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Does Equity Crowdfunding Democratize Entrepreneurial Finance?

January 2018
SSRN Electronic Journal

January 2018

DOI:10.2139/ssrn.3281727

Authors:

Douglas Cumming

Florida Atlantic University

Silvio Vismara

University of Bergamo

Michele Meoli

University of Bergamo

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Electronic copy available at: https://ssrn.com/abstract=3247120

Does equity crowdfunding democratize entrepreneurial finance?

Douglas Cumminga, Michele Meolib, Silvio Vismarab, c

a York University, Schulich School of Business, Canada

b University of Bergamo, Italy

c Ghent University, Belgium

Abstract

Policy-makers expect equity crowdfunding to democratize entrepreneurial finance, by providing

access to funding to underrepresented groups of potential entrepreneurs. This paper investigates

whether gender, age, ethnicity, and geography affect the choice of equity crowdfunding offerings vs

initial public offerings (IPO) on traditional stock markets and whether these characteristics increase

the likelihood of a successful offering. Using 167 equity offerings in Crowdcube and 99 equity

offerings on London’s Alternative Investment Market raising between 300,000 £ and 5 £m, we find

that companies with younger top management team (TMT) members are both more likely to launch

equity crowdfunding offerings than IPOs, and have higher chances to successfully complete an

equity crowdfunding offering. Remotely located companies are more likely to launch equity

crowdfunding offerings than IPOs and have higher chances to successfully complete an equity

crowdfunding offering. On the contrary, female entrepreneurs do not have higher chances to raise

fund in equity crowdfunding. Minority entrepreneurs do not have higher chances of successfully

raising capital but attract a higher number of investors.

Electronic copy available at: https://ssrn.com/abstract=3247120

1. Introduction

A growing interest in crowdfunding is shared by practitioners, policymakers, the media, and scholars

alike. As a new and powerful tool for entrepreneurs, crowdfunding can help push the boundaries of

existing theories and help develop new ones. In fact, new digital and information communication

technologies (ICT) have transformed the nature of uncertainty inherent in entrepreneurial processes

and outcomes as well as the ways of dealing with such uncertainty (Nambisan et al., 2017). ICT can

indeed alleviate some of the problems of traditional entrepreneurial finance markets and solve market

failure.

As a parallelism, we look at the impact of ICT on urban bike-sharing programs. Already in 1965,

Provos released the White Bike Plan in Amsterdam. With no record of who checked out which bike,

the plan failed a few weeks after as bikes were often stolen or damaged. After many other attempts,

in 1995, a coin-deposit system was established in Copenhagen (Bycyken), with 2,000 distinguishable

bicycles with docking stations. Nevertheless, the program was terminated due to frequent thefts and

damages attributed customer anonymity. More recently, Shaheen et al. (2010) report that in 2009

bike-sharing programs were operating with 150,000 bikes in 125 (mostly European) cities. The

estimates grow to over 1m bikes in 800 bike-sharing programs in 2014 (Campbell et al., 2016). In

2017, Beijing banned new shared bikes as riders can already access 2.5m. Currently, urban bike-

sharing programs run station-less scan&ride systems with real-time monitoring of occupancy, credit

scores, and penalties, that ultimately allows for selection of users. This parallelism shows that ICT

has the potential to lower information asymmetries and alleviate market failure problems.

Similarly, ICT can reduce adverse selection and moral hazard problems in entrepreneurial finance.

As far as the availability of finance is a critical element to entrepreneurship, understanding why some

categories of individuals are underrepresented in entrepreneurship is a question of both academic and

social interest. For instance, the paucity of ethnic entrepreneurs or the unequal access between

genders to the necessary resources to establish sustainable new ventures has received increasing

Electronic copy available at: https://ssrn.com/abstract=3247120

media attention. To add to this debate, this paper investigates whether crowdfunding is as inclusive

as often portrayed. The expectation is indeed that by replacing a small set of homogeneous experts

with a diverse crowd, the significance of a founder’s gender or race will decline. In particular, existing

studies have found a more pronounced diversity in sophistication and experience among investors in

equity crowdfunding relative to traditional equity offerings (Cumming et al., 2018).

While

professional investors follow a market logic also when investing in crowdfunding, small,

unsophisticated investors are found to consider community logic (Vismara, 2018b).

Clear associations between gender, ethnic or geographic disadvantage and funding are difficult to

isolate given that exogenous variables intrude into the process of finance and performance in general.

There is, in general, conflicting or scarce evidence regarding whether fundraising via crowdfunding

platforms is actually easier for traditionally underrepresented groups. In particular, most of the

existing studies focus on a specific aspect, such as gender or geography, in the context of reward-

based crowdfunding. Equity-based crowdfunding is, however, intrinsically different from reward-

based crowdfunding. While in equity crowdfunding, the proponent is by definition a company,

reward-based campaigns are launched mostly by individuals. The motivations to bid for a reward are

also likely to be different from those to invest in a company’s equity. Coherently, Vismara (2016)

finds that offering rewards to investors does not increase the probability of success of equity

crowdfunding campaigns. The governance and organizational implications of the process of raising

equity capital through crowdfunding are arguably different from those of pre-selling a product or a

service in reward-based crowdfunding (Cumming et al., 2018). Consistently, prior studies on

minorities in crowdfunding are mainly based on consumer theory (e.g., Younkin and Kuppuswamy,

2017).

While the majority of recent IPOs have been offered exclusively to institutional investors, crowdfunding

investors are likely to be much more diverse. Over the last two decades, three quarters of the IPOs in Europe

took place in secondary markets, such as London’s Alternative Investment Market (AIM). Most of these IPOs

were offered exclusively to institutional investors (Vismara, Paleari, & Ritter, 2012). Although institutional

investors are being allocated the largest fraction of IPO shares (Aggarwal, Prabhala, & Puri, 2002), equity

crowdfunding is likely to attract a much more diverse set of investors.

Electronic copy available at: https://ssrn.com/abstract=3247120

Crowdfunding platforms allow anyone to view projects posted online, allowing for a more

heterogeneous population of backers. This results in a promising path to funding categories that

typically find it difficult to deal with business angels or venture capitalists (VCs). Recent research

has indeed shown that these private investors bid in equity crowdfunding (Signori and Vismara,

2018). The complementarity between crowdfunding and early-stage private equity makes it more

appealing for entrepreneurs to launch a crowdfunding campaign, as the availability of professional

investors will help in case low participation by small investors (Schwienbacher, 2018). In private

equity, the deal is between the entrepreneur and a restricted number of providers of capital.

Entrepreneurs can choose who they deal with and are able to negotiate the terms of the contract,

including the price and amount of shares. In equity crowdfunding, instead, offerings are open to the

public. Once the offering is listed on the crowdfunding platform, the price is fixed and the ownership

structure is solely defined by investors’ demand for shares. For this reason, we believe that traditional

initial public offerings (IPOs) represent a more appropriate term of comparison for equity

crowdfunding offerings than private equity deals. Interviews with practitioners support this

contention. For instance, Marcus Stuttard, Head of AIM and UK Primary Markets at London Stock

Exchange Group, has recently declared that both IPos and equity crowdfunding offerings

“democratise how equity investments are made and make it easier for people to invest. Equity

crowdfunding was the first step – and, after all, the stock market was one of the original forms of

crowdfunding”.

While traditional private deals are limited to a relatively small group of private investors, equity

crowdfunding allows issuers to broadly solicit and advertise their securities to the general public,

thereby increasing the diversification of potential investors. Two decades ago, online auction IPOs

were viewed as alternatives to the traditional book-building method of IPO underwriting (Ritter,

2013). However, despite being considered an efficient market mechanism to lower the costs of going

https://www.syndicateroom.com/learn/investor-tools-reports/why-aim-needs-crowdfunding-an-interview-

with-marcus-stuttard

Electronic copy available at: https://ssrn.com/abstract=3247120

public, the expectations of online auction IPOs were never realized. Only one investment bank, W.R.

Hambrecht, has developed a platform for online public offerings, and only 20 companies in the US,

most notably Google, have gone public this way, with the last occurring in 2007 (Ritter, 2013).

Despite the unmatched expectations of democratization and disintermediation, IPOs in traditional

stock markets are the closest term of comparison for equity crowdfunding offerings.

The present paper is among the first to empirically assess the potential of equity crowdfunding to

finance underrepresented categories of entrepreneurs. Specifically, we believe that democratization

in entrepreneurial finance should be investigated along four dimensions, namely geography, age,

gender, and ethnicity biases. If equity crowdfunding is effectively democratizing access to funding,

it should provide means of financing to these four categories which are typically referred to as

financially constrained. This paper, therefore, investigates the democratization potential of equity

crowdfunding from a broader perspective then previous studies. Most importantly, this paper

integrates the analysis of the determinants of success of the offerings with a first-stage investigation

of the self-selection into equity crowdfunding. We compare a sample of 167 equity offerings in

Crowdcube, the world largest equity crowdfunding platform, with 99 IPOs on the loosely regulated

London’s Alternative Investment Market (AIM). These two samples were identified by including

only offerings in Crowdcube or on the AIM between 2013 and 2016, raising more than £300,000 and

less than £5 million.

The paper is organized as follows. Section 2 reviews previous studies and present our hypotheses.

Section 3 illustrates the research design. Econometric results are reported in Section 4, and

conclusions are provided in Section 5.

2. Literature review and hypotheses

This paper is not the first to question whether crowdfunding democratizes access to finance, by

investigating whether individuals discriminated by traditional financial institutions have more

Electronic copy available at: https://ssrn.com/abstract=3247120

opportunities when targeting crowdfunding. Some previous studies have looked at specific individual

characteristics of entrepreneurs such as gender and race (Catalini et al., 2016; Pope and Sydnor, 2011;

Marom et al., 2016; Greenberg and Mollick, 2017; Younkin and Kuppuswamy, 2017). In this Section,

we review the entrepreneurial finance literature with regard to four dimensions, namely gender, age,

ethnicity, and geography.

2.1. Gender

Gender differences in capital markets do exist. Although there is no evidence of discrimination in

terms of approval/turndown rates, few women apply for debt capital (Cavalluzzo et al. 2002) and they

are charged a higher interest rate on their loans or have greater collateral requirements compared to

men (Coleman 2000; Fabowale et al. 1995; Riding & Swift 1990). Gender skewness is more evident

in accessing external equity, women receive a substantially smaller proportion of VC financing than

men do. Part of the motivations points to gender differences in human capital, social capital or growth

aspirations, or differences between men’s and women’s ventures (Carter & Rosa 1998). Women are

less likely to have prior entrepreneurial or/and managerial experience and to participate in networks

with high net worth individuals (Verheul & Thurik 2001). Stereotypically, masculine characteristics

associated with leader emergence (Fagenson 1993) may attract VCs, as they expect a funded venture

to grow rapidly in term of sales and profits. Additionally, male dominance among VCs and traditions

related to investment in male-dominated industries (Greene et al. 2001) impact the gender bias in

entrepreneurial finance.

Gender studies in crowdfunding see it as more democratic, at least relative to traditional seed

investors such as business angels. In reward crowdfunding, females are more likely to successful raise

capital than male founders, all else being equal. Marom et al. (2016) find that women make up about

Brush et al. (2004) document that although women own more than 30 percent of US businesses, they

receive less than 5 percent of venture capital funds distributed annually. The angel market is predominantly

comprised of male investors. Only about 10 percent of VCs and less than 15 percent of business angels are

women. In addition, only 15% of women-led companies were successful in raising capital, as compared with

22% for male-led companies (Stengel, 2015).

Electronic copy available at: https://ssrn.com/abstract=3247120

35 percent of the project leaders and 44 percent of the investors on the Kickstarter platform. Using

data from a laboratory experiment, Greenberg and Mollick (2017) document that women are more

likely to succeed at a reward-based crowdfunding campaign and this effect primarily holds for female

founders proposing technological projects. Radford (2016) uses data from DonorsChoose, a US-

based crowdfunding website for public school teachers, to document that inequality only emerges

after educators’ identities were published. Deanonymization (teachers’ identities were hidden until

2008) caused inequality to emerge across all types of gender difference. Using data from a Swedish

crowdfunding platform, Mohammadi and Shafi (2018) find that female investors are more likely to

invest in projects in which the proportion of male investors is higher.

Some of the arguments to support the above mentioned studies, however, apply more to reward-based

crowdfunding than to equity crowdfunding. While men are guided by agentic goals, and therefore,

focus more on the pursuit of personal achievement, women are guided by communal goals and put

more emphasis on the development of interpersonal relationships (Carlson 1972). They also have

stronger feelings than men about ethical issues concerning disclosure (Roxas & Stoneback 2004).

The social role theory of leadership (Eagly et al. 1995) contends that female leaders are more likely

to show concern for people, whereas male leaders are more likely to possess traits that reinforce

competition. This line of thought is in line with the decision to donate or to bid small amounts of

money to pledge rewards. The motivations to become costumers in reward-based crowdfunding are

indeed likely more linked to ethical motivation than in entrepreneurial financial markets (Vismara,

2018a).

For this reason, the equity crowdfunding market offers a complementary perspective, at the crossroad

between entrepreneurial and consumer finance. So far, the evidence is rather mixed. In a study of the

UK platform Crowdcube, Vismara et al. (2016) find that female investors in female-led businesses

are twice those in male-led businesses. Using projects listed on German platforms, Prokop and Wang

(2018) find that equity crowdfunding campaigns initiated by women attract fewer investors, as well

Electronic copy available at: https://ssrn.com/abstract=3247120

as lower funding amounts than those initiated by men. In this study, we test whether female-led

companies are more likely to launch equity crowdfunding offerings than IPOs and whether they have

higher chances to successfully complete an equity crowdfunding offering.

Hypothesis 1a. Female-led companies are more likely to launch equity crowdfunding offerings than

IPOs.

Hypothesis 1b. Female-led companies have higher chances to successfully complete an equity

crowdfunding offering.

2.2. Age

Bill Gates founded Microsoft in 1975 at age nineteen. Just four years after the relevant state passed

legislation lowering the age of contractual capacity from 21 to 18 (Manes and Andrews, 1993). More

recently, Mark Zuckerberg co-founded Facebook at age nineteen. These two examples offer an idea

of the importance of the young entrepreneurship, which has been so far underinvestigated. On one

hand, entrepreneurial intention decrease with age, due to the increasing opportunity cost of time with

age (Lévesque and Minniti 2006). On the other, entrepreneurial opportunities increase with age

because of higher accumulated physical, social, and human capital (Lee and Vouchilas 2016).

Coherently, entrepreneurial propensity is found to increase with age in some studies (Fairlie et al.

2016) but declining in others (Parker 2009). Zhang and Acs (2018) argue that the relationship between

age and entrepreneurship depends on the type of entrepreneurship, as non-novice and novice

entrepreneurs have significantly different skills, competencies, and information. They find that

entrepreneurial propensity of novice (versus non-novice) entrepreneurs has a U-shaped age trend

dipping around age 60, while the propensity of full-time (versus part-time) declines since age 30s.

Electronic copy available at: https://ssrn.com/abstract=3247120

Studies on equity crowdfunding have so far neglected the role of the age of the proponents. On one

hand, the experience of the founders might be perceived positively by external investors. In a quasi-

equity crowdfunding context, Piva and Rossi-Lamastra (2017) find that entrepreneurs’

entrepreneurial experience significantly contribute to entrepreneurs’ success in equity crowdfunding.

Nevertheless, crowdfunding has the potential to broaden the categories of individuals raising external

equity also with regard to age. Schwartz (2015) argues that teens are well positioned to exploit this

new opportunity, with the upshot being that securities crowdfunding may become an important way

for youthful entrepreneurs. For these reasons, we hypothesize:

Hypothesis 2a. Companies with younger TMT members are more likely to launch equity

crowdfunding offerings than IPOs.

Hypothesis 2b. Companies with younger TMT members have higher chances to successfully complete

an equity crowdfunding offering.

2.3. Ethnicity

The role of ethnicity in entrepreneurship and the underrepresentation of minorities among the

population of funded ventures (Aldrich and Waldinger, 1990) is the subject of increasing attention.

Fairlie and Robb (2007) show that the availability of startup capital is conditioned by race. Similarly,

the argument for gender bias, an explanation for this underrepresentation is that resource providers

are biased against minority founders, thereby ascribing the bias also to pre-entry constraints. The

theory of statistical discrimination (Arrow 1998) suggests that prospective supporters use race as a

proxy for unobserved traits that indicate the investment is more likely to fail (Morse, 2017).

Alternately, taste-based discrimination (Becker 1957) implies that prospective supporters reject

minority founders, irrespective of their qualifications, out of their own distaste for minorities more

broadly.

Electronic copy available at: https://ssrn.com/abstract=3247120

Crowdfunding moves the locus of funding decisions away from a small pool of experts and spreads

them out across a much broader population of potential contributors. While crowdfunding platforms

presumably remove one of the primary causes of racial disparities in entrepreneurship (access to

capital), recent studies indicate that minority founders continue to face significant bias even on these

platforms. If, indeed, Herzenstein et al. (2008) find that P2P lenders are less influenced by racial

stereotypes than are banks, racial bias is found by Pope and Sydnor (2011) in Prosper.com. Duarte et

al. (2012) show that P2P lenders rely on impressionistic short-hand information such as prospects’

appearance. Crowdfunding is indeed a context in which the race of the founder is readily apparent

and easily identified by potential backers, making it more plausible that founder race influences

backer behaviour. Younkin and Kuppuswamy (2017) find that minority founders face price discounts,

rooted in an assumption that minority founders invest less time and have lesser aspirations. Using

experimental data, Younkin and Kuppuswamy (2018) find that despite the promise of crowdfunding,

prospective funders remain biased against African American founders. They explain these results

using Becker’s (1957) theory of consumer discrimination.

In this paper, we move from consumer theory to finance, to text for the first time the effect of ethnicity

in equity crowdfunding.

Hypothesis 3. Companies with TMT members belonging to minorities have higher chances to

successfully complete an equity crowdfunding offering.

2.4. Geography

The VC literature has frequently noted that the likelihood of investing in a venture decreases with

geographic distance, because of, e.g., due diligence costs and ongoing monitoring efforts (see

Sorenson and Stuart 2001). More broadly, finance literature shows that investors tend to prefer

geographically close investment opportunities (see, e.g., French and Poterba 1991; Sulaeman (2014).

Electronic copy available at: https://ssrn.com/abstract=3247120

The arguments for such preference, and related “home bias” are related to lower information

asymmetries, better monitoring capabilities and lower associated costs (Coval and Moskowitz 2001).

In crowdfunding, equal and close to zero cost access to portals should facilitate exposure, increase

familiarity, and improve access to information about entrepreneurial projects for investors. Thus,

geographic distance should largely cease to matter to investors. Coherently, policymakers have

identified crowdfunding as a promising means to cost-effectively bridge geographic boundaries. They

hope to at least partially eliminate distance-related economic frictions that are apparent in the early-

stage VC market through these types of internet-based funding platforms (Lin and Viswanathan

2016). As asserted by Agrawal et al. (2011), the online platform seems indeed to reduce some

distance-related economic frictions such as monitoring progress, providing input, and gathering

information.

Equity crowdfunding is therefore expected to increase the opportunity of financing for remotely

located and less connected individuals. Nevertheless, social connections tend to exist locally not just

in physical space but also in social space. Afonso et al. (2014) demonstrate that personal interaction

is a desirable ingredient in relationship banking. Social network connections between investors and

entrepreneurs are found to valuable also in reward-based (Colombo et al., 2014; Polzin et al., 2018)

and in equity crowdfunding (Vismara, 2016). Hence, needing real-world connections limits the scope

of information advantages in the crowd. Moreover, challenges of investment protection might become

an impediment when investing outside of the home country. Despite equity crowdfunding should

overcome geographical barriers, the first evidence is that geographical proximity matters. Ordadini

et al. (2011) find that investors in reward-based crowdfunding are often located in the same

geographical area as the proponent. Guenther et al. (2018) find that very few investors and companies

are located in rural areas. Burtch et al. (2014) confirm that P2P lenders prefer culturally similar and

geographically proximate borrowers.

Electronic copy available at: https://ssrn.com/abstract=3247120

There are therefore conflicting arguments about the geographical aspects of crowdfunding. However,

if distance is not as important as before, as its online, this means that traditionally constraints business

should “tap” this new opportunity. This means that, relative to traditional finance markets, equity

crowdfunding should be more attractive for remotely located companies. For this reason, we

hypothesize that:

Hypothesis 4a. Remotely located companies are more likely to launch equity crowdfunding offerings

than IPOs.

Hypothesis 4b. Remotely located companies have higher chances to successfully complete an equity

crowdfunding offering.

3. Research design

3.1. Sample

Given that our analysis aims, first, to compare the access to alternative sources of financing for young

entrepreneurial ventures, namely crowdfunding and initial public offerings (IPOs), we need to set up

a dataset comprising both types of offerings. In this respect, the UK market is a natural testing bed,

given the presence of one of the most popular second markets for IPOs in the world, the AIM

(Alternative Investment Market), as well as that of a well-developed platform for crowdfunding

platform such as Crowdcube. Indeed, extant literature has largely discussed how the AIM is preferred

by firms that do not meet the listing requirements of the prime market (Baker et al., 2002; Ritter et

al., 2013; Vismara et al., 2012), and its popularity is largely due to flexible listing requirements.

Crowdcube, on the other hand, is by far the largest equity crowdfunding platform in the UK, which,

Electronic copy available at: https://ssrn.com/abstract=3247120

is the largest equity crowdfunding market (Estrin et al., 2018)

. Established in 2011, Crowdcube is,

as of February 2017, the world’s largest platform, with £215 million successfully raised from more

than 350,000 investors from over 100 countries. Extant literature has discussed how the regulation of

equity crowdfunding in the UK is often put forward as an important ingredient of its development, so

that it serves as a model for other legislations (Steinhoff, 2015), and how the specific regulatory

framework provided by Crowdcube has allowed a lively participation of crowd as well as professional

investors (Cumming et al., 2018). Moreover, the emergence and the optimal regulation of equity

crowdfunding can be achieved only in the presence of developed alternative entrepreneurial finance

markets (Hornuf and Schwienbacher, 2017). In summary, the contemporaneous existence of AIM

and Crowdcube allows an analysis of the choice of sources of entrepreneurial financing.

Indeed, we have to take into consideration the fact that Crowdcube has been recently launched and

that an IPO, even on an exchange-regulated market, provides costs that require a minimum investment

scale. Therefore, in order to identify only those issues that were potentially the object of an offering

on the AIM or on Crowdcube, we selected Crowdcube’s and AIM’s offerings that were placed

between 2013 and 2016, raising more than £300,000 and less than £5 million. This procedure has

lead us to identify a list of 167 equity offerings offered on Crowdcube and 99 IPOs on the AIM

3.2. Model

Crowdcube has raised more capital than all other competing platforms (AltFi.com, 2015). Different sources agree on

the leading role of Crowdcube. Beauhurst names Crowdcube as the leading equity investor in 2015 and the most prolific

investor in the e-commerce sector. Crowdsurfer estimates Crowdcube’s share in the UK investment crowdfunding market

in 2015 at 52%.

The £300,000 lower boundary has been chosen in order to drop out a 1% share of extremely small IPOs on the AIM.

The £5,000,000 upper boundary has been chosen in order to drop out a less than 1% share of extremely large crowdfunding

campaigns. In between, we have a sample of 167 equity crowdfunding campaigns (out of our full sample of, 643

campaigns) and 99 IPOs on the AIM (out of the population of 224 IPOs), comparable in size. While we are aware that

the two subsamples may not perfectly poolable, and this is why we try to control for as many variable as possible, when

trying to collect such an amount of money, a venture has had the possibility to opt either for a crowdfunding campaign or

for an IPO on the AIM, conditional on several variables. The goal of our first stage is indeed to try and identify how such

contextual variables are correlated with the choice of financing mechanism.

Electronic copy available at: https://ssrn.com/abstract=3247120

Our analysis comes in two stages. In a first stage, we aim to disentangle whether the features

traditionally linked to the limited availability of funding (gender, age, and regional remoteness), drive

the choice of financing source towards crowdfunding, vis-à-vis IPOs on the AIM. This analysis aims

to provide empirical support for hypotheses 1a, 2a, and 4a. In a second stage, we analyse whether the

same determinants are correlated with the success of crowdfunding offerings (in terms of probability

to reach the target, or in terms of number of investors). This stage aims to validate hypotheses 1b, 2b,

3 and 4b.

Indeed, the features increasing the likelihood to choose a crowdfunding offering versus an IPO on the

AIM may be at the same time determinants of success. Therefore, we need to deal with a potential

sample selection bias (Heckman, 1979), by estimating the two following system of equations

 

  [1]

  

    [2]

And:

 

  [3]

  

    [4]

Where  is a dummy variable equal to 1 for firms choosing a crowdfunding offering;

 and  are the dependent variables in the second stages; 

 and 

 contain

the observable determinants of the latent propensity to prefer a crowdfunding offering over a listing

on the AIM, and of the dependent variables in the second stages, respectively;  is the inverse

Mill’s ratio proposed by Heckman, estimated out of the first stage and included in the second stage

in order to account for the potential bias caused by the sample selection described above. Given that

Each system is a pair of equation, where the former is the selection equation and the latter the outcome equation.

Following Heckman (1979) the two equations are estimated sequentially (first and second stage), in order to grant the

correct estimation of the IMR’s standard errors.

Electronic copy available at: https://ssrn.com/abstract=3247120

this  accounts for the unobservable component in the decision to choose a crowdfunding initiative

over a listing in the AIM, we are identifying this parameter as Prone-to-Crowdfunding in our

regression setting

The second stage measures the success of equity crowdfunding offerings. Therefore, we compare

both successful and failed crowdfunding campaigns against only successful IPOs. This is done for

two reasons. First, differently from what happens in the United States, IPOs are infrequently

withdrawn in Europe (Ritter, 2003). In our sample period, less than 5% of the IPOs on the AIM have

been withdrawn during the process. Second, while failing to reach the target capital in an equity

crowdfunding offerings is due to an insufficient demand for shares, an IPO withdrawal can be a

positive event, as IPOs are often withdrawn due to superior option for cashing out options for

entrepreneurs (Boeh and Dunbar, 2013).

Given that the dependent variable in equation 2 is a dummy variable, the system composed by

equation 1 and 2 is a probit model

with sample selection, and can be estimated according to Van de

Ven and Van Pragg (1988). By contrast, the dependent variable in equation 4 is a count variable, such

that the system composed by equation 3 and 4 is a count model, namely a negative binomial regression

model, with sample selection, which can be estimated according to Terza (1998).

3.3. Variables

In the first stage of our analysis, the dependent variable is a dummy identifying crowdfunding

initiatives in a sample comprising crowdfunding offerings and IPOs on the AIM. In the second stage,

Please consider that, following Heckman (1979), 

 should grant identification by an exclusion restriction, i.e. there

should be at least one parameter excluded from 

. In our setting, the exclusion restriction is given by the presence in

the first stage of industry dummies.

In the case of binary dependent variable, it is common practice to use either Logit or Probit models, with preference

for the one or the other often based on empirical issues. In our case, given that we need to implement a model with

sample selection, we need to rely on the Heckman (1979) assumption that both error terms (in the selection and in the

outcome equation) are normally distributed, in order to calculated and use the Inverse Mill’s Ratio. This is why, in line

with previous literature, we opt for a Probit, rather than a Logit model, for both our equations. This choice grants

estimation feasibility according to Ven and Van Pragg (1988).

Electronic copy available at: https://ssrn.com/abstract=3247120

limited to crowdfunding offerings, our analyses are performed with reference to two alternative

measures of performance.

First, we investigate the determinants of Success, a dummy variable equal to 1 for successful

offerings. Second, we look at investor participation in crowdfunding offerings. Our variable here is

the Number of investors participating in the offering as an alternative dependent variable assessing

the success in terms of investor participation.

In both stages, our goal is that of identifying the effects of characteristics typically associated with

financial constraints. In order to test hypotheses 1a and 1b, we use Female leadership, a dummy

variable equal to one when the majority of the members in the TMT are women

. We took several

steps to code genders based on first names. We first algorithmically used the API of genderize.io.

The algorithm returns the gender and a probability that a specific name-gender attribution (male or

female) was correct. In a second step, a research assistant double-checked the accuracy of the codes

and completed the missing variables, with additional help from the pictures displayed on the platform

website. Hypotheses 2a and 2b are tested by including Age in our model, namely the average age of

all members of the TMT, calculated at the end of 2016, the latest point in our sample. Hypothesis 3

is tested by using Ethnical minority, a dummy variable, equal to 1 if at least one member of the TMT

is non-Caucasian

. To obtain such information, we had at least two separate raters visit the project

webpage and examine the photo associated with the entrepreneurial team. Ethnical minority take the

value 1 only if all raters agreed that one of the team members is non-Caucasian, as in Herzenstein et

al. (2008). This approach captures the perceived identity of the founder irrespective of self-

identification. We used a conservative measure, which requires full agreement. In cases of

disagreement, the offerings were removed from the study. Last, Hypotheses 4a and 4b are tested by

The simple presence of women in the TMT is also tested in the robustness analysis, by replacing Female leadership

with Female presence, a dummy variable equal to 1 for all offerings when at least one woman belongs to the TMT of

the focal firm.

This variable is not available for our sample of IPOs, and is therefore used only in the second stage analysis.

Electronic copy available at: https://ssrn.com/abstract=3247120

using Metropolitan area

, a dummy variable, equal to 1 if the firm belongs to a metropolitan area,

according to the Census 2011 classification (i.e. metropolitan areas of London, Birmingham,

Manchester, Leeds-Bradford, Liverpool-Birkenhead, Newcastle, Sheffield, South Hampshire,

Nottingham-Derby, and Glasgow).

To control for potential variation in the quality of the projects, we include in all our analyses a series

of variables concerning the project and its proponents, collected through the presentation pages for

each project made available by Crowdcube, and through the prospectus in the case of IPOs: Equity

offered is the share of equity made available for the crowdfunding campaign, or for the offering on

the AIM; Target is the amount bid for crowdfunding initiatives, and total proceeds for IPO offerings;

Firm Age is the difference, in years, between the beginning of the crowdfunding campaign, or the

offering on the AIM, and the foundation date; TMT size is the number of people in the top

management team (TMT members are identified in the “team” section of each offering, as reported

on the platform’s portal); Positive sales is a dummy variable equal to 1 if the company has already

reported positive sales at the campaign/IPO; Patents is a dummy variable equal to 1 if the company

owns or is filing patents at the campaign/IPO; and Population refers to inhabitants in the NUTS-3

area where the firm is located. In order to grant the identification conditions required by Heckman

(1979), the set of controls in the first stage is increased by the inclusion of industry dummies

In the robustness analysis, this variable is replaced with GDP per capita and Unemployment rate, both measured at

the NUTS-3 level.

The Classification of Territorial Units for Statistics (NUTS; French: Nomenclature des unités territoriales statistiques)

is a geocode standard for referencing the subdivisions of countries for statistical purposes, developed and regulated by

the European Union. For each EU member country, a hierarchy of three NUTS levels is established by Eurostat in

agreement with each member state. In the UK, the NUTS-3 level refers to upper tier authorities and groups of unitary

authorities and districts: there are 93 NUT-3 areas in England, 12 in Wales, 23 in Scotland and 5 in Northern Ireland.

We make use of 9 dummies, according to the first digit (industry) of the ICB, the Industry Classification Benchmark,

a taxonomy launched by Dow Jones and FTSE in 2005 and now owned solely by FTSE International. Notice that ICB is

available from prospectuses for IPOs, while it has been manually identified for Crowdcube’s campaign, based on the

industry description available on the platform. We are aware that the set of industry dummies is likely to potentially

affect the outcome of a crowdfunding campaign. Empirically, in our setting we tested for the excludability condition

through the Hansen’s J test. The joint null hypothesis of this test is that the instruments are valid instruments, i.e.,

excludable from the outcome equation, and the p value states the probability that the test statistic is zero, which would

imply acceptance of the null hypothesis. Given that p is much greater than 10% in our case, we have evidence

supporting our choice.

Electronic copy available at: https://ssrn.com/abstract=3247120

In Table 1, a summary of variable description is provided.

[INSERT SOMEWHERE HERE TABLE 1]

Table 2 provides descriptive statistics for all the variables employed in our analyses. Our sample is

composed of 167 equity offerings on Crowdcube and 99 IPOs on the AIM, each of them raising more

than £300,000 and less than £5 million, between 2013 and 2016. 48.5 of crowdfunding campaigns

have been successful, with an average of 237.9 investors involved.

Descriptive statistics on the explanatory variables provide univariate evidence on the different

attractiveness of crowdfunding and IPOs for financially constrained categories. No statistically

significant difference is found for Female leadership, though when looking at Female presence one

can notice how the vast majority of IPOs provides for at least one female member in the TMT

(81.3%), differently from crowdfunding offering, where a woman is present in 52.1% of the

campaigns. Crowdfunding offerings are preferred by younger teams, with an average age of 42, with

respect to 46.2 average years of an IPO’s TMT. Further, a large majority of IPOs are performed by

firms located in metropolitan areas (57.2%), with respect to a limited 50.4% of crowdfunding

campaigns. This corresponds to areas promoting crowdfunding offerings characterized by a smaller

population, lower GDP per capita and lower unemployment rates, with respect to the average NUTS-

3 are promoting an IPO. Last, crowdfunding offerings campaigns involve ethnical minorities in 16%

of cases.

Indeed, crowdfunding and IPOs differ also under several perspectives which are controlled in our

analysis. Crowdfunding offerings, on average, offer a smaller percentage of equity (15.7 vs. 33.3),

are much smaller in size (£925,000 vs £2,312.1) and TMT size (3.5 vs. 5 members). Firms are similar

in age and have reported positive sales in half of the cases both in crowdfunding (49.2%) and IPOs

Electronic copy available at: https://ssrn.com/abstract=3247120

(50.4), although crowdfunding firms have patented less often (19.7% of cases) than IPO counterparts

(36.8%).

Correlations among all variables employed in this study are provided in Table A1 in the Appendix.

[INSERT SOMEWHERE HERE TABLE 2]

4. Results

Our analyses provide validation for our hypotheses with the two-stage models presented in equation

1-2 and 3-4. Hypotheses 1a, 2a, and 4a are tested in the first stage, while Hypotheses 1b, 2b, 3 and

4b in the second stages.

First-stage results are reported in the first column of Table 3

. We find evidence that crowdfunding

initiatives are preferred by younger TMTs (the coefficient for Age is equal to -0.033, and statistically

significant at a 5% level), and by firms out of metropolitan areas (the coefficient for Metropolitan

area is equal to -0.874, significant at a 1% level, implies lower probability of crowdfunding for firms

located in urban areas, with respect to rural/remote areas, and vice versa). No statistical significance

is found with respect to Female leadership. Our results, therefore, provide support for Hypotheses 2a

and 4a, while we do not have statistical evidence in support of Hypothesis 1a.

As far as control variables are concerned, we find confirmation of differences highlighted by

descriptive statistics, in that crowdfunding initiatives are more likely in the case of smaller equity

offered, smaller target, smaller TMT size, and smaller population for the NUTS-3 area of origin.

Models (2) to (6) in Table 3 reports our result on the determinants of success for the crowdfunding

initiatives in our sample. Model (1) reports a baseline specification with all control variables. Models

A first stage is estimated for all second-stage equation presented. Given that results are qualitatively identical, and

numerically extremely close, the first-stage equation is reported only once.

Electronic copy available at: https://ssrn.com/abstract=3247120

from (2) to (5) include a variable testing for the role of gender, age, ethnical minority and regional

features, respectively, while Model (6) jointly test for the presence of all these characteristics. Our

results show that female leadership and presence of ethnical minorities do not statistically impact on

the success of crowdfunding offerings, while younger TMTs and campaigns from non-metropolitan

areas are more likely to succeed (as provided by the negative sign of the Metropolitan area dummy).

Results are confirmed both when separately assessed and when jointly tested, and provide support for

Hypotheses 2b and 4b, while we do not have enough statistical evidence to confirm Hypotheses 1b,

and 3.

As far as the control variables are concerned, we find confirmation of findings in previous literature

in that both the share of equity offered and the target size reduce the probability of success.

Interestingly, the coefficient for the inverse Mill’s ratio, i.e. our measure of how Prone to

crowdfunding is any offering, is negative and statistically significant in all models (either at 5 or

10%). In practise, those features increasing the likelihood to choose a crowdfunding offering over an

IPO are negatively correlated to the probability of success.

[INSERT SOMEWHERE HERE TABLE 3]

In Table 4, we replicate the former analysis, after replacing Success with the Number of investors as

an outcome dependent variable. Again, model (1) reports a baseline specification with all control

variables, Models from (2) to (5) include a variable testing for the role of gender, age, ethnical

minority and regional features, respectively, while Model (6) jointly test for the presence of all these

characteristics. Results from the last Model show that Age is weakly significant in determining the

number of participating investors, such that younger TMTs typically attract more the crowd

(coefficient=-0.007, significant at less than 10%). Also offerings with a presence of an Ethnical

minority (coefficient=0.158, significant at less than 5%) and originated in non-metropolitan areas

Electronic copy available at: https://ssrn.com/abstract=3247120

(coefficient of Metropolitan area=-0.216, significant at less than 5%) have higher likelihood to attract

a high number of investors, while no statistically significant effect is found with respect to a Female

leadership. These results are in support of Hypotheses 2b, 3 and 4b, while again we do not have

enough statistical significance in support of Hypothesis 1b.

As far as controls are concerned, we find evidence that higher targets typically attract a larger number

of investors, while we have weak evidence that a large TMT size reduces the number of investors.

Our results also show how Positive Sales and Patents are interesting features in the eyes of investors.

Interestingly, the coefficient of the IMR is positive and significant, such that features increasing the

likelihood of a crowdfunding offering, over an IPO, are correlated to a larger number of participating

investors. This result, interestingly, differs from what has been observed in the former table,

highlighting that unobserved determinants of preference for crowdfunding over IPOs positively affect

the attraction of investors, but have a (weak) negative impact on the probability to succeed. This may

be due to a capability to attract a large number of small investors, i.e. by hype creation, while not

necessarily attracting enough funds for the success of the campaign.

[INSERT SOMEWHERE HERE TABLE 4]

4.1. Robustness analysis

In this section, we provide robustness analysis with respect to the variables employed for testing our

hypothesis. First, we test whether the presence of a woman (Female presence), rather than the

leadership in the team, might have an impact in the choice of a crowdfunding initiative, and in the

following success. Second, we replace our Metropolitan area dummy with variables measuring

specific features of the local area, such as the GDP per capita and the Unemployment rate. Last, our

findings with regard to geography might indeed depend on some specificities of the United Kingdom.

Electronic copy available at: https://ssrn.com/abstract=3247120

While we cannot rule out this possibility, we acknowledge that (1) distance might matters less in the

UK than in other countries, and (2) the leading role of London as financial centre might condition our

results. Third, we take into account the specificity of the UK geographical context, repeating our

analysis either including dummy variables for the 9 NUT-2 regions in the UK

or dropping all

observations for firms located in London.

All our robustness checks are reported in Table 5. Models A1-5 repeat our first stage when replacing

Female leadership with Female presence (Model A1), Metropolitan area with GDP per capita

(Model A2), Metropolitan area with Unemployment rate (Model A3), when including regional

dummies (Model A4) and when dropping London offerings (Model A5). Results show that Female

presence is negatively correlated to the probability to choose a crowdfunding initiative over an IPO.

This is likely to be due to the larger TMT size of IPO firms, as well as to the greater attention to

gender equality in official listing. GDP per capita and Unemployment, vice versa, are not correlated

to the likelihood to prefer a crowdfunding offering, although the signs (negative for GDP per capita

and positive for Unemployment) are coherent with the intuition that disadvantaged areas are more

likely to give raise to crowdfunding initiatives.

Models B1-5 and C1-5 report the results of our second stages. Again, we replace Female leadership

with Female presence (Models B1 and C1), Metropolitan area with GDP per capita (Models B2 and

C2), and Metropolitan area with Unemployment rate (Models B3 and C3), when including regional

dummies (Models B4 and C4) and when dropping London offerings (Models B5 and C5). Our results

show that Female presence does not significantly impact on the success of a crowdfunding campaign,

nor on the number of investors. As far as GDP per capita and Unemployment rate are concerned,

coefficients are weakly significant when analysing the Number of investors. Again, the signs support

that disadvantaged areas (with lower GDP per capita and higher Unemployment rate) are more likely

There are 12 NUTS-1 statistical regions in the UK: Northern Ireland, Scotland, Wales, and 9 regions for England

(North East; North West; Yorkshire and the Humber; East Midlands; West Midlands; East of England; Greater London;

South East and South West). Greater London is the reference case. See footnote 10 for details on the NUTS

classifications.

Electronic copy available at: https://ssrn.com/abstract=3247120

to generate a large participation of investors. Signs are coherent, but no statistical significance is

found, with respect to the probability of success. Finally, when including regional dummies our

results are qualitatively unchanged, while when removing London offerings, our findings are

confirmed, with lower significance in a few cases, probably because of the smaller sample size.

[INSERT SOMEWHERE HERE TABLE 5]

5. Conclusions

Although a growing number of studies are exploring the nuances of crowdfunding and its various

online platforms, research in this field is rapidly expanding (Block et al., 2018). The general

expectation is that crowdfunding “democratizes” entrepreneurial finance, thereby increasing the

possibility of underrepresented categories to raise finance. Gender, age, ethnicity, and geography are

among the most important aspects that affect the capacity to gain access to external capital. This

problem holds true for both debt and equity financing, where female, minorities and rural

entrepreneurs may face discrimination from external funding sources. Despite such premises, our

understanding of whether and how such characteristics of prospective entrepreneurs play in raising

funds in equity crowdfunding is still missing.

This study offers a timely contribution to the growing stream of research seeking to unveil the

possibilities of equity crowdfunding in facilitating entrepreneurship for those most vulnerable. First,

we find that age matters in equity crowdfunding, as companies with younger TMT members are both

more likely to launch equity crowdfunding offerings than IPOs, and have higher chances to

successfully complete an equity crowdfunding offering. This is a novel result in the crowdfunding

literature. Second, we find evidence that equity crowdfunding alleviates some of the distance-related

economic frictions between entrepreneurs and investors. Indeed, remotely located companies are

Electronic copy available at: https://ssrn.com/abstract=3247120

more likely to launch equity crowdfunding offerings than IPOs and have higher chances to

successfully complete an equity crowdfunding offering. On the contrary, female entrepreneurs,

typically considered financially constrained in traditional entrepreneurial markets, do not have higher

chances to raise fund in equity crowdfunding. Similarly, minority entrepreneurs do not have higher

chances of successfully raising capital. Nevertheless, this type of entrepreneurs is associated with a

higher number of investors. We interpret this evidence as a higher sensitivity to ethnicity from small

investors, relative to professional investors. Equity crowdfunding offerings, indeed, attract small and

professional investors alike. As these two types of investors have been found to have different

investment preferences (Signori and Vismara, 2018), their attitude towards ethnicity is likely to be

different. Future research might dig deeper in this direction, also leveraging the insights from

institutional logics (Friedland and Alford, 1991). While professional investors might follow a market

logic, small investors might also consider a community logic (Vismara, 2018b). This would explain

why ethnic entrepreneurs attract a higher number of investors but are at the end not more likely to

secure their target funding.

Future research might expand the assessment of the democratization potential of equity

crowdfunding from the demand side (entrepreneurs) to the supply side (investors), thereby delivering

a better understanding of the financial inclusion offered by disintermediated entrepreneurial finance.

Relatedly, studies are needed with regard to the matching between entrepreneurs and investors.

Research in entrepreneurship indicates that investors are attracted to entrepreneurs with whom they

share similarities. For instance, co-ethnicity increases the likelihood that a VC firm invests in a

company (Bengtsson and Hsu, 2015). The diverse backgrounds of participants in equity

crowdfunding markets permit researchers greater nuance in studying the influence of similarity

attraction in funding decisions. While we have investigated democratization along four dimensions

of constraints, other aspects are of interest. For instance, the socio-economic status or the religion of

proponents have not been investigated yet. In a preliminary analysis of the videos used to present the

Electronic copy available at: https://ssrn.com/abstract=3247120

offerings in our sample, we could not find any religious symbol. Beautiful people seem to attract

more favorable peer-to-peer loans (Ravina, 2012). Given crowdfunding applications gain less

publicity (and may be less face-to-face than other means of negotiating to obtain financing), could it

democratize for less beautiful people?

Electronic copy available at: https://ssrn.com/abstract=3247120

References

Afonso, G., Kovner, A., and Schoar, A. 2014. Trading Partners in the Interbank Lending Market.

Staff Reports, No. 620. New York: Federal Reserve Bank of New York.

Aggarwal, R., Prabhala, N. R., & Puri, M. 2002. Institutional allocation in initial public offerings:

Empirical evidence. The Journal of Finance, 57(3), 1421–1442.

Agrawal, A.K., Catalini, C. and Goldfarb, A.. 2011. The geography of crowdfunding. National

Bureau of Economic Research working paper.

Ahlers, G.K., Cumming, D., Guenther, C. and Schweizer, D., 2015. Signaling in equity

crowdfunding. Entrepreneurship: Theory and Practice, 39(4), 955–980.

Aldrich, H. and Waldinger, R., 1990. Ethnicity and entrepreneurship. Annual Rev. Sociology

16(1):111–135.

Arrow KJ (1998) What has economics to say about racial discrimination? Journal of Economic

Perspective, 12(2), 91–100.

Baker, H. K., Nofsinger, J. R., and Weaver, D. G., 2002. International cross-listing and visibility.

Journal of Financial and Quantitative Analysis, 37(3), 495-521.

Becker, G., 1957. The Economics of Discrimination (University of Chicago Press, Chicago).

Bengtsson, O., and Hsu, D.H., 2015. Ethnic matching in the U.S. venture capital market. Journal of

business Venturing, 30, 338-354.

Block, J. H., Colombo, M. G., Cumming, D. J., and Vismara, S., 2018. New players in entrepreneurial

finance and why they are there. Small Business Economics, 50 (2), 239-250.

Boeh, K. K. and C. G. Dunbar, 2013. Post IPO Withdrawal Outcomes. SSRN Working Paper.

Brush, C.G., Carter, N.M., Gatwood, E.J. Greene, P.G., and Hart, M., 2004, Gatekeepers of Venture

Growth: A Diana Project Report on the Role and Participation of Women in the Venture Capital

Industry, Kansas City, MO: The Kauffman Foundation.

Burtch, G., Ghose, A., and Wattal, S., 2014. Cultural differences and geography as determinants of

online pro-social lending. MIS Quarterly, 38 (3), 773-794

Campbell, A.A., Cherry, C.R., Ryerson, M.S., and Yang, X., 2016. Factors influencing the choice of

shared bicycles and shared electric bikes in Beijing. Transportation Research Part C: Emerging

Technologies, 67, 399–414.

Carlson, R., 1972. Understanding women: implications for personality theory and research. The

Journal of Social Issues, 28, 17–32.

Carter, S. and Rosa, P., 1998. The financing of male and female-owned businesses. Entrepreneurship

and Regional Development, 10(3), 225–241.

Catalini, C., Fazio, C. and Murray, F., 2016. Can Equity Crowdfunding Democratize Access to

Capital and Investment Opportunities? SSRN working paper.

Cavalluzzo, K.S., Cavalluzzo L.C. and Wolken, J.D. 2002. Competition, small business financing,

and discrimination: evidence from a new survey. Journal of Business, 75(4), 641–679.

Coleman, S., 2000. Access to capital: a comparison of men and women-owned small businesses’,

Journal of Small Business Management, 38(3), 37–52.

Electronic copy available at: https://ssrn.com/abstract=3247120

Colombo, M. G., Franzoni, C., and Rossi-Lamastra, C., 2014. Internal social capital and the

attractions on early contributions. Entrepreneurship Theory and Practice, 39, 75–100.

Coval, J., and Moskowitz, T., 2001. The geography of investment: informed trading and asset prices.

Journal of Political Economy, 109, 811–841.

Cumming, D. J., Meoli, M. & Vismara, S., 2018. Investors’ choice between cash and voting rights:

evidence from dual-class equity crowdfunding. University of Bergamo Working Paper.

Duarte, J., Siegel, S. and Young, L., 2012. Trust and credit: The role of appearance in peer-to-peer

lending, Review of Financial Studies, 25(8), 2455–2483.

Eagly, A.H., Karau, S.J., and Makhijani, M.G., 1995. Gender and the effectiveness of leaders: a meta-

analysis. Psychological Bulletin, 117, 125–145.

Estrin, S., Gozman, D., and Khavul, S., 2018. The evolution and adoption of equity crowdfunding:

entrepreneur and investor entry into a new market. Small Business Economics, forthcoming.

Fabowale, L., Orser, B., and Riding, A., 1995. Gender, structural factors, and credit terms between

Canadian small businesses and financial institutions. Entrepreneurship Theory and Practice, 19(4),

41–65.

Fagenson, E., 1993. Personal value systems of men and women: entrepreneurs versus managers.

Journal of Business Venturing, 8(5), 409–430.

Fairlie, R.W., and Robb, A., 2007. Why are black-owned businesses less successful than white-owned

businesses? The role of families, inheritances, and business human capital. Journal of Labor

Economics, 25(2):289–323.

Fairlie, R. W., Morelix, A., Reedy, E. J., and Russell, J., 2016. The Kauffman index of startup activity:

national trends. Kansas City: The Ewing Marion Kauffman Foundation.

French, K.R., and Poterba, J.M., 1991. Investor diversification and international equity markets.

American Economic Review, 81, 222–226.

Friedland, R., and Alford, R.R., 1991. Bringing Society Back In: Symbols, Practices and Institutional

Contradictions. In Powell,W.W., DiMaggio, P.J. (Eds.), The New Institutionalism in Organizational

Analysis (pp. 232-263). Chicago: University of Chicago Press.

Greenberg, J. and Mollick, E., 2017. Activist choice homophily and the crowdfunding of female

founders. Administrative Science Quarterly 62(2): 341–374.

Greene, P., C. Brush, M. Hart and P. Saparito, 2001. Patterns of venture capital funding: is gender a

factor?Venture Capital, 3, 63–83.

Guenther, C., Johan, S., & Schweizer, D. (2017). Is the crowd sensitive to distance?—How

investment decisions differ by investor type. Small Business Economics, 50 (2), 289-305.

Heckman, J. J., 1979. Sample selection bias as a specification error. Econometrica, 47, 153-162.

Herzenstein, M., Andrews, R. L., Dholakia, U. M., and Lyandres, E., 2008. The Democratization of

Personal Consumer Loans? Determinants of Success in Online Peer-to-Peer Lending Communities.

Working Paper, http://ssrn.com/abstract=1147856.

Hornuf, L., and Schwienbacher, A., 2017. Should securities regulation promote equity crowdfunding?

Small Business Economics, 49 (3), 579-593.

Electronic copy available at: https://ssrn.com/abstract=3247120

Lee, M. O., and Vouchilas, G., 2016. Preparing to age in place: attitudes, approaches, and actions.

Housing and Society, 43(6), 69–81.

Lévesque, M., and Minniti, M., 2006. The effect of aging on entrepreneurial behavior. Journal of

Business Venturing, 21, 177–194.

Lin, M., and Viswanathan, S., 2016. Home bias in online investments: an empirical study of an online

crowdfunding market. Management Science, 62, 1393–1414.

Mohammadi, A., and Shafi, K. 2018. Gender differences in the contribution patterns of equity-

crowdfunding investors. Small Business Economics, 50 (2), 275-287.

Manes, S., Andrews, P., 1993. Gates: How Microsoft's Mogul Reinvented an Industry--and Made

Himself the Richest Man in America. New York: Doubleday.

Marom, D., Robb, A. and O. Sade, O., 2016. Gender dynamics in crowdfunding (Kickstarter):

evidence on entrepreneurs, investors, deals and taste based discrimination. SSRN working paper.

Morse, A., 2015. Peer-to-Peer Crowdfunding: Information and the Potential for Disruption in

Consumer Lending. NBER Working Paper n. 20899

Nambisan, S., Lyytinen, K., Majchrzak, A., and Song, M., 2017. Digital innovation management:

Reinventing innovation management research in a digital world. MIS Quarterly, 41 (1), 223-238.

Parker, S. C., 2009. The economics of entrepreneurship. Cambridge: Cambridge University Press.

Piva, E., and Rossi-Lamastra, C., 2017. Human capital signals and entrepreneurs’ success in equity

crowdfunding. Small Business Economics, forthcoming.

Polzin, F., Toxopeus, H., and Stam, E., 2018. The wisdom of the crowd in funding: information

heterogeneity and social networks of crowdfunders. Small Business Economics, 50 (2), 251-273.

Pope, D.G. and Sydnor, J.R., 2011. What’s in a Picture? Evidence of Discrimination from

Prosper.com. Journal of Human Resources, 46(1), 53–92

Prokop, J., and Wang, D., 2018. Is there a gender gap in equity crowdfunding? Proceedings of the

INFINITI Conference on International Finance 2018.

Radford, J.S., 2016. The emergence of gender inequality in a crowdfunding market: an experimental

test of gender system theory. SSRN working paper.

Ravina，E, 2012. Love&Loans: The Effect of Beauty and Personal Charachteristics in Credit

Markets. SSRN Working Paper.

Riding, A. and Swift, C., 1990. Women business owners and terms of credit: some empirical findings

of the Canadian experience. Journal of Business Venturing, 5(5), 327–340.

Ritter, J.R., 2003. Differences between European and American IPO Markets. European Financial

Management, 9, 421-434.

Ritter, J.R., 2013. Re-energizing the IPO market. Journal of Applied Finance, 24(1), 37–48.

Ritter, J. R., Signori, A., and Vismara, S., 2013. Economies of scope and IPO activity in Europe. In

Mario Levis and Silvio Vismara (Eds.), Handbook of research on IPOs (pp. 11–34). Cheltenham:

Edward Elgar.

Roxas, M.L. and Stoneback, J.Y., 2004. The importance of gender across cultures in ethical decision-

making. Journal of Business Ethics, 50, 149–165.

Electronic copy available at: https://ssrn.com/abstract=3247120

Schwartz, 2015. Teenage Crowdfunding. SSRN Working paper.

Schwienbacher, A., 2018. Entrepreneurial risk-taking in crowdfunding campaigns. Small business

Economics, forthcoming.

Shaheen, S., Guzman, S., and Zhang, H., 2010. Bikesharing in Europe, the Americas, and Asia.

Transportation Research Record: Journal of the Transportation Research Board, 2143 (1), 159-167.

Signori, A. and Vismara, S. 2018. Does success bring success? The post-offering lives of equity-

crowdfunded firms. Journal of Corporate Finance, 50, 575-591.

Sorenson, O., and Stuart, T., 2001. Syndication networks and the spatial distribution of venture capital

investments. American Journal of Sociology, 106, 1546–1588.

Stengel, G., 2015. Women-Owned Businesses: A Tale of Two Types Of Entrepreneurs. Forbes

[Online] Available at: http://www.forbes.com/sites/geristengel/2015/08/26/women-owned-

businesses-a-tale-of-two-types-of-entrepreneurs/#1de811693e8c

Sulaeman, J., 2014. Do local investors know more? Evidence from mutual fund location and

investments. Quarterly Journal of Finance, 4, 1450010.

Terza, J.V., 1998. Estimating Count Models with Endogenous Switching: Sample Selection and

Endogenous Treatment Effects. Journal of Econometrics, 84, 129–154.

Younkin, P., and Kuppuswamy, V., 2017. The colorblind crowd? Founder race and performance in

crowdfunding. Management Science, forthcoming.

Younkin, P., and Kuppuswamy, V., 2018. Discounted: The effect of founder race on the price of new

products. Journal of Business Venturing, forthcoming.

Van de Ven, W.P.M.M., and Van Pragg, B.M.S., 1981. The demand for deductibles in private health

insurance: A probit model with sample selection. Journal of Econometrics, 17, 229–252.

Verheul, I. and Thurik, R., 2001. Start-up capital: does gender matter? Small Business Economics,

16 (4), 329–346.

Vismara, S., 2016. Equity retention and social network theory in equity crowdfunding. Small

Business Economics, 46(4), 579–590.

Vismara, S. 2018a. Information cascades among investors in equity crowdfunding. Entrepreneurship

Theory and Practice, 42(3), 467-497.

Vismara, S. 2018b. Sustainability in equity crowdfunding. Technological Forecasting and Social

Change. Forthcoming.

Vismara, S., Benaroio, D., and Carne, F., 2017. Gender in entrepreneurial finance: Matching investors

and entrepreneurs in equity crowdfunding. In Albert Link (Ed.), Gender and entrepreneurial activity

(pp. 271–288). Cheltenham: Edward Elgar.

Vismara, S., Paleari, S., and Ritter, J.R., 2012. Europe’s second markets for small companies.

European Financial Management, 18(3), 352-388.

Zhang, T., and Acs, Z., 2018. Age and entrepreneurship: nuances from entrepreneur types and

generation effects. Small business Economics. Forthcoming.

Electronic copy available at: https://ssrn.com/abstract=3247120

Table 1. Variable description

Dependent variables

Success

Dummy variable equal to 1 for successfully funded offerings, 0 otherwise.

Number of investors

Number of investors in the offering.

Explanatory variables

Female leadership

Dummy variable equal to 1 for firms with the CEO of the firms is a woman, 0 otherwise.

Age

Average age of TMT members.

Ethnical minority

Dummy variable equal to 1 if at least one TMT member if at least one member of the

TMT is non-Caucasian

Metropolitan area

Dummy variable, equal to 1 if the firm belongs to a metropolitan area, according to the

Census 2001 classification (i.e. metropolitan areas of London, Birmingham, Manchester,

Leeds-Bradford, Liverpool-Birkenhead, Newcastle, Sheffield, South Hampshire,

Nottingham-Derby and Glasgow)

Controls

Equity offered

Percentage of equity offered.

Target

Amount bid for crowdfunding initiatives, and total proceeds for IPO offerings (natural

logarithms are used in regression analyses).

Firm age

Difference, in years, between the beginning of the crowdfunding campaign, or the

offering on the AIM, and the foundation date.

TMT size

Number of people in the top management team.

Positive sales

Dummy variable equal to 1 if the company has already reported positive sales at the

campaign/IPO, 0 otherwise.

Patents

Dummy variable equal to 1 if the company owns or is filing patents at the campaign/IPO,

0 otherwise.

Population

Population in the NUTS-3 area where the firm is located (natural logarithms are used in

regression analyses).

Additional controls in the selection process

Industry dummies

Set of dummy variables controlling for industries according to the Industry

Classification Benchmark (ICB).

Variables included in the robustness analysis

Female presence

Dummy variable equal to 1 for firms with at least one woman in the TMT.

GDP per capita

GDP per capita in the NUTS-3 area where the firm is located (natural logarithms are

used in regression analyses).

Unemployment rate

Unemployment rate in the NUTS-3 area where the firm is located.

NUTS-1 dummies

Set of dummy variables controlling for the 12 NUTS-1 statistical regions in the UK.

Electronic copy available at: https://ssrn.com/abstract=3247120

Table 2. Descriptive statistics. Mean, standard deviation, maximum and minimum values for all variables employed in the analysis, refereed to the

sample of 167 equity offerings on Crowdcube and to the sample of 99 IPOs on the AIM raising more than £300,000 and less than £5 million between

2013 and 2016. The last column reports tests for difference in means (or proportions) between equity offerings on Crowdcube and AIM. ***, ** and

* represent statistical significance, at 1%, 5% or 10%, respectively.

Crowdcube

AIM

Difference in

Means

Mean

Std

Max

Min

Mean

Std

Max

Min

Depedent variables

Success (dummy, %)

48.5

50.1

Number of investors (No.)

237.9

325.8

2,209

Explanatory variables

Female leadership (dummy, %)

31.2

46.4

36.8

48.2

5.6

Age (years)

42.0

9.8

46.2

9.0

4.2***

Ethnical minority (dummy, %)

16.0

36.9

Metropolitan area (dummy, %)

50.4

50.1

57.2

49.5

6.8*

Controls

Equity offered (%)

15.7

8.30

54.3

2.3

33.3

23.3

89.1

9.0

17.6***

Target (000£)

925.0

530.5

3,990.0

300.0

2,312.1

1,392.8

5,000

300.0

1,387.1***

Firm age (years)

3.1

3.3

3.4

3.9

0.8

TMT size (No.)

3.5

1.4

5.0

1.5

1.5***

Positive sales (dummy, %)

49.2

45.6

50.4

50.1

0.8

Patents (dummy, %)

19.7

39.9

36.8

48.2

17.1***

Population (millions)

4.1

3.9

8.8

0.1

4.9

3.8

8.8

0.1

0.8**

Variables included in the robustness analysis

Female presence (dummy, %)

52.1

50.1

81.3

39.0

29.2***

GDP per capita (000£)

58.0

24.5

86.4

24.9

61.7

24.8

86.4

24.9

3.7*

Unemployment rate (%)

4.8

1.1

7.2

2.7

5.1

10.9

7.2

2.7

0.3*

Electronic copy available at: https://ssrn.com/abstract=3247120

Table 3. Probability of success. The table reports the results of Probit models with a selection equation, i.e. a two-stage model. The first stage

(selection equation) is a probit model on the likelihood to propose a crowdfunding offerings, vis-à-vis a public offering on the AIM, estimated on a

sample of 167 offerings offered on Crowdcube and 99 IPOs on the AIM between 2013 and 2016. The identification condition is granted by the

inclusion of Industry dummies in the regression specification. The first stage is reported only for the selection equation of Model (1). Results for all

the other selection equations are qualitatively the same. The second stage is a probit model on the success of crowdfunding offerings, estimated on a

sample of 167 equity offerings offered on Crowdcube, and including the Inverse Mills Ratio esatimated from the first model. Model (1) is our baseline

specification. Model (2) adds Female leadership. Model (3) adds Age. Model (4) adds Ethnical minority. Model (5) adds Metropolitan area. Model

(6) adds all variables included in Models (2-5). Robust standard errors in parentheses. ***, ** and * identify significance levels at less than 1, 5 and

10%, respectively.

Electronic copy available at: https://ssrn.com/abstract=3247120

Crowdfunding

(1)

(2)

(3)

(4)

(5)

(6)

Female leadership

-0.416

0.602

0.572

(0.269)

(0.498)

(0.462)

Age

-0.033**

-0.047***

-0.045***

(0.013)

(0.017)

(0.016)

Ethnical minority

0.137

0.077

(0.377)

(0.354)

Metropolitan area

0.874***

-0.532*

-0.480*

(0.235)

(0.312)

(0.286)

Equity offered

-5.089***

-2.502

-2.857

-3.607**

-2.636

-3.011*

-4.230**

(1.183)

(1.723)

(1.798)

(1.691)

(1.767)

(1.746)

(1.789)

Target

-0.498***

-1.133***

-1.180***

-1.246***

-1.141***

-1.177***

-1.300***

(0.151)

(0.157)

(0.168)

(0.164)

(0.154)

(0.155)

(0.161)

Firm age

0.035

0.003

0.002

-0.003

0.005

-0.003

-0.009

(0.046)

(0.042)

(0.041)

(0.042)

TMT size

-0.584***

-0.072

-0.010

-0.035

-0.067

-0.043

0.048

(0.109)

(0.160)

(0.173)

(0.178)

(0.163)

(0.158)

(0.188)

Positive sales

0.266

0.093

0.044

0.051

0.095

0.037

0.031

(0.275)

(0.299)

(0.302)

(0.309)

(0.300)

(0.299)

(0.312)

Patents

0.350

0.529

0.518

0.433

0.537

0.450

0.367

(0.280)

(0.356)

(0.349)

(0.365)

(0.357)

(0.372)

(0.374)

Population

-0.335***

0.029

0.022

-0.027

0.023

0.182

0.113

(0.092)

(0.098)

(0.101)

(0.100)

(0.167)

(0.168)

Prone to crowdfunding (IMR)

0.134

-0.975**

-0.985**

-0.991**

-0.906*

-0.993**

(0.689)

(0.444)

(0.447)

(0.424)

(0.503)

(0.421)

Industry dummies

YES***

Constant

-13.553***

-14.209***

-12.410***

-13.617***

-16.150***

-15.231***

-13.553***

(2.348)

(2.632)

(2.436)

(2.304)

(3.134)

(3.177)

(2.348)

Observations

266

167

Pseudo R-squared

0.73

0.32

0.34

0.43

0.39

0.42

0.48

Electronic copy available at: https://ssrn.com/abstract=3247120

Table 4. Number of investors. The table reports the results of Negative binomial regressions with a selection equation, i.e. a two-stage model. The

first stage (selection equation) is a probit model on the likelihood to propose a crowdfunding offering, vis-à-vis a public offering on the AIM, estimated

on a sample of 167 offerings offered on Crowdcube and 99 IPOs on the AIM between 2013 and 2016. The identification condition is granted by the

inclusion of Size and Industry dummies in the regression specification. The first stage is not reported, as coefficients are in all cases qualitatively the

same as in the model reported in Table 3, Model 1. The second stage is a negative binomial regression on the number of investors, estimated on a

sample of 167 equity offerings offered on Crowdcube, and including the Inverse Mills Ratio estimated from the first model. Model (1) is our baseline

specification. Model (2) adds Female leadership. Model (3) adds Age. Model (4) adds Ethnical minority. Model (5) adds Metropolitan area. Model

(6) adds all variables included in Models (2-5). Robust standard errors in parentheses. ***, ** and * identify significance levels at less than 1, 5 and

10%, respectively.

Electronic copy available at: https://ssrn.com/abstract=3247120

(1)

(2)

(3)

(4)

(5)

(6)

Female leadership

0.038

0.035

(0.156)

(0.146)

Age

-0.008*

-0.007*

(0.004)

Ethnical minority

0.149**

0.158**

(0.068)

(0.076)

Metropolitan area

-0.273**

-0.216**

(0.115)

(0.103)

Equity offered

-0.835*

-0.819

-0.836*

-0.684

-0.703

-0.519

(0.492)

(0.507)

(0.492)

(0.501)

(0.473)

(0.488)

Target

0.546***

0.547***

0.546***

0.549***

0.553***

0.556***

(0.026)

Firm age

0.010

0.011

0.010

0.011

(0.014)

TMT size

-0.104**

-0.101*

-0.105**

-0.104**

-0.094*

-0.089*

(0.051)

(0.055)

(0.050)

(0.051)

(0.049)

(0.052)

Positive sales

0.273***

0.270***

0.273***

0.281***

0.257***

0.262***

(0.090)

(0.094)

(0.090)

(0.092)

(0.088)

(0.093)

Patents

0.229**

0.231**

0.229**

0.263***

0.205**

0.241***

(0.098)

(0.097)

(0.092)

(0.097)

(0.093)

Population

-0.067**

-0.066**

-0.067**

-0.073***

-0.009

-0.011

(0.026)

(0.027)

(0.026)

(0.038)

(0.036)

Prone to Crowdfunding (IMR)

0.457***

0.449***

0.457***

0.429***

0.432***

0.390***

(0.150)

(0.155)

(0.150)

(0.144)

(0.154)

(0.151)

Constant

-0.014

-0.043

-0.025

0.001

-0.878

-0.943

(0.491)

(0.501)

(0.549)

(0.485)

(0.640)

(0.648)

Observations

167

Pseudo R-squared

0.47

0.49

0.48

0.51

0.52

0.57

Electronic copy available at: https://ssrn.com/abstract=3247120

Table 5. Robustness analysis. The table reports the results of robustness analysis on the selection equation reported in the first column of Table 3 –

Crowdfunding (Models A1-4), on the success equation reported in Table 3, Model 6 (Models B1-4) and on the investor equation reported in Table 4,

Model 6 (Models C1-4). Models A1-4 are probit models on the likelihood to propose a crowdfunding offering, vis-à-vis a public offering on the AIM.

The identification condition is granted by the inclusion of Industry dummies in the regression specification. Models B1-4 are probit models on the

success of crowdfunding offerings, including the Inverse Mills Ratio estimated from the first model (Models A1-3, respectively). Models C1-4 are

negative binomial regressions on the number of investors, and including the Inverse Mills Ratio estimated from the first model (not reported, but

qualitatively equivalent to Models A1-3). In Models A1, B1 and C1, Female presence replaces Female leadership. In Models A2, B2 and C2, GDP

per capita replaces Metropolitan area. In Models A3, B3 and C3, Unemployment replaces Metropolitan area. In Models A4, B4 and C4, we include

also a set of dummy variables for the 12 NUTS-1 statistical regions. In Models A5, B5 and C5, offerings from London are dropped. The sample size

is therefore given by 167 Crowdcube offerings and 99 AIM offerings between 2013 and 2016 in Models A1-A4; 100 offerings on Crowdcube and 59

offerings on the AIM in Model A5; 167 offerings on Crowdcube in Models B1-B4 and C1-C4; 100 offerings on Crowdcube in Models B5 and C5.

Robust standard errors in parentheses. ***, ** and * identify significance levels at less than 1, 5 and 10%, respectively.

Electronic copy available at: https://ssrn.com/abstract=3247120

(A1)

(A2)

(A3)

(A4)

(A5)

(B1)

(B2)

(B3)

(B4)

(B5)

(C1)

(C2)

(C3)

(C4)

(C5)

Female leadership

-0.331

-0.339

-0.384

-0.362

0.581

0.569

0.670

0.352

0.034

0.031

0.221

0.165

(0.222)

(0.270)

(0.298)

(0.475)

(0.491)

(0.604)

(0.297)

(0.149)

(0.150)

(0.202)

(0.200)

Femaly presence

-0.969***

0.093

0.048

(0.227)

(0.308)

(0.083)

Age

-0.029**

-0.026**

-0.025**

-0.026**

-0.019*

-0.045***

-0.046***

-0.045***

-0.068***

-0.057***

-0.008**

0.009**

-0.009**

-0.007*

(0.012)

(0.013)

(0.012)

(0.016)

(0.017)

(0.023)

(0.022)

(0.003)

(0.004)

Ethnical minority

0.084

0.061

0.068

0.051

0.058

0.157*

0.153*

0.144*

0.188*

0.133*

(0.353)

(0.378)

(0.521)

(0.523)

(0.086)

(0.087)

(0.089)

(0.106)

(0.076)

Metropolitan area

-0.732***

-1.331***

-0.393*

-0.446*

-0.911*

-0.529*

-0.215*

-0.269**

(0.231)

(0.390)

(0.218)

(0.243)

(0.490)

(0.294)

(0.113)

(0.118)

(0.105)

GDP per capita

-0.208

-0.107

-0.163*

(0.398)

(0.581)

(0.068)

Unemployment

-1.436

1.685

-3.615*

(1.564)

(1.899)

(2.175)

Equity offered

-5.361***

-4.513***

-4.423***

-5.721***

-3.644**

-4.031**

-3.897**

-3.978**

-8.612***

-9.127***

-0.503

-0.689

-0.671

-0.235

-0.352

(1.126)

(1.113)

(1.099)

(1.144)

(1.601)

(1.753)

(1.766)

(1.797)

(3.341)

(2.900)

(0.488)

(0.527)

(0.509)

(0.624)

(0.582)

Target

-0.549***

-0.444***

-0.457***

-0.463***

-0.525**

-1.282***

-1.280***

-1.284***

-1.515***

-1.409***

0.559***

0.551***

0.548***

0.568***

0.546***

(0.135)

(0.137)

(0.135)

(0.145)

(0.214)

(0.163)

(0.165)

(0.166)

(0.240)

(0.201)

(0.025)

(0.027)

(0.026)

(0.032)

Firm age

0.050

0.051

0.048

0.047

-0.001

-0.007

-0.005

-0.004

-0.013

-0.001

0.011

0.012

-0.001

(0.042)

(0.047)

(0.046)

(0.058)

(0.043)

(0.042)

(0.041)

(0.058)

(0.052)

(0.014)

(0.015)

TMT size

-0.424***

-0.585***

-0.583***

-0.629***

-0.565***

-0.013

0.026

0.019

0.196

0.044

-0.096**

-0.102*

-0.104*

-0.030

-0.092

(0.101)

(0.103)

(0.104)

(0.108)

(0.151)

(0.170)

(0.191)

(0.206)

(0.199)

(0.049)

(0.053)

(0.055)

(0.077)

(0.070)

Positive sales

-0.027

-0.351

-0.198

-0.288

0.016

0.002

0.004

0.561

0.290

0.268***

0.270***

0.281***

0.337***

0.317**

(0.256)

(0.273)

(0.291)

(0.297)

(0.303)

(0.315)

(0.311)

(0.477)

(0.439)

(0.089)

(0.090)

(0.095)

(0.128)

(0.125)

Patents

-0.234

-0.330

-0.326

-0.497

-0.207

0.364

0.437

0.454

0.463

0.431

0.237***

-0.272***

0.261***

0.300**

0.266**

(0.280)

(0.263)

(0.261)

(0.305)

(0.320)

(0.386)

(0.363)

(0.357)

(0.636)

(0.507)

(0.092)

(0.095)

(0.092)

(0.153)

(0.125)

Population

-0.345***

-0.265**

-0.111

-0.312***

-0.717***

0.104

0.001

-0.144

-0.392

-0.086

-0.009

-0.052

-0.049

0.015

-0.054

(0.092)

(0.133)

(0.124)

(0.098)

(0.131)

(0.163)

(0.196)

(0.176)

(0.342)

(0.299)

(0.037)

(0.048)

(0.036)

(0.069)

(0.064)

Prone to Crowdfunding (IMR)

-0.796*

-0.790*

-0.782*

-1.100*

-0.945

0.390***

0.415***

0.428***

0.466**

0.397***

(0.401)

(0.403)

(0.420)

(0.575)

(0.651)

(0.145)

(0.149)

(0.153)

(0.193)

(0.136)

Industry dummies

YES***

NUTS-1 dummies

YES***

Constant

14.896***

11.180***

12.015***

13.432***

20.724***

-14.710***

-12.304***

-12.255***

-10.134**

-13.836***

-1.003

0.416

-0.194

-1.521

-0.207

(2.424)

(3.656)

(2.472)

(2.512)

(3.618)

(3.055)

(4.460)

(2.652)

(4.966)

(0.653)

(1.365)

(0.552)

(1.022)

(0.958)

Observations

266

159

167

100

167

100

Pseudo R-squared

0.74

0.70

0.71

0.79

0.77

0.49

0.47

0.58

0.56

0.52

0.54

0.64

0.63

Electronic copy available at: https://ssrn.com/abstract=3247120

Table A1. Correlation matrix. Correlation coefficients calculated on the sample of 167 equity offerings on Crowdcube, and 99 IPOs on the AIM

raising more than £300,000 and less than £5 million between 2013 and 2016. Values for Success, Number of investors and Ethnical minorities refer

only to crowdfunding offerings. * represents statistical significance at 5%.

Variables

Success

1.000

N. of investors

0.345*

1.000

Female leadership

0.006

-0.058

1.000

Age

-0.118*

-0.157*

0.017

1.000

Ehnical minority

0.073

0.135*

0.082

-0.071

1.000

Metropolitan area

-0.107*

-0.098*

0.062

-0.052

0.140*

1.000

Equity offered

-0.084*

-0.057

0.075*

0.037

-0.146*

0.028

1.000

Target

-0.278*

0.392*

0.107*

0.148*

0.097*

0.084

0.102*

1.000

Firm Age

-0.058

-0.084*

-0.014

-0.019

-0.075*

-0.006

0.052

0.018

1.000

TMT Size

0.274*

0.249*

-0.043

0.135*

0.079

-0.014

0.004

0.580*

-0.063

1.000

Positive Sales

0.083*

0.131*

0.006

0.038

-0.029

0.048

0.020

0.047

0.161*

0.047

1.000

Patents

0.051

0.080*

-0.012

0.004

0.113*

0.061

-0.027

0.008

-0.043

0.067

0.068

1.000

Population

0.109*

-0.052

0.054

-0.028

0.145*

0.199*

-0.033

0.073

-0.036

0.082

-0.032

-0.024

1.000

Female presence

-0.056

0.053

0.343

0.064

0.095

-0.004

0.029

0.026

-0.034

0.309

-0.035

0.047

0.022

1.000

GDP per capita

-0.117*

-0.029

0.043

-0.002

0.144

0.121*

-0.020

0.068

-0.040

0.042

-0.029

-0.026

0.596*

0.043

1.000

Unemployment

0.113*

-0.033

0.031

-0.029

0.053

0.177*

-0.056

0.062

-0.021

0.059

-0.032

-0.012

0.632*

-0.013

0.461*

Equity Based Crowdfunding : Determinants of Successful Campaign: the Case of Crowdcube Platform in the United Kingdom

Article

Full-text available

Jan 2022
Publ Finance Rev

The study is aimed at exploring what influences the amount of money raised which can either lead to the success or failure of equity-based crowdfunding using Crowdcube. The study used Pearson correlations and multiple regression analysis. The regression model was considered a good fit as it was statistically significant. The findings of the paper revealed that the number of investors, target amount, and pre-money valuation strongly and positively influence the success of equity-based crowdfunding campaigns. Additionally, equity, display of share price information, and online social media presence are other factors that influence the success of equity-based crowdfunding campaigns. However, previous crowdfunding history was negatively associated with the success of campaigns. The uniqueness of the study will benefit investors and founders who aim at running or investing in successful equity-based crowdfunding campaigns in the UK and globally. The study recommends further research using other equity-based crowdfunding platforms in different countries and continents.

The CEO Beauty Premium: Founder CEO Attractiveness and Firm Valuation in Initial Coin Offerings

Article

Full-text available

Jan 2021

We apply insights from research insocial psychology and labor economics to the domain ofentrepreneurial finance and investigate how founder chiefexecutive officers' (founder CEOs') facial attractivenessinfluences firm valuation. Leveraging the novel context ofinitial coin offerings (ICOs), we document a pronouncedfounder CEO beauty premium, with a positive relationshipbetween founder CEO attractiveness and firm valuation.We find only very limited evidence of stereotype-basedevaluations, through the association of founder CEO attrac-tiveness with latent traits such as competence, intelligence,likeability, or trustworthiness. Rather, attractiveness seemsto bear economic value per se, especially in a context inwhich investors base their decisions on a limited informa-tion set. Indeed, attractiveness has a sustainable effect onpost-ICO performance.

The CEO Beauty Premium: Founder CEO Attractiveness and Firm Valuation in Initial Coin Offerings

Article

Full-text available

Dec 2021

Research summary We apply insights from research in social psychology and labor economics to the domain of entrepreneurial finance and investigate how founder chief executive officers’ (founder CEOs’) facial attractiveness influences firm valuation. Leveraging the novel context of initial coin offerings (ICOs), we document a pronounced founder CEO beauty premium, with a positive relationship between founder CEO attractiveness and firm valuation. We find only very limited evidence of stereotype-based evaluations, through the association of founder CEO attractiveness with latent traits such as competence, intelligence, likeability, or trustworthiness. Rather, attractiveness seems to bear economic value per se, especially in a context in which investors base their decisions on a limited information set. Indeed, attractiveness has a sustainable effect on post-ICO performance. Managerial summary ICOs allow ventures to collect funding from investors using blockchain technology. We leverage this novel funding context, in which information on the ventures and their future prospects is scarce, to empirically investigate whether the founder CEOs’ physical attractiveness is associated with increased funding (i.e. amount raised) and post-funding performance (i.e. buy-and-hold returns). We find that ventures with more attractive founder CEOs outperform ventures with less attractive CEOs in both dimensions. For ICO investors, this suggests that ICOs of firms with more attractive founder CEOs are more appealing investment targets. Our findings are also interesting for startups seeking external finance in uncertain contexts, such as ICOs. If startups can appoint attractive leaders, they may have better access to growth capital.

Disentangling Crowdfunding from Fraudfunding

Article

Full-text available

Oct 2021
J BUS ETHICS

Unlabelled: Fraud in the reward-based crowdfunding market has been of concern to regulators, but it is arguably of greater importance to the nascent industry itself. Despite its significance for entrepreneurial finance, our knowledge of the occurrence, determinants, and consequences of fraud in this market, as well as the implications for the business ethics literature, remain limited. In this study, we conduct an exhaustive search of all media reports on Kickstarter campaign fraud allegations from 2010 through 2015. We then follow up until 2018 to assess the ultimate outcome of each allegedly fraudulent campaign. First, we construct a sample of 193 fraud cases, and categorize them into detected vs. suspected fraud, based on a set of well-defined criteria. Next, using multiple matched samples of non-fraudulent campaigns, we determine which features are associated with a higher probability of fraudulent behavior. Second, we document the short-term negative consequences of possible breaches of trust in the market, using a sample of more than 270,000 crowdfunding campaigns from 2010 through 2018 on Kickstarter. Our results show that crowdfunding projects launched around the public announcement of a late and significant misconduct detection (resulting in suspension) tend to have a lower probability of success, raise less funds, and attract fewer backers. Supplementary information: The online version contains supplementary material available at 10.1007/s10551-021-04942-w.

IPOs and Entrepreneurial Firms

Article

Oct 2021

The listing on a stock exchange is a paramount milestone in the life cycle of an enterprise. By taking their company public on a stock market through an Initial Public Offering (IPO), entrepreneurs may target several benefits (e.g., raising money, facilitating acquisitions, offering valuable stock ownership plans to employees) but their firms will bear new costs and requirements. In this work we review the academic literature on IPOs of entrepreneurial firms, focusing on five main topics: (i) the going public decision, (ii) pricing and valuation, (iii) the role of intermediaries and underwriters in the listing process, (iv) the performance of IPO-firms in the short and long run, and (v) market cycles in the IPO industry.

Liquidity risk in FinTech lending: Early impact of the COVID-19 pandemic on the P2P lending market

Article

Nov 2023
Emerg Market Rev

Innovation finance ecosystems for entrepreneurial firms: A conceptual model and research propositions

Article

Full-text available

Feb 2023
J BUS RES

This paper presents a conceptual model for examining the matching of entrepreneurial firms and sources of finance under conditions of innovation. The model applies to entrepreneurial ecosystems, typically the site for studying venture capital investment in technology start-ups. By delimiting ecosystems along sectoral and temporal dimensions, the model considers a diversity of industry sectors and a diversity of funders, across the early, growth, and mature stages of a firm. The conceptual model suggests that where there might appear to be funding gaps, there could instead be overlaps. Based on the sectoral and temporal dimensions, research propositions are formulated. These propositions outline a research agenda that examines the relationship between innovation and sectoral and temporal dimensions, the impact of innovation on firms and funders, the role of reinvestment into the ecosystem as the lifeblood for a self-reproducing healthy ecosystem, and the possible geographic limitations of ecosystem models.

FinTech and capital allocation efficiency: Another equity-efficiency dilemma?

Article

May 2022
Global Finance J

The emergence of financial technology (FinTech) introduces new tools and solutions to lending and equity markets, and has significantly increased the accessibility of marginal firms to funds, a property known as financial inclusion. However, little is known about whether such inclusion is acquired at the cost of efficiency. This paper provides evidence on how FinTech affects the efficiency of capital allocation using firm-level data for China over the period of 2010–2020. The development of FinTech is measured as the number of FinTech firms in a city. We find interesting evidence that the growth of FinTech reduces the capital available to more efficient firms. The evidence stands robust at both the firm- and industry-level. We identify two mechanisms that can explain the inefficiencies of FinTech in capital allocation. The first mechanism involves FinTech-induced competition in the lending market, and the second explanation relates to the property of equity-efficiency dilemma of FinTech. Finally, we show that the inefficiencies of FinTech in capital allocation arise mainly from its impact on debt financing.

Tulajdonositőke-alapú közösségi finanszírozás : A kampányok kimenetelét meghatározó tényezők a Crowdcube-platform vizsgálatán keresztül az Egyesült Királyságban

Article

Full-text available

Jan 2022
Publ Finance Rev

A jelen tanulmány azt vizsgálja, hogy az összegyűjtött források nagyságát, valamint a Crowdcubeplatformon keresztül történő tulajdonositőke-alapú közösségi finanszírozás sikerét vagy sikertelenségét milyen tényezők befolyásolják. Vizsgálatunkhoz Pearson-féle korrelációt és többszörös regreszsziót használtunk. A statisztikai szignifikancia miatt a regressziós modell jó illeszkedésnek bizonyult. A tanulmány megállapította, hogy a tőkealapú közösségi finanszírozási kampányok kimenetelét a befektetők száma, a célösszeg, valamint a cég befektetés előtti értéke erősen és pozitívan befolyásolja. További befolyásoló tényezőként a tulajdonrész (tőke), a részvényár-információk megjelenítése és a közösségi média jelenléte említhető. A közösségi finanszírozással kapcsolatos előzmény (korábbi részvétel) ugyanakkor a kampányok sikeréhez negatívan kapcsolódott. A tanulmány egyedisége azon vállalkozók (alapítók) és befektetők számára fog segítséget jelenteni, akik sikeres tőkealapú közösségi finanszírozási kampányokat kívánnak folytatni, illetve támogatni az Egyesült Királyságban és a világ más részein. A tanulmány ugyanakkor ajánlást fogalmaz meg más országok és földrészek tőkealapú közösségi finanszírozási platformjainak további vizsgálatára is.

Growing pains and blessings: Manifestations and implications of equity crowdfunding industry maturation

Article

Full-text available

Mar 2022
DECIS SUPPORT SYST

The equity crowdfunding industry has grown significantly in the past decade. Industry life cycle theory suggests that growth dynamics and relations between stakeholders change as industries mature. The present study examines the characteristics and implications of maturation in the equity crowdfunding industry via the lens of industry life cycle theory. Specifically, we explore whether the industry is reverting to traditional entrepreneurial finance practice, or whether it retains its original distinguishing characteristics. Accordingly, we first assess changes with respect to users (investors) and products (campaigns and investment objects). Second, we assess the implications of these changes by comparing the determinants of fundraising campaign success in earlier and later industry stages. We use a longitudinal database and survey data sourced from a long-standing European equity crowdfunding platform. We show that equity crowdfunding seems to be converging towards traditional entrepreneurial finance practice, yet maintaining certain unique features stemming from digitality, platform nature, and investor diversity. Specifically, we show that (1) fundraising ventures and their campaigns have become larger and more professional, and (2) engaged investors became more knowledgeable and return-oriented. Accordingly, traditional investment criteria, such as team and commercial terms ratings, have become more important predictors of campaign success, and easily observable campaign characteristics, such as B2C business models, and minimum investment thresholds, less so. The findings support platform managers and entrepreneurs as they plan for campaigns seeking to attract investors in the industry's later stages.

Investors' choices between cash and voting rights: Evidence from dual-class equity crowdfunding

Article

Full-text available

Mar 2019
RES POLICY

This paper examines for the first time dual-class equity crowdfunding as a digital ownership model. Unique to this context, companies can set an investment threshold under which no voting rights are granted, making the issuance of Class A vs. Class B shares, depending on individual investors. Using a sample of 491 offerings on the UK platform Crowdcube from 2011 to 2015, we find that a higher separation between ownership and control rights lowers the probability of success of the offering, the likelihood of attracting professional investors, as well as the long-run prospects. Different from small investors, professional investors care about the implementation of a threshold for the attribution of voting rights and often bid the Class A threshold exactly. Family businesses, although less attractive to small investors, are relatively safer investments, because of their lower chances of failure. Abstract This paper examines for the first time dual-class equity crowdfunding as a digital ownership model. Unique to this context, companies can set an investment threshold under which no voting rights are granted, making the issuance of Class A vs. Class B shares, depending on individual investors. Using a sample of 491 offerings on the UK platform Crowdcube from 2011 to 2015, we find that a higher separation between ownership and control rights lowers the probability of success of the offering, the likelihood of attracting professional investors, as well as the long-run prospects. Different from small investors, professional investors care about the implementation of a threshold for the attribution of voting rights and often bid the Class A threshold exactly. Family businesses, although less attractive to small investors, are relatively safer investments, because of their lower chances of failure.

Sustainability in equity crowdfunding

Article

Full-text available

Jul 2018
TECHNOL FORECAST SOC

Silvio Vismara

Existing studies on the relationship between sustainability and crowdfunding are focused on campaigns that provide rewards for backers. Equity crowdfunding is substantially different in terms of motivations to invest as well as in size, horizon, and expectations of the investment. For the first time – using a sample of 345 initial equity offerings in United Kingdom platforms Crowdcube and Seedrs in the period 2014–2015 – this study provides evidence of the attractiveness of sustainability-oriented ventures in equity crowdfunding. Results show that, although sustainability orientation does not increase the chances of success or of engaging professional investors, it attracts a higher number of restricted investors. This evidence is interpreted considering institutional logic, whereas professionals follow a market logic, and restricted investors consider also a community logic.

Age and entrepreneurship: nuances from entrepreneur types and generation effects

Article

Full-text available

Dec 2018
SMALL BUS ECON

The literature on the relationship between age and entrepreneurship has been inconclusive. This study for the first time examines this relationship by extending the occupational choice literature to eight entrepreneur types and four generational modification effects in the USA. Multilevel mixed-effect logistic regression models are estimated to examine the age effects in entrepreneur type propensities. Generational modification effects are compared for the same ages across neighboring generations by hierarchical age-period-cohort (HAPC) models. We find that entrepreneurial propensity rises with age until around 80. The propensity of novice (versus non-novice) and unincorporated (versus incorporated) entrepreneurs has a U-shaped age trend dipping around age 60, while the propensity of full-time (versus part-time) declines since age 30s. The propensity of incorporated (versus unincorporated) entrepreneurs declines from ages 44 to 51 for Gen-Xers, but not for Boomers; this propensity also declines faster for Boomers than for Traditionalists from ages 63 to 70.

The evolution and adoption of equity crowdfunding: entrepreneur and investor entry into a new market

Article

Full-text available

Aug 2018
SMALL BUS ECON

Equity crowdfunding (ECF) offers entrepreneurs an online social media marketplace where they can access numerous potential investors who, in exchange for an ownership stake, may supply them with finance. In this paper, we describe the evolution of this market in the UK. Using an inductive qualitative longitudinal research design, we analyse the emerging views of entrepreneurs and investors towards ECF. Our interviewees include large and small-scale investors, as well as market participants who have chosen not to invest or raise funds via ECF. We find that the large financial flows to entrepreneurs in the UK via the ECF platforms, nearly half a billion GBP since 2011, have probably been largely incremental to traditional sources of early stage entrepreneurial finance. Moreover, our research indicates that for the most part, investors appear to understand and appropriately evaluate the risks that they are bearing; ECF investments are perceived as a high risk, high return component within individuals’ portfolios. Investors also use their communication with peers and entrepreneurs via the ECF platform as a learning tool. On the entrepreneurs’ side, ECF allows them to test their products, to develop their brand, to build a loyal customer base and to turn customers into investors. We conclude that policymakers, with the support of a locally appropriate regulatory framework, could support equity crowdfunding as one of the market choices available for entrepreneurs looking to start or grow their ventures.

Entrepreneurial risk-taking in crowdfunding campaigns

Article

Full-text available

Dec 2018
SMALL BUS ECON

Armin Schwienbacher

This paper examines how different sources of risk in reward-based crowdfunding campaigns influence the entrepreneur’s choice of targeted crowdfunding goal. This form of crowdfunding helps entrepreneurs to obtain feedback on market demand (next to raising money), since the pre-purchase decision of the crowd generates useful public information about product demand. However, it may also lead to project discontinuation if not enough money is raised during the campaign. We therefore derive conditions under which the entrepreneur sets a higher target. At other times, this leads entrepreneurs to raise sometimes even more money than necessary when there is a risk that the idea is quickly replicated by others, leading to even larger campaigns but also to fewer projects offered on platforms. Conversely, the increased presence of professional investors (business angels, venture capitalists) on platforms reduces the entrepreneurs’ incentives in their crowdfunding campaign, which leads to more but on average smaller crowdfunding campaigns.

Human capital signals and entrepreneurs’ success in equity crowdfunding

Article

Full-text available

Oct 2018
SMALL BUS ECON

Grounding on research about the role of signals in the attraction of equity finance, this paper studies the effects of diverse human capital signals on entrepreneurs’ success in equity crowdfunding. We argue that the human capital of an entrepreneur, who launches (alone or with other teammates) an equity crowdfunding campaign to finance her start-up, constitutes a set of signals of the start-up quality. The impact of each human capital signal on entrepreneur’s success in equity crowdfunding depends on both signal fit with start-up quality and signal ambiguity. Empirical estimates on 284 entrepreneurs who launched equity crowdfunding campaigns indicate that only entrepreneurs’ business education and entrepreneurial experience, two human capital signals that have both a good fit with start-up quality and a low degree of ambiguity, significantly contribute to entrepreneurs’ success in equity crowdfunding.

Gender in entrepreneurial finance: matching investors and entrepreneurs in equity crowdfunding

Chapter

May 2017

Discounted: The effect of founder race on the price of new products

Article

Mar 2018
J BUS VENTURING

Economies of scope and IPO activity in Europe

Chapter

Nov 2013

Does success bring success? The post-offering lives of equity-crowdfunded firms

Article

Nov 2017
J CORP FINANC

Using an augmented dataset with combined information from Crowdcube, Crunchbase, and Companies House, we study the population of 212 successfully funded initial equity offerings on the UK's largest crowdfunding platform Crowdcube from inception (2011) to 2015. We find that 18% of these firms failed, while 35% pursued one or more seasoned equity offerings in the form of either private equity injection (9%) or follow-on crowdfunding offering (25%), while three firms were acquired. Among the determinants of the post-campaign scenarios, we find that the degree of investor participation in the initial offering plays a relevant role. In particular, firms with more dispersed ownership are less likely to issue further equity, while those that reach the target capital more quickly are more likely to launch a follow-on offering. Further, none of the companies initially backed by qualified investors subsequently failed.

Does Equity Crowdfunding Democratize Entrepreneurial Finance?

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