DUQUESNE UNIVERSITY
SCHOOL OF LAW
LEGAL STUDIES RESEARCH PAPER SERIES
Female entrepreneurs and equity
crowd
---
unding in the US:
Receiving less when asking
---
or more
Seth C. Oranburg
Assistant Pro
---
essor o
---
Law
and
Mark Geiger
Assistant Pro
---
essor o
---
Business
2018
Duquesne University School o
---
Law Research Paper
No. 2018-20
Originally published in: JOURNAL OF BUSINESS VENTURING INSIGHTS
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Female entrepreneurs and equity crowd
---
unding in the US:
Receiving less when asking
---
or more
Mark Geiger a,*
Seth C. Oranburg b,*
Duquesne University
Note: When citing this research, please re
---
erence the published version o
---
the manuscript.
Re
---
erence
---
or this research (APA
---
ormat):
Geiger, M., & Oranburg, S. C. (2018). Female entrepreneurs and equity crowd
---
unding in the
US: Receiving less when asking
---
or more. Journal o
---
Business Venturing Insights, 10.
https://doi.org/10.1016/j.jbvi.2018.e00099
a
Duquesne University, Palumbo Donahue School o
---
Business, 600 Forbes Avenue, Pittsburgh,
PA, 15282, United States.
b
Duquesne University, School o
---
Law, 600 Forbes Avenue, Pittsburgh, PA, 15282, United
States.
*Author ordered alphabetically; author contributed equally as a
---
irst author.
E-mail addresses: geigerm1@duq.edu (M. Geiger), oranburgs@duq.edu (S. C. Oranburg).
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Female entrepreneurs and equity crowd
---
unding in the US:
Receiving less when asking
---
or more
ABSTRACT
In this paper, we explore the relationship between gender and
---
unding raised
through equity crowd
---
unding. Using data collected
---
rom the population o
---
US
equity crowd
---
unding campaigns, we
---
ind that campaigns receive signi
---
icantly less
---
unding when the primary signatory is
---
emale. Furthermore, we explore interactions
between gender and a campaign’s
---
unding target. The results suggest that
campaigns raise signi
---
icantly less
---
unding, as the target amount increases, when the
primary signatory is
---
emale. These results are the
---
irst to suggest a relationship
between gender and
---
unding among the population o
---
US equity crowd
---
unding
campaigns. Implications and
---
uture directions are discussed.
Keywords: gender; crowd
---
unding; equity crowd
---
unding.
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INTRODUCTION
On April 5, 2012, the Jumpstart Our Business Startups (JOBS) Act was signed into law,
mandating that the Securities and Exchange Commission (SEC) create rules to allow equity
crowd
---
unding in the United States (US). When these rules became e
---
---
ective on May 16, 2016,
equity crowd
---
unding in the US became a legitimate source o
---
---
unding
---
or startups. While
startups have raised money via rewards-based crowd
---
unding on plat
---
orms like Kickstarter
---
or
over a decade, equity crowd
---
unding is di
---
---
erent in that entrepreneurs raise money in exchange
---
or a pro
---
it interest in their company. While research has begun to examine equity crowd
---
unding
in Europe (Vulkan, Astebro, & Sierra, 2016) and Australia (Ahlers, Cumming, Günther, &
Schweizer, 2015), we still know very little about this phenomenon in the US.
Equity crowd
---
unding in the US has generated excitement about its potential to make
capital available to more entrepreneurs. Some scholars believe that equity crowd
---
unding
provides a plat
---
orm
---
or underrepresented groups to raise
---
unding
---
or their companies. For
example, crowd
---
unding supporters argue that crowd
---
unding o
---
all kinds provides more accessible
---
unding
---
or women entrepreneurs (Mollick & Robb, 2016). In
---
act, research suggests that
rewards-based crowd
---
unding (e.g., Kickstarter) may be democratizing access to capital
---
or
women entrepreneurs (Marom, Robb, & Sade, 2016; Mollick & Robb, 2016). However, equity
crowd
---
unding is a di
---
---
erent phenomenon, creating a big unknown concerning the democratizing
issue.
In this study, our goal is to examine the relationship between women entrepreneurs and
---
unding by exploring this relationship among the population o
---
US equity crowd
---
unding
campaigns. In the
---
orthcoming sections, we brie
---
ly review key concepts o
---
the study, provide an
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exploratory examination o
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gender and
---
unding raised, and conclude with a discussion o
---
the
results.
LITERATURE AND CONCEPTS
Research suggests there is a strong interest in the relationship between gender and
---
unding (Greenberg & Mollick, 2017; Kanze, Huang, Conley, & Higgins, 2018; Mollick &
Robb, 2016). In
---
act, a paper by Mollick and Robb (2016) discussed the results o
---
working
papers concerning gender bias and rewards-based crowd
---
unding. For example, a working paper
by Marom et al. (2016) examined Kickstarter campaigns and
---
ound that women entrepreneurs
had higher success rates in meeting
---
unding targets, which was signi
---
icant regardless o
---
the
---
unding target. A working paper by Meek and Sullivan (c.
---
. Mollick & Robb, 2016), however,
examined Kickstarter campaigns and displayed no di
---
---
erence in
---
unding targets or
---
unding raised
between women and men. Given these limited, preliminary, and contrary results, there seems to
be a need
---
or more research on gender and crowd
---
unding. Moreover, prior studies’ results stem
---
rom the context o
---
rewards-based crowd
---
unding, a context that di
---
---
ers
---
rom that o
---
equity
crowd
---
unding.
Crowd
---
unding
Crowd
---
unding is a process whereby entrepreneurs seek
---
unding
---
rom a crowd o
---
contributors, o
---
ten through plat
---
orms on the Internet (e.g., Kickstarter). Unlike traditional
venture
---
inance, where an entrepreneur solicits large contributions
---
rom a
---
ew contributors, in
crowd
---
unding, the entrepreneur requests a large number o
---
relatively small contributions.
Crowd
---
unding can take di
---
---
erent
---
orms, such as donations, rewards, pre-purchases, loans, or
equity investments (Oranburg, 2016a).
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Rewards-based crowd
---
unding. The most
---
amiliar
---
orm o
---
crowd
---
unding is rewards-
based, where a
---
undraiser o
---
---
ers something in return
---
or a contribution to a project. For example,
---
ilmmaker Matt Porter
---
ield rewards
---
unders who contribute $1000 by tattooing their initials in
his arm; but the law prohibits such
---
undraisers
---
rom o
---
---
ering
---
inancial returns such as a percent
o
---
pro
---
its
---
rom sales o
---
the
---
ilm. Relatively speaking, rewards-based plat
---
orms like Kickstarter
o
---
---
er a donative-type o
---
crowd
---
unding, whereby the
---
under may also receive something tangible
in return
---
or the contribution (e.g., a sample o
---
the entrepreneur’s product). Evidence suggests
that donors o
---
rewards-based crowd
---
unding are primarily motived by intrinsic
---
actors. For
example, Gerber (2012)
---
ound that even when a reward is provided,
---
unders contribute to
crowd
---
unding campaigns to satis
---
y intrinsic motivations. Additionally, research by Ordanini,
Miceli, Pizzetti, and Parasuraman (2001) suggests that crowd
---
unding donors value their role as
co-creators, and they are primarily driven by intrinsic motivation.
Equity crowd
---
unding. Equity crowd
---
unding is the process whereby entrepreneurs seek
---
unding
---
rom a crowd
---
or an equity stake in their business. In contrast to rewards-based
crowd
---
unding,
---
unders o
---
equity crowd
---
unding are investors. As such, raising capital through
equity crowd
---
unding may di
---
---
er
---
rom rewards-based crowd
---
unding in substantive ways. For
example, whereas donors o
---
rewards-based campaigns are mostly driven by intrinsic
---
actors,
investors o
---
equity crowd
---
unding campaigns may be primarily motivated by pro
---
its. In
---
act,
research by Cholakova and Clarlysse (2015: 147) showed that “the decision to invest in equity
[crowd
---
unding] was positively predicted only by
---
inancial return motivations.” I
---
the motivations
o
---
investors
---
or equity crowd
---
unding campaigns are mostly driven by pro
---
its, the patterns o
---
---
unding with respect to gender may be similar to those o
---
more traditional
---
orms o
---
venture
---
inance.
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Gender and Venture Finance
When seeking venture
---
unding that involves elements o
---
pro
---
it and risk, discrimination
against
---
emale entrepreneurs is well documented. Indeed, a paper was dedicated to address the
question: “Why does the gender gap persist in obtaining new venture
---
inance?” (Leitch, 2018:
103). Research consistently shows that
---
emale entrepreneurs
---
ace greater challenges than their
male counterparts do with respect to venture
---
unding. For example, studies indicate that
---
emale
entrepreneurs receive less venture capital (Lins & Lutz, 2016), receive less
---
unding
---
rom banks
(Ste
---
ani & Vacca, 2013), pay more
---
or credit (Alesina, 2013), and are charged higher interest
rates on micro
---
inance loans (Dor
---
leitner, 2013). All o
---
these challenges women experience when
trying to raise venture capital
---
rom traditional sources has led some scholars to inquire, “Is
crowd
---
unding di
---
---
erent?” (Barasinska & Sha
---
er, 2014)1.
Gender and crowd
---
unding. While
---
emale entrepreneurs are known to raise less than their
male counterparts
---
rom traditional investors, research examining Kickstarter has shown
preliminary evidence that
---
emale entrepreneurs may be more success
---
ul than males when using
rewards-based crowd
---
unding (Kanze et al., 2018). However, research suggests that the motives
o
---
---
unders may be di
---
---
erent
---
or equity crowd
---
unding. As such, the ability o
---
---
emale entrepreneurs
to raise
---
unds via equity crowd
---
unding may be quite di
---
---
erent. In this research, using the
population o
---
equity crowd
---
unding campaigns in the US, we explored whether a relationship
exists between gender and
---
unding raised.
To examine the relationship between gender and equity crowd
---
unding, we
---
ocused on the
gender o
---
the primary signatory o
---
the campaign. The primary signatory is the individual who is
most responsible
---
or the company that
---
iled the equity crowd
---
unding campaign with the SEC.
1
Barasinkska and Sha
---
er (2014) examined loan-based crowd
---
unding in Germany and
---
ound no gender e
---
---
ect on a
borrower’s chance to raise
---
unds. They noted that lenders are protected
---
rom losses, which likely a
---
---
ects lender behavior.
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This individual is usually the key
---
ounder, president, or CEO o
---
the company. The primary
signatory is liable
---
or legalities (e.g.,
---
raud or misconduct) and is generally the
---
ace o
---
the equity
crowd
---
unding campaign. As such, we provide the
---
ollowing research question:
Research Question: In the context o
---
equity crowd
---
unding campaigns, is the gender o
---
the
primary signatory related to the amount o
---
---
unding raised?
METHODS
Sample and Procedure
To examine the relationship between gender and the amount o
---
---
unding raised through
equity crowd
---
unding campaigns, we used the population o
---
US equity crowd
---
unding campaigns
through mid-March 2018. Using custom so
---
tware, we scraped publicly available in
---
ormation
available on the SEC’s Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system.
Based on this data, 773 startups
---
iled an o
---
---
ering statement
---
or an equity crowd
---
unding campaign
with the SEC. O
---
those that
---
iled an o
---
---
ering statement, 276
---
iled a progress update. O
---
those that
---
iled a progress update, 243 reported a
---
unding amount raised.
For gender coding, we
---
ollowed established procedures in crowd
---
unding research and
used the genderize.io tool to code primary signatories o
---
equity crowd
---
unding campaigns as
---
emale or male (Greenberg & Mollick, 2017; Marom et al., 2016). When the automated gender
tool returned an unknown
---
or a primary signatory’s gender, we manually searched the respective
equity crowd
---
unding campaign
---
or gender identi
---
iers (he/she). Moreover, we collected the
---
unding targets o
---
the campaigns and in
---
ormation on
---
irm characteristics that are reported to the
SEC (e.g., assets, revenue, debt, number o
---
employees, etc.). Funding targets and
---
irm
characteristics are relatively objective
---
actors that may in
---
luence a startup’s ability to raise
---
unding. In all, we collected data on a sample o
---
243 equity crowd
---
unding campaigns (N = 243)
---
or our analyses.
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Sample bias checks. To assess the extent to which the sample is representative o
---
the
population we conducted sample bias checks. First, we used the raw genderize.io coding to
examine the gender ratio o
---
signatories o
---
the population and the sample. For the population o
---
773, results returned 108
---
emale (~14%), 648 male (~84%), and 17 unknown (~2%). For the
sample o
---
243, results returned 40
---
emale (~16%), 198 male (~81%), and 5 unknown (~2%).
Based on this observation, the gender representation o
---
the sample was similar to that o
---
the
population. Second, we conducted a logistic regression to compare the 530 campaigns not
reporting
---
unding amount raised (coded 0) with the 243 campaigns reporting
---
unding amount
raised (coded 1). We conducted this analysis
---
or the
---
unding targets and
---
irm characteristics.
Neither
---
unding targets nor
---
irm characteristics were signi
---
icant in predicting campaigns
reporting versus not reporting
---
unding amount raised.
Project category (supplemental data and analysis). In addition to
---
irm characteristics,
the type o
---
business or product
---
or which a startup is seeking
---
unding may in
---
luence a
campaign’s ability to raise
---
unds. As such, in a supplemental
---
ashion, we reviewed the 243
campaigns to assess the extent to which the campaigns could be organized into categories. A
---
ter
reviewing the campaigns, we identi
---
ied some consistencies with respect to the markets in which
the startups were operating. Based on our review, we developed seven categories, which we
labeled: (a) Apps/eCommerce/Plat
---
orm, (b) Restaurant/Food/Beverage, (c) Entertainment/
Recreation, (d) Exercise/Health, (e) Clothing/Fashion/Cosmetic, (
---
) Hardware/Electronics, and
(g) Other. The number o
---
project categories by gender are reported at the bottom o
---
Table 1.
Analyses and Results
First, we conducted a preliminary examination comparing the means o
---
---
unding amount
raised,
---
unding targets o
---
the campaign, and
---
irm characteristics by gender. We conducted a one-
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way ANOVA to compare the means o
---
these variables between
---
emale and male signatories. As
displayed in Table 1,
---
emale signatories received signi
---
icantly less
---
unding
---
rom their equity
crowd
---
unding campaigns ($152,918 vs. $258,098, p < .05). However, no signi
---
icant di
---
---
erences
between
---
emale and male signatories were
---
ound
---
or
---
unding targets or
---
irm characteristics.
------------------------------------------------
Insert Table 1 about here.
------------------------------------------------
Second, we examined the correlations. As displayed in Table 2, there was a signi
---
icant
negative relationship between
---
emale signatories and
---
unding raised (r = -.14, p < .05). There
were also signi
---
icant correlations between
---
emale signatories and project categories:
Clothing/Fashion/Cosmetic (r = .28, p < .01); Entertainment/Recreation (r = -.15, p < .05);
Hardware/Electronics (r = -.13, p < .05). However, these categories showed no signi
---
icant
correlations with
---
unding raised. With respect to
---
unding targets, as expected, both the target
o
---
---
ering amount and maximum o
---
---
ering amount had a positive correlation with
---
unding raised (r
= .23, p < .01; r = .41, p < .01, respectively). Moreover,
---
irm characteristics, such as a
---
irm’s
assets (r = .38, p < .01) and revenues (r = .29, p < .01), among others, had strong correlations
with
---
unding raised.
------------------------------------------------
Insert Table 2 about here.
------------------------------------------------
To examine our research question, “In the context o
---
equity crowd
---
unding campaigns, is
the gender o
---
the primary signatory related to the amount o
---
---
unding raised?,” we conducted OLS
regression analyses. We examined the extent to which gender o
---
the primary signatory predicts
---
unding raised, beyond all other variables. Additionally, we explored how gender moderates the
relationship between a campaign’s
---
unding targets and the amount o
---
---
unding raised. As
displayed in Model 1 o
---
Table 3, we
---
irst ran a regression with
---
irm characteristics and project
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categories predicting
---
unding raised. This model accounted
---
or 32% o
---
the total variance o
---
---
unding raised (R2 = .32). In Model 2, we added the
---
unding targets, which accounted
---
or an
additional 12% o
---
the total variance o
---
---
unding raised (R2 = .44).
To test the direct relationship between
---
emale signatory and the amount o
---
---
unding raised,
we added the
---
emale variable to Model 3. The results showed a signi
---
icant negative relationship
between
---
emale signatory and the amount o
---
---
unding raised (B = -.11, p < .05). Moreover, the
---
emale signatory variable alone accounted
---
or an additional 1% o
---
the total variance o
---
---
unding
raised (R2 = .45). In Model 4, we entered the interaction between
---
unding targets and
---
emale
signatory predicting the amount o
---
---
unding raised. The results showed a signi
---
icant negative
relationship with
---
unding raised
---
or the interaction between target o
---
---
ering amount and
---
emale
signatory (B = -.31, p < .01) and
---
or the interaction between maximum o
---
---
ering amount and
---
emale signatory (B = -.20, p < .01). These interactions accounted
---
or an additional 5% o
---
the
total variance o
---
---
unding raised (R2 = .50).
------------------------------------------------
Insert Table 3 about here.
------------------------------------------------
To examine the signi
---
icant interactions, we
---
irst explored the magnitude o
---
the e
---
---
ect o
---
target o
---
---
ering amount on
---
unding raised as a
---
unction o
---
gender by plotting a two-way
interaction. By exploring the signi
---
icant interaction in this manner, we improved our ability to
interpret the e
---
---
ects (Preacher, Curran, & Bauer, 2006). As displayed in Figure 1, campaigns
with a low target o
---
---
ering had little di
---
---
erence in
---
unding raised when the primary signatory was
---
emale versus male. However, as the target o
---
---
ering increased, campaigns raised signi
---
icantly
less
---
unding when the primary signatory was
---
emale. We also explored the interaction
---
or the
e
---
---
ect o
---
maximum o
---
---
ering amount on
---
unding raised as a
---
unction o
---
gender. As displayed in
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23
Figure 1,
---
unding raised was relatively stable
---
or male signatories regardless o
---
maximum
o
---
---
ering amount. In contrast, campaigns received increasingly less as the maximum o
---
---
ering
amount increased when the primary signatory was
---
emale.
------------------------------------------------
Insert Figure 1 about here.
------------------------------------------------
DISCUSSION
In this research, we explored the relationship between gender (
---
emale) o
---
primary
signatories o
---
equity crowd
---
unding campaigns and the amount o
---
---
unding raised. Prior research
suggests that crowd
---
unding o
---
all types might bene
---
it women (Mollick & Robb, 2016). Yet, we
---
ound signi
---
icant evidence that crowd
---
unding campaigns that have a
---
emale primary signatory
receive less
---
unding. This relationship exists even when controlling
---
or other
---
actors related to
the amount raised including the target amounts o
---
the campaign,
---
irm characteristics, and project
categories.
Moreover, we
---
ound a signi
---
icant interaction between a campaign’s o
---
---
ering amount and
gender (
---
emale) o
---
the primary signatory in predicting
---
unding raised. Treating gender as a
moderator o
---
the relationship between o
---
---
ering amount and
---
unding raised, we
---
ound that
---
emale
signatories received increasingly less
---
unding than male signatories as the o
---
---
ering amount
increased. Furthermore, we
---
ound that maximum o
---
---
ering had little in
---
luence on
---
unding raised
---
or male signatories, whereas, as maximum o
---
---
ering increased
---
or
---
emale signatories, the amount
o
---
---
unding raised decreased substantially. These
---
indings may have important implications
---
or
research and practice.
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Implications
---
or Research
The results o
---
this study may have several implications
---
or research. First, to the best o
---
our knowledge, this research is the
---
irst to provide evidence o
---
a relationship between gender and
---
unding raised through US equity crowd
---
unding. These
---
indings support previous research that
suggests
---
emale entrepreneurs raise signi
---
icantly less
---
unding than their male counterparts
(Kanze et al., 2018). This is contradictory to the
---
indings o
---
research on the relationship between
gender and
---
unding in the context o
---
rewards-based crowd
---
unding (Marom et al., 2016; c
---
.
Mollick & Robb, 2016).
One explanation
---
or the mixed results between those o
---
rewards-based crowd
---
unding and
this study may reside in a donation versus investment distinction. For example, women
entrepreneurs may receive support
---
rom other women when using a donative approach to raising
---
unds
---
or their venture. This argument is supported by research that used Kickstarter data to
show that campaigns
---
ounded by women had signi
---
icantly greater odds at success
---
ully raising
---
unds via rewards-based campaigns and theorized that this e
---
---
ect is due to “activist choice
homophily” (Greenberg & Mollick, 2017). Additionally, a study by PwC (2017)
---
ound that
women are 32% more likely than men to raise money on Kickstarter, while a Pew Research
Center survey (Smith, 2016)
---
ound that women are 5% more likely than men to contribute to a
crowdsourced
---
undraising project. Thus, data and theory suggest that women are more likely
than men to succeed in donative crowd
---
unding.
Conversely, when it comes to investment
---
unding, women entrepreneurs may be
disadvantaged at raising
---
unds compared to men. For example, while 17% o
---
startups are
women-led, and 7% o
---
venture capital partners are women, less than 3% o
---
venture capital
---
unding goes to women-led startups (First Round Capital, 2015). Additionally, a study using a
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---
23
sample o
---
startups raising capital through a venture capital
---
unding competition
---
ound that
---
emale entrepreneurs received signi
---
icantly less
---
unding (Kanze et al., 2018). As such, consistent
with investment research and the results presented in our study, activist choice homophily may
not explain equity crowd
---
unding behavior as well as it explains other
---
orms o
---
crowd
---
unding.
In general, our results suggest that equity crowd
---
unding is more similar to venture capital
---
unding than to rewards-based crowd
---
unding concerning
---
unding raised as a
---
unction o
---
gender.
This perspective would support our argument that the context o
---
equity crowd
---
unding may di
---
---
er
drastically
---
rom that o
---
rewards-based crowd
---
unding. As such,
---
indings stemming
---
rom research
on Kickstarter, and similar plat
---
orms, should not be generalized to the context o
---
equity
crowd
---
unding.
Implications
---
or Policy and Practice
Equity crowd
---
unding was signed into law in order to democratize access to capital so a
more diverse range o
---
entrepreneurs could start up
---
irms (Oranburg, 2016b). However, our data
show that it is not having this democratizing e
---
---
ect, at least with respect to gender. These
---
indings raise critical policy questions about whether Congress needs to
---
ix the JOBS Act so it
---
ul
---
ills its intended purpose. Indeed, the Fix Crowd
---
unding Act (114th Congress H.R. 4855) was
introduced soon a
---
ter the SEC promulgated its complex
---
inal rules to make it simpler
---
or a wider
range o
---
entrepreneurs to use equity crowd
---
unding, but its
---
orm and passage has been the source
o
---
much debate.
Our data suggest that the crowd
---
unding regulations may indeed need to change i
---
equity
crowd
---
unding is to provide more equal access to capital, although some proposed changes such
as raising the total contribution limit
---
rom $1 million to $5 million may not primarily have a
democratizing impact (Oranburg, 2016c). Indeed, adjacent studies on gender and campaign
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---
23
---
inance show that the average size o
---
donations to
---
emale candidates is smaller than to male
candidates; thus, “By simply increasing the individual contribution limit
---
rom $1,000 to $2,000,
[the Bipartisan Campaign Re
---
orm Act o
---
2002], in e
---
---
ect, exacerbated the
---
emale candidates’
disadvantage in each o
---
the three a
---
orementioned
---
acets o
---
gender speci
---
ic
---
undraising” (Baker,
2006: 20). Our data likewise suggest that, in equity crowd
---
unding, women might raise more
when asking
---
or less. There
---
ore, to make equity crowd
---
unding more equitable, policymakers
should consider making it easier to solicit smaller individual donations
---
rom a larger number o
---
people.
For practitioners who are seeking
---
unding, our
---
indings might help an entrepreneur
decide whether to pursue that
---
unding via rewards-based or equity crowd
---
unding or by seeking
venture capital investment. Based on preliminary data, women experience a higher likelihood o
---
raising
---
unds via a rewards campaign, a signi
---
icantly lower chance o
---
raising
---
unds via equity
crowd
---
unding, and a substantially lower likelihood o
---
raising
---
unds via venture capital than men
do. Meanwhile, our data also show that company characteristics such as higher assets and
revenue also increased the likelihood o
---
a success
---
ul campaign, regardless o
---
gender. There
---
ore,
a women entrepreneur might choose to maximize
---
undraising potential by engaging in a rewards-
based campaign
---
irst to generate revenue and assets; then, second, leveraging that success to
increase the likelihood o
---
success in a
---
ollow-on equity crowd
---
unding campaign. Theoretically,
completing a success
---
ul equity crowd
---
unding campaign would also improve the likelihood o
---
success in venture-capital
---
undraising as a third step (Oranburg, 2016c).
Limitations and Future Directions
While the present research provides evidence o
---
a relationship between gender and
---
unding raised through equity crowd
---
unding, limitations and
---
uture directions should be
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---
23
discussed. For example, this is an exploratory study on a sample o
---
243 equity crowd
---
unding
campaigns in the US. Over time, the number o
---
equity crowd
---
unding campaigns in the US will
increase, and the relationships
---
ound in our research may change. As such, our
---
indings should
be considered preliminary evidence. Follow-up studies will be needed concerning the
relationships examined in this study.
Furthermore, research may need to explore the underlying reasons
---
or why campaigns
with
---
emale primary signatories receive less
---
unding. One avenue o
---
research may need to
examine the quality o
---
the campaigns. For example, using data collected
---
rom Kickstarter,
Mollick and Robb (2016)
---
ound that signals o
---
quality, such as, outside endorsements, evidence
o
---
prototypes, and past success in
---
luence
---
unding decisions. On the other hand, there is evidence
that men and women raise money di
---
---
erently in campaign
---
inance (Baker, 2006), public
---
inance
(Palmer, 1995), and personal
---
inance (Shin, 2015), so it is important to determine whether
crowd
---
unding and other venture
---
inance laws create or maintain any structural bias against the
ways that women raise venture capital.
Another avenue may be to explore the characteristics o
---
those who are investing in the
campaigns. For example, research by Greenberg and Mollick (2017) showed that women are
likely to support other women when making decisions. They argued that “activist choice
homophily, which entails support
---
or
---
ellow members o
---
disadvantaged groups,” (364) may
explain di
---
---
erences in
---
unding based on demographics such as gender. That is,
---
emale-run
campaigns may seek and receive less
---
unding due to a limited pool o
---
---
emale investors. On the
other hand, activist choice homophily may not apply when
---
unding decisions are an investment.
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---
23
Conclusion
This paper provides empirical evidence that gender has an e
---
---
ect on the amount o
---
---
unding raised through US equity crowd
---
unding. There is much to learn about equity
crowd
---
unding in the US and we hope this paper is help
---
ul
---
or
---
uture research.
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23
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TABLE 1
Firm and Funding Characteristics by Gendera
Variable Female (41)c Male (202)c F-statisticb
Funding Outcome
1. Funding Raised ($) 152,918 258,098 5.07*
Funding Targets
2. Target O
---
---
ering ($) 78,415 71,373 0.27 ns
3. Maximum O
---
---
ering ($) 578,823 639,909 0.82 ns
Firm Characteristics
4. Firm Age (days) 1,308 1,326 0.00 ns
5. Number o
---
Employees 4 7 1.50 ns
6. Assets ($) 269,595 382,882 0.39 ns
7. Cash & Cash Equivalents ($) 70,775 92,670 0.18 ns
8. Accounts Receivable ($) 10,270 22,986 0.60 ns
9. Short-term Debt ($) 118,747 142,821 0.17 ns
10. Long-term Debt ($) 266,084 224,076 0.33 ns
11. Revenue/Sales ($) 338,230 410,236 0.04 ns
12. Cost o
---
Goods Sold ($) 154,345 208,582 0.04 ns
13. Taxes Paid ($) 5,719 2,249 1.53 ns
14. Net Income ($) -169,249 -256,864 0.46 ns
Project Category
15. Apps/eCommerce/Plat
---
orm 18 64 -
16. Restaurant/Food/Beverage 5 47 -
17. Entertainment/Recreation 1 34 -
18. Exercise/Health 4 11 -
19. Clothing/Fashion/Cosmetic 8 5 -
20. Hardware/Electronics 0 19 -
21. Other 5 22 -
a
Gender o
---
the primary signatory o
---
the equity crowd
---
unding campaign.
b
F-statistic o
---
one-way ANOVA test
---
or signi
---
icant di
---
---
erence between Female and Male.
c
Means
---
or each variable are reported; total number o
---
campaigns are reported in parentheses.
ns
p > .10
* p < .05
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TABLE 2
Correlations
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
1 Female
2 Funding Raised -.14
3 Target O
---
---
ering .02 .23
4 Maximum O
---
---
ering -.06 .41 .13
5 Firm Age -.01 .04 -.10 .12
6 Number o
---
Employees -.08 .33 -.02 .16 .36
7 Assets -.05 .38 .00 .19 .33 .48
8 Cash & Cash Equivalents -.04 .32 .03 .20 .20 .32 .55
9 Accounts Receivable -.06 .15 -.01 .18 .32 .26 .51 .48
10 Short-term Debt -.02 .19 -.01 .24 .43 .43 .38 .22 .40
11 Long-term Debt .03 .20 .00 .14 .25 .35 .49 .19 .18 .30
12 Revenue/Sales -.02 .29 .01 .22 .44 .67 .61 .48 .68 .66 .29
13 Cost o
---
Goods Sold -.02 .14 -.02 .16 .39 .52 .48 .38 .62 .75 .19 .87
14 Taxes Paid .07 .21 .02 .04 .20 .42 .24 .12 .12 .15 .16 .40 .22
15 Net Income .05 -.32 -.01 -.24 -.17 -.35 -.38 -.35 -.17 -.45 -.54 -.26 -.29 -.05
16 Apps/eCommerce/Plat
---
orm .10 -.04 -.19 .07 -.09 -.07 -.13 -.02 -.02 .04 -.03 -.06 .01 -.10 .01
17 Restaurant/Food/Beverage -.10 .03 .10 -.16 -.05 -.01 .00 -.04 .04 -.10 -.05 -.03 -.03 .11 .14 -.37
18 Entertainment/Recreation -.15 .12 -.01 .17 .05 .16 .08 .08 .05 -.01 -.02 .06 .04 -.05 -.05 -.29 -.21
19 Exercise/Health .07 -.04 .10 -.15 .03 -.03 .05 -.03 -.06 -.04 -.06 -.05 -.04 -.03 .04 -.18 -.13 -.11
20 Clothing/Fashion/Cosmetic .28 .03 .02 .05 .04 .02 .11 .06 .04 .11 .04 .16 .08 .18 -.05 -.17 -.12 -.10 -.06
21 Hardware/Electronics -.13 -.05 -.02 .01 .01 -.06 -.06 -.02 -.07 -.02 -.01 -.07 -.04 -.05 -.05 -.21 -.15 -.12 -.08 -.07
22 Other .02 -.06 .09 -.01 .09 -.01 .04 -.02 .00 .06 .16 .04 -.01 -.01 -.10 -.25 -.18 -.15 -.09 -.08 -.10
N = 241-243. Pairwise deletion. Correlations ≥ .13 signi
---
icant at p < .05 level; Correlations ≥ .17 signi
---
icant at p < .01 level.
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TABLE 3
Regression Analyses: Dependent Variable = Funding Raised
Model 1 Model 2 Model 3 Model 4
Firm Characteristics
Firm Age -.13* -.11 -.10 -.09
Number o
---
Employees .01 .05 .04 .01
Assets .24** .24** .24** .23**
Cash & Cash Equivalents .10 .06 .06 .04
Accounts Receivable -.12 -.11 -.12 -.12
Short-term Debt .15 .07 .06 .03
Long-term Debt -.13 -.13 -.11 -.11
Revenue/Sales .65** .49** .48** .48**
Cost o
---
Goods Sold -.64** -.48** -.47** -.43**
Taxes Paid .05 .06 .07 .10
Net Income -.27** -.23** -.23** -.22**
Project Categorya
Apps/eCommerce/Plat
---
orm .16 .14 .14 .17*
Restaurant/Food/Beverage .17 .14 .13 .10
Entertainment/Recreation .17* .11 .09 .09
Exercise/Health .05 .03 .03 .06
Clothing/Fashion/Cosmetic -.01 -.02 .01 .00
Hardware/Electronics .05 .03 .01 .01
Funding Targets
Target O
---
---
ering .22** .23** .42**
Maximum O
---
---
ering .27** .26** .31**
Primary Signatory Gender
Female -.11* .13
Interactions
Target O
---
---
ering X Female -.31**
Maximum O
---
---
ering X Female -.20*
Model R2 .32 .44 .45 .50
Δ R
---
or step
2
.12** .01* .05**
N = 241-243. Listwise deletion. Standardized coe
---
---
icients are reported. Δ R2
---
or step indicates change
---
rom
preceding model.
a
Other is the excluded category.
* p < .05
** p < .01
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FIGURE 1
E
---
---
ect o
---
Target O
---
---
ering and Maximum O
---
---
ering on Funding Raised as a
---
unction o
---
Gender
Male
Female
Funding
Raised
$10,000 $1,000,000
Target O
---
---
ering
Male
Female
Funding
Raised
$10,000 $1,000,000
Maximum O
---
---
ering
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