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Investors Prefer Entrepreneurial Ventures Pitched by Attractive Men

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Significance We identify a profound and consistent gender gap in entrepreneurship, a central path to job creation, economic growth, and prosperity. Across a field setting (three entrepreneurial pitch competitions in the United States) and two controlled experiments, we find that investors prefer entrepreneurial pitches presented by male entrepreneurs compared with pitches presented by female entrepreneurs, even when the content of the pitch is the same. This effect is moderated by male physical attractiveness: attractive males are particularly persuasive, whereas physical attractiveness does not matter among female entrepreneurs. These findings fundamentally advance the science related to gender, physical attractiveness, psychological persuasion, bias, role expectations, and entrepreneurship.
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Investors prefer entrepreneurial ventures pitched by
attractive men
Alison Wood Brooks
a,1
, Laura Huang
b
, Sarah Wood Kearney
c
, and Fiona E. Murray
c
a
Harvard Business School, Harvard University, Boston, MA 02163;
b
Wharton School, University of Pennsylvania, Philadelphia, PA 19104; and
c
MIT Sloan School,
Massachusetts Institute of Technology, Cambridge, MA 02142
Edited* by Nancy Hopkins, Massachusetts Institute of Technology, Cambridge, MA, and approved February 20, 2014 (received for review November 11, 2013)
Entrepreneurship is a central path to job creation, economic growth,
and prosperity. In the earliest stages of start-up business creation,
the matching of entrepreneurial ventures to investors is critically
important. The entrepreneurs business proposition and previous
experience are regarded as the main criteria for investment deci-
sions. Our research, however, documents other critical criteria that
investors use to make these decisions: the gender and physical at-
tractiveness of the entrepreneurs themselves. Across a field setting
(three entrepreneurial pitch competitions in the United States) and
two experiments, we identify a profound and consistent gender
gap in entrepreneur persuasiveness. Investors prefer pitches pre-
sented by male entrepreneurs compared with pitches made by fe-
male entrepreneurs, even when the content of the pitch is the same.
This effect is moderated by male physical attractiveness: attractive
males were particularly persuasive, whereas physical attractiveness
did not matter among female entrepreneurs.
physical appearance
|
persuasion
Entrepreneurship, the creation and construction of new-to-the-
world ventures by individuals and small teams, is a critical
activity in modern economies (1). Although new ventures of all
types have a role in the economy, the formation of high-potential,
innovation-driven ventures is widely regarded as a central path to
job creation (1), economic growth, and prosperity (24). For
example, entrepreneurial start-up ventures contribute almost
20% of new job creation annually in the United States.
In the earliest stages of start-up business creation, the matching
of entrepreneurial ventures to investors is important because
new businesses need funding to survive, and high-potential
ventures need capital to grow and succeed (5, 6). The funda-
mentals of the entrepreneurs business proposition and the pre-
vious experiences of the entrepreneurs themselves are regarded
as the main criteria for investment decisions (7, 8). Our re-
search, however, documents other criteria that investors use to
make these decisions: the gender and physical attractiveness of
the entrepreneurs themselves.
Around the world, there are more male entrepreneurs than
female entrepreneurs, with total entrepreneurial activity led by
men in the vast majority of countries (9). In the United States,
men engage in entrepreneurial activity at almost twice the rate of
women (10). Among high-growth-potential ventures, only 11%
of US firms with venture-capital backing, past and present, have
been founded or led by women (11), and women-led ventures
have received only 7% of all venture funds (12).
The gender imbalance in entrepreneurship has been attributed
to a persistent incongruence between personality attributes as-
cribed to women and personality attributes ascribed to entre-
preneurs (13, 14). This perceived lack of fit makes women less
likely to pursue and to be selected for male gender-typed roles
such as that of entrepreneur (15, 16). Compared with men,
women in male gender-typed positions are more likely to have
their performance devalued, less likely to receive opportunities
for career advancement, and more likely to encounter challenges
and skepticism in starting and running ventures (1727).
Although the gender imbalance is undesirable and challenging
for female entrepreneurs, it remains unclear whether the gender
imbalance is due to irrational investor behavior. If male entre-
preneurs are inherently more talented or more likely to be at an
advantage throughout their ventures or throughout their careers,
then the gender gap in entrepreneurship may result from rational
statistical discrimination by investors. In the same way that par-
ticipants in the classic Keynesian beauty contest game were asked
to choose the most popular (rather than the most beautiful)
contestant, investors may rationally seek to invest in male-led
ventures that other investors and future customers are most likely
to prefer.
Across the broad landscape of entrepreneurial ventures, it is
unclear whether men outperform women. Some prior work has
found that, compared with men, women are likely to have fewer
employees, lower growth projections, and lower levels of in-
ternationalization (9). On the other hand, recent work using 15 y
of panel data from the Standard & Poors Financial Services
1,500 firms suggests that female managers improve overall firm
performance by bringing informational and social diversity ben-
efits to the management team, enriching the behaviors exhibited
by managers throughout the firm, and motivating lower-status
women in the firm (28).
Answering the question about gender and entrepreneurial
performance has been limited by two main challenges (29, 30).
First, male- and female-led ventures tend to focus on different
types of market opportunities with differing levels of underlying
growth potential. Male entrepreneurs tend to pursue ventures
across a broad spectrum of industries, whereas female entre-
preneurs have predominantly pursued ventures that focus on the
female consumer, such as fashion, cosmetics, and cooking. No-
table examples of female-founded, female-focused companies
include Mary Kay Inc., Estee Lauder Companies, Chanel S.A.,
Significance
We identify a profound and consistent gender gap in entre-
preneurship, a central path to job creation, economic growth,
and prosperity. Across a field setting (three entrepreneurial
pitch competitions in the United States) and two controlled
experiments, we find that investors prefer entrepreneurial
pitches presented by male entrepreneurs compared with pitches
presented by female entrepreneurs, even when the content of
the pitch is the same. This effect is moderated by male physical
attractiveness: attractive males are particularly persuasive,
whereas physical attractiveness does not matter among female
entrepreneurs. These findings fundamentally advance the sci-
ence related to gender, physical attractiveness, psychological
persuasion, bias, role expectations, and entrepreneurship.
Author contributions: A.W.B., L.H., S.W.K., and F.E.M. designed research; A.W.B., L.H., and
S.W.K. performed research; A.W.B. and L.H. analyzed data; and A.W.B., L.H., S.W.K., and
F.E.M. wrote the paper.
The authors declare no conflict of interest.
*This Direct Submission article had a prearranged editor.
1
To whom correspondence should be addressed. E-mail: awbrooks@hbs.edu.
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Martha Stewart Living Omnimedia, and, most recently, Spanx
Inc. and Tory Burch. Second, available sample sizes are small
because there are far more male entrepreneurs than female
entrepreneurs. Therefore, it has been difficult for researchers to
make gender comparisons with matched samples. As a result,
research has not disentangled the impact of entrepreneur gender
from the impact of business type on entrepreneurial success. In
the present research, we focus on how entrepreneur gender
influences investment decisions, controlling for business type.
The modes of communication entrepreneurs use to convey
their ideas to investors today fall into two broad categories:
nonverbal and verbal presentations. Nonverbal presentations in-
clude executive summaries, pitch decks (i.e., a short series of ex-
planatory slides), and written business plans that may be sent to
potential investors. Verbal presentations, on the other hand, vary
according to audience size, level of formality, and mode of com-
munication (e.g., over the phone, face to face). One format,
used by the majority of venture capital firms and entrepre-
neurship competitions, has emerged as an industry standard:
a 5-min verbal pitch in which the entrepreneur narrates a se-
ries of slides, providing an overview of the business plan to
potential investors.
Pitches are characterized by high levels of uncertainty, as
investors must evaluate the business opportunity and the entre-
preneurs themselves based on limited information. Therefore,
the entrepreneurs ability to persuade during his or her pitch
is particularly salient in shaping evaluator preferences and in-
vestment outcomes.
Prior research suggests that several factors influence whether
investors are persuaded, including characteristics of the entrepre-
neur, characteristics of the management team, the interpersonal
chemistrybetween the entrepreneurs and the investors, and the
investors’“gut instincts(31, 32).We consider very basic charac-
teristics of the entrepreneur that have been neglected by previous
research: gender and physical attractiveness. Prior studies show
that women pay more attention to their appearance than do men
and physical appearance influences more outcomes for women
than for men (3339). However, across field, laboratory, and Web-
based settings, we document a profound and persistent preference
for entrepreneurial ventures pitched by men, particularly attractive
men. These findings fundamentally advance the science related
to gender, physical attractiveness, psychological persuasion, role
expectations, and entrepreneurship.
Results
Study 1: Entrepreneurial Pitch Success in the Field. In study 1, we
explore the relationships between entrepreneur gender, physical
attractiveness, and investor funding decisions using real entre-
preneurial pitches in a field setting. We examined the pitches
presented at three entrepreneurial pitch competitions in the
United States over the course of 3 y. In each competition,
entrepreneurs made pitches to a panel of angel investor judges,
providing an overview of their business plan. The angel investors
judged the pitches and awarded funding prizes to the most
promising ventures. The prize winners were awarded start-up
capital as an infusion of cash to help develop their business ideas.
In study 1, we analyzed video recordings of the entrepreneurs
pitches to test the relationship between entrepreneur gender,
physical attractiveness, and pitch success.
There was a significant main effect of entrepreneur gender on
pitch success (odds ratio of 1.57, P<0.01). Male entrepreneurs
were 60% more likely to achieve pitch competition success than
were female entrepreneurs. There was a significant interaction
between gender and attractiveness on the likelihood of pitch
success (P<0.05). Among the male entrepreneurs, there was
wide and significant variation across levels of attractiveness on
pitch success (P<0.01). Among women, variation in pitch
success across levels of attractiveness was not significant (P=
0.18). We depict this pattern of results in Fig. 1.
We also estimated a multiple logistic regression model of pitch
success (Table 1). The main effects model (model 1), which in-
cluded only gender as a predictor variable, explained 24% of the
variance in pitch success. The full model, which included gender
and interaction terms (model 2), explained 42% of the variance
in pitch success (ΔR
2
=0.18). (These effects remained the same
when codersgender and race were included as control varia-
bles.) The odds ratio for gender by attractiveness was 1.36 (P<
0.001), suggesting that gender was a stronger predictor of pitch
success when attractiveness was included in the model. Specif-
ically, attractiveness led to a 36% increase in pitch success, and
the overall difference in pitch success was attributable both to
gender and to differences among attractive and unattractive
males (40). This pattern of results remained the same when we
included business sector (digital media, cleantech, education, legal
services, or technology innovation), entrepreneurship competition
(out of the three included in our dataset), pitch timing (morning
or afternoon), pitch duration (in seconds), and entrepreneur age
and years of experience in our regression analysis.
Study 2: The Effect of Entrepreneur Gender on Pitch Success. In study
2, we isolated the effect of gender on entrepreneurial persua-
siveness in a controlled Web-based experiment. Our design
provided three important points of experimental control over
study 1. First, we held the content of the entrepreneurial pitches
constant across experimental conditions. Second, we controlled
for the possibility that distinctive gender-based presentation
styles (e.g., body posture and body size) influenced persuasive-
ness and outcomes (41). Third, participants were personally in-
centivized to make optimal investment decisions.
We recruited adult participants to watch two entrepreneurial
pitch videos
(n=521). The videos featured real start-up ven-
tures whose pitches had been developed for a university-based
business plan competition. Participants were paid based on the
success of the venture they chose. We determined the success
Fig. 1. The effect of entrepreneur gender and physical attractiveness on
pitch success rate in a field setting (n=90). ns, not significant.
Video pitches are very common. Web sites such as Kickstarter (www.kickstarter.com) and
IndieGoGo (www.indiegogo.com) enable all investor types to donate based on video
pitches. Organizations like AngelList (https://angel.co) and Gust (www.gust.com) have
created online platforms that enable accredited investors to make equity investments
into new businesses that upload video pitches onto their Web platforms. In early 2013,
legislative action by the US federal governmentthe Jumpstart Our Business Startups
Actlifted constraints on unaccredited investors, which is likely to encourage even more
equity investment into early-stage entrepreneurial firms based on video pitches.
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of each venture by asking a separate panel of twelve expert
investors to predict each ventures likelihood of success (1 =very
unlikely to succeed, 7 =very likely to succeed). In this way,
participants were personally incentivized to make an optimal
investment choice.
The pitch videos showed images related to the ventures, but
they did not show the entrepreneurs themselves. Participants
heard the entrepreneurs voice-over narration while they watched
each video. This video pitch format allowed us to dub in a male
voice and a female voice (randomly assigned), holding the nar-
ration script constant. After watching the videos, participants
chose which company to fund.
To determine the influence of entrepreneur gender on in-
vestment choice, we conducted a multiple logistic regression
using investment choice as the outcome variable and narrator
gender and video presentation order as predictor variables.
There was a significant effect of entrepreneur gender on in-
vestment choice. Although the female and male voices presented
identical pitches, 68.33% of participants (356 of 521) chose to
fund the ventures pitched by a male voice and only 31.67% of
participants (165 of 521) chose to fund the ventures pitched by
a female voice (β=0.372, SE =0.040, P<0.0001). There was
a primacy effect such that 57.97% of participants (302 of 521)
chose to fund the video pitch they watched first (β=0.177, SE =
0.039, P<0.0001). The gender effect remained the same
whether or not the presentation order was included in the re-
gression. There were no effects of participant age (P=0.29) or
participant gender (P=0.86) on investment decisions.
Study 3: Entrepreneur Attractiveness and Pitch Success. In study 3,
we tested the effects of physical attractiveness directly. We used
the same design as in study 2 with two important differences.
First, for parsimony in experimental design and sufficient ex-
perimental power, participants watched only one pitch video.
This meant that instead of using investment choice as the main
dependent variable, participants rated how likely they were to
invest in the venture on a scale measure (1 =very unlikely to
invest, 7 =very likely to invest). Second, in addition to narrator
gender, we also manipulated the physical attractiveness of the
entrepreneur by presenting a gender-matched high- or low-at-
tractiveness photo along with the video. [Although our photo
stimuli had been validated in previous work (42), we also pretested
the photos in a nonoverlapping sample of 207 participants, in
which the high-attractiveness photos were rated as significantly
more attractive than the low-attractiveness photos (P<0.03).]
As in studies 1 and 2, we found a strong main effect of en-
trepreneur gender on persuasiveness. Participants reported that
they were significantly more likely to invest when the pitch was
narrated by a male voice [mean (M) =4.90, SD =1.34] than
when the same pitch was narrated by a female voice [M =4.25,
SD =1.47, F(1,192) =20.48, P=0.001]. Participants also
reported on 17 scales that the male-narrated pitches were more
persuasive[M
male
=5.04 vs. M
female
=4.45, F(1,192) =10.19,
P=0.002], fact based[M
male
=5.51 vs. M
female
=4.81,
F(1,192) =17.11, P<0.001], and logical[M
male
=5.87 vs.
M
female
=5.32, F(1,192) =14.77, P<0.001] than were the same
pitches narrated by a female voice.
There was an interaction effect between entrepreneur gender
and physical attractiveness on ratings of investment likelihood
[F(1,192) =4.81, P=0.029]. This interaction was driven by reac-
tions to the male entrepreneurs. Participants reported being sig-
nificantly more likely to invest after watching the high-attractiveness
malespitch(M=5.21, SD =1.13) than after the low-attractiveness
malespitch[M=4.59, SD =1.48, t(92) =2.29, P=0.024]. The
measure of investment likelihood after watching the high-attrac-
tiveness female entrepreneur (M =4.14, SD =1.49) and low-
attractiveness female entrepreneur (M =4.35, SD =1.47) did
not differ significantly (P=0.48), and the main effect of physical
attractiveness on ratings of investment likelihood was not significant
(P=0.34). We depict this pattern of results in Fig. 2.
Discussion
The results of the three studies document a profound and con-
sistent gender gap in entrepreneur persuasiveness. Both pro-
fessional investors and nonprofessional evaluators preferred
pitches presented by male entrepreneurs compared with pitches
made by female entrepreneurs, even when the content of the
pitch was the same. Our results also suggest that persuasiveness
is moderated by male physical attractiveness: attractive males
were particularly persuasive, whereas physical attractiveness did
not matter among female entrepreneurs.
Our findings are qualified by some limitations that offer fruitful
directions for future research. First, in studies 2 and 3, we focused
on one industry type (veterinary technology) to control for industry-
specific variation in investment preferences. However, Heilmans
lack-of-fit model (15) suggests that women may be more persuasive
when they pitch female gender-typed ventures, suggesting possible
boundary conditions for our results. Second, our results document
gender discrimination in entrepreneurship, but this discrimination
does not necessarily represent irrational marketplace behavior. If
discrimination arises along the entire growth path of female-led
ventures, then early stage investors may rationally seek to avoid
such investments. Third, we found that male-narrated pitches were
rated as more persuasive, logical, and fact-based than were the
same pitches narrated by a female voice. However, we did not ask
investors to explain their decision process (i.e., how they judged the
perceived value of an entrepreneur and his or her venture). It
Fig. 2. The effect of entrepreneur gender and physical attractiveness on
ratings of investment likelihood in an experimental setting (n=520). ns, not
significant.
Table 1. Logistic regression predicting pitch competition success
Variables Model 1 Model 2
Dependent variable: pitch success rate
Step 1: main effects
Gender 1.57** 0.11
Attractiveness 0.10 0.05
Step 2: interaction term
Gender ×attractiveness 1.36**
Reported coefficients are odds ratios. *P<0.05, **P<0.01.
Brooks et al. PNAS Early Edition
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PSYCHOLOGICAL AND
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would be interesting to investigate the naïve theories underlying
investorsconscious and subconscious search criteria.
To the extent that female entrepreneurs are disadvantaged in
entrepreneurial pitching simply by virtue of their gender, then
women may remain underrepresented in the entrepreneurial econ-
omy. Moreover, the power of male attractiveness to persuade eval-
uators to select one pitch over another suggests that entre-
preneurial opportunities may also be unevenly distributed even
within the male population.
Materials and Methods
Study 1. We randomly selected 90 pitches from three entrepreneurial pitch
competitions for our sample, holding the proportion of successful and un-
successful pitches constant across each of the 3 pitch competitions (10 suc-
cessful pitches and 20 unsuccessful pitches from each competition). The
pitches were between 5 and 8 min in duration and were judged by a live
panel of angel investors. We defined a successful pitch as one that was
awarded a funding prize in one of the competitions. The prize winners were
awarded start-up capital as an infusion of cash to help develop their business
ideas. The competitions were quite competitive: entrepreneurs had a 3%
chance of winning a funding prize. Of the 90 pitches in our randomly drawn
sample, 70 were given by male entrepreneurs (77.78%) and 20 were given
by female entrepreneurs (22.22%) across a range of business sectors, in-
cluding digital media, cleantech, education, legal services, and technology
innovation. After the pitch competitions, we recruited a separate panel of
60 angel investors to code the pitch videos across several measures, including
physical attractiveness: How physically attractive was the entrepreneur?
(1 =very unattractive, 7 =very attractive). The investors were blind to the
actual competition outcomes and had more than 16 y of investment ex-
perience on average (M
experience
=16.13 y, SD =6.78 y).
Study 2. We recruited a nationally representative sample of 521 Americans
(46.64% female) over Amazons Mechanical Turk (www.mturk.com)to
participate in a study. Participants watched two pitch videos, which featured
real start-up ventures whose pitches had been developed for a university-
based business plan competition. We chose two companies from the same
business sector (veterinary technology) to control for industry-specific vari-
ation in investment preferences. Here we call them venture Aand ven-
ture B.We recruited a separate panel of 12 expert investors to rate the
probability of success of the two ventures on a scale measure of success
likelihood (1 =extremely unlikely to be successful, 7 =extremely likely to be
successful). The expert investors had more than 8 y of venture capital ex-
perience on average (M
experience
=8.50 y, SD =3.10 y). On average, the panel
of investors rated venture As likelihood of success as 4.40 out of 7 (SD =
0.97) and venture Bs likelihood of success as 3.75 out of 7 (SD =0.92). Study
participants earned US$1 for each rating point. Therefore, if they chose
venture A, they earned US$4.40, and if they chose venture B, they earned US
$3.75. Of the 521 participants, 298 participants (57.20%) chose to fund
venture A, and 223 participants (42.80%) chose to fund venture B, and we
present our results pooled across video stimuli.
The pitch videos showed images and diagrams related to ventures A and B,
but they did not show the entrepreneurs themselves. Participants heard the
entrepreneurs voice-over narration while they watched each video. This
video pitch format allowed us to dub in a male voice and a female voice,
holding the narration script constant. Every participant watched both pitch
videos, one narrated by a male voice and the other narrated by a female
voice. We randomly assigned entrepreneur gender and video presentation
order in a 2 (entrepreneur gender: venture A male/venture B female vs.
venture A female/venture B male) ×2 (presentation order: venture A first vs.
venture B first) between-subjects experimental design. After watching the
videos, participants chose which company to fund, venture A or B, and were
paid based on their investment choice.
Study 3. We recruited 194 participants (57.73% female) to a behavioral
laboratory to participate in a study in exchange for US$5. We used the same
design as in study 2 with two important differences. First, for parsimony in
experimental design and sufficient experimental power, participants watched
only one pitch video. This meant that instead of using investment choice as
the main dependent variable, participants rated how likely they were to
invest in the venture on a scale measure (1 =very unlikely to invest, 7 =very
likely to invest). We also asked participants to report the extent to which
they thought the pitch was persuasive,”“the pitch was fact-based,and
the pitch was logicalon 17 scales. Second, in addition to narrator
gender, we also manipulated the physical attractiveness of the entrepre-
neur by presenting a gender-matched high- or low-attractiveness photo
along with the video. Although our photo stimuli had been validated in
previous work (42), we also pretested the photos in a nonoverlapping
sample of 207 participants, in which the high-attractiveness photos were
rated as significantly more attractive than the low-attractiveness photos
(P<0.03). This produced a 2 (entrepreneur gender: male vs. female) ×2
(entrepreneur physical attractiveness: high vs. low) between-subjects
experimental design.
The University of Pennsylvania Internal Review Board approved these
experiments. Informed consent was obtained from all participants. All data
are available from the corresponding author.
ACKNOWLEDGMENTS. We thank Maurice E. Schweitzer, Michael I. Norton,
and Linda Babcock for feedback and Ethan Ludwin-Peery for research
assistance. We received funding from the Wharton Schools Russell
Ackoff Fellowship.
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PSYCHOLOGICAL AND
COGNITIVE SCIENCES
... The error of underestimating and missing out on subsequently successful opportunities is studied less often but also entails considerable costs for angel investors (Sohl, 2022). The occurrence of both types of systematic error can be explored in relation to founder characteristics, such as the gender, age, or physical attractiveness of entrepreneurs (Boulton et al., 2019;Brooks et al., 2014;Hohl et al., 2021). By considering the subsequent success of startups, it is possible to not to only show high-level investor preferences in pitch competitions, but to identify their bias with respect to decision-making error with negative consequences for angel investors. ...
... In addition to age and gender, recent studies show that funding decisions are influenced by the entrepreneur's "beauty capital", that is their physical attractiveness (Brooks et al., 2014;Colombo et al., 2022;Smith & Viceisza, 2018). Specifically, angel investors are shown to make more investment offers to attractive founders and underestimate ventures by less attractive individuals, respectively. ...
... Physical attractiveness. All observers rated the physical attractiveness of each entrepreneur in the pitch given its presumed impact on investor decision-making (Brooks et al., 2014;Smith & Viceisza, 2018). As in prior social psychological research on physical attractiveness (Mueser et al., 1984;Parks & Kennedy, 2007), a Likert scale ranging from 1 (very unattractive) to 10 (very attractive) was used. ...
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... This indicates that specific superficial characteristics of entrepreneurial teams compensate for more rationally relevant criteria in their investment decisions. In practice, this means that angel investor decision-making is often influenced by the demographics or appearance of the entrepreneur, with preferences for stereotypically representative groups, relating to age, gender, ethnicity, and physical attractiveness (Boulton et al. 2019;Brooks et al. 2014;Jetter and Stockley 2023). Assuming that subsequent startup success is not directly driven through these superficial personal characteristics, the use of stereotypes leads to suboptimal decision outcomes for investors and is a significant source for decision bias (Harrison et al. 2015;Morazzoni and Sy 2022). ...
... Furthermore, investors may gauge women's ventures to be less likely to succeed in the market due to potential discrimination and bias from customers and suppliers (Bates 2002). Ultimately, business pitches by female entrepreneurs are considered to be less persuasive, and in interaction, women are asked more risk-related questions, while men are asked more potential-related questions (Balachandra et al. 2019;Brooks et al. 2014). Notably, recent studies show that the bias against female entrepreneurs is shown to be particularly strong for socially attributed characteristics (Pistilli et al. 2023), when angel investors are politically conservative (Chen et al. 2023), and when objective information about prior experiences and qualifications is not available (Tinkler et al. 2015), which is often the case in the context of televised pitch competitions. ...
... In the realm of entrepreneurial finance, there is still a substantial research gap regarding the impact of attractiveness. Initial evidence from Brooks et al. (2014) suggests a systematic attractiveness bias in pitch settings: Attractive male entrepreneurs were rated as significantly more persuasive, even when the content of the pitch was exactly the same. Interestingly, this effect was not found for female entrepreneurs. ...
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... Thirdly, entrepreneurs and their ventures play a critical role in the economy, particularly in innovation and job creation [10,11], making them important subjects for research, education, and policy making. Lastly, there is considerable interdisciplinary research interest in private personal attributes as correlates of entrepreneurship [12,13,14,15,16]. ...
... For example, certain groups could be exposed to discrimination and stereotyping which could affect their likelihood of becoming an entrepreneur and hence representation in the dataset we used and the respective classification results. Social bias in the real world is well documented in a myriad of studies (e.g., in investment decisions affecting entrepreneurs [13] or the 'what is beautiful is good' stereotype [41]; see also [25]). We also acknowledge the well-documented dangers of following any 'illusions' of understanding AI-driven research results [42]. ...
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... For example, certain groups could be exposed to discrimination and stereotyping which could affect their likelihood of becoming an entrepreneur and hence representation in the dataset we used and the respective classi cation results. Social bias in the real world is well documented in a myriad of studies (e.g., in investment decisions affecting entrepreneurs [13] or the 'what is beautiful is good' stereotype [41]; see also [25]). We also acknowledge the well-documented dangers of following any 'illusions' of understanding AI-driven research results [42]. ...
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Full-text available
Occupational outcomes like entrepreneurship are generally considered personal information that individuals should have the autonomy to disclose. With the advancing capability of artificial intelligence (AI) to infer private details from widely available human-centric data, such as social media, it is crucial to investigate whether AI can accurately extract private occupational information from such data. In this study, we demonstrate that deep neural networks can classify individuals as entrepreneurs based on a single facial image with high accuracy in data sourced from Crunchbase, a premier source for entrepreneurship data. Utilizing a dataset comprising facial images of 40,728 individuals, including both entrepreneurs and non-entrepreneurs, we trained a Convolutional Neural Network (CNN) and evaluated its classification performance. While human experts (n = 650) and trained participants (n = 133) were unable to classify entrepreneurs with accuracy above chance levels (> 50%), the AI model achieved a classification accuracy of 79.51%. Several robustness tests show that this high level of accuracy is maintained under various conditions.
... In this instance, the sending of signalsdescribed as quantities that transmit information about the state of a system to an audience-is deliberate (Spence, 1973). However, on other occasions, signals may lack intentionality (Milosevic, 2018) in that any observable cue, such as one's physiognomy (Brooks et al., 2014;Graham et al., 2017), could be a target for inference by a receiver. Signaling theory therefore relates to the process of communicating information, both intended and nonintended, via verbal and nonverbal modes. ...
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