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VENTURING FOR OTHERS, SUBJECT TO ROLE EXPECTATIONS?
A ROLE CONGRUITY THEORY APPROACH
TO SOCIAL VENTURE CROWDFUNDING
AARON H. ANGLIN*
Department of Entrepreneurship and Innovation
Neeley School of Business
2900 Lubbock Avenue
Texas Christian University
Fort Worth, Texas 76109
Tel: (817) 257-4899
Email: a.anglin@tcu.edu
CHRISTOPHER COURTNEY
Department of Management
Robins School of Business
102 UR Drive
University of Richmond,
Richmond, Virginia 23173
Tel: (804) 287-1821
Email: ccourtney@richmond.edu
THOMAS H. ALLISON
Department of Entrepreneurship and Innovation
Neeley School of Business
2900 Lubbock Avenue
Texas Christian University
Fort Worth, Texas 76109
Tel: (817) 257-6435
Email: t.allison@tcu.edu
*Corresponding author
Venturing For Others, Subject To Role Expectations?
A Role Congruity Theory Approach To
Social Venture Crowdfunding
Abstract
Scant attention has been paid to the differences in fundraising for social versus commercial
ventures. We adopt a role congruity theory perspective to argue that because women and people
of color are more congruent with role expectations attributed to social entrepreneurs, they
experience better fundraising performance when raising crowdfunded capital for social ventures
compared to commercial ventures. We then argue entrepreneur race heightens fundraising
differences for men and women. Results indicate women experience better funding performance
when funding a social versus commercial venture—an effect that is larger for women of color.
Men of color experience worse performance when funding a social venture. We find no
differences for White men.
Introduction
Social entrepreneurs face significant challenges in acquiring funding because doing social
good does not always align with early-stage investors’ motives which often emphasize growth,
market share, and the maximization of future economic gains (e.g., Gupta et al., 2020; Rey-Martí
et al., 2019). Crowdfunding has emerged as a viable alternative funding source for social
ventures, yet we know little about why crowdfunding backers may support an entrepreneur
creating a social venture compared to those creating a commercial venture (Calic &
Mosakowski, 2016). This oversight is important for three reasons. First, a scattering of recent
work has begun to note that the drivers of crowdfunding for social ventures differ from those of
commercial ventures (e.g., Parhankangas & Renko, 2017). Thus, we cannot assume current
knowledge concerning the predictors of crowdfunding applies directly to social ventures.
Second, because social ventures remain an emerging venture type and are less well understood
by external stakeholders (Battilana & Lee, 2014), it is difficult for social entrepreneurs to know
what stakeholders expect when funding a social venture. Yet, crowdfunding contributions are
often shaped by broadly held expectations of funders (Anglin et al., 2018b; Warnick et al., 2021).
As such, it is vital to understand how differing expectations for social versus commercial
entrepreneurs may shape crowdfunding outcomes. Third, social ventures can potentially address
poverty, gender and racial inequities, or environmental challenges (Saebi et al., 2019), but these
ventures cannot move forward without financing. Given the recent popular interest in tackling
social challenges (Baskin, 2021) and that crowdfunding may be a critical source of financing for
social ventures primed to tackle such challenges, it is incumbent on researchers to demarcate
why a social venture may be funded compared to why a commercial venture may be funded.
We seek to extend recent inquiry concerning fundraising differences between social and
commercial ventures by leveraging role congruity theory to examine how entrepreneur gender
and race influence fundraising outcomes for social versus commercial ventures. Role congruity
theory contends that there are prevailing norms, expectations, and stereotypes (i.e., social roles)
concerning how groups of individuals should behave (Eagly & Karau, 2002). Members of a
particular social group that behave in a manner consistent with ascribed roles are evaluated
positively by others, while those that behave in a manner inconsistent with ascribed roles are
often socially sanctioned. Gender differences lie at the heart of role congruity theory (Eagly &
Karau, 2002) and play a critical role in garnering crowdfunding contributions (Johnson et al.,
2018). Likewise, whether an individual is a person of color or not is a key social role that
influences how one is perceived by others (Koenig & Eagly, 2014), has been shown to wield
substantial influence over crowdfunding contributions (e.g., Younkin & Kuppuswamy, 2018),
and may further alter the influence of established gender roles (Rosette et al., 2018). As such,
examining entrepreneur gender and race provides a natural launching point from prior work to
begin to understand why a social venture may be funded compared to a commercial venture.
Social entrepreneurs are often associated with the characteristics of compassion, empathy,
and concern for others (Pan et al., 2019; Saebi et al., 2019). From a role congruity perspective,
this would suggest that a social entrepreneur’s ‘role’ embodies communal, other-oriented
characteristics, which shares norms of behavior with the gender role typically assigned to women
(e.g., Lee & Huang, 2018). This would suggest that women, because their gender role is
congruent with the social entrepreneur role, will be evaluated more favorably when engaging in
social entrepreneurship. This may lead to better fundraising performance when raising funds for
a social venture compared to a commercial venture. In contrast, traditional commercial
entrepreneurship has been stereotyped as masculine (Eddleston & Powell, 2008). Accordingly,
we should expect men to be more favorably viewed when pursuing a commercial venture than a
social venture, potentially leading to better funding performance for a commercial venture
compared to a social venture. In addition, people of color, particularly those that are Black and
Hispanic, are often associated with social and political activism to bring about change and help
those that are disenfranchised (Garay et al., 2019; Wilkin et al., 2009). Association with social
activism and social organizations makes it more likely that people of color would appear
consistent with the role of a social entrepreneur. Thus, we expect that entrepreneurs of color will
be evaluated more favorably when seeking funds for a social venture compared to a commercial
venture. In contrast, because White individuals do not possess the same association with social
activism and concern for change, they may appear more congruent with a commercial venture.
As such, they should experience better funding performance when raising money for a
commercial venture compared to a social venture.
While isolating the influence of gender and race can set the stage for understanding how
these characteristics shape funding, individuals occupy both roles simultaneously (e.g., White
woman, Black man, etc.). Gender roles and associated stereotypes may be heightened, mitigated,
or altered depending on whether or not an individual identifies as a person of color (Rosette &
Livingston, 2012; Sanchez-Hucles & Davis, 2010). We argue that whether an entrepreneur is a
person of color strengthens the influence of gender when raising funds for a social venture
compared to a commercial venture. Women of color, in particular, are frequently associated with
social activism, feminism, and non-profit work (Adesaogun et al., 2015; Cole, 2009). From a role
congruity perspective, dual role congruity for women of color suggests that the funding
performance difference between a social versus commercial venture will be greater for women of
color than for White women. Further, research comparing attitudes toward managers of differing
races reports that men of color are stereotyped as more agentic, less competent, and having fewer
social skills than White men (e.g., Block et al., 2012; Moss-Racusin et al., 2010) and generally
elicit more negative attitudes than do women of color (e.g., Phills et al., 2018). These stereotypes
about men of color suggest that, compared to White men, they may reflect a larger departure
from the social entrepreneur 'role.' As such, we also expect that the funding performance
difference for men between a social versus commercial venture will be greater for men of color
than for White men.
We make two key contributions. First, we contribute to the conversation in
entrepreneurship concerning the influence of role congruity on key outcomes for entrepreneurs
(e.g., Alsos & Ljunggren, 2017; Malmström et al., 2017). We provide a detailed view of venture
finance outcomes relative to prior research examining the impact of entrepreneur gender (e.g.,
Johnson et al., 2018) and race (e.g., Younkin & Kuppuswamy, 2018) on funding decisions. In
doing so, our work illustrates that the 'double jeopardy' often faced by women of color (i.e.,
simultaneously experiencing gender and racial bias; Rosette & Livingston, 2012) are not only
eliminated when crowdfunding a social venture, but that the dual role expectations of women
and people of color combine in favor of women of color when crowdfunding for social ventures.
Our work also suggests that only focusing on gender may obscure our understanding of how
social roles influence funding relationships as the influence of gender roles may change in light
of other prevailing social roles, such as those tied to race.
Second, we contribute to social entrepreneurship research. Scholars have called for
research to evaluate how characteristics of the entrepreneur impact observable actions taken by
the entrepreneur (Saebi et al., 2019). We answer these calls by investigating how entrepreneurs'
visible characteristics influence the funding performance of socially-oriented versus
commercially-oriented crowdfunding campaigns. Our study shows that observable, surface-level
characteristics influence how potential funders perceive the act of social entrepreneurship. We
suggest that increased attention to such characteristics has the potential to improve our
understanding of social entrepreneurship outcomes. In turn, this may help us understand how
entrepreneurs can counter or embrace perceptions arising from surface-level characteristics.
Role Congruity Theory
A ’role’ is a set of core behavioral expectations attached to an individual’s position
relative to a particular social group or setting (Biddle, 1986). An individual is often perceived as
part of a social group based on surface-level characteristics, such as age, race, gender, or
occupation. Individuals are assumed to embody characteristics linked to a social group,
regardless of whether they actually possess stereotyped characteristics (Harrison et al., 1998).
For instance, women’s gender roles often imply that women should be sensitive to the needs of
others (Heilman & Okimoto, 2007). So, an individual woman may face the expectation of being
sensitive regardless of whether she actually is sensitive to the needs of others. Role congruity
theory contends that conforming to these prescribed behavioral expectations drives others'
evaluations (Eagly & Karau, 2002). Typically, acting in accordance with prescribed roles brings
benefits, while acting incongruent with prescribed roles may elicit backlash (Bolino & Turnley,
2003). For example, White male leaders are often associated with social dominance and are thus
viewed as strong and competent when they display social dominance in speeches; however,
leaders of color may face backlash for portraying social dominance as this characteristic is
inconsistent with the role of a person of color in Western society (Hoyt & Simon, 2016).
While prior work in new venture funding notes the salience of social roles across various
funding domains (e.g., Alsos & Ljunggren, 2017; Malmström et al., 2017), role expectations
should be especially salient in funding decisions for crowdfunding. Compared to other funding
domains, such as venture capital, the absence of objective information is high given the online
setting (Anglin et al., 2018a). Likewise, crowdfunding has fewer explicit norms of behavior (i.e.,
no formal vetting requirements) and is provided mostly by unsophisticated investors (Allison et
al., 2017; Davis et al., 2017). In such situations, evaluations are often made from non-objective
information, such as the observable characteristics of the entrepreneur (Lee & Huang, 2018).
Further, because role expectations are often activated by surface-level characteristics visible to
an observer and because they can be activated simply by viewing images of an individual
(Dwivedi et al., 2018), the images of an entrepreneur in crowdfunding campaigns should trigger
prevailing role expectations. Indeed, our reasoning is consistent with past work showing that role
expectations are a salient influence on contributions to crowdfunding campaigns (e.g., Anglin et
al., 2018b).
The 'Role' of Social Entrepreneurs versus Commercial Entrepreneurs
Social entrepreneurship entails the activities and processes undertaken to discover, define,
and exploit opportunities to enhance social wealth by creating new ventures or managing
existing organizations in an innovative manner (Zahra et al., 2008; 2009). Social entrepreneurs
often enhance societal wealth by focusing on poverty, inequality, or social justice (e.g., Ruskin et
al., 2016), which explains why social entrepreneurs are frequently associated with communal
characteristics, such as empathy, altruism, agreeableness, and compassion (e.g., Nga &
Shamuganathan, 2010; Miller et al., 2012; Saebi et al., 2019). These perceptions of social
entrepreneurs are not limited to academic research and frequently manifest in the mass media
(e.g., Sagawa, 2020; Stolman, 2018), suggesting that such perceptions are widely held. From a
role congruity perspective, these findings suggest that the 'role' of a social entrepreneur would
consist of expectations that a social entrepreneur is communal, compassionate, empathic, and
concerned about social causes, such as inequality and social justice.
Commercial (traditional) entrepreneurs create economic value by developing a business
that generates profit for its owners (Estrin et al., 2016). The role characteristics of a commercial
entrepreneur are ingrained in popular culture: masculine, self-reliant, overconfident, aggressive,
risk-taking, or even narcissistic (Anglin et al., 2018b; Balachandra et al., 2019; Hmieleski &
Baron, 2008). Indeed, the popular press highlights the perception that entrepreneurs are
masculine, confident, risk-takers (Carnevale, 2020). Given the prevalence and persistence of
such perceptions, it is likely that individuals evaluating commercial entrepreneurs look for
qualities consistent with these perceptions.
Gender and Raising Funds for Social Ventures versus Commercial Ventures
The role of a social entrepreneur aligns well with the gender roles stereotypically
assigned to women. The gender role of women is frequently associated with communal
characteristics (Rosette & Tost, 2010). Women are often expected to show care for others, exhibit
empathy, and be agreeable (Eagly & Karau, 2002; Graça et al., 2018). Conformity to these
characteristics may partially explain why women express greater intentions to engage in social
entrepreneurship compared to men (Dickel & Eckardt, 2020) and create 49% of social ventures
in the United States, despite founding a smaller proportion of all new ventures (39%; Terjesen,
2017). Further, Lee and Huang (2018) illustrated that women are viewed favorably when
highlighting social impact in their business plans because such framing appears consistent with
women’s gender roles.
The role of a commercial entrepreneur aligns well with gender roles stereotypically
assigned to men. The gender role of men embodies more agentic, self-oriented, and dominance-
oriented behaviors (Anglin et al., 2018b; Jonason & Fletcher, 2018). Indeed, a substantial body
of research has shown that the 'masculine' stereotype of an entrepreneur affords men a variety of
benefits within entrepreneurship because this stereotype is consistent with male gender roles
(e.g., Kanze et al., 2018; Jennings & Brush, 2013; Malmström et al., 2020). This same research
has consistently illustrated that women often suffer from bias in entrepreneurship domains
because they do not appear consistent with the stereotype.
Role congruity work finds that consistency with gender roles often elicits a positive
response from observers, while inconsistency with gender roles elicits a negative response (e.g.,
Eagly & Karau, 2002; Gupta et al., 2018; Yang et al., 2020). When applied to the fundraising
efforts of social versus commercial ventures for women and men, this suggests two predictions.
First, the role congruity for women with that of a social entrepreneur suggests women will be
viewed more positively when pursuing a social venture versus a commercial venture, for which
they may appear less congruent. Because positive perceptions increase funding performance
(Anglin et al., 2018a), we should expect women crowdfunding social ventures to have higher
levels of performance than those women crowdfunding commercial ventures. Second, the role
incongruity for men suggests that those crowdfunding a social venture will be viewed more
negatively than those crowdfunding a commercial venture, where they may appear more role
congruent. Accordingly, we should expect men who crowdfund a social venture to experience
worse performance than those men crowdfunding a commercial venture. Thus, we hypothesize:
Hypothesis 1: The relationship between venture type and crowdfunding performance
will be moderated by gender, such that women (men) will experience better (worse)
crowdfunding performance when fundraising for social ventures than when fundraising
for commercial ventures.
Race and Raising Funds for Social Ventures versus Commercial Ventures
The role of a social entrepreneur appears to align with role expectations stereotypically
assigned to people of color. Relative to White individuals in most western societies, people of
color are more frequently associated with social and political activism to bring about change in
an effort to help those who are disenfranchised (Garay et al., 2019; Wilkin et al., 2009). Such
individuals have higher participation rates in volunteer and prosocial organizations (Stoll, 2001).
Among non-profit organizations, those with more board members of color are viewed as more
authentic in their mission because they are perceived to be more sensitive to the interests and
concerns of stakeholders (Bernstein & Bilimoria, 2013).
The role of a commercial entrepreneur appears to align more closely with the role
expectations stereotypically assigned to White individuals. Compared to people of color, White
individuals show less concern on average for many social issues, such as racism and poverty, and
are less likely to take action to combat these issues (NPR/Ipsos, 2020; Quadagno, 1994).
Likewise, because White individuals often have a more privileged social status, they may be
viewed as less aware of social and community issues (Conley et al., 2010). Thus, concern for
such issues may be perceived as less authentic. Indeed, research suggests that the prevailing
archetype for a traditional entrepreneur is not only 'male,' but also 'White' (e.g., Neumeyer et al.,
2019).
Because congruity with stereotypical roles often elicits a positive response from
observers, while incongruity with gender roles elicits a negative response (e.g., Anglin et al.,
2018b), this again suggests two predictions. First, people of color will be viewed more positively
when pursuing a social venture versus a commercial venture. Thus, we should expect
entrepreneurs of color to have better funding performance when funding a social venture
compared to a commercial venture. Second, role incongruity for White entrepreneurs occurs
when pursuing a social venture. Accordingly, we should expect White entrepreneurs to have
worse performance when funding a social venture compared to a commercial venture. Thus, we
hypothesize:
Hypothesis 2: The relationship between venture type and crowdfunding performance
will be moderated by entrepreneur race, such that entrepreneurs of color (White
entrepreneurs) will experience better (worse) crowdfunding performance when
fundraising for social ventures than when fundraising for commercial ventures.
Joint Influence of Gender and Race in Raising Funds for Social Ventures versus
Commercial Ventures
People exist in multiple social groups and are subject to simultaneous, sometimes
competing, sets of role expectations. The influence of one set of role expectations is frequently
additive or interactive with another set of role expectations (Moore‐Berg & Karpinski, 2019).
For instance, work examining differences among women of color and White women in
leadership positions has revealed that, while women of color, particularly Black women, are
punished less for assertive leadership qualities than White women, they are also promoted less
than White women (Hall et al., 2019). This is likely due to the 'double jeopardy' created from
discrimination tied to being a woman and discrimination as a person of color. When examining
differences between funding social ventures compared to commercial ventures, it is likely then
that an entrepreneur’s status as a person of color will interact with their gender, further
influencing differences between funding a social versus commercial venture.
While people of color may be viewed as having more concerns for social causes, women
of color are particularly associated with social activism, feminism, and non-profit work
(Adesaogun et al., 2015: Cole, 2009). Indeed, over the past few decades, women of color have
been viewed as critical activists for social change (Farmer, 2017; Ross et al., 2016). For example,
the Black Lives Matter movement was founded by three Black women in an effort to stop
violence inflicted on Black communities. Engagement in social activism may be due, in part, to
the fact that women of color have a unique vantage point: marginalization due to race, while also
facing gender discrimination (Love et al., 2018). For instance, women of color show a higher
association with community organizing groups that seek to address inequities, and in doing so,
often openly express a commitment to their community or ethnic group (Gutierrez et al., 2012).
Taken together, this suggests women of color may be viewed as more strongly aligned with the
role of a social entrepreneur than White women. In contrast, women of color may be viewed as
even less strongly aligned with the role of a commercial entrepreneur than White women.
Men of color may readily suffer from negative stereotypes that conflict with the role of a
social entrepreneur, outweighing the potential positive association of being a person of color. For
instance, Black and Hispanic men are often viewed as more agentic and less competent than
White men (e.g., Block et al., 2012; Moss-Racusin et al., 2010). Men of color may generally
elicit more negative attitudes when observed by others than women of color (e.g., Phills et al.,
2018). Further, men of color may often be viewed as untrustworthy, leading to them
downplaying characteristics tied to specific racial groups to mitigate this lack of trust (La
Macchia et al., 2016). Finally, men of color may be viewed as more likely to harm others or
engage in criminality than White men (Steffensmeier & Demuth, 2006). While such stereotypes
harm fundraising performance in general (e.g., Anglin et al., 2018b; Younkin & Kuppuswamy,
2018), they substantially conflict with the role expectations attributed to social entrepreneurs —
that a social entrepreneur should care for others and make the world a better place. Indeed, men
of color can face backlash when advocating for social change if they appear to be in a position of
power (e.g., Duvall, 2020), and becoming a social entrepreneur may trigger this due to the
agentic associations of traditional entrepreneurs.
In sum, the dual congruity of women of color with the role of a social entrepreneur
suggests that the relationship between funding a social versus commercial venture should be
more pronounced. Specifically, the funding performance difference between a social versus
commercial venture will be greater for women of color than for White women. Moreover, role
congruity theory predicts that divergent expectations elicit negative reactions (Eagly & Karau,
2002). As such, while 'person of color' may appear congruent with a social entrepreneur, 'male'
combined with 'person of color' appears incongruent. Such conflict between roles can cause a
negative perception to be weighted more heavily. Thus, we should also expect that the funding
performance difference between a social versus commercial venture will be greater for men of
color than for White men. Thus, we hypothesize:
Hypothesis 3: There will be a three-way interaction between venture type, entrepreneur
gender, and entrepreneur race such that 1) that women of color will experience better
crowdfunding performance when fundraising for social ventures than White women, and
2) men of color will experience worse crowdfunding performance when fundraising for
social ventures than White men.
Methods
Matched Pair Sample
Crowdfunding has shown promise as a funding source for social ventures (Calic &
Mosakowski, 2016). Given our theoretical framework, crowdfunding is an ideal context because
there is limited objective information upon which backers can make a decision. As a result of this
limited information, there is a greater likelihood that resource providers may rely on prevailing
role expectations as a guide when making their contribution decisions (Anglin et al., 2018b).
Indeed, under low-information conditions, people are much more likely to rely upon stereotypes
of surface-level characteristics (e.g., McDermott, 1998), such as gender and race. These role
expectations can be triggered by the images used in crowdfunding campaigns (e.g., Anglin et al.,
2018b).
Given our study’s need to compare social ventures to commercial ventures, we settled
upon a matched-pair design, targeting a sample size of 1,000. The choice of our sample size
reflects an effort to be consistent with past research weighed against the need to code important
variables (e.g., Anglin et al., 2018a; Calic & Mosakowski, 2016). We first selected our sample
from all Kickstarter campaigns launched in 2019, excluding canceled and suspended campaigns.
Our next step was to code campaigns from the sampling frame until we had identified 500 social
ventures. To narrow down the search for potential socially-oriented ventures, we followed
Parhankangas & Renko (2017) and searched campaign texts for the keywords "social", "social
justice", "human rights", "economic development", "health", "education", and "hunger". After
compiling a list of potential social ventures, two coders followed the definition offered by Zahra
and colleagues (2008, 2009), where social entrepreneurship encompasses the activities and
processes undertaken to discover, define, and exploit opportunities to enhance social wealth by
creating new ventures or managing existing organizations in an innovative manner. The coders
independently assessed whether a campaign supported a social or commercial venture. The two
coders assessed the first hundred projects to identify social ventures. Interrater reliability was
high (Cohen Kappa = 0.90; K-alpha = 0.94); therefore, the remaining campaigns were coded by
a single coder (e.g., George & Bock, 2011) until we had identified 500 crowdfunding campaigns
for social ventures.
Each social venture was then matched with a commercial venture, using nearest-
neighbor matching without replacement (e.g., Luzzi & Sasson, 2016; i.e., there were no
duplicates or replacements, all projects are unique) using the STATA command teffects nnmatch,
which estimates treatment effects from observational data. The matching variables were selected
based on prior research. We use exact matches for whether the campaign included a video and
the product category, which reflects the industry and business of the ventures. Projects with
videos demonstrate preparation which has been linked to project success (Mollick, 2014) and
entrepreneurial intention (e.g., Wang & Wong, 2004). Our bias-adjusted matching criteria
included the amount of money the campaign sought to raise and the campaign duration in days.
The amount of money sought and the campaign duration are known predictors of project success
and are theoretically related to our independent variables of interest (e.g., Gafni et al., 2019;
Greenberg & Mollick, 2017; Saebi et al., 2019). Since the nearest neighbor matching estimators
are not consistent when matching on more than one continuous variable, we also apply the bias-
corrected heteroskedasticity-consistent estimator (Abadie & Imbens, 2011). Each matched
campaign was checked to ensure social ventures were properly matched to commercial ventures;
for the few that were initially matched to another social venture, the next nearest match was
selected. Overall, the nearest-neighbor‐matched sample appears to achieve a suitable balance.
For each covariate in the matched sample, we measured the standardized mean difference
(difference in the means for the social venture group versus the commercial venture group,
scaled by the average of their standard deviations). The value for each covariate was well under
the commonly accepted threshold of 0.1 (the largest value was 0.061) (Austin, 2011).
Dependent Variables
Past work has illustrated that crowdfunding performance is "multifaceted" and should be
operationalized through several variables (Ahlers et al., 2015; Anglin et al., 2018b). Consistent
with this work, we measure and model three dependent variables, which are formative of
crowdfunding performance (e.g., Anglin et al., 2018b). First, Funds Raised captures the total
funds raised by the end of the campaign and is a measure of total backer support for the
campaign (e.g., Anglin et al., 2018a). This measure is also important because although
Kickstarter requires that campaigns meet their funding goal to receive any funds, other platforms
do not. Thus, this measure allows for generalizability to other platforms. In addition, there is no
limit to the amount of funding that may be contributed to campaigns; thus, this measure allows
for differentiation among firms that barely meet their fundraising goals and firms that raise far
more than their fundraising goals.
Second, Number of Backers reflects the number of individual backers that contributed to
the campaign. This is important because, in addition to raising funding, a key purpose and
objective of crowdfunding is to raise awareness for a product/service/campaign, as well as to
receive feedback and input from a large number of people. Here, gaining more individual
backers is indicative of the potential market for the product or service (Anglin et al., 2018b).
Third, we use a Goal Success variable, which captures whether the funding goal set at the
beginning of the campaign was met (e.g., Oo et al., 2019). For campaigns that met their goal,
Goal Success was coded as ‘1’ and ‘0’ otherwise. Success is an important component of
crowdfunding performance because the goal amount is often the amount of money the
entrepreneur needs to execute the planned venture, and many forms of crowdfunding use an all-
or-nothing approach wherein entrepreneurs only receive funds if they meet or exceed their goal.
That said, the first two dependent variables remain important: the actual level of funds pledged
and the specific number of backers, provide useful information about backer interest and
engagement with the campaign. Overall, this set of three variables reflect the facets of
crowdfunding performance.
Independent Variables
Our first independent variable, Venture Type, takes on a value of ‘1’ if the member of the
matched pair was coded as pursuing a social venture and ‘0’ otherwise. Gender is coded as ‘1’
when the lead entrepreneur is a woman and ‘0’ otherwise. Race is coded as ‘1’ if the entrepreneur
is a person of color (POC) (i.e., non-White entrepreneurs) and ‘0’ otherwise (e.g., Anglin et al.,
2018b, Davis et al., 2017).
Controls
We include a broad set of established predictors of crowdfunding performance as control
variables (e.g., Allison et al., 2013; 2015). We control for the length of text in the campaign
where Length is equal to the natural log of one plus the number of words in the campaign
description, and for the presence of any campaign Media, which is equal to zero if a project has
no video and no image, one if it has only images, two if it has only a video, and three if it has
both images and video. To account for information outside the campaign, we include Links as the
natural log of one plus the number of external web links (Courtney et al., 2017). We control for
campaign Duration as the natural log of the number of days the campaign ran (shorter projects
have less time to raise funds; Mollick, 2014). We include the natural log of the funding Goal in
USD (e.g., Oo et al., 2019) because unrealistic project goals may make the project less likely to
succeed (Mollick & Nanda, 2016). To account for the entrepreneur’s past experience on the
platform, we reviewed each entrepreneurs’ prior campaigns, coding for whether the campaign
was for a social versus commercial venture. The resulting Social Experience variable addresses
prior social cause crowdfunding experience and is equal to the natural log of one plus the number
of prior successful crowdfunding campaigns for social ventures. The resulting Commercial
Experience does the same for prior commercial crowdfunding experience and is equal to the
natural log of one plus the number of prior successful crowdfunding campaigns for commercial
ventures. Prior studies suggest backing others’ campaigns confers a benefit; thus, we include
Backed as the natural log of one plus the number of past campaigns backed by the entrepreneur
(e.g., Anglin et al., 2018b). Last, pricing has been linked to founder gender and race (e.g.,
Younkin & Kuppuswamy, 2019). To account for the influence of gender and race on how an
entrepreneur chooses to price rewards they offer backers, we include Average Price of Rewards,
calculated as the natural log of one plus the average price of offered rewards.
Statistical procedures
We use multi-level modeling to estimate our results (e.g., Anglin et al., 2018b; Davis et
al., 2017). Crowdfunding campaigns are often nested within categories, notably the project
category (e.g., technology, design). Such categories can influence the composition of the
individual campaigns within each category; thus, the individual campaign observations are not
independent. Multi-level modeling allows us to correct for this non-independence. In our models,
our independent variables and controls comprise level 1 of the models, while the project
categories comprise level 2.
Our Funds Raised and Number of Backers variables are positively skewed, with long
right tails, suggesting a gamma distribution. Dependent variables with these distributions often
result in non-normal residuals, thus violating the normality assumption of linear models. Past
work has addressed this issue by using a generalized linear modeling (GLM) approach (e.g.,
Anglin et al., 2018a), which accounts for non-normality (McCullagh, 2018). Accordingly, we use
a multi-level generalized linear model with a gamma family and log link function for our funds
raised and number of backers models. Gamma models with a log-link function are particularly
useful for modeling non-negative data with long right tails because they are more robust to
heteroscedastic errors caused by such distributions than are natural log or inverse hyperbolic sine
transformations (Ng & Cribbie, 2017). For our goal success model, we used multi-level logit
regression.
Results
Table 1 provides descriptive statistics for our sample. Tables 2, 3, and 4 provide
coefficients, standard errors (S.E.), and p-values for our funds raised, number of backers, and
goal success dependent variables, respectively. The success coefficients in Table 4 are log odds.
Hypothesis 1 proposed that women (men) have better (worse) fundraising performance
when raising money for social ventures compared to commercial ventures. We find a positive
and statistically significant interaction for the funds raised (b = 0.577, p = 0.004) and number of
backers models (b = 0.575, p = 0.001), but not the dichotomous goal success model (b = 0.481, p
= 0.173). Figures 1 and 2 provide a visual interpretation of the statistically significant
interactions and show the marginal predicted means for each scenario. For the funds raised
models, the simple slope analysis suggests a positive and significant slope for women (b = 0.520,
p = 0.000) and a negative, but not significant, slope for men (b = -0.060, p = 0.671). For the
number of backers models, the simple slope analysis suggests a positive and significant slope for
women (b = 0.400, p = 0.000) and a negative and significant slope for men (b = -0.200, p =
0.046). Both results support the idea that women have better performance when pursuing social
ventures compared to social ventures. Men perform worse when pursuing social ventures
compared to commercial ventures when examining the number of backers.
Hypothesis 2 proposed that entrepreneurs of color (White entrepreneurs) will have better
(worse) fundraising performance when raising money for social ventures compared to
commercial ventures. None of the interaction terms yield statistically significant differences
(funds raised, b = -0.185, p = 0.441; number of backers, b = -0.201, p = 0.324; goal success, b =
-0.122, p = 0.764). This hypothesis is not supported.
Hypothesis 3 proposed a three-way interaction between venture type, entrepreneur
gender, and race where women of color will experience better crowdfunding performance when
fundraising for social ventures than White women, and men of color will experience worse
crowdfunding performance when fundraising for social ventures than White men. The three-way
interactions are positive and significant for the funds raised model (b = 2.351, p = 0.000), the
number of backers model (b = 2.137, p = 0.000), and the dichotomous goal success model (b =
1.897, p = 0.024). The significant three-way interactions provide initial support for our
hypothesis. Figures 3, 4, and 5 provide a visual interpretation of these interactions and show the
marginal predicted means for each scenario. For the funds raised model, we find a positive and
significant slope for women of color (b = 1.690, p = 0.000), a negative and significant slope for
men of color (b = -0.850, p = 0.001), and a positive and significant slope for White women (b =
0.290, p = 0.018). The slope for White men (b = 0.150, p = 0.343) is not statistically significant.
For the number of backers model, we find a positive and significant slope for women of color (b
= 1.390, p = 0.011), a negative and significant slope for men of color (b = -0.871, p = 0.000), and
a positive and significant slope for White women (b = 0.300, p = 0.014). Again, the slope for
White men (b = -0.070, p = 0.205) is not statistically significant. For the success model, we find
a positive and significant slope (i.e., change in log odds) for women of color (b = 1.160, p =
0.000) and a negative and significant slope for men of color (b = -0.940, p = 0.045). The slopes
for White women (b = 0.160, p = 0.644) and White men (b = 0.060, p = 0.832) are not
significant. In all cases, the positive slope for women of color is much larger than the slope for
White women. Likewise, in all cases, the negative slope for men of color is statistically
significant. In contrast, White men show no funding differences between social versus
commercial ventures, indicating a more pronounced difference for men of color. Taken together,
these results lend further support for Hypothesis 3.
“Insert Tables 1 – 4 and Figures 1 – 5”
Discussion
We contribute to the growing conversation in the entrepreneurship literature regarding the
influence of prevailing role expectations on key outcomes for entrepreneurs. This work has
sought to understand how entrepreneurs may benefit or suffer by appearing congruent (or
incongruent) with social roles and accompanying stereotypes (e.g., Anglin et al., 2018b;
Hmieleski & Sheppard, 2019; Malmström et al., 2017). We extend this line of inquiry to
incorporate social ventures, highlighting that fundraising for a social venture in crowdfunding
may be driven, in part, by whether the entrepreneur appears congruent or incongruent with the
‘role’ of a social entrepreneur. Consistent with this notion, we show that women experience both
a significant increase in the amount of money raised and in the number of individual backers
when launching a social venture compared to a commercial venture. For example, the marginal
predicted means for the amount of funds raised and number of backers for women launching a
social venture were approximately $30,742 and 307 backers, respectively. In contrast, for
commercial ventures, the marginal predicted means for the amount of money raised and number
of backers for women were approximately $19,627 and 184 backers, respectively. The marginal
predicted means for the amount of money raised and number of individuals backer for men when
launching a social venture were $23,121 and 222 backers, respectively; for a commercial
venture, $26,275 and 237 backers, respectively.
While role congruity work has largely focused on gender differences when examining the
impact of social roles on funding outcomes (e.g., Balachandra et al., 2019; Eddleston et al.,
2016), we call attention to the salience of incorporating whether the entrepreneur is a person of
color when examining gender differences. To do so, we draw from research that stresses that the
influence of one set of social roles (e.g., gender) is often altered, enhanced, or reduced when
viewed in light of another set of social roles (e.g., race; Cole, 2009). Here, we illustrate how
traditional gender stereotypes may be exacerbated when incorporating an entrepreneur’s person
of color status. In practical terms, the marginal predicted change in the amount of funds raised
for women of color when launching a social venture versus a commercial venture is an increase
of $22,683, but for White women, the marginal predicted change is just $6,325. The marginal
predicted change in the amount of funds raised when launching a social venture compared to a
commercial is $18,619 less when raising funds for a social venture for men of color and just
$4,553 for White men. In sum, to the best of our knowledge, this is the first study to incorporate
gender, race, and venture type in an effort to provide a more nuanced view of how the perception
of role congruence shapes funding outcomes.
An intriguing finding of this analysis is that once race is considered, differences between
White men and women appear to dissipate rather substantially, yet differences between men and
women of color are pronounced. While we predicted that race would drive gender differences
further apart, we were surprised by the magnitude of the differences. While White women
experienced a statistically significant increase in the amount of funds raised and the number of
backers, women of color experienced a nearly three-fold increase in these performance variables
compared to White women. Further, analysis of differences in the marginal means for White men
shows no statistically significant differences between funding a social versus commercial
venture. Past work in crowdfunding has frequently noted that women, unlike in other forms of
financing, generally appear to have a fundraising advantage over men (e.g., Greenberg &
Mollick, 2017; Johnson et al., 2018). This advantage has been explained by experimental results
suggesting that women are perceived as more trustworthy (Johnson et al., 2018) and that women
activist investors often seek to back women (Greenberg & Mollick, 2017). Our results might
suggest that any gender advantage is more nuanced than previously thought and may be
strengthened or weakened depending on entrepreneur race and venture type. One interpretation is
that this may be due to effects ascribed to intersectionality (e.g., McCluney & Rabelo, 2019;
Rosette et al., 2018; Sawyer et al., 2013). Intersectionality is concerned with the interconnected
nature of social categories, such as race, class, gender, or sexuality, and contends that
simultaneous membership in social categories may result in a more complex set of consequences
than consideration of any single category alone (Rosette et al., 2016). Our study is consistent
with this view suggesting that entrepreneurs experience inseparable effects of both their race and
gender during the fundraising process for social versus commercial ventures. Indeed, we
encourage entrepreneurship scholars to move beyond the examination of one category and its
corresponding social roles to adopt a more intersectional approach in answering fundamental
questions surrounding entrepreneurial outcomes.
Our work adds nuance to the work of Lee and Huang (2018), who found that social
impact framing reduces gender penalties for women during business evaluations by
professionals, although men gained no benefit from social impact framing. When considered in
tandem with this study, our work suggests context appears to alter these relationships. In the
crowdfunding context, where businesses are evaluated by unsophisticated investors, pursuing a
social venture leads to positive (not just less negative) outcomes for women. In addition, only
focusing on gender may mask the true cause of variance in funding relationships. As such, we
believe that much of the work examining gender differences in fundraising should be revisited to
incorporate effects of other observable personal characteristics, particularly race. We believe that
doing so will allow for a fuller understanding of how the interaction of gender and race shapes
the critical process of acquiring needed capital.
We also draw attention to what appears to be an emerging tension in the entrepreneurship
literature concerning the benefits of role congruity with that of expectancy violation theory. This
theory posits that forms of counterstereotypical behavior can have positive consequences when
the unexpected characteristic carries positive connotations (e.g., cooperation) and not negative
ones (e.g., dominance) (Jussim et al., 1987). For instance, our study and several others (e.g.,
Anglin et al., 2018b; Eddleston et al., 2016; Yang et al., 2020) suggest appearing congruent with
prevailing stereotypes proves beneficial for entrepreneurs, while appearing inconsistent may
harm entrepreneurs. However, this contention does not apply to all situations. For instance,
Hmieleski & Sheppard (2019) show that possessing qualities incongruent with an entrepreneur’s
gender may lead to higher creativity and teamwork levels. Likewise, the organizational behavior
literature is replete with examples of expectancy violation benefits (e.g., Luksyte et al., 2018).
Thus, it appears that whether the entrepreneur benefits from being congruent or incongruent with
established roles is dependent on the specific roles and characteristics expected in the context. If
the benefits and drawbacks of role congruence are as contextual as they appear, then it is
important that entrepreneurship researchers are cognizant of context when theorizing about how
roles shape outcomes for entrepreneurs.
Our work also contributes to social entrepreneurship research. A recent review noted that
it is “important to extend the main outcome variable [of social entrepreneurship] to include
observable action…rather than self-reported intention. This, however, implies that the analysis
needs to look beyond the individual level and consider the links to the organization level” (Saebi
et al., 2019, p. 79). We heed this call: first, we examine the pursuit of venture funding, an
observable outcome, which has only received limited attention in the literature (e.g.,
Parhankangas & Renko, 2017; Yang et al., 2020). Second, we connect individual characteristics,
specifically gender and race, as drivers of venture funding, a key organizational-level outcome
(Drover et al., 2017). In doing so, we advance social entrepreneurship research by providing a
new theoretical explanation for why some social entrepreneurs may fare better in raising funds
for social ventures compared to commercial ventures.
As of 2019, women of color run 50% of all women-owned businesses. Despite being a
major force in entrepreneurship, access to funding remains a profound problem for women of
color (Zipkin, 2018). From a practical perspective, our study suggests that women of color
interested in launching a social venture may find a greater likelihood of acquiring funding by
leveraging crowdfunding. Unfortunately, this does not extend to men of color seeking to fund
social ventures. Our success models also suggest that those entrepreneurs of color may have a
more challenging time achieving their fundraising goals in general. Indeed, while crowdfunding
has often been lauded as a means to equalize the opportunity to obtain funding, our study
suggests that this promise remains unfulfilled. More work remains in eliminating racial bias from
crowdfunding (e.g., Younkin & Kuppuswamy, 2018).
Limitations and Future Research
Our work should be considered in light of its limitations. First, we do not distinguish
among different racial groups; the non-White groups in our sample were primarily Black and
Hispanic. While it is common to examine differences among people of color and White
individuals because of the difficulty of drawing a sample with enough members in each group to
conduct adequate statistical tests (La Macchia et al., 2016), and while Black and Hispanic
individuals often face similar forms of discrimination (e.g., Hoyt & Simon, 2016), other racial
groups may have different experiences (e.g., Rosette et al., 2016). Future research might employ
vignette experiments to probe differences among racial groups.
Factors related to crowd composition may drive funding to a social versus commercial
venture. Specifically, a number of studies suggest that relationships, whether interpersonal or
parasocial, between the crowd and funders, may influence funding outcomes (e.g., Argwal et al.,
2015; Borst et al., 2018; Simon et al., 2019). For example, women funders may actively seek to
provide funds to other women (Greenberg & Mollick, 2017). Accounting for these specific,
unique relationships would be an important step in validating our results. As with all studies, we
cannot completely rule out every possible alternative explanation. While we have made an effort
to control for relevant variables that may shape performance differences and our results are
consistent with our theory, this reflects a key limitation of our study. Future research might
leverage multi-method designs to understand how the specific relationships which exist (i.e.,
social networks), as well as crowd composition, may shape fundraising differences between
social and commercial ventures.
Our study cannot assess how identity, personality differences, or other individual
differences shape the decision to pursue a social venture. However, we know that one’s
experience as a member of social groups (e.g., gender, race, ethnicity, religion, socioeconomic
status) shapes individual identity (Sanchez-Hucles & Davis, 2010), and perhaps the choice to
pursue a social venture. Indeed, work in social entrepreneurship has frequently sought to
understand the motivations and intentions of social entrepreneurs (Saebi et al., 2019). Future
research might extend this line of inquiry by examining how reflections of identity or personality
in crowdfunding campaigns can shape funding performance and how the influence of such
characteristics varies by other characteristics (gender, race, experience) of the entrepreneur (e.g.,
Anglin et al., 2018a; 2018b). For example, future work could examine how expressions of
personality (e.g., Big Five traits, narcissism, moral values) shape differences in funding
performance between social and commercial ventures in light of gender and race influences.
Further, we suggest researchers seek out other instances where gender and racial role
expectations, which typically appear harmful, may prove beneficial. For example, future research
might investigate the leadership effectiveness of women and women of color within social
ventures and link such effectiveness to measures of social performance. Given that women of
color appear to fit the role of a social entrepreneur best, they may be best able to lead the
resulting firm.
Finally, in this study, we examined social entrepreneurs at the early stages of their
entrepreneurial process. Others’ evaluations of social entrepreneurs according to gender and/or
race may change at later stages when information about success becomes available. For example,
expectancy violation theory (e.g., Lanaj & Hollenbeck, 2015) predicts countervailing biases such
that “women are attributed with higher levels of leadership emergence than men when they
engage in agentic leadership behaviors.” For our study, this might suggest that successful social
entrepreneurs experience opposing countervailing biases such that men leading social ventures
may be evaluated more favorably once the social venture has launched. While this is a
possibility, we think it is just as likely that countervailing biases may net-out role stereotypes
such that in later stages, differences in evaluation may be eliminated.
Conclusion
We draw from role congruity theory to examine how entrepreneur gender and race shape
fundraising differences between commercial and social ventures in crowdfunding. We show that
women perform better than men when funding a social venture, while men perform better when
funding a commercial venture. Women of color increase their funding performance when
funding a social venture more so than White women. Men of color perform substantially better
when funding a commercial venture, although we see no funding differences between social
versus commercial ventures for White men. For scholars, we contribute an understanding of how
social roles may impact the funding of social ventures compared to commercial ventures. For
entrepreneurs, we provide insight into how they may be evaluated, based on their gender and
race, in crowdfunding when seeking funds for a social or commercial venture.
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Table 1. Descriptive Statistics
Variables1,2 Mean S.D. 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1 Funds Raised 14599.31 54903.05
2 Number of Backers 189.75 1141.84 0.63
3 Goal Success 0.52 0.50 0.22 0.14
4 Length (ln) 6.49 1.00 0.05 0.05 0.21
5 Media 2.36 1.01 0.14 0.08 0.30 0.29
6 Links (ln) 0.88 1.00 0.13 0.06 0.24 0.38 0.32
7 Goal (ln) 9.12 1.45 0.17 0.09 -0.27 0.12 0.17 0.08
8 Duration (ln) 3.50 0.36 -0.04 -0.04 -0.22 -0.08 -0.14 -0.12 0.21
9 Backed (ln) 0.70 1.06 0.18 0.20 0.38 0.13 0.20 0.26 -0.12 -0.17
10 Avg. Price of
Reward (ln)
3.68 1.55 0.17 0.07 0.34 0.17 0.34 0.23 0.12 -0.12 0.14
11 Commercial
Experience (ln)
0.04 0.20 0.02 0.01 0.17 0.09 0.05 0.15 -0.01 -0.10 0.18 0.03
12 Social Experience
(ln)
0.12 0.41 0.10 0.09 0.24 -0.03 0.04 0.11 -0.17 -0.19 0.52 0.02 0.05
13 Venture Type 0.50 0.50 -0.06 -0.01 0.01 0.35 0.03 0.16 0.04 0.00 -0.08 -0.01 0.17 -0.20
14 Gender 0.46 0.50 -0.07 0.00 0.03 0.08 -0.04 0.02 -0.08 -0.08 0.00 -0.02 0.00 -0.03 0.26
15 Race 0.25 0.43 -0.02 0.03 -0.16 0.01 -0.07 0.00 0.08 0.09 -0.10 -0.01 -0.04 -0.08 0.11 0.05
1Correlations with an absolute value greater than or equal to 0.07, 0.09, and 0.11 are statistically significant at p < 0.05, 0.01, 0.001, respectively. 2Venture Type,
Gender, and Race are coded as 1 for social ventures, women, and people of color, respectively. Commercial ventures, men, and White people are coded as 0,
respectively.
Controls Main Effects
Venture Type x Gender
and Venture Type x Race
Interactions
Venture Type x Gender x
Race Interaction
Variables1Coeff. S.E. p-
value Coeff. S.E. p-
value Coeff. S.E. p-
value Coeff. S.E. p-
value
Length (ln) 0.042 0.049 0.393 0.020 0.053 0.699 0.019 0.052 0.721 0.038 0.051 0.462
Media 0.305*** 0.059 0.000 0.325*** 0.059 0.000 0.328*** 0.059 0.000 0.317*** 0.059 0.000
Links (ln) 0.278*** 0.056 0.000 0.278*** 0.056 0.000 0.270*** 0.055 0.000 0.271*** 0.055 0.000
Goal (ln) 0.138** 0.042 0.001 0.138** 0.042 0.001 0.142** 0.042 0.001 0.152*** 0.042 0.000
Duration (ln) -0.614*** 0.173 0.000 -0.575** 0.174 0.001 -0.532** 0.174 0.002 -0.551** 0.171 0.001
Backed (ln) 0.248*** 0.053 0.000 0.242*** 0.052 0.000 0.251*** 0.052 0.000 0.274*** 0.053 0.000
Avg. Price of Reward (ln) 1.036*** 0.051 0.000 1.057*** 0.052 0.000 1.044*** 0.052 0.000 1.049*** 0.051 0.000
Commercial Experience (ln) 0.293 0.253 0.246 0.209 0.255 0.412 0.199 0.251 0.429 0.165 0.251 0.512
Social Experience (ln) 0.712*** 0.150 0.000 0.723*** 0.150 0.000 0.695*** 0.151 0.000 0.779*** 0.150 0.000
Venture Type 0.147 0.112 0.192 -0.063 0.152 0.680 0.154 0.160 0.336
Gender 0.010 0.104 0.927 -0.292 0.151 0.053 -0.007 0.163 0.966
Race -0.292** 0.112 0.009 -0.264 0.182 0.146 0.169 0.211 0.422
Venture Type x Gender 0.577** 0.202 0.004 0.113 0.226 0.616
Venture Type x Race -0.185 0.240 0.441 -1.007** 0.316 0.001
Gender x Race -1.739*** 0.359 0.000
Venture Type x Gender x Race 2.351*** 0.462 0.000
Constant 4.097*** 0.695 0.000 3.968*** 0.702 0.000 3.917*** 0.715 0.000 3.637*** 0.710 0.000
Category variance 0.184 0.088 0.201 0.096 0.211 0.102
Logs 0.349*** 0.019 0.000 0.346*** 0.019 0.000 0.343*** 0.019 0.000 0.334*** 0.019 0.000
Log pseudo-likelihood -9311.56 -9307.55 -9303.09 -9290.95
Chi Square 1333.18 1361.37 1383.02 1433.01
N1000 1000 1000 1000
Table 2. Results for Funds Raised
* p < 0.05, **p < 0.01, ***p < 0.001; 1Venture Type, Gender, and Race are coded as 1 for social ventures, women, and people of color, respectively. Commercial
ventures, men, and White people are coded as 0, respectively.
Controls Main Effects
Venture Type x Gender
and Venture Type x
Race Interactions
Venture Type x Gender x
Race Interaction
Variables1Coeff. S.E. p-
value Coeff. S.E. p-
value Coeff. S.E. p-
value Coeff. S.E. p-
value
Length (ln) 0.109** 0.042 0.009 0.073 0.045 0.106 0.074 0.045 0.099 0.076 0.044 0.084
Media 0.337*** 0.048 0.000 0.355*** 0.048 0.000 0.356*** 0.048 0.000 0.347*** 0.048 0.000
Links (ln) 0.248*** 0.047 0.000 0.243*** 0.047 0.000 0.233*** 0.047 0.000 0.244*** 0.046 0.000
Goal (ln) 0.104** 0.033 0.001 0.103** 0.032 0.002 0.110** 0.033 0.001 0.113*** 0.033 0.000
Duration (ln) -0.428** 0.140 0.002 -0.418** 0.141 0.003 -0.382** 0.141 0.007 -0.384** 0.138 0.006
Backed (ln) 0.376*** 0.042 0.000 0.373*** 0.042 0.000 0.383*** 0.042 0.000 0.375*** 0.042 0.000
Avg. Price of Reward (ln) 0.450*** 0.040 0.000 0.458*** 0.040 0.000 0.449*** 0.039 0.000 0.438*** 0.038 0.000
Commercial Experience (ln) 0.222 0.209 0.286 0.162 0.209 0.438 0.157 0.206 0.448 0.131 0.206 0.524
Social Experience (ln) 0.999*** 0.139 0.000 1.020*** 0.138 0.000 0.973*** 0.138 0.000 1.025*** 0.136 0.000
Venture Type 0.183* 0.091 0.045 -0.023 0.126 0.857 0.172 0.133 0.194
Gender 0.040 0.090 0.656 -0.250* 0.126 0.047 -0.025 0.136 0.853
Race -0.044 0.094 0.642 -0.013 0.150 0.929 0.352* 0.177 0.047
Venture Type x Gender 0.575** 0.172 0.001 0.131 0.193 0.495
Venture Type x Race -0.201 0.204 0.324 -1.037*** 0.268 0.000
Gender x Race -1.390*** 0.300 0.000
Venture Type x Gender x Race 2.137*** 0.393 0.000
Constant 1.193* 0.605 0.049 1.238* 0.613 0.043 1.168 0.619 0.059 1.096 0.611 0.073
Category variance 0.210 0.092 0.223 0.098 0.217 0.096 0.203 0.092
Logs 0.187*** 0.019 0.000 0.185*** 0.019 0.000 0.180*** 0.019 0.000 0.171*** 0.019 0.000
Log pseudo-likelihood -5444.41 -5441.73 -5435.63 -5422.07
Chi Square 895.30 919.92 951.77 1020.85
N1000 1000 1000 1000
Table 3. Results for Number of Backers
* p < 0.05, **p < 0.01, ***p < 0.001; 1Venture Type, Gender, and Race are coded as 1 for social ventures, women, and people of color, respectively. Commercial
ventures, men, and White people are coded as 0, respectively.
Controls Main Effects
Venture Type x Gender
and Venture Type x Race
Interactions
Venture Type x Gender x
Race Interaction
Variables1Coeff. S.E. p-
value Coeff. S.E. p-
value Coeff S.E. p-
value Coeff S.E. p-
value
Length (ln) 0.390*** 0.103 0.000 0.384*** 0.109 0.000 0.390*** 0.109 0.000 0.384*** 0.109 0.000
Media 0.601*** 0.106 0.000 0.582*** 0.107 0.000 0.584*** 0.107 0.000 0.587*** 0.108 0.000
Links (ln) 0.107 0.093 0.252 0.127 0.095 0.181 0.128 0.095 0.178 0.132 0.095 0.167
Goal (ln) -0.846*** 0.085 0.000 -0.834*** 0.085 0.000 -0.839*** 0.086 0.000 -0.839*** 0.086 0.000
Duration (ln) -0.292 0.258 0.257 -0.226 0.262 0.388 -0.234 0.262 0.372 -0.209 0.264 0.428
Backed (ln) 0.552*** 0.106 0.000 0.546*** 0.106 0.000 0.554*** 0.107 0.000 0.558*** 0.108 0.000
Avg. Price of Reward (ln) 0.735*** 0.088 0.000 0.743*** 0.089 0.000 0.742*** 0.089 0.000 0.756*** 0.090 0.000
Commercial Experience (ln) 4.127** 1.476 0.005 4.028** 1.471 0.006 4.008** 1.471 0.006 3.983** 1.470 0.007
Social Experience (ln) 1.289*** 0.392 0.001 1.268** 0.396 0.001 1.269** 0.398 0.001 1.292** 0.396 0.001
Venture Type 0.067 0.192 0.726 -0.129 0.268 0.631 0.054 0.286 0.850
Gender 0.043 0.178 0.807 -0.209 0.259 0.420 -0.022 0.283 0.938
Race -0.616** 0.201 0.002 -0.562 0.313 0.072 -0.260 0.362 0.473
Venture Type x Gender 0.481 0.353 0.173 0.104 0.400 0.795
Venture Type x Race -0.122 0.408 0.764 -0.898 0.581 0.122
Gender x Race -1.176 0.717 0.101
Venture Type x Gender x Race 1.897* 0.911 0.037
Constant 1.363 1.193 0.253 1.143 1.213 0.346 1.255 1.221 0.304 1.070 1.227 0.383
Category variance 0.058 0.064 0.060 0.065 0.060 0.066 0.064 0.069
Log pseudo-likelihood -442.78 -437.97 -436.99 -434.78
Chi Square 204.35 208.97 209.14 209.53
N1000 1000 1000 1000
Table 4. Results for Goal Success
* p < 0.05, **p < 0.01, ***p < 0.001; 1Venture Type, Gender, and Race are coded as 1 for social ventures, women, and people of color, respectively. Commercial
ventures, men, and White people are coded as 0, respectively.
Figure 1. Venture Type x Gender for Funds Raised
Male Entrepreneur Female Entrepreneur
$0
$5,000
$10,000
$15,000
$20,000
$25,000
$30,000
$35,000
Marginal Predicted Means of Funds Raised
Commercial Social
Figure 2. Venture Type x Gender for Number of Backers
Male Entrepreneur Female Entrepreneur
0
200
400
Marginal Predicted Means of Number of Backers
Commercial Social
Figure 3. Venture Type x Gender x Race for Funds Raised
White Male White Female Male of Color Female of Color
$0
$10,000
$20,000
$30,000
$40,000
Marginal Predicted Means of Funds Raised
Commercial Social
Figure 4. Venture Type x Gender x Race for Number of Backers
White Male White Female Male of Color Female of Color
0
200
400
Marginal Predicted Means of Number of Backers
Commercial Social
Figure 5. Venture Type x Gender x Race for Goal Success
White Male White Female Male of Color Female of Color
0
0.1
0.2
0.3
0.4
0.5
0.6
Marginal Predicted Means of Success
Commercial Social