to the full number of deals (Kaufman Foundation, 2011; Dell, 2013).
Prior research suggests that this is one of many obstacles investors and entrepreneurs face. Men and women also tend to prefer different jobs, occupations, and firms (Baron and Bielby, 1985). Other issues entrepreneurs face on the demand side is a preference for industry sector, profits, risk, control and growth, while on the other hand investors show preference for specific types of firms, industries and entrepreneurs. (Carter and Rosa, 1998; Orser et al., 2006). Further,
research has shown evidence of woman having significantly more problems in terms of relationships with their investors (Marlow, 2005). Based on these observations, we will investigate whether this is also the case with entrepreneurs and investors on a Dutch crowdfund platform. Because crowdfunding is different from the current ways to raise capital, it has the potential to reduce or even eliminate differences between men and women seeking financing and/or engaging in entrepreneurial activity. This study concentrates on this issue. The central question of this study is the following:
‘Does crowdfunding have the potential to free the entrepreneurship and funding markets by serving as a means for both Dutch female entrepreneurs and female investors to participate more fully?’
We used data of a Dutch crowdfund platform crowdaboutnow.nl and since these are rather small crowdfund platforms, data of 184 projects and 15879 investors has been collected. The platform works with the ‘all or nothing model’, this means that the entrepreneur has to set a goal and must reach it in order to get access to the invested funds. This is beneficial for the research as it sets a clear definition of success. The platform utilize the donation-based and loan-based model, which means that the investor can either donate, receiving nothing in return, or the investor can has the possibility to invest in a project and is promised an interest on the funds that they loan.
With the help of this platform we will investigate whether or not this crowdfunding platform attracts higher female participation as project leads then in entrepreneurship more generally. On the demand side, we document different participation rates by men and women across the different industries they are active in. Literature indicates that female entrepreneurs tend to be more risk averse; therefore we will investigate the average financing goal by the gender of the entrepreneur. Furthermore, the benefits or loss of team formation will be
researched. On the investor site we investigate whether the platforms attracts more participation in investing by women, compared with business investing more generally. We also investigate the preferences of investors for specific types of industries; male dominated industries tend to attract more male investors, which could indicate that there is a preference for same sex investments. At last we will investigate whether there are differences in donation and loan-based projects of investors and project initiators.
3.0 Literature review
This chapter gives an overview of the relevant research and literature on crowdfunding, female entrepreneurship and gender biases that account for the many aspects the phenomenon has. For this purpose journal articles, industry reports, various online resources and working papers were used. The amount of literature on crowdfunding that qualifies as academic is increasing over the last few years but is arguably still quite limited.
3.1 Crowdfunding
3.1.1 From crowdsourcing to crowdfunding
Crowdfunding is a concept that can be understood best as a corollary of the concept of crowdsourcing. In theory crowdsourcing comes down to the use of knowledge and skills of different users to back up or accelerate the development of products or the solving of complex issues. Although the concept itself has been put to use for a long time, the term crowsourcing has only been widely adopted since 2006. Among others, Brabham (2008), Schwienbacher et al. (2010) and Belleflamme et al (2011) believe that the article The Rise of Crowdsourcing written by Jeff Howe (2006) was the starting point for the emergence of crowdsourcing. Howe (2006) defines crowdsourcing in his article as follows:
“The act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and general large) network of people in the form of an open call.”
Crowdsourcing is not directly focused on obtaining financing. Crowdsourcing often involves connecting the knowledge of the crowd with a problem or dilemma of an organization. Reichwald and Piller (2009) distinguish two different types of crowdsourcing: mass customization and open innovation. Mass customization refers to a process in which individual
consumers can adapt a product to their own requirements and criteria. Open innovation is more about the collaboration between an organization and its customers in the development or improvement of new or existing products. These collaborations can be rewarded, but this does not necessarily have to be with money.
In a broad sense crowdfunding can be seen as a central part of crowdsourcing, using the crowd as a source of feedback, ideas and solutions for the development of new businesses. The crowdsourcing definition can provide a key understanding why crowdfunding is embedded into crowdsourcing. In crowdfunding initiatives, consumers can volunteer to provide help into the development of a product or the support a cause with financial support. From this perspective, crowdfunding is a subset of crowdsourcing, since the latter includes also financial help (Belleflamme et al. 2010).
3.1.2 Definition of Crowdfunding
Crowdfunding refers to the idea that small individual contributions of money are combined to fund a certain goal. Building upon the meaning of crowdsourcing Schwienbacher and Larralde (2010) define crowdfunding as:
“an open call, essentially through the Internet, for the provision of financial resources either in form of donation or in exchange for some form of reward and/or voting rights in order to support initiatives for specific purposes”(p. 4).
In short, a business or project leader needs money for a new project and asks the crowd (the public) for money on a crowdfunding platform. The crowd then has the choice to meet the request and can provide money for the project. While this call can be made offline, usually an online platform serves as a market place. The money is given on the basis of a contract, without the intervention of a bank or other financial institution. In return, the investors can get some form of reward or simply donate (Schwienbacher & Larralde, 2010).
Donation-based, reward-Donation-based, equity-Donation-based, and Lending-based crowdfunding. Investors of donation-based crowdfunding do not receive a valuable reward for their donation, while investors of reward-based crowdfunding receive an item or a service in return for their contribution. This form is also referred to as pre-ordering or pre-selling (Hemer, 2011). In contrast, equity-based and lending-based crowdfunding promise a return on the initial investment. Lending-based crowdfunding provides investors with an interest rate that varies typically between 4 to 12% per year over the invested amount and equity-based crowdfunding gives investors the possibility to buy a stake in the project or company (Crowdfundinsider.com, 2013). More recently lending-based crowdfund platforms where private lenders provide capital to SME’s are gaining popularity. The focus of this thesis is on donation-based and lending-based crowdfunding.
Most crowdfunding platforms make use of the all-or-nothing model, which means that funds for a project are only rewarded when the set goal of the project is met, but some platforms wield different forms such as take-it-all or 90% tipping point models (Douwenkoren.nl, 2014). 3.1.3 Industry development
Crowdfunding on the Internet is a new industry that has emerged from a number of coherent developments. In particular, Web 2.0 and social media, but also the advancement of information and communication technologies has formed the technical basis for rapid financial transactions and communications. Reaching a large crowd in a cost efficient manner has therefore become possible (Pierrakis & Collins, 2013).
Many scholars argue that crowdfunding originated around 2006 in the United States with the launch of the well-known platform SellaBand.com, one of the earliest successful crowdfunding platform. Sellaband.com was a music platform where artists could use crowdfunding in order to finance their album. Artists could then record an album if they were able to raise $50,000 (SellaBand.com, 2010). Sellaband.com is the clear example that an alternative was created because of a lack of finances in the creative sector, a sector that is
typically underfunded. On the other hand, consumers, citizens and people want to play a greater participatory role through the use of Web 2.0 technologies. The capabilities of the new technologies, the will to participate more democratic and the lack of capital in the creative industries was the foundation for the emergence of crowdfunding.
Another reason for the explosive growth of crowdfunding, especially for equity and loan-based crowdfunding is the financial crisis beginning 2008, making it virtually impossible for entrepreneurs to find start-up capital. As banks were less willing to lend money to entrepreneurs and project owners, entrepreneurs went looking for funding outside the traditional ways. The lack of trust in the current financial system among all layers of the population is another reason for the development of crowdfunding (Ahlers, 2012).
At the end of 2013, more than € 5.1 billion has been raised through around 536 crowdfunding platforms worldwide. The majority of these platforms can be found in North-America (59%) and Western-Europe (37%) (Statista.com, 2013). The Dutch market is still rather small, raising 32 million in 2013, but growing at a fast pace with 128% in 2013 (crowdfunding.nl, 2013). In 2012 there where over 1 million successful projects on all crowdfund platforms combined and the market is still rapidly growing. Reward-based crowdfunding has grown by 524% in 2012 and accounts for 43% of the industry (Appendix 1). Equity-based crowdfunding raised the most funds per project as compared to donation-based and reward-based crowdfunding with 68% of the donations over $50.000 dollar. The most active categories could be found in social causes (30%) and business & entrepreneurship (16.9%) (Crowdsourcing.org, 2012). Interestingly the Dutch market differs from the American market in terms of funds invested per crowdfund category. While the North-American market is dominated by rewards-based and donation rewards-based projects, the Dutch market seems to focus more on lending-rewards-based projects which consist of a lot of SME’s. Market leaders in this category are geldvoorelkaar.nl and crowdaboutnow.nl, the latter also operating the donation-based model.
Table 1: CF projects Invested per category in the Netherlands (millions)
Social projects Creative SME’s
Projects Amount Per project Projects Amount Per project Projects Amount Per project
2012 199 € 1.00 € 5,025 262 € 1.90 € 7,252 108 € 4.10 € 37,963
2013 409 € 1.30 € 3,178 482 € 2.90 € 6,017 367 € 27.80 € 75,749
2014 673 € 6.50 € 9,658 752 € 5.40 € 7,181 602 € 51.10 € 84,884 Source: Het crowdfunding rapport, 2014
In 2014, 63 million was raised in the Netherlands through crowdfunding. That is double compared to 2013. In 2014, more than 2,000 projects and companies where funded successfully. In total the Dutch crowdfund market has retrieved more than 100 million Euros through crowdfunding. Crowdfunding is taking a more solid position in financing options for both social projects, creative projects and enterprises. The increased awareness and increased use of crowdfunding enhanced the growth of the market. It is notable that more and more established organizations (such as cultural institutions and SMEs companies) are using crowdfunding to finance a part of a project or working capital (Het Crowdfunding Rapport, 2014).
As the crowdfunding market grows and diversifies, initiatives are established to increase sustainable growth. One of those initiatives is the regulation from the AFM (Authority Financial Markets). The AFM makes recommendations to help grow the regulation of crowdfunding at the same pace as the development of the market. Additionally the association of Nederlandse Crowdfunding has established a code of conduct , which includes focus on protecting of both funders and project owners and entrepreneurs. The association also provides guidance towards entrepreneurs, financial advisors and investors regarding the opportunities and risks of crowdfunding (Douw&Koren, 2014; Crowdfunding.nl, 2013).
Much of the entrepreneurs in the Netherlands that use crowdfunding, deliberately choose to use crowdfunding as a secondary form of financing. These businesses often provide funders with an interesting financial compensation. As you can see in Table 1, the proportion of successful crowdfunding campaigns for social projects, creative projects and businesses are roughly comparable. However, the average amount raised does differ dramatically. A social
project took an average of 9,700 euros. Creative projects had an average of 7,200 euros. And SME's took an average of 85,000 euros, double of what was raised the year before. When comparing year of year growth for the Dutch, European and Worldwide market, the Dutch crowdfund market has seen rapid growth in the beginning but that growth is slowly stagnating (Douwenkoren.nl, 2014).
Table 2: Crowdfunding Industry YoY growth (in millions)
Netherlands Europe World
Raised (m) € 3 € 14 € 32 € 63
Growth Raised (m) Growth Raised (m) Growth 2011 € 400 € 1,000
2012 460% € 487 22% € 2,000 100% 2013 129% € 1,211 149% € 4,500 125% 2014 97% € 2,957 144% € 12,500 178%
Source: Het crowdfunding rapport; Dow&Koren, 2014) 3.1.5 Research streams
Research on crowdfunding can be broadly divided into four different streams: (1) information asymmetry, which includes the general principal-agent theory, (2) entrepreneurial finance, (3) regulations for crowdfunding and (4 ) the motivation to invest in crowdfunding.
The first research stream focuses on situations where information is shared asymmetrically between project owners, intermediaries, investors, and platforms. It is mainly about the general principal-agent theory and the effects that can be described such as identifying certain effects on different variables. KortLeben and Vollmar (2012) focus on conflicts that may arise between investors, platforms, and project owners. Crowdfunding platforms in general play an important role as a mediator in reducing information asymmetry and transaction costs. They are essential for safeguarding market efficiency by reducing the risk of adverse selection and moral hazard (Berger & Gleisner, 2009). Schwienbacher and Larralde (2010) also emphasize the importance of good communication between project owners and investors and show that a strong network is beneficial for a successful campaign. In this research stream the emphasis lies on the design and capabilities of the platform. Wash and Solomon (2011) discuss what forms have more
sense for project owners and platforms in different situations. They also examined the difference between "all or nothing" and "take it all" models. Mäschle (2012a, 2012b) created a list of information that platforms should disclose to reduce information asymmetries between project owners and investors and examined the effect of "first come, first served" principle when investors invest in a project. Hemer (2011) examines which reward structures have an impact on the business model of various crowd fund platforms, entrepreneurs and investors.
Signalling effects. Another part of this research stream focuses on the investors in crowd-fund projects. Ahlers, Cumming, Günther and Schweizer (2012) make use of a data set derived from an Australian crowdfund platform to examine what it is that investors look for when they analyze projects to invest in. They found that the education and the size of the social network of the project owners played an important role in the investment choice of investors. The size of the management team, the planned exit strategy, the age of the company and the budget also played a significant role, very similar to the screening tactic of venture capitalists. Also Mollick (2013) found that investors on crowdfund platforms, consciously or unconsciously, look for the same kind of qualities as venture capitalists. The biggest difference was that investors on crowdfund platforms adhere less to the geographical distance and gender of the project owners. Herzenstein, Sonenshein and Dholakia (2011) investigate the narratives of the project owners on the project page. When the information of the project was unclear and lacked hard facts, investors used other signals to determine if they are going to invest in a project. The main focus then lay on the appearance of the project owner(s) as a measure of quality. Duarte, Siegel and Young (2012) and Pope and Sydnor (2011) show that minor things, like having pictures on the project page, has a significant impact on building trust and increases the chance of funding success. However, if hard facts are available, investors will make more use of them to proceed with an investment (Shue, 2009).
Peer behaviour and herding effects: When an individual has limited information and it is also costly to collect information, they tend to copy the behavior of other people in their environment in order to make a decision. This was also with reward-based crowd-fund platforms and the behavior of others had a significant influence on the investment decisions of the investors (Burtch et al., 2013; Ghose et al, 2013). Research in Loan-based crowdfund projects found similar findings. For example, early investments in a project by expert investors had a positive impact on the number of subsequent investors. One than relies on the skill of the expert investor to determine whether an investment is worth it (Hildebrand et al. 2013; Kim and Viswanathan, 2013).
Spatial effects: Agrawal, Goldfarb and Goldfarb (2010) found proof of spatial effects analyzing data of the crowdfund platform SellaBand. While crowdfunding over the Internet enables every citizen of the world in to invest in a particular project, data shows that the initial investments in a project comes from investors who are physically and socially close to the project owner. These early investors are divided into the three F's: Family, friends & fans and are very important for the campaign's success, as they provide a sense of trust towards other investors. The crowd fund platform largely eliminated frictions that can be caused by distance, such as monitoring of progress, but also collecting information and providing input. They could not prove that social related frictions between entrepreneurs and investors could be eliminated (Agrawal et. al., 2011). Furthermore, Lin and Viswanathan (2014) found a similar effect called "home bias". Home bias is the tendency of investors to invest in a large amount of domestic equities, despite the supposed benefits of diversification in foreign shares. Lin et al. (2014) distinguish between the economic and social perspective as an explanation for the home bias. The social perspective describes factors such as optimism towards domestic markets and homophily, which is the inclination to like people more who are comparable to themselves. The
economic perspective includes the cost of information acquisition, cultural differences and the advantage of spatial proximity in regards to information.
Entrepreneurial finance: The second research stream focuses on the potential of crowdfunding to close the so-called 'funding gap'. The "funding gap" refers to the lack of investment in the early stages of a start-up. This gap usually begins after donation and reward-based crowdfunding investments no longer meet and there is increased demand for capital. At that moment loan-based and equity-based crowdfunding seems to be a better way to raise funding (World Bank, 2013). Financing a start-up is traditionally done by banks, venture capitalists and business angels, therefore many researchers discuss whether crowdfunding of start-ups, associated with the funding gap, can be supplemented or replaced with additional investors from outside of the traditional routes. They also investigated the influence of crowdfunding on the rate of innovation and growth, and the impact on the creation of new jobs (Hemer, 2011; Hemer, et al. 2011; Tomczak et al., 2013; Dapp et al., 2014). Dapp and Laskawi (2014) discuss how you can best value a start-up. They see potential in investing in crowdfunding, and recon that there are possibilities for closing the funding gap. They also see opportunities in driving growth and innovation, but emphasize that there are risks associated with investing in crowdfunding. They think that it is still difficult to appreciate a start-up in a crowd fund platform and they find that this platform should play a greater role in crediting larger startups.
Crowdfund regulations: The third research stream viewing crowdfunding from a legal and regulatory perspective. As researchers discuss the laws and requirements to enable crowdfunding. The United States has adopted the JOBS Act, a law that makes it easier to finance start-ups by easing various securities regulations, but is currently still limited to accredited investors. Most of the studies on regulation are about creating jobs and growth by minimizing the legislation to make it easier for small businesses to raise capital from the public. The
protection of investors is central to these studies: How to ensure that project owners act responsibly with the investments received? (Fink, 2012; Cohn, 2012; Bradford, 2012; Parsont, 2014). Schwienbacher (2014) joined this discussion in the context of the Dutch crowd investing market. They give a thorough introduction of crowdinvesting in the Netherlands and it’s legal situation. Because crowd investing is limited in the US, crowd investing could grow in several European countries because the regulation on securities issuance under certain conditions can be done without approval of the state and therefore can be offered to the general public. They found that crowdinvesting is still too young to draw conclusions in terms of risk and return on crowdinvesting, because almost no investments have experienced an exit yet.
Motivation: The final research stream focusses on the motivation and decision to participate in all kinds of crowdfunding. The literature on this subject is limited, so we use the knowledge on this subject in crowdsourcing as a principle for the motivation to participate in crowdfunding. Kleemann et al. (2008) explores why people spend their time and skills to crowdsourcing activities. They thereby distinguish between intrinsic and extrinsic motivation. Intrinsic means that one can find the task in itself interesting and extrinsic motivation is a form of reward for the work the main motivator. Brabham (2008) found similar motivations to participate. He found that the financial reward was the main driver for participation in crowdsourcing and the possibility to learn something new and having fun came secondary to this. A few studies have investigated the reason why one participates in a crowdfund platform. In most cases, the understanding of the motivation of the entrepreneur is better illuminated than the motivation of the investor. The main reasons to participate as an entrepreneur include: The lack of funding capital, the use of an inexpensive form of marketing for the new company and getting feedback from people about their products and services (Gerber et al, 2012; Lambert. & Schwienbacher, 2010). Van Vliet (2014) distinguishes between three types of investors. Firstly, the investor who sympathizes with the entrepreneur(s) behind the project. Second, the investor
who is interested in the implementation or the goal of the project and thirdly, the person who is interested in the return for his donation.
To the best of our knowledge there is little published research differentiating between the gender of the project owners and the investors. The closest we could find is a working paper written by Marom et. al. (2014), they examine gender differences on the leading American crowdfund platform Kickstarter. They conclude that the participation of women, both in investment and entrepreneurship, is higher than the average in the traditional market. Since their study is focused on the rewards-based model and the Dutch crowdfund market is focused more towards the lending-based model it would be interesting to conduct a similar research in the Dutch market. In this way we hope to contribute to the research gap on the female participation in crowdfunding in the Dutch market.
3.2 Relevant research gender differences
3.2.1 Gender differences in Entrepreneurship
In the recent years entrepreneurship is seen as the growth engine of the global economy, wherein an important fact is that the number of women becoming an entrepreneur is rising faster than the number of men. Nevertheless, research has shown that some women have difficulty in setting up and maintaining their company. Although a large part of the difficulties applies to both sexes, it appears that in many cases, the problems are more significant for female entrepreneurs. This is due to factors such as a poor business environment, the choice of business types and sectors, poor information, lack of contacts and access to entrepreneurial networks, stereotyping, difficulties to reconcile between corporate and family obligations, and finally, differences in the way men and women approach entrepreneurship (Truman, 1996).
Until recently, there was an additional problem by the fact that research was largely "gender-blind". During the 70s and 80s, gender was not included in important studies as a variable that could affect the process of business formation or business routine. This aspect was
mentioned by Holmquist and Sundin (Marlow & strange, 1994; Tanton, 1994) who argue that the entrepreneurial theories are made by men, created for men and can be applied to men. The implication is either that women do not own businesses or that they do not act different from men. Even the fact that hardly any academic articles on gender-related issues have been published, underscores the male-dominated nature. This masculine approach assumes that women act on the basis of the same motivation and looking for the same rewards from their entrepreneurial activities as their male counterparts. Because there is no tradeoff made if female entrepreneurship differs from the male approach, the decision-making of financial institutions is adjusted to the analysis of experiences and actions of male entrepreneurs. Therefore women are measured based on standards that do not take into account the gender factor. Although this factor has been neglected in previous research, this factor "gender" can cause fundamental differences in motivation of the entrepreneur, which in turn can have a major impact on the way the company’s success is defined by the success of the company itself (Marlow & Strange 1994 Tanton, 1994).
In the last decade the interest for gender in entrepreneurship has become more apparent as gender is often included within entrepreneurship studies, either as a focal or control variable. Baron and Biebly (1985) documented the differences between males and females in the structure of organizations. They found that both are over/ underrepresented in very different occupations, firms, jobs and industries. In the Netherlands women make up about one third of all entrepreneurs, and more than 85% works on their own. Even today the industries in which woman are active, differ from male entrepreneurs (See Table 3). The largest number of female let businesses can be found in the personal services sector in the following branches: information & communication, consultancy & research, education and culture, sport & recreation (KvK, 2013; Rapport Startersprofiel, 2014). Other studies have also found that female entrepreneurs tend to start businesses in low-growth sectors, which are less capital intensive, an indication that
female entrepreneurs might face higher financing barriers than their male counterparts (Perry, 2002; Robb, 2002; Watson, 2003; Fairlie and Robb, 2009). However, we might expect gender gaps to be smaller in terms of participation in acquiring capital on crowdfunding platforms. Because there is little contact between investors and project leaders, it is possible that gender biases are flattened, therefore giving female entrepreneurs the feeling that they have easier access to more male dominated industries.
Table 3: Sector distribution entrepreneurs by gender in % (Netherlands, 2011)
2011 Male Female Total
Agriculture 9 % 8 % 9 %
Mining, industry, energy 5 % 3 % 5 %
Construction 15 % 3 % 11 %
Retail and repair 17 % 18 % 17 %
Hotel services 4 % 6 % 5 %
Transport, storage and communication 8 % 4 % 7 %
Financial services 7 % 3 % 6 %
Business services 21 % 21 % 21 %
Care, public administration, education 6 % 17 % 10 %
Other services 6 % 17 % 9 %
total 100 % 100 % 100 %
Source: Panteia (2014), based on CBS micro data files.
3.2.2 Female Investment and funding success
Many scholars have argued that there are significant gender differences in firm size, industry employment and firm growth rates (Bitler et al. 2001; Coleman & Robb, 2009). Cliff (1998) argues that female entrepreneurs intend to set smaller thresholds for firm growth then man, because female entrepreneurs feel less confident in running a larger sized business. Furthermore, they also seem more concerned than men about the possible risks that are associated with fast growth, deliberately choosing for a slow and steady growth rate (Croson & Gneezy, 2009; Byrnez et al. 1999). Besides, female entrepreneurs settle for less then what they intend to raise and manage to negotiate lower amounts of capital then man (Babcock et al., 2003; Babcock et al., 2006; Bowles et al., 2007). Studies carried out in Germany, the UK and the Netherlands showed
that females start ventures with smaller loans than males, and that they have less resources to bank finance, often relying on their own financing (Fourth Annual Report 1996).
Entrepreneurs play a critical role in starting organizations, in setting role expectations, creating cultures and hiring protocols (Baron, Mittman, and Newman, 1991; Baron, Hannan, and Burton, 2001; Burton and Beckman, 2007; Beckman and Burton, 2008). Why female entrepreneurs obtain and receive less startup capital is important because minimizing gender disparities in startup rates may have effects on other organizational outcomes. One of the most stated reasons as to why is the significant underrepresentation of female business angels and females in venture capital firms (Greene and Brush, 2001; Stuart and Sorenson, 2003a, 2003b; Harrison and Mason, 2007; Coleman and Robb, 2009; Miller, 2010; Canning, Haque, and Wang, 2012).
In 2013, 20,2% of all angel investments in the US was for women-led businesses. This number has grown more than 10% over the past 5 years, but still only accounts for 19,4% of all angel-backed companies in the US. Recent research in the US has shown that crowdfund platforms can significantly help lowering these barriers (Maron et al, 2014; Mollick, 2014). Maron et al. (2014) analyzed the data of 16.151 crowdfund campaigns on the biggest American crowdfund platform Kickstarter and found that female entrepreneurs accounted for 35% of the campaign leaders and 44% of the investors.
In the Netherlands the numbers are even more alarming, a study by Betlem (2014) found that only 6.4% of venture backed companies in the Netherlands is (partly) led or was created by a woman. Betlem (2014) examined shareholdings among the members of the Dutch Association of Venture Capital Association (NVP). Only 8 of the 125 active investments where from female (co)founders. Men are not only dominant at the receiving end. They also pre-dominate the investment funds. Only 3 out of 48 leading figures in the investments funds examined where female. So the Netherlands scores below par internationally (Financieel dagblad, 2013). Through
crowdfunding the market of investing in women-owned businesses gets more transparent. Due to the low threshold people who otherwise would not think of investing are more likely to invest, hence crowdfunding might partially close the gap for female entrepreneurs that seek financing. 3.2.3 Homophily
Maron et al. (2014) also noted that female investors financed the majority of female led projects. They indicated that there were signs of homophily, the tendency to like someone that is similar to one self. People of the same gender, race, and/or ethnic group tend to associate and bond with each other. Angels are more likely to invest in startups founded by entrepreneurs who are of the same gender, according to research conducted by John Becker-Blease of Washington State University and Sohl.
A McKinsey & Company report has shown that when equivalent companies pitched by either a man or a woman, the man was more likely to receive funding. Much the same way people might prefer a female childcare taker instead of male childcare taker. Women stick together in Women’s Clubs, Women’s Awards, etc. Just as men have men’s clubs and old boys network. Women are not only more likely than men to invest in women-led companies, some will sit on the boards of the companies they invest in, according to the Kauffman foundation. This also means that if more women want to get funded, more women need to become business angels, high female investor participation on crowdfund platforms thus might be the key.
Furthermore research has also found that female entrepreneurs are significantly more likely to seek financing from angel networks that have higher rates of female investors (Becker-Blease and Sohl, 2007). This implies that female entrepreneurs’ willingness to seek financing may be suppressed by the low amount of female angel investors and venture capitalists. This can be a reason why more investment platforms targeted specifically for female entrepreneurs are being founded.
Marom et al. (2014) found that only 23% of female led projects were funded by men. On the other hand, women funded 40% of female led projects. Multivariate analysis showed that there was a significant positive correlation between the sex of the project owner and the percentage of same sex investors. Furthermore, they found trough a survey that some of the smaller investments made by men in female-led projects can be attributed to homophily.
3.2.5 Team formation
Although much of the literature on entrepreneurship concentrates exclusively on the individual entrepreneur, many new ventures are in fact created by a team of individuals (Gartner et al., 1994). As a result of sex-based preference and stereotypes, female entrepreneurs face various difficulties in securing access to resources for their businesses. Specifically in male-dominated sectors such as technology, games and comics it is hard for female entrepreneurs to set foot on ground (Marom et al., 2014).
The research conducted on team formation in new ventures has rarely mentioned the impact of gender composition on the success of these ventures. Elizabeth et al. (2006) measured business performance out of a sample of 200 businesses and team formation. They found no significant differences in performance of one male or one female owned businesses. However, they did find that businesses jointly owned by 2 or more males had the highest performance. Businesses owned by two females performed extremely well, but were excluded from the research due to a small sample size (2). Overall, businesses with an unrelated male and female founder performed 15% better compared to individually run businesses. This implicates that it is beneficial for both men and women to team up when creating a new venture. Other research done by Timmons (1994) showed ventures created by teams outperform single led ventures, while Kamm and Shuman (1990) argue that team based ventures are more likely to be considered by venture capital firms for financing. Kor et al. (2000) argues that each extra team
member can contribute to the team’s diversity of views and skills, and can provide the venture with valuable resources and connections.
Marom et al. (2014) compared crowdfund campaigns on Kickstarter and found the mean number of investors for single female led projects was 65 investors compared to 99 when teaming up. This provides some evidence that teaming up can help female entrepreneurs reach larger networks of potential investors.
Statistics from the 2nd biggest US crowdfund platform Indiegogo.com (2013) also shows that it can be beneficial to partner up. When starting a campaign with 2 people chances for a successful campaign increase with 20% and campaigns run with 4 or more raise over 138% more. The crowdfund platform argues that a campaign with a team gives you a larger network to reach out to, therefore increasing chances of successful funding.
3.3 Gender related crowdfunding research
Since crowdfunding is a rather new phenomenon, the amount of research is still limited. As more articles appear, different subjects around crowdfunding are explored and documented. Above a small overview is given on gender and entrepreneurship and gender and investment and funding success. Now we will extend this knowledge to the crowdfund platforms. One of the first researches to investigate gender on crowdfund platform was conducted by Radford (2013). He compared 5 years of data of an American crowdfund platform to investigate the likelihood a project to be funded. After 2,5 years of data, the gender was published on the platform and the likelihood of funding changed significantly for female entrepreneurs. Male teachers in male-dominated sectors became more likely to be funded then male and female in female-male-dominated sectors. Marom et. al (2014) found contradicting evidence using data from Kickstarter.com, the largest rewards-based crowdfunding platform in the United States. They conducted an exploratory study on gender dynamics in crowdfunding. They found that female entrepreneurs where 7% more likely to be funded than their male counterparts, controlling for category and
fundraising goals. They also found that projects with male leadership there was a lower participation of female investors. Posegga et al. (2015) followed a similar approach on Kickstarter; however they could not show evidence of preference in same-sex investments, most likely because the sample was not controlled for same amount of investments and categories. Mollick (2014) empirically examine if higher proportions of female funders lead towards a higher success rate and find that female entrepreneurs outperform men. They do not blame the proportion of female backers for a higher female success rate, but found that a small population of female investors disproportionately supports (activist behavior) female founders in areas in which they are underrepresented. Mollick (2013) also found statistical proof that female participation on crowdfunding compared to venture capital funding was 15 times higher, providing strong evidence of less gender bias in crowdfunding then in VC selection. Our approach is closely related to research conducted by Marom et. al. (2014) on gender dynamics in crowdfunding. In the Netherlands research in crowdfunding is almost at a minimum, let alone research regarding gender differences in crowdfunding and crowd investing. This research tends to explore gender differences in donation and equity-based projects on a Dutch crowdfund platform. We explore if different variables, impact the success and participation of female and male entrepreneurs across different categories. After that we take a closer look at the investor side, exploring gender differences in investment behavior across categories. No known gender related research has been conducted based on the Dutch crowdfund market; therefore we will explore if crowdfunding has the potential to free the entrepreneurship and funding markets by serving as a means for both female entrepreneurs and female investors to participate more fully’.
4.0 Methodology
4.1 Research approach
To find answers on the research question, this research decided to use a quantitative approach. Many of the theoretical constructs and analysis as discussed in the literature review are built on the quantitative approach and it seems logical to follow that path. To gain more quantitative empirical insights in the research question, a dataset was obtained from one of the bigger Dutch crowdfund websites, including important variables such as the names of the project initiators, and the names of the investors. Statistical analyses were done to compare the results between female and male entrepreneurs and investors and additional tests were run to explore other variables that influenced these differences.
4.2 Data collection
After contacting various crowdfund platforms in the Netherlands we were able to obtain a dataset from one of the biggest platform currently operation in the Netherlands and first started operating at the end of 2012. After a meeting in which the requirements for this study where discussed a non-disclosure agreement was signed to make sure all the data would be anonymized. The data contained a total of 3 ongoing projects, 55 unsuccessful projects and 126 successful projects. Every project consisted out of 1 or more project owners/entrepreneurs. Divided over the projects a total number 15.954 investors where obtained, contributing to a total investment of over 4.56 million euros. The first project was started at the beginning of the launch of the crowdfund platform on the 28th of April 2011 until receiving the dataset on December 2014. The total dataset contained 15.957 rows of raw data which had to be sorted into usable data. First the rows where divided into columns and labelled according to the data relevant for the column. From the data the following variables where obtained:
-‐ Kind of investment -‐ Project name
-‐ Project address
-‐ Investor name -‐ Project goal amount
-‐ Invested amount by investor -‐ Address of investor
-‐ Legal form of company -‐ Start/Stop project -‐ Link to Project
Where ‘Kind of Investment’ means if the investor made a donation or provided funds as a loan, ‘Project name’ and ‘Project address’ refers to the company’s name and the place where the project was carried out. The ‘Investor name’ and ‘Invested amount by investor’ is the name of the investor and the money invested in the project he or she has invested in. 15.607 usable investor names where received, this because the platform did not require you to fill in your name in the early stages of the inception of the crowdfund platform. From these investors we first removed all the names that where either a Company (for example B.V.) or names that were impossible to identify (for example Aannemer 1) leaving the dataset with 13.466 names.
‘Project goal amount’ is the amount the project has to raise in order to receive the funds. The ‘Address of investor’ refers to the address of the investor and ‘Start/Stop project’ is the date the project started and ended (e.g. 12-02-2014/12-04-2014). The ‘Link to project’ provides a link to the project page on the crowdfund platform.
4.3 Data preparation
After the data collection, several variables were added to the dataset to be able to conduct the necessary analyses. We first labelled every project from 1 to 184. From these projects the entrepreneurs’ gender was retrieved by visiting links to the projects manually. In most cases an image of the project owners on the website was enough to determine the gender of the project
owners. If this was not sufficient, the description of the project provided a team introduction which was used as a double check. With this information a new variable was created ‘Gender project owner’. We were able to retrieve the gender of 181 projects (out of 184) because 3 projects where initiated by a company, therefore being unable to determine the gender. Multiple projects where created by a team, therefore we labeled the variable “gender project initiator” 1= male, 2= female, 3= male/female, 4= two males, 5= two females, 6= +3 containing a female, 7= +3 no females.
Next we created a variable ‘Gender investor’. To identify the gender of the investor we separated the first names from all the 15.607 investors and linked these to a list of 2000 common Dutch male and female names from various online sources to classify each investor by gender, a method used by several papers, for example Belenzon & Zarutskie (2012) and Marom et. all (2014). This left us with the gender of 12.314 investors. The other 1152 names that we were not able to obtain where then checked manually by using genderize.io, a website that gives the probability of a name being male or female by checking in a database of 200.000 first names. Ultimately, we were able to identify 13.971 (90%) out of 15.607 investors by gender. After this we calculated the number of female and male investors per project and we created two new variables called “Number of female investors” and “Number of male investors”.
In order to see if crowdfunding utilizes the proposed benefit to obtain financing from a greater distance, two variables where added; ‘State Project’ and ‘State investor’. The dataset contained all the addresses of the projects and the investors investing in each project. Of each address the state was retrieved by isolating the city name and connecting the name to a custom made script that connects the city name to the state that it is in. For this script a list of city names, postal codes and states was retrieved from postcodedata.nl. Every state was then numbered 0= Drenthe, 1= Enschede, …. 12= Zuid-Holland 13= Outside NL.
Afterwards we divided all the projects into several categories based on a report by Pantheia and CBS (Pantheia, 2014) on entrepreneurship between men and women. They consist of the following categories: Agriculture (0); Mining, industry, energy (0); Construction (0); Retail & repair (62); Hospitality services (Horeca) (57); Transport storage and communication (0); Financial & Business services (23); Education (12); Other (6). After that we created an additional category; Nature conservation (16), this because of the relatively high amount of projects within that specific group.
Next we calculated the variable ‘Total pledged per project’ for each project by adding up all the investments per project. With this data a dummy-‐variable was made called ‘Project Successful’ where the value of 1 indicates that the project was successfully funded and a value of 0 that the project has failed to meet the required goal amount. Everything as described above was done in Excel. Thus the treatment of the data in a preparatory stage was done in Excel. Once the data was ready for statistical analysis, the data was brought over the SPSS.
5.0 Analysis / Results
With all the variables in place and a clean dataset, it became possible to conduct the necessary analysis to gain insight on the research question. As mentioned before, all statistical analysis was conducted in SPSS. The following paragraphs describe the analyses made and the results of the analyses. The first part of the analysis conducted research on individual male and female led projects. Because of the relatively small sample size every analysis was complemented with teams that consisted of 2 males and 2 females. After that team formation statistics is compared to the individual analysis to see if there are any differences when teaming up. Lastly, the gender differences on the investor side will be investigated.
5.1 Descriptive statistics dataset
In order give an overview of the data we begin with the descriptive statistics of the entire dataset. The entire results section is divided in a project owner and project investor side. The project owners and the project investors each starts with their own descriptive statistics.
Overall a total of 179 finished projects where in the dataset with a total goal of over 5.7 million euros with an average goal of 32.000 per project. The total money pledged on this platform was over 4.5 million euros and averaged 25.000 euros per project. The overall success rate of the platform was found to be 70.4%.
Table 4.1: Total of 179 projects
Total goal € 5,741,731 Pledged € 4,561,783
Average goal p.project € 32,076 Average pledged p. project € 25,484
Success rate 71.02%
All the projects where divided into categories and can be found in table 4.1. The platform is headed by single male lead and 2 male teams, followed by single female lead and male/female teams. After teams consisting of 3+ members, teams consisting of 2 females where the least present on this platform. Most projects can be found in the Retail/product category (65 projects)
followed closely by the Hospitality Services Industry (Horeca, 57 projects). The Service, Education, Nature and Other categories where less present.
Table 4.2: Distribution of projects per leader(s) per category
Category
Retail/Product Horeca Service Education Nature Other Total
Male 21 17 5 4 8 2 57
Female 18 6 4 7 1 0 36
Male & Female 5 14 4 0 1 0 24
2 Males 14 10 7 2 2 2 37
2 Females 6 7 3 2 0 1 19
+3 leaders 1 3 0 1 0 1 6
Total 65 57 23 16 12 6 179
5.2 Differences in Entrepreneurs
5.2.1 Entrepreneurial participation per gender per category
First the distributional shape of ‘project goal’ was examined to determine the extent to which the assumption of normality was met. Results for the Kolmogorov-Smirnov test for normality (D = .185, p = .00) and for the Shapiro-Wil test of normality (S-W = .185, p = .00) indicated that the ‘project goal’ distribution deviated significantly from a normal distribution. Furthermore the boxplot didn't suggested a normal distribution, neither did the Q-Q plot and the histogram. The Stem-and-Leaf plot indicated 11 extremes, projects with a goal ≥ 75.000. These cases (project numbers 30, 57, 58, 74, 81, 83, 89, 93, 134,154,178) were removed from the dataset .
Overall, a total of 165 projects where found to be suitable for statistical analysis. The crowdfund platform consists of 54 projects (60%) run by one male and 36 projects (40%) run by one female. The other projects consisted of teams in different team formations and can be found in Table 5.
We used a Chi square test to find if there are gender differences in the distribution of the projects through the different categories. As shown in Table 6a, the share of female investors in Education and Retail range between 50,0-63,6%, while a majority of male entrepreneurs can be found in the Food Service Industry (73,9%), Service Industry (55,6%) and Nature conservation (88,9%) categories. These gender differences in the category distributions are comparable to the industry distribution of Dutch entrepreneurs, although a significant difference can be found in the Food Service Industry category. Here female entrepreneurs participate at only 26.1%, while industry rapports show equal participation in this category. Table 6a presents the gender distribution per category of projects that have only one project leader. In two categories, there is a male statistically-significant majority – Horeca, and Nature preservation. ∗, ∗∗, and ∗∗∗ indicate that the coefficients are statistically significantly different at the 10%, 5%, and 1% level, respectively.
Table 6a: Distribution of Projects by Gender (Single Project Leaders only, n=85) Chi square test
Gender # of projects
Category Male Female
Retail/ Product 48.5% 51.5% 33 Horeca 72.7%** 27.3% 22 Service 50.0% 50.0% 8 Education 36.4% 63.6% 11 Nature preservation 88.9%** 11.1% 9 Other 100% 0% 5 Total 58.8% 41.2% 85
Table 5: Project owner statistics.
Project owner(s) Total Percentage
Male 50 30.3%
Female 35 21.2%
Male & Female 22 13.3%
2 males 33 20.0%
2 females 19 11.5%
Mixed big teams 6 3.6%
Because of the relatively low sample size, we decided to combine projects with 2 male project leads and 2 female projects leads with the single projects leaders of the same sex. Once we did this the sample size increased to N=137 and a male statistically-significant majority occurred for Retail/ Product, Horeca, Service and Nature preservation as can be seen in Table 6b. Overall, male entrepreneurs were to be found statistically-significant at the 10% level on this platform with 74.5%. ∗, ∗∗, and ∗∗∗ indicate that the coefficients are statistically significantly different at the 10%, 5%, and 1% level, respectively.
5.2.2 Gender and funding success
We used an independent-samples t-test to examine if there are differences in the financial goals by gender within the different categories as well as the differences in successfully getting funded. Then we investigate whether there is a difference in the amount raised and success within different categories.
As seen in Table 7a, the gender differences in the mean goal are very large in some categories. Mean goals of female entrepreneurs range from €2.500 in Nature preservation to a mean goal of €22.250 in the Food Service Industry category. For male entrepreneurs the mean goals are higher and range from €5.650 in the “Other” category to €27.812 in the Food Service Industry category. Interestingly, the average goal of female entrepreneurs in the Service category
Table 6b: Distribution of Projects by Gender (1 and 2 Project Leaders of same sex, n=137)
Chi square test
Gender # of projects
Category All Male All Female
Retail/ Product 67.9%*** 32.1% 53 Horeca 82.9%*** 17.1% 35 Service 77.8%** 22.2% 18 Education 53.3% 46.7% 15 Nature preservation 90.9%*** 9.1% 11 Other 100.0% 0.0% 5 Total 74.5%* 25.5% 137
is the only category where the mean goal exceeds that of male entrepreneurs. Overall, the average goal of female led projects was €19.083 against €20.746 for men. Overall, no significant differences in average goal amount were found.
Table 7a: Fundraising campaign mean goal by gender (single project leaders) (N=84) Independent-samples T-test
Mean of goal Difference Diff at % of
female Goal
Category Male Female
Retail/ Product € 23906.25 € 21735.29 € 2170.96 +10% Horeca € 27812.50 € 22250.00 € 5562.50 +25% Service € 19727.36 € 14166.67 € -916.67 +39% Education € 23125.00 € 14404.29 € 8720.14 +61% Nature preservation € 6625.00 € 2500.00 € 4125.00 +165% Other € 5650.00 - € 5650.00 - Total € 20746.00 € 15011.25 € 5734.75 +38%
However, if we again to decide to accumulate single project leads with 2 female and 2 male teams, significant differences in goal amount arise in the Education and Other category.
Table 7b: Fundraising campaign mean goal by gender (single and same sex team project leaders) (N=137) Independent-samples T-test
Mean of goal Difference Diff at % of
female Goal
Category All Male All Female
Retail/ Product € 24446.67 € 20065.22 € 4401.45 +21.94% Horeca € 26136.36 € 20692.31 € 5444.06 +26.31% Service € 19727.36 € 20833.33 € -1105.97 -5.31% Education € 26250.00 € 13981.11 € 12268.89** +87.75% Nature preservation € 8800.00 € 2500.00 € 6300.00 +252.00% Other € 6433.33 € 25000.00 € -18566.67** -74.27% Total € 21839.04 € 19034.53 € 2804.51 +14.73%
5.2.3 (Fe)male success rates
Female entrepreneurs show significant higher rates of success compared to men: 76.4% of female entrepreneurs are successful compared to 62% of men. With the use of a Chi Square test we looked at the difference between the distribution of projects by gender. In Table 8a we see that women enjoyed higher rates of success in every category. This table presents the distribution of projects by a single project leader. First two columns are calculated from the full sample (both successful and failed campaigns). The second two columns are campaigns that were successful
