Equity crowdfunding in italy campaign success factors analisys manuel cristofaro

UNIVERSITÀ DEGLI STUDI DI BERGAMO
Dipartimento di Scienze aziendali, economiche e metodi quantitativi
Corso di Laurea Magistrale in International Management, Entrepreneurship
and Finance
Classe n. 77 – Scienze Economico - Aziendali
EQUITY CROWDFUNDING IN ITALY.
CAMPAIGNS’ SUCCESS FACTOR ANALYSIS
Relatore:
Chiar.mo Prof. Davide Castellani
Correlatore:
Dottor Fabio Allegreni
Tesi di Laurea Magistrale
Manuel Cristofaro
Matricola n. 1055197
ANNO ACCADEMICO 2018/ 2019

Equity Crowdfunding in Italy. Campaign’s success factor analysis.
Manuel Cristofaro – Università degli studi di Bergamo 2
Abstract
The literature about equity crowdfunding factor analysis is focused only on some main
markets, such as the UK ones. Through this thesis, the analysis models used for these
markets are applied on the Italian ones. The main aim is to evaluate if it followed the
same path of the most developed markets and, as a result, it would have the potential to
achieve that development. To do so the study is focused on the success drivers of equity
online offers published and successfully ended through Crowdfundme and Mamacrowd,
the leader platforms in the Italian equity crowdfunding market, over 2016-2019 period.
The analysis combines different theories enunciated about the topic, in particular equity
retention theory, information cascade theory, rational investor theory and theories
regarding social networks. Based on the findings, some hints have been provided about
how the equity online offers’ proposers should behave in order to obtain the higher
amount of overfunding.

Table of contents
1. INTRODUCTION............................................................................................................................. 4
1.1. HISTORIC PILLS........................................................................................................................ 4
1.2. RESEARCH QUESTION AND THESIS STRUCTURE ...................................................................... 7
2. RESEARCH LITERATURE AND HYPOTHESES ..................................................................... 9
2.1. BACKGROUND ........................................................................................................................... 9
2.2. SUCCESSFUL FACTORS ANALYSIS AND SIGNALING THEORY ................................................... 9
2.2.1. Equity retention .................................................................................................................. 10
2.2.2. Investor rationality ............................................................................................................. 11
2.2.3. Information Cascade .......................................................................................................... 13
2.2.4. Social networks................................................................................................................... 15
3. EQUITY CROWDFUNDING MARKET IN ITALY ................................................................. 17
3.1. REGULATION........................................................................................................................... 17
3.1.1. Platforms regulation........................................................................................................... 18
3.1.2. Investors regulation............................................................................................................ 19
3.1.3. Bidder regulation................................................................................................................ 20
3.1.4. Tax regulation..................................................................................................................... 21
3.2. MARKET ANALYSIS ................................................................................................................. 21
APPENDIX .............................................................................................................................................. 25
4. DATA SAMPLES ........................................................................................................................... 28
4.1. DATA RESEARCH..................................................................................................................... 28
4.2. DATA ANALYSIS ...................................................................................................................... 29
5. RESEARCH VARIABLES ............................................................................................................ 33
5.1. VARIABLES DESCRIPTION ...................................................................................................... 33
5.1.1. Independent variables......................................................................................................... 33
5.1.2. Dependent variables........................................................................................................... 34
5.2. DESCRIPTIVE STATISTICS ....................................................................................................... 40
6. LINEAR REGRESSION MODEL................................................................................................ 42
6.1. METHODOLOGY...................................................................................................................... 42
6.1.1. Data transformation ........................................................................................................... 42
6.1.2. Regression fits..................................................................................................................... 44
6.2. RESULTS AND DISCUSSIONS.................................................................................................... 47
6.2.1. Success Drivers................................................................................................................... 47
6.2.2. Early funded and Late funded analysis .............................................................................. 55
APPENDIX .............................................................................................................................................. 62
7. CONCLUSIONS ............................................................................................................................. 64
7.1. RESEARCH LIMITATIONS ....................................................................................................... 66
7.2. BUSINESS IMPLICATIONS........................................................................................................ 67
BIBLIOGRAPHY..................................................................................................................................... 69

1. Introduction
Through crowdfunding, entrepreneurs, founders and creators ask funds for their
companies, ideas and startups to a wide range of people, via internet and without
intermediaries. Crowdfunding rose as a consequence of the 2008 financial crisis and
represent an alternative to the more common financing methods, such as Banks issues,
Venture Capitals (VCs) and Business Angels (BAs). In fact, this financial market tries to
fill the funding gap which was always present between these ones. Crowdfunding is the
general definition of a set of different models. They have strong similarities and vast
differences which characterize each other and make them more suitable for a situation
rather than another. The first distinction within Crowdfunding markets consist on the
recognition of three main models: Reward Crowdfunding (RCF), Donation
Crowdfunding (DCF) and Investment Crowdfunding (ICF). This latter one is additionally
split in Lending Crowdfunding (LCF) and finally Equity Crowdfunding (ECF) which is
the model discussed in this thesis.
1.1. Historic Pills
The firsts online Crowdfunding platforms were ‘artistic’ focused. ArtistShare was
established in 2000 and it is recognized as the first online crowdfunding web site ever.
Then, in 2006, Sellaband become the first crowdfunding web site based outside the US.
Both these platforms were based on the idea that an artist could publish its own project
proposal, either previous songs, on them to attract fans, which would turn into investors
rewarded with some perks, such as limited-edition copies of the album. One of the first
benefits for artists would be the possibility to create higher fanbase and to affiliate this
crowd to him/her. Another benefit, in particular on Sellaband, concern the fact that artists
would dispose of all the things necessary for the record, like location, instruments and
any kind of support needed. This platform fixed the target fund that projects had to
achieve to $50K. If that threshold was not satisfied, the gathered money would have
returned to the investor which would have the possibility to choose to withdraw their

investment or to readdress it to another artist. (All-or-Nothing model1
). The structure used
by Sellaband, and previously by ArtistShare belong to Reward Crowdfunding definition:
the crowdfunders invest in a campaign while, in exchange for their contribution, they
receive a reward, for instance the product or the service regarding the campaign or some
discounts on them.
The worldwide most known crowdfunding platforms, Kickstarter and Indiegogo, are
Reward Crowdfunding web sites. Rather than for Sellaband and ArtistShare they use to
publish offers regarding to many different types of projects, not concentrating on one
single field, for instance like in the previous cases only about artistic projects. Thus, these
Crowdfunding platforms are defined Generalist ones.
Literature about crowdfunding, especially the equity ones, embrace the idea that this
alternative way of financing showed up mainly because of the 2008 financial crisis.
During that period, financial markets were facing their trust’s lower point. The vast
majority of the economic environment was composed by small and medium enterprises
(SMEs) which were, economically and financially speaking the crisis’ firsts victims.
Especially Startups and growing companies, they were considered too risky from
investment banks to issue them loans, and too small for institutional investors, like VCs
and Bas, to invest on them, as the latter were better aligned with investments on larger
and later stage businesses. This ‘funding gap’, which already existed, was increased its
magnitude due to the financial distress caused initially by subprime mortgages occurred
in 2008. This crisis situation combined with the already existing funding gap, ended up
with the necessity to find a solution for these kinds of companies which presented severe
difficulties to finance themselves. By definition Startups and growing companies are
innovative and this nature would be extended to their environment. As a matter of fact,
they exploited the outbreak of technology and the funding gap was filled by an innovative
financing method. Equity crowdfunding actually rose due to the described critical time,
financially speaking, and the explosion of new technologies, in particular the wide spread
of internet. As well as these features, the advent of the social networks boosted
crowdfunding environment. Their fast pace acceptance as reliable information media and
1
Reward and Donation Crowdfunding could be based on All-or-Nothing or Keep-it-All models. In the first
case the money collected through the platform by the campaign would be withdraw by the company only if
the target is reached. Keep-it-All model doesn’t take in consideration targets, in fact, in this case the
company at the campaign ending date would take the amount collected whatever it is.

their power to spread information quickly and without borders, made them be another
really important feature especially for the firms which decided to launch an offer and the
online platforms. Social networks represented the top of the democratization iceberg,
which included also crowdfunding.
Equity crowdfunding is a really young financial market. It was officially established
worldwide in April 2012, when the first regulation was signed in the USA. Barack
Obama’s Jumpstart Our Business Startup (JOBS) act put equity crowdfunding in the
public eye as one of the most reliable financial instruments to invest in startups and to
boost the real economy. The main aim of this act was to give the possibility to create new
ventures, preferably innovative, which could push the entire economic environment with
their innovative products and services and through their capability to create new job
positions. The JOBS act gave for the first time the opportunity to anyone to invest in the
stock market without financial intermediaries, doing it through authorized online
platforms. Inevitably, SEC (Security Exchange Committee) followed closely the
government act, introducing rules about the equity crowdfunding market operations, for
instance, first of all it established that the platforms would have to be approved and
authorized by SEC and listed into ad hoc register. The JOBS act, as a matter of fact,
represents the crowdfunding regulation’s worldwide groundbreaking. Most of the other
countries’ regulations are based on this act, whereas each legislator produced its own
regulation to adapt these general rules to their environments. In Italy, for example, the
first regulation concerning crowdfunding was signed by Monti’s Government in 2012
with the “Decreto Sviluppo bis”. It gave the opportunity thought the CONSOB, to
implement and structure the equity crowdfunding market with the creation of ad hoc
register for online platforms and it opened the possibility to collect funds to innovative
startups. Later, the CONSOB amended financial and bank regulation, TUB (Testo Unico
Bancario), to follow the pace of equity crowdfunding market that growth year by year: in
2013 the listed platforms were 15 (World Bank, 2013), while in 2019 the register counts
35 authorized platforms (Osservatori Entrepreneuship & Finance, 2019). This is mainly
due to the fact that the legislator in Italy set up a very favorable environment. For instance,
according to the fact that the Italian entrepreneurial environment is mostly composed by
SMEs, some amendments were signed to avoid that the equity crowdfunding market
would have been exclusively used for innovative startups. As a result, the market was

opened to a lot of different firms over the years, such as innovative SMEs and institutional
investors in innovative startups, in 2015, and to all the SMEs, in 2017. This ‘smoothing’
regulation’s trend is related also to other features of equity crowdfunding market, such as
tax regimes, players limitations and funders protections. According to 2013 World Bank
report Crowdfunding’s Potential for the Developing World, together with information
and communication technologies, regulation is one of the first elements that equity
crowdfunding market needs to grow and to represent a great alternative to traditional
financial markets. The World Bank, in particular, focused its study on the effect that this
financial market could have on Developing countries. According to them, this kind of
innovation could boost their entire economies, and, in the best scenario, it would lead
them to leapfrog, financially speaking, some developed countries and compete with some
others. In the case of Italy, due to fruitful conditions facilitated also by the regulator,
Equity Crowdfunding in 2019 counted investments for € 65.7 millions (Crowdfunding
Buzz, 2020)2
and it is expected to continue its growth also in 2020 where it could arrive
around € 80 millions per year (Osservatori Entrepreneurship & Finance, 2019),
representing one of the firsts market in Europe, even if so far from the UK which is one
of the best market in the world.
1.2. Research question and thesis structure
The empirical setting of this thesis is about the equity crowdfunding market in Italy.
Usually, the literature, and quite all the studies about the ECF market, are focused on the
UK. In fact, the equity crowdfunding market in Italy is a small fraction respect to the one
of UK, in term of campaign numbers, investors amount and funds collected (£ 333
Millions in UK and € 11,3 Millions in Italy, in 2017)3. As the market analysis literature
doesn’t really mentioned the Italian one, to investigate how it works and which are its
main features, underlying their strengthens and weaknesses, the model used is a
combination of some ones already implemented in the literature.
Some questions spontaneously come up after a first sight of this market: Which are
the main reasons, beside the ones already mentioned, that drive the success of equity
2
http://www.crowdfundingbuzz.it/equity-crowdfunding-in-italia-infografica/
3
According to the 4th edition of Italian crowdfunding markets published by Osservatori Entrepreneurship
& Finance of Politecnico di Milano, June 2019.

crowdfunding? Which are the features that made equity crowdfunding platforms so
attractive? Why the Italian equity crowdfunding market has not the dimension of the UK
one? Does it have the capability to reach it or not?
Due to the fact that the vast majority of the analysis in the literature about equity
crowdfunding are based on findings come out from UK market, is important to take it as
a reference point in the analysis of the Italian one. After a deeper focus on the topic, it
notable that the success of the entire market depends on the success of the single offers.
For this reason, it could be assumed that the main question to solve in order to finally
reply to those reported before is: Which are the main features of a successful equity
crowdfunding campaign in Italy?
It is quite unlikely to find a unique and true answer to this question. The first steps
to adopt consist on the analysis of the Italian equity crowdfunding market, because it is
not possible to make hypothesis about the single campaign without knowing everything
that is behind it. Starting from the market history and its regulation, already briefly
mentioned, the study of the main players about their features and their role into the
market. After that is important to go down the surface of the growing market
characteristics already mentioned, to have a better vision and assess their real impact.
When the market would not represent an insolvable question mark, we would focus on
the platforms, briefly studying their structure and the tools they use to offer. The main
part of the thesis would be the last one in which starting from the literature, we would
find finally to solve the main research question about which of their features characterized
a successful campaign. According to all the previous finding reported in the relative
literature, an OLS regression model would be applied to the dataset. Finally, the
regression model outcomes would be combined with all the theoretical traits to try to
solve the main research questions and the hypotheses formulated during the preliminary
part of the thesis. As the exact and unique answer to this question is really difficult to
assess, in the last chapter, alongside with the final conclusions, there would be reported
the limitations occurred during the analysis.

2. Research literature and hypotheses
2.1. Background
Financial markets are by definition imperfect. Likewise, equity crowdfunding markets
suffer from the same imperfections but, in particular, due to its nature, information
asymmetries and the associated agency costs are even greater than in others. In this
market, on the demand side, the vast majority of market users is composed of early-stage
enterprises which are young, small and growth-oriented. Although, on the offer side, the
wide presence of unexperienced investors (crowd-investors) further increases those
asymmetries. Information related costs are higher for both sides and this, combined with
risk capital markets’ intrinsic asymmetries and agency problems, increase those
imperfections, finally resulting in huge constraints for accessing finance. For these
reasons, firstly legislators decided to create regulations concerning mandatory disclosure
in order to try to reduce constraints within the equity crowdfunding market. Alongside
with policy makers, equity crowdfunding market players recognize the importance of
signals as reliable information asymmetry reduction instruments.
2.2. Successful factors analysis and signaling theory
Success rate features analysis literature has been one of the most widely implemented in
recent years regarding equity crowdfunding. According to this, some studies were
conducted to try to figure out which offer’s components affected their success the most.
(Ahlers et al 2015, Vismara 2016, Vulkan, Åstebro and Sierra 2016, Lukkarinen, Tehich,
Wallenius and Wllenius 2016, Nitani, Riding and He 2019). Papers concerning this topic
dealt with it in different ways. Some compared successful campaigns to unsuccessful ones
(Vulkan et al 2016) in order to study how certain features, lead to offers’ opposite results.
Some others concentrated on one market side perspective. For instance, based on the
knowledge that bidders’ characteristics could affect the final outcome of their equity
crowdfunding campaign, some analysis identified how they used to do it. Furthers studied
focused on how some campaign parameters, such as minimum funds target or portion of
equity offered, should be properly set down before the pitch, according to their leverage
on success rate and how they could affect investors behaviors. To summarize, literature

on successful factors analysis, used to deal with all those internal and external signals,
referred to campaigns’ proposer firms and how crowd-funders interpret them resulting in
the offer’s good performance or its fail. According to this, we decided to analyze some
of the Italian crowdfunding market’s successful campaigns. This analysis a few years ago
would have been impossible due to the fact that there were more crowdfunding platforms
than successfully funded campaigns (Vismara, 2016). To do so, we readapted the research
question proposed by Lukkarinen, Teich, Wallenius and Wallenius (2016).
What are the main success drivers for Italian equity crowdfunding campaigns?
Even if the research question and its aim appear really close, we did not base our
analysis only on this paper. We noticed that this article set robust bases for our study, but
we looked for something more in other relevant literature. Finally, our model is made up
of a mixture of knowledge collected from success drivers’ analysis literature.
2.2.1. Equity retention
For sure Lukkarinen et al (2016) represented our starting point. We used almost all
the success drivers’ features that they listed in their paper: funding target, minimum
investment and campaign duration. In order to add further instruments to better
understand firms’ internal attributes, Vismara (2016) helped us. Through this latter paper,
success factor analysis literature was enriched with investigation into about how equity
retention influences the final outcomes of campaigns. Equity retention is an important
signal about the quality of a firm that entrepreneurs, who have a higher amount of
information about a company, send to crowdfunders, who are less informed. The choice
to finance the company through equity crowdfunding market consist on adverse selection
problem for their shareholders. In fact, one of the most important decisions to take is
much equity they should offer to the crowd, leaving them part of their ownership and
potential returns. Higher equity fraction would be associated with low commitment to
future venture success by entrepreneurs, which would be interpreted as a signal of the low
quality of the firm. Lower equity fraction bid, on the contrary, is a good quality signal
(Vismara 2016). This campaign feature could not be considered as independent from any
others. Not forgetting that through equity crowdfunding, firms offer their own risk capital,
so the price at which that fraction is offered is represented by the value the company itself

attributed to it, which is based on the total valuation of the firm. For instance, if ‘Company
A’ is worth € 10 million and 2% is offered to the crowd, whereas ‘Company B’ is valued
at € 2 million and 10% is offered, they are both setting the price of their offer equal to €
200,000. According to the equity retention theory (Vismara 2016), ‘Company A’ is
sending a signal of higher firm quality and ‘Company B’ evidences a lower quality to
crowdfunders. Firm quality is a discriminant used to define share investment associated
risk. In financial markets higher risks are associated with higher returns and this happens
in the equity crowdfunding market as well, where most of the firms are startups or
growing companies. In this regard, let us suppose that in one year from the end of the
campaign, the valuation increases by € 2 million for both companies: Company A’s equity
fraction offered value would be € 240,000, while Company B’s would be € 400.000. How
does signal interpretation change?
2.2.2. Investor rationality
Generally, crowd-investors have less experience than sophisticated financial market
investors. Markets’ policy makers, over time, tried to reduce this lack of knowledge. In
Italy, in particular, Consob introduced a specialized equity crowdfunding section into its
“Investor Education” web page4
and the platforms are obliged to report its link into their
own web sites5
. Some platforms have built learning sections into their web sites, in order
to provide directly useful information and try to attract more users. Moreover, the
Crowdfunding rules, established by Consob, oblige the equity crowdfunding platforms to
provide to not sophisticated investors all the information about opportunities and risks
associated with this high risk market’s investments. In addition, the legislator, following
the European regulation, established that only those crowd-investors who are able to
prove (1) their risk knowledge level, (2) their awareness of their investment decision
consequences, (3) their ability to support the eventual entire loss, could invest through
internet crowdfunding portals6
. Further, the latter, if in charge, is committed to verify if
their investments are appropriate to their profile and, if not, to communicate it to them.
4
http://www.consob.it/web/investor-education/consultazioni-sul-crowdfunding
5
Point k) of Article 14 paragraph 1 of Regolamento sulla raccolta di capitali tramite portali on-line
6
Article 15 paragraph 2 of Regolamento sulla raccolta di capitali tramite portali on-line

In some cases7
, this verification process belongs to who is in charge of the investors’
orders management. If crowd-investors have enough expertise to take responsible
investment decisions, it means that they are able to interpret signals concerning
campaigns. According to this statement, Nitani, Riding and He (2019) affirm that as
crowd-investors use firms’ attributes and financial statements, allowing them to reduce
risks and increase returns and therefore to take rational investment decisions, though ,
this implies proper interpretation of signals. They assess that firms’ attributes, which
represent their quality level, derives from financial statements. For instance, pre-money
evaluation should be computed on balance sheet values. Based on literature’s previous
findings, they split firms’ and boards’ attributes into reliable and relatively less reliable
signals to interpret success driver features analysis, regarding investor rational decision
making. The less reliable signals are all those which come from financial statements,
whilst the first category is composed of internal firm attributes, the most interesting one
being business age. This signal is controversial, in fact, as low firm age is considered as
a positive sign for risk seekers, while negative for risk adverse investors and vice versa.
Lower business age means higher growth potential besides higher potential return, while,
on the other hand, more experienced firms have higher valuation related to lower growth
pace in the future, resulting though in lower returns. Let us remember the example of
Company A and Company B. First of all, from their pre-money evaluation, we assume
that at their campaigns’ launch dates B is younger than A. Dividing crowd-funders into
risk adverse and risk seekers investors, we can note that according to both equity retention
and investor rationality theories they interpret signals in opposite ways. Risk seekers
investors would be more interested in participating in the Company B campaign, due to
its lower business age, lower evaluation and higher growth potential, while Company A
ones would attract more risk adverse investors. Our final hypothesis is that due to equity
crowdfunding market characteristics crowd-investors are more risk seekers.
Hypothesis 1: Italian crowd-investors prefer campaign with lower pre-money
valuation, lower equity retention and lower business age.
7
Article 17 paragraph 3, Regolamento sulla raccolta di capitali tramite portali on-line

Table 2.1. Summary signals Company A and B
Company A Company B
High
retention
High
evaluation
High ages
Low
retention
Low
evaluation
Low ages
Risk seekers Negative Negative Negative Positive Positive Positive
Risk adverse Positive Positive Positive Negative Negative Negative
2.2.3. Information Cascade
Even if regulators provided learning instruments for investors, to increase their
knowledge and to reduce information asymmetries, the offer side of the market is
basically split between ‘sophisticated’ and crowd investors. This distinction is recognized
by Italian Crowdfunding rules as well8
, which includes commitments for every campaign,
about mandatory fund amounts invested by ‘professional’ investors on total collection.
Investors labeled as ‘sophisticated’ are those who have more expertise in the market, due
to their long practice in it and they could be individuals, such as ‘serial’ investors (i.e
Business Angels), or companies, like Venture Capitals or startup accelerators. Due to
their significant acquired know-how, they have more useful informative instruments for
their decision-making process, for example, due diligence processes. As a result, their
investment decisions are considered external signals for equity online campaigns. On the
other hand, crowd-investors usually work with a tremendous information gap. This
situation puts them in a weak position in the market regarding risks associated with
investments. In order to decide how to invest, they usually face high and, sometimes
unsustainable, costs for example, a proper due diligence is quite impossible for them to
undertake. As a result, crowd-investors are, most of the time, unable to assess the real
quality of signal provided by bidding firms and this would drive them to wrong
investment decision or would finally lead them to decide to leave the market for instance,
due to high unsolvable adverse selection issues. According to information asymmetry
literature, the crowd could exploit its collective wisdom to fill the information gap. It is
generally known that people who are dealing with something they do not know, usually
8
Article 24 paragraph 2, Regolamento sulla raccolta di capitali tramite portali on-line

look at the others to try to manage it. Psychologists call it behavioral social learning
(Bandura, 1977), but in the financial field it is defined as ‘information cascade’ (Welch,
1992). According to this literature, the two main characteristics are sequential decisions
and uncertainty, which is more severe in the equity crowdfunding market than in any
other financial one (Bikhandani et al., 1992). This concept became the topic of analysis
concerning the market, due to its high relevance to the latter. One of the most important
papers in the literature was published in 2018 by Vismara9
. Its analysis dealt with two
main issues related to crowd-investors’ information cascade, such as (1) which signals
are incorporated into early investments and (2) how investor’s public information are
related to early contribution. Due to the high amount of studies in IPOs setting, the
information cascade study method used by the paper belongs to the latter. Its main
assumption is that early investors are generally the more informed, ‘sophisticated’ ones
though, and that their investment decision would provide high relevance signals among
crowd-funders, who would use them effectively to reduce information costs and as a gap
instrument, for instance, as alternative screening methods. Alongside this, less informed
funders’ investment decisions are related also to positive payoff externalities, such as the
decision to invest in the campaign immediately before it would achieve the success
funding threshold (Vismara, 2018). As platforms are based on the all-or-nothing
principle, investments during that time would result as catch or loss of participating
possibility to successful offers. Since one of the sophisticate investors features consist of
participation to campaign successful rate and, due to the fact that any investor could
decide to publicly provide its own information, these externalities are considered positive
signals too. Because of Italian legislation, which requires ‘sophisticate’ funds as a
mandatory threshold for campaign success, we assume that early investors’ public
information is in the Italian market case less reliable success drivers.
Hypothesis 2: public investors are not related to higher amounts of early investors.
However, we are interested in a detailed study of the information cascade as a general
topic, assessing if this principle was respected or not by the Italian market as well. For
this reason, we assess that high early success about the campaign drive it to the success.
9
Information Cascades Among Investors in Equity Crowdfunding, Silvio Vismara, 2018. Vol.42(3) 467-
497, Entrepreneurship Theory and Practice. SAGE publications

Hypothesis 3: early investors are able to attract late investors, and this would lead the
related campaign to high success.
Another tool of investors information gap reduction is related to how some investors
interact with others. On this topic some researchers conducted quantitative and qualitative
analysis on investor-initiated discussion boards, which investors use to deal with agency
problems. Kleinert and Volkmann (2019) stated that discussion boards enhance campaign
success, providing neutral endorsements, like third-party ones, to investors of different
bidder campaigns signals. Furthermore, they assess through qualitative and qualitative
analysis that discussion boards’ level of influence depends on their referred topic. Finally,
according to those outcomes, discussion boards are relevant as information cascade
signals. This does not represent a study topic in our analysis due to the fact that we only
based it on quantitative data. In fact, discussion board analysis would be mentioned into
the limitation section.
All the literature about information cascade leads us to the news to study early funded
campaigns and late ones in detail. As a result, we purpose another two questions which
define those sub-analysis.
- What are the signals that drove a campaign to be funded earlier?
- What are those ones that drove campaign to be funded later?
2.2.4. Social networks
The way in which signals are spread out among investors is another important
instrument that would reduce information asymmetries. Regarding fundraisers, the first
crowd which would receive their internal signals would probably belong to their close
social network. Literature about crowdfunding largely analyzed how social networks’
engagement affect campaign success, and most of the publications assert that they have
a positive influence on the latter. This result referred to any crowdfunding markets type,
as previous researches were conducted on all of them. As a consequence, it is generally
accepted that the higher the company social network is, the higher success would be
achieved by its campaign. Lukkarinen et al. (2016), using this variable as predictor for
their success driver analysis’ model, divided it into Private network and Social network.

Crowdfunding markets growth has a high link with information technology innovation
and specifically, social medias played a leading role. Through them proposers’
information is easily widespread among their close network members, moreover they
could be used as an effective tool to extend their existing private network, creating word-
of-month mechanisms related to their campaign. Even the equity campaign could be used
to enlarge firms’ networks. Though its publication, fundraisers could collect feedback
from subjects already close to them and those who are not. Nathan Rose (2016), defined
some proponents’ companies as ‘Local businesses with a Crowd’. According to this
book10
, those companies have already a strong recognition, at least within their close
customers community, and their decision to launch crowdfunding offer would easily
drive those potential investors to became early investors and produce positive signals for
later ones. In addition, early investors community members are potentially more inclined
to create positive word-of-month mechanisms that would finally produce a social network
enlargement effect. Even though most of the existent studies regarding this topic, based
on social network size assessment on total amount of fundraisers’ social media
connections, we decided to not include this variable in our analysis due to its weak
computational method making it possibly not so reliable.
10
Equity Crowdfunding, The complete guide for startups and growing companies. Natan Rose (2016).
Pages 46-47

3. Equity crowdfunding market in Italy
3.1. Regulation
Equity crowdfunding markets do not have unified regulation across countries, not even
within regions such as the European Union. However, each country’s ECF legislation is
based on the JOBS Act issued in 2012 by the USA, the first equity crowdfunding
regulation in the world. As in the case of the USA, the regulator in each country usually
aims to try to create the best environment possible for every player to foster economic
development and innovation, through startups and fast innovative growing companies,
attempting to reduce, or better, remove the markets’ issues which restrict its work and
potentials. Information asymmetry, moral hazard and financial loss risks, as for all the
other financial markets, are the main challenging features to be solved for equity
crowdfunding, while if fraud risk represents a big issue in reward crowdfunding, it does
not affect this market so heavily, mainly due to what they deal with. Equity crowdfunding
offers concern risk capital share, which is intrinsically high risk and ordinary due
diligence is higher than for products or services offered by reward campaigns. In addition,
equity crowdfunding platforms use to preselect the offers before their publications into
their web sites. Thus, fraud risk is furtherly reduced by this process.
The equity crowdfunding market was introduced to Italy in 2012 with D.L.
179/2012, ‘Decreto Sviluppo-bis’ issued by the Monti Government and converted to law
in the same year (Legge 221/2012). It generally referred to financial fund collection
through the internet amending the TUF11
, the Italian general financial regulatory system.
In fact, it did not only regulate the equity crowdfunding market, by way of introducing
new firm status, for example innovative startups, but it also regulated other forms of
crowdfunding, such as lending with obligation issue simplifications. Some specific rules
were included in art.30 of the TUF setting out which subjects are allowed to collect funds
through internet platforms and their limitations, in addition to which types of firms can
access equity crowdfunding and what is the maximum amount of capital they can collect.
11
amendment on art.30 Testo Unico della Finanza

In June 2013, CONSOB12
issued Crowdfunding rules13
after shareholders and expert
caucus, took place in the first days of that year, and this could be considered as the Italian
equity crowdfunding ‘Magna Carta’. It is composed of 25 articles, divided into three main
parts: the first sets out the general provisions; the second part, the largest, regulates
platforms management, comprising four titles; the last main part disciplines equity share
online offers. Three attachments were also produced to complete the regulation. They
focus on specific issues and are instructions about platform enrollment in ordinary and
special registers, mandatory descriptive disclose about platforms’ organization and
mandatory disclosure about single offers. The most relevant principles set up by
Crowdfunding rules relate to market operating methods, according to platforms, investors
and equity bidders.
3.1.1. Platforms regulation
Firstly, equity crowdfunding ordinary and special platforms registers were created.
Through register listing, platforms are legally authorized to publish equity crowdfunding
bids and collect funds from investors. At June 2019, 35 authorized platforms were
recorded in Crowdfunding registers. To be listed, their internet portal managers have to
provide mandatory disclosure about the business’s organization, fulfill patrimonial
requirements and there are the firm’s and managers’ integrity requirements. If some of
these mandatory conditions during the validation process or even throughout its activity
were to be lost, the platform would lose its authorization as well. As regards the integrity
requirements, the 2017 amendment obliges managers to obtain insurance for clients’
damages deriving from platform activities in order to increase investors protection.
Secondly, equity crowdfunding platforms are required to follow a set of rules of
conduct. These commitments fall on managers who must be diligent, honest and
transparent while running their platform business, avoiding any conflicts of interest which
could negatively affect investors’ and bidders’ interests14
. Moreover, they must divulge a
vast set of information, such as management activity reports, investment consequences
12
Italian financial markets supervisor organ. Equal to SEC in US and FCA in UK.
13
‘Regolamento sulla raccolta di capitali tramite portali on-line’ adopted with Consob approval n.18592,
June 26th
2013, then amended with approval n.19520, February 24th
2016, approval n. 20204, November
29th
2017, approval n.20264, January 17th
2018, approval n.21110, October 10th
2019 and approval
n.21259, February 6th
2020
14
Article 13, paragraph 1, Regolamento sulla raccolta di capitali tramite portali on-line

and single offers details and finally, they are responsible for reporting potential violations
to the supervisory authority. The last amendment issued in 2020, platforms were allowed
to publish a campaign about obligations issues, creating reserved sections in their web
sites for them, so as to distinguish them from the equity ones due to their different offered
instruments. Another market innovation was introduced in the 2019 amendment, with the
possibility to create notice boards on platforms’ websites, where backers who have
invested in one of their previous campaigns, can publish their share transfer
announcements. The only task platforms have is to host it and privately disclose investors
information to interested parts.
3.1.2. Investors regulation
According to which investors are allowed to participate in equity share offers, their
protection and their limits, Crowdfunding rules have changed quickly from their first
publication to today.
Firstly, the Italian regulations are the only ones which require a mandatory faction
of the offer target funds, to be subscribed by ‘qualified’ investors. More precisely, 5% of
the minimum target must be pledged by investors who fall into the list of ‘sophisticated’
subject and firms, defined and constantly updated by the legislator. Investors defined as
‘qualified’ are banking foundations, financial firms which invest mainly (at least 70% of
their portfolio) in innovation and development, innovative startup incubators, ‘serial’
equity crowdfunding investors (i.e. Business Angels) and former innovative startups’ and
SMEs’ managers15
. An exception to this rule is established for campaigns launched by
SMEs with consolidated balance sheets, relating to the two-year period before their pitch.
In these cases, the threshold of ‘qualified’ investments decreases to 3% on target16
. These
rules are about providing reliable information about the campaign, to inexperienced
investors and trying to reduce their information asymmetry. On the other hand, this
threshold would benefit bidders. On this extant, information cascade theory is recalled.
According to the latter, higher crowd wisdom about campaigns result to positively affect
success rate and, consequentially, to increase the total funds collected.
Secondly, investors interests are also protected by the fact that Crowdfunding rules
15
Article 24, paragraph 2, Regolamento sulla raccolta di capitali tramite portali on-line
16
Article 24, paragraph 2-ter, Regolamento sulla raccolta di capitali tramite portali on-line

oblige bidder companies to include in their constitutional document the ‘tag along’
clause, destined at crowdfunding investors. As a consequence, if company controllers
should decide to sell their participations, after the campaign’s end, investors are allowed
to sell theirs too.
Finally, the 2016 amendment introduced the possibility of share dematerialization in
order to try to create a secondary market. Because of the amendment issued in 2019 about
notice board’ creations too, some attempts at this are already in process, but, unto now,
high transfer costs have represented heavy disincentives, especially for lower investment
amounts.
3.1.3. Bidder regulation
The company types, which Crowdfunding rules allowed to publish equity share
offers, significantly expanded from 2013. At that time, only ‘innovative startups’ could
bid their equity shares online. As already reported, the ‘innovative startup’ definition was
introduced alongside with Crowdfunding rules. According to this regulation, companies
are so defined if they respect certain requirements17
: firstly, that their headquarters and
main affairs are based in Italy; secondly, that starting from the second business year, the
production value reported in their consolidated balance sheet is not higher than € 5
million; thirdly, that they do not distribute their profits; fourthly, that their principal or
prevalent business purpose relates to high-tech innovative services or products’
development, production and commercialization; fifthly, that they have not been
constituted from mergers and acquisitions or spin-offs; finally, that they satisfy at least
one of the following requirements: R&D spend of 15% or more of the higher of
production cost and value; Master Degree workers of over 2/3 of the work force;
possession of certain type of licenses related to innovations. The main idea of the
regulator was to achieve general rules based on US and UK experiences, where,
especially in the US, equity crowdfunding markets were established by regulation with
the goal to boost the economy, exploiting high contribution companies as innovative
startups. After the first period of appreciation from some Italian investors, combined with
continued booming innovation, Consob decided to extend the set of possible bidders to
17
http://startup.registroimprese.it/isin/static/startup/index.html#

exploit this equity crowdfunding potential further. Since 2016, innovative SMEs were
introduced into the Italian legal system18
. They differ slightly from innovative startups
due to their higher dimensions and experiences. That year, these new companies were
immediately allowed to finance through equity crowdfunding, and this possibility was
extended to ETFs, to limited companies which allocate mainly their investment to
innovative startups and innovative SMEs and finally to other types of startups, like
touristic ones.
The innovative SMEs system did not succeed as the legislator had hoped, so later the
Italian equity crowdfunding market was opened up to all Italian companies defined as
SMEs, according to European Commission legislation. This means that now all Italian
SMEs companies, which represent the vast majority of Italian enterprises, are allowed to
finance through own risk capital offers through internet platforms. Even European SMEs
could now launch equity crowdfunding campaigns through the Italian platforms.
3.1.4. Tax regulation
Equity share offers are not tax objects for bidders, due to the fact that according to
the European Regulation on VAT, issue of share is tax free, and all the costs related to
the issue are tax deductible. On the other hand, equity crowdfunding investors are entitled
to tax relief, according to current tax legislation in this regard. Since 2019, all equity
crowdfunding investors, both individuals and legal persons, which allocate their
investments into Italian startups and innovative SMEs, are entitled to 40% of tax
reduction on those amounts, whilst before that amendment this tax relief was about 30%.
This is another instrument used by legislators to try to attract more funds into the market.
3.2. Market analysis
All the updates to the 2013 version of the Crowdfunding rules, lead to a booming phase
in Italian equity crowdfunding started in 2016 along with firsts main amendments. It was
not a random occurrence that the yearly base collected funds tripled each year since 2016,
arriving in 2019 to count around € 65.7 million. This last amount is more than the half of
18
http://startup.registroimprese.it/isin/static/pminnovative/index.html#

total funds collected from the market establishment in 2014, which is around € 121
million. There have been 333 campaigns that have ended successfully since 2014 and, as
for collected funds, their numbers per year increase to arrive in 2019, when 140 offers
were overfunded. Furthermore, crowd investors increased dramatically over the years,
but according to their yearly average pledge, which roughly highlights their behaviors, it
seems that Italian equity crowdfunding attracted different types of investors, lower than
in previous years. In 2014 each investor, on average, pledged around € 9,800, while they
have constantly decreased their investment amounts to finally arrive at the lower value of
€ 3,600 in 2017. Despite the huge increase in total investors, between 2017 and 2019 the
average pledge offered to equity campaigns stayed constant. Based on this data, one could
assume that apparently during the early years of the market, the majority of investors
were sophisticated ones, with higher investments possibility and with greater knowledge
and experience of the market. After 2017, the Italian equity market followed the hype
around crowdfunding in general and more crowd investors, characterized by lower
average investment usually because of their lack of experience and lower available funds
than professional investors, entered in the market. As we already know, regulation has
significant influence on market performance, and the crowd investors increasing
attraction was highly correlated to the introduction of investors protection rules into
market regulation19
. This allows one to presume that 2017 is the turning year which
divides the Italian equity crowdfunding market between the early more sophisticated
market, since 2014, and later wider crowd-oriented market. To confirm this assumption,
offers performance were analyzed further over the years. The average success rate
increased year on year from 5% of overfunding in 2014 to 111% in 2019. Average
minimum target results were interesting in this sphere, as its peak, € 311,000, was in 2014
and it registered a decreasing trend to € 126,000 in 2017 and began a slight yearly base
constant increase. Besides this trend, the overall increasing offers’ success rate was
explained by the already noticed constant increase in total collected funds. According to
these last observations, it could further assume that also bidders during the period have
built the awareness of how to deal with the market in terms of starting funds requirements.
19
For instance, D.L. 129/2017 imposed platforms managers to draft insurance cover to investors
protection, followed by Consob’s approval n.20264, which amended the 2013 Crowdfunding rules
assessing the minimum insurance coverage for investors protection related either to single offer either to
general platform level.

For this reason, the assumptions of the Italian equity crowdfunding can now be reworked.
It can be concluded that it is still in its development period. The high boost obtained
so far from regulators give it a solid base and high growth potential. Hype around
crowdfunding markets is serving as further impulse to this booming phase which seems
not yet to be expired. Every player is increasing its maturity, in particular bidder firms
which are learning constantly how to deal with this market due to higher sets of peer
experiences and sometimes also by personal ones. In fact, some firms have already used
this financial market more than once and usually their further rounds ended with higher
collected funds, so higher successful rates.
Due to the market age, in few years, investors could be able to evaluate their
investments in this market. Risk capital investments are generally illiquid and the only
way to receive returns are through share profits, share transfers, mainly in the cases of
buyouts or stock exchange listings. In the case of Italian equity crowdfunding, profits are
usually not distributed due to the fact that the majority of bidders are Innovative startups
which are unable to distribute them by law. In addition, according to the Osservatorio
Entrepreneurship and Finance 2019 report, none of SMEs bidders decided to distribute
2018 profits. Furthermore, only a few bidders have already closed a buyout or have been
listed on the stock exchange market. Regarding the first share transfer cases, they are all
referred to firms which concluded their crowdfunding offer before 2016. For all these
reasons, one can conclude that is not so easy for investors to evaluate their investments
in the equity crowdfunding market. Osservatorio Entrepreneurship and Finance decided
to create an index, called the Italian Equity Crowdfunding Index, which represents the
theoretical return of equity crowdfunding investments if the investor portfolio is
composed by 1% of each crowdfunding campaign launched in the market. This index,
due to the lack of information about exits, is mainly based on the reevaluation of
investments resulting from follow-ups. Where they decide to launch a new offer, bidders
have to evaluate their value which normally is higher than the pre-money evaluation
assessed before the first crowdfunding round. This is due to fact that, by definition, during
the time firms usually increase their value and, in this case, part of it is thanks to the first
round collected funds. The Osservatorio’s theory asserts that, if through follow-up
campaigns, firms bid equity shares with higher premiums than in the previous round, as
a result investors’ shares value would appreciate. The Osservatorio reminds that without

exits, the index is based only on a theoretical approach, as such less reliable, but still a
good reference for the crowd. They launched it 2017 with a starting value of 103.04,
which meant a theoretical investment appreciation of 3.04%. During the year it moves
randomly, like a normal index, and in May 2018 it reached its peak value, equal to 117.51,
due to the follow-up registered during that period, to then return to the starting values
until July 2019, when it was 109.43, concerning a theoretical equity crowdfunding
investment return of about 9.43%.

Appendix
Table 3.1. Distinctive features of bidder company types
Company Type Distinctive features
Innovative
Startups
D.L. 179/2012
- Less than 60 months of business activity at application date
- Headquarter and main affairs based in Italy
- Starting from the second business year, production value reported in
their consolidated balance sheet is not higher than € 5 million.
- No profits distribution
- Principal or prevalent business purpose is high-tech innovative services
or products’ development, production and commercialization
- Not constituted from Mergers and Acquisitions or Spin-offs
- Satisfy at least one of following requirements
• R&D costs 15% or more over the higher between production cost
and value
• Master Degree workers over 2/3 of the working force
• possession of license about industrial invention, biotechnological
invention, new vegetal variety and semiconductor product
topography.
Innovative SMEs
D.L. 3/2015
- Headquarter and main affairs based in Italy
- Not listed on stock exchange market
- A certified balance sheet has been already deposited with institutional
firms register
- Revenue under € 50 million or Turnover under € 43 million
- Less than 250 employed workers
- Satisfy at least one of following requirements
• R&D costs 3% or more over the higher between production cost
and value
• Master degree workers over 1/3 of the working force
• possession of license about industrial invention, biotechnological
invention, new vegetal variety and semiconductor product
topography.
- Not listed in the special section of innovative startup and certified
incubator register
SMEs
European Union
recommendation
2003/361/CE
- Less than 250 employed workers
- Revenues under € 50 million
- Turnover under € 43 million

Table 3.2. Summary Amendments and Effects on the Rules
Amendment Effect on Crowdfunding rules
Approval
n.19520
February
24th
2016
- Introduction of Innovative SME to equity crowdfunding market
- Inclusion into ‘sophisticated’ investors of ‘serial’ investors, like
Business Angels, and individuals which are former innovative startups
and innovative SMEs manager
- Obligation for platforms to start the activity within 6 months form
authorization, if not authorization’s disqualification.
- Possibility for platforms to internally run the verification of investors
knowledge about risks and consequences connected to their offer
- Possibility of dematerialization system to cut transaction costs and
incentive secondary market
Approval n.
20204
November
29th
2017
- Extension to all SMEs defined by European Union recommendation the
possibility to finance in equity crowdfunding market
- Removal of limitation to some limited company to launch campaigns
- Obligation for platform managers to enter into insurance contracts which
cover investors from damages deriving from platforms activities
- Extension offers’ financial managers list to Italian SGR, SICAV and
SICAF
Approval
n.20264
January 17th
2018
- Extension to all SMEs defined by European Commission
recommendation the possibility to finance in equity crowdfunding
market, with obligation to indicate in their statute all the necessary
clause
- Obligation to adhere to investors indemnity system
- Definition of requirements about insurance contracts related to investors
damages
- Possibility for platforms to voluntary opt-out about authorization
- Strength of rules about conflicts of interests in particular for platforms
which decide to launch own campaign into through themselves
- Reduction of 5% fraction to 3% for offers published by SMEs which
have balance sheet certification or consolidated balance sheet for the
previous 2 year before the pitch
- Definition of whistleblowing policy
Approval
n.21110
October 10th
2019
- Rules name change in ‘Regolamento sulla raccolta di capitali tramite
portali on-line’
- Extension of bidders to foreign SMEs defined according to European
Commission recommendation
- Extension of bidders to ETFs which invest at least 70% of their portfolio
in SMEs and to limited companies with the same investment behaviors
- Possibility for platforms to create separate sections reserved to
obligation offers
- Possibility for platforms to create announcements board for share
transfer
Approval
n.21259
February 6th
2020
- Removal of indemnity system
- Indication into the register of platform business activity

Table 3.3. Trends by year of observations features compared with Italian market
Dataset 122 observations Italian Market
2016 2017 2018 2019 2016 2017 2018 2019
Successful Campaigns 2 21 56 43 19 50 113 140
Funds Collected 373.962 € 6.642.358 € 17.965.808 € 24.147.476 € 4.363.000 € 11.790.000 € 36.113.000 € 65.711.000 €
Total investor 247 2.143 6.422 9.919 747 3.277 9.496 18.046
Average Pledge 1.514 € 3.099 € 2.797 € 2.434 € 5.800 € 3.600 € 3.800 € 3.600 €
Av. Investors 123 102 115 231 39 66 84 129
Av. Minimum Target 111.971 € 117.680 € 137.510 € 214.548 € 178.000 € 125.000 € 160.000 € 223.000 €
Av. Overfunding 75.010 € 198.622 € 183.307 € 347.021 € 52.000 € 111.000 € 160.000 € 247.000 €
% overfunding 67% 169% 133% 162% 29% 89% 100% 111%
Av. Business age in years 2,31 1,99 2,99 3,65
Av. Minimum pledge 175 € 2.008 € 442 € 831 €
Av. Top share contribution 8.050 € 17.003 € 13.325 € 21.749 €
Av. Pre-money 5.178.928 € 7.096.700 € 5.372.097 € 3.964.066 €
Av. Equity target 3,9% 6,2% 5,1% 8,1%
Blind spots are related to unavailable information.

4. Data samples
4.1. Data research
The data set is composed of campaigns closed with success from Mamacrowd and
Crowdfundme platforms from 2016 to 2019. We selected these platforms because they
are generalized, not sector specific, market leaders so, consequently they are highly
representative of the Italian equity crowdfunding market. Both platforms follow the “all
or nothing” model, where only campaigns able to achieve the minimum target fixed by
their bidders would be considered funded and successful. According to the 4th edition of
the Italian crowdfunding markets published by Osservatori Entrepreneurship & Finance
of Politecnico di Milano, at the end of Q2 2019 they were the main platforms in terms of
campaigns published. Crowdfundme, since its legal authorization to publish campaigns
in late 2014, launched 79 campaigns, 32 in the first half of 2019, while Mamacrowd
totalled 71 launches in the same period, 33 in Q2 2019. Thus, they published 150
campaigns altogether, 37% of the total market publication (401), during the same period.
In terms of total funds collected through these two platforms, according to
Crowdfundingbuzz20
, the Italian web site high specialized in crowdfunding markets and
official press partner of Osservatori Entrepreneurship & Finance, these two platforms
were able to collect about 64.7% of total 2018 funds (€18,375 million out of a total of
€28,419 million) and about 49.5% in 2019 (€24,072 million out of a total of €48,590
million). In terms of investors amounts, Crowdfundme and Mamacrowd attracted the vast
majority of them as well, 79.5% of the total in 2018 (6,598 out of 8,298) and 64.8% of
them in 2019 (9,840 on 15,166). The last data confirm that these two platforms are the
market leaders, and although their strong competitive position decreased during the time
considered due to increasing competition from other platforms, they still remained in a
dominant situation up to the end of 2019. Another really important discriminant for
platform selection process is related to information availability. Crowdfundme and
Mamacrowd had significant information available regarding the data relevant for this
thesis. The most important data were included in the descriptive “investment” window,
available within single campaign web pages. This segment comprises single investments
20
http://www.crowdfundingbuzz.it/

pledged details, including the name of investor, the amount pledged and the date of the
pledge. Based on information cascade theory, the latter data is crucial for our thesis’s
hypotheses. None of the other Italian platforms presented the same level of information
availability on these data, consequently focus was on these two portals. In addition to this,
even if Crowdfundme and Mamacrowd were authorized by the CONSOB in 2014,
respectively 5th
and 7th
in chronological order to be included into the Ordinary Equity
Crowdfunding Register since its establishment, both web sites reported campaigns only
after 2016, so the starting point was automatically set by the platforms themselves. It is
important to remember that, even if some of the papers mentioned as inspirers for the
analysis included both successful and unsuccessful campaigns, in particular Vulkan,
Åstebro, Sierra (2016), the focus was only on successful pitches. This is due to the fact
that for unsuccessful ones the data available was not enough to complete the data set
compared to the ones of the successful campaigns.
4.2. Data analysis
The complete data set is composed of 122 observations. Each of these represents a single
equity crowdfunding campaign which was successfully closed, published on Mamacrowd
and Crowdfundme and ended between 2016 and 2019. Those campaigns were pitched by
different types of firms according to their product and services offered, their sector and
their corporate structure. With reference to the latter, the reader is reminded that the
Italian equity crowdfunding regulation has changed a lot since its first version adopted in
2013. Before 2015, only Innovative Startups could collect funds through equity share
offers, but after Dl. 3/2015 this possibility was extended to Innovative SME, ETF and
other firms which were specialized in investments in Innovative Startups and Innovative
SME. Due to the fact that this extension did not give the results expected, in 2016 the
equity crowdfunding market was finally opened up to all SME. The successful campaigns
observed in our dataset belong mainly to Innovative startups (97), which remain the first
equity crowdfunding markets demand side users, due to the high match between the
market and these businesses’ characteristics. There were 15 Innovative SMEs’ campaigns
during the total period, 6 SME and 4 ETF campaigns. Even if SMEs started to use this
financial market after Innovative SMEs, and the fact that in Italy there are fewer small

businesses which are innovative that the ones which are not, during the analyzes it was
noted that these firms did not exploit this market significantly.
Business maturity was another interesting data in the set about funders. On average,
campaigns in 2017 were proposed by firms with about 2 years of running a business,
while in 2018 they were around 3 years of experience and in 2019 they were in business
on average more than 3.6 years from the date of their constitution. As their bid users, the
studied platforms markets seem to become more mature as the period went on. After a
boom phase in 2018, where successful campaigns of Mamacrowd and Crowdfundme
totalled 56, more than double that in 2017 (21), in 2019 43 offers were launched and
completed with overfunding. Regardless of this, the trend of funds collected by successful
campaigns continued to increase year by year. In 2017 on the two platforms around € 6.6
million was collected, in 2018, when the higher peak of overfunding was registered, funds
amounted to around € 18 million while in 2019 relative fewer campaigns collected around
€ 24 million. This is due to the fact that, according to our observations, successful offers
launched on Mamacrowd and Crowdfundme were able to attract more investors during
the year (9,919 in 2019, 6,422 in 2018 and 2,143 in 2017) while their yearly based average
pledge, calculated on the aggregate amount of investors and funds collected, although
decreasing, remained relatively the same during the whole period (Table 3.3).
Through equity crowdfunding campaigns, firms could offer investors different kinds
of shares, which have value differences and distinctive associated rights. The successful
campaigns included into the dataset usually offer shares labled as “A”, “B”, “C” and “D”.
Those types of shares are not standardized, they may have the same label but different
rights, but generally “A” stands for ordinary equity share with voting and patrimonial
rights, while the others are secondary shares with patrimonial rights but usually without
or with fewer voting rights and subordinated to ordinary shareholders. Usually, equity
share types offered by the single campaign are two out of the four described, but some of
them could offer one, and others three, types. It must be considered that through these
platforms, firms are offering part of their ownership and, for this reason, they assess their
value in different ways. To receive the lower valued share, investors need to invest funds
equal to the minimum contribution, which is fixed by the campaign, to participate in the
offer. On the other hand, if investors would like to gain a better position in bidders’
shareholders group, they ought to invest the contribution required to obtain that type of

shares. Every investor, according to his/her investment decisions could create his/her own
portfolio with a multiple combination of shares. Table 1 shows data about the average
minimum contribution and the contribution required to obtain higher valued share both
registered year by year.
To assess the share price, the first information needed is the value of the company.
In the equity crowdfunding market, it is called Pre-money evaluation. During the period
considered, it was noted that bidders’ valuation was constantly decreasing for
Mamacrowd and Crowdfundme single campaigns. This value is usually assessed
personally by the bidders, so information regarding how they reach this value is generally
not disclosed. For this reason, is quite impossible to study it singularly, so a combination
of other factors, such as minimum target and equity retention must be used. The Average
minimum target constantly increased from 2016 to 2019. With lower firm valuation and
higher required funds, the offered company equity portion should increase. In fact, it was
noted that, on average, equity target, which is the percentage value of this portion,
increased following the pre-money evaluation trend.
Finally, yearly based overfunding collection was examined, and it was noted that
their average values did not have a linear trend. In 2018 successful campaigns examined
registered worse results in terms of absolute values than in 2017. Thus, combined with
the minimum target increase, this resulted in registering a decrease in the relative value
of successful rate. To the contrary, in 2019 the huge increase in funds collected over the
minimum target with respect to 2018 resulted in an average higher yearly based
percentage successful rate.
Our 122 observations, as cited above, also included 2 campaigns which closed in
2016: one published and overfunded through Mamacrowd and the other successfully
closed on Crowdfundme. Due to the fact that there were few observations relating to these
campaigns and also that they may not be the only campaigns that were successful in 2016,
no mention of them had been made before. However, they were included in the data set
as all the campaigns available on Mamacrowd and Crowdfundme web sites were analyzed
because the analysis is not conduced on each single year but on their aggregate
observations. The amount of observations available about the single years are not enough
to apply the study on each year considered.

Moreover, into the dataset some successfully funded campaigns belong to the same
proposer. As firms could finance through equity crowdfunding market anytime they want,
it was noticed that some of them, following the past success, decided to launch follow-up
offers. The firms know which are their actual financial needs and sometimes these could
be more than what they could collect from a single equity crowdfunding campaign. This
is due to the fact that (1) a too high minimum target is difficult to achieve, (2) if the target
is too lower than the actual financial need, the latter would not be collected. As a result,
companies with high financial needs may decide to split their fund collection in different
rounds. There are no evidences that the follow-up offers come out from firm’s plans. In
fact, it could be possible as well that they could resort to crowdfunding market to further
finance themselves as a result of different needs than those about the first launched
campaign.
Follow-ups are not so common in our observations and focused analysis about their
success drivers would result not so significant. It is assumed that their proposers would
have a larger social network due to the previous successful collection round. Moreover,
crowd wisdom is higher than for first rounds pitches, resulting in higher probability of
success. Thus, the firms could set higher minimum target and finally collect higher funds.
The Table 4.1 data highlight the veracity of these latter assumption.
Table 4.1. Follow-ups evidences on their first rounds
Follow-ups First rounds
Target Min 230,798.29 € 93,333.33 €
Min Pledge 462.89 € 349.87 €
Top share Pledge 21,426.50 € 10,874.88 €
Day to Target 17.29 26.83
1W € on Target 72% 65%
1W #P on Total 19% 15%
1M € on Target 167% 141%
1M #P on Total 46% 48%
Pre-money 6,144,925.86 € 2,715,484.17 €
Pledgers 291.14 154.67
Average Pledge 2,684.43 € 1,728.22 €
% Overfunding 228% 196%
Data are related to those follow-up campaign with first rounds reported in the dataset. The others are not included.

5. Research Variables
5.1. Variables Description
The complete data set is composed of 38 variables collected from the Mamacrowd and
Crowdfundme web sites. Concerning the complete success driver analysis performed,
there would have been too much data in addition to the available observations and, due
to the excess of variables, the regression model may not have produced reliable and clean
results. As some of these variables are ratios of others, they incorporate more information
therefore selecting them for the regression set of variables would be a starting cleaning
method. Furthermore, clear ups, based on variable reliability according to relative
literature, strengthen the regression model with the selection of 17 variables, where one
is the dependent (y) and the other sixteen are the independents (x). In the latter, another
distinction between signals and performance variables has been made. After the complete
analysis, in order to answer the remaining research questions, further analysis would be
carried out. These would have a different structure regarding dependent and independent
variables, and, in some cases, variables not used for the complete analysis would be used.
Then, we could analyze the variables according to their influence in the complete success
driver analysis, indicating their expected relevance and their mutual relationships.
5.1.1. Independent variables
As the final goal of our research is to define which variables best explain the
observed campaigns’ success rate, the model’s independent variable is ‘% overfunding’.
It represents how much the campaign has been overfunded with respect to the minimum
target fixed by its proposing firm in order to be consider it successfully funded. According
to the way in which the analysis is structured, to find the most precise results possible,
the success rate was represented as continuous variable. This makes our final results not
simple computations of success probability, but they provide a more detailed explanation
of which campaign aspects contributed the most to its success according to their
consistency, in addition to trying to find coherence within different campaigns. Our
outcomes could be finally helpful for funders’ decision making about offers and signal
features campaigns in order to try to succeed.

5.1.2. Dependent variables
The first step to organize the dependent variables is based on variable recognition.
The following question must be solved: Does this variable send a signal to crowdfunders
or does it evidence how the campaign worked during it life?
According to this, the variable in two main clusters are identified as Signal Variables and
Performance Variables.
Signal Variables
This group of variables includes those which need to be fixed by the proposing firms
and are essential for the campaign itself, for example, the minimum target. Some other
variables are computational but could be calculated using ‘essential’ variables and they
give information about the firm and its crowdfunding offer. They are important because
they represent information that can be used by the investors in their decision making, and
for this analysis as well, to better evaluate the decisions taken by the proposers before the
bid launch.
- Business Age: represents how old the proposer firm was at the moment in which the
pitch was published on the platform. It is computed as the difference between the
date of constitution of the firm and the date of campaign’s publication. This variable
is expected to indicate which kind of investors use it to deal with the studied
platforms.
- Minimum Target: is the threshold of the ‘All or nothing’ model of the platform. If
this minimum amount of collected funds would not be reached, not only would the
campaign be declared a failure, but the funders could not take back the amount of
money already invested. The founders use to launch equity crowdfunding campaigns
to finance through risk capital shares as an alternative to traditional financing. In
other words, they are selling to crowdfunders part of their ownership and the
minimum target represents the price associated to that offered equity. As for
financing operations, those funds could be used in many different ways and, for this
reason, one of the most important documents that founders have to produce and
disclose is the financial plan, which includes all the information about how the funds

collected thought the campaign would be used. This financial plan would furtherly
strength the signal effect of this variable, which is already high significant.
- Minimum Pledge: is the minimum fund the crowdinvestors were required to invest
in order to participate in the offer. As funds contribution is associated with equity
shares of the same value, to this extent it is based on the price of the lower valued
equity share offered by the firm proposal’s founders.
- Top share Pledge in other words, the amount of funds investors were required to
contribute in order to obtain one unit of higher valued equity share. They used to
have more patrimonial rights than the ones acquired with a lower investment and, in
some cases, they included voting rights. This investment option is offered in order to
achieve shareholders diversification. In fact, it is usually assumed that whoever bids
more funds in a single campaign would be more interested, more skilled and, for
these reasons, also a better shareholders’ meeting member. This variable could
represent a significant signal for crowd-investors according to the information
cascade theory. In fact, if many of them contribute to the campaign with this amount
of funds, it indicates a sign of high quality.
- Day from first pledge to Minimum Target this variable is the difference between the
day of the first pledge made on the pitch web site and the day the campaign collected
the minimum target. It represents the temporal aspect related to the success of the
campaign, that is, when the offer accomplished its success threshold. According to
its definition, this variable should be considered into the performance ones, but due
to the information cascade theory, it is a relevant signal to crowd-funders. The day
of first pledge was used in the analyzes and not the launch’s day because of problems
with the availability of the latter’s data. The date of the first pledge was very easy to
collect, while the launch date was not always indicated and, sometimes, it was also
reported as consecutive to the first pledge, which is theoretically impossible. Due to
the fact that this variable differentiates campaigns between early and late funded
ones, it would be used as dependent variable in the sub-analysis model relating to
which signals led to these results.

- Percentage amount collected on Minimum Target: these are another performance
variable considered as signal one. They are based on the percentage of total funds
collected with respect to the minimum target. These ratios were studied relative to
different periods of time after the day of first pledge. All the periods studied gave
relatively significant signals as they evidence crowd-funders average behavior
relative to the information cascade theory. According to our hypotheses, the
performance variables relative to the first week and month since the day of first
pledge were selected as a more reliable variable for the complete model.
- Percentage pledge amount on Total Pledgers: these variables represent how fast the
campaign reached its total amount of investors relative to the study of the same
investment periods analyzed for the previous variable. They underlined how many
investors have participated in the campaign during its different life’s periods. These
variables are also representative of an investor’s decision-making behavior point of
view.
- Public investors: this is the percentage of investors who decided to disclose their
information publicly when they invest in the campaigns, usually made up of
sophisticated investors. They are divided in early investors, those who invested in
the first month, and total investors. One of our hypotheses is based on the fact that
this variable is not a reliable signal for success in the Italian market, contrary to
literature theories which are based mainly on markets where there are no
requirements about minimum funds collected from sophisticated crowd-investors for
each online offer.
- Pre-money valuation: this is the evaluation of the proposing company at the moment
of the pitch. It derives generally from balance sheet values, but the methods adopted
to obtain it did not used to be so clear. This evaluation process could be used by the
firms who choose which entrepreneurial finance theory to adopt or through
methodology proposed by the platforms. Its consistency and producing methods have
caused huge disagreement within the financial markets and it also created one of the
main information asymmetry topics. Usually equity crowdfunding proposers’ firms

are Startups and growing ventures, as in the data sample used. The evaluation of
Startups is an important topic in the entrepreneurial finance theory, but this is not the
object of this present research and thesis. According to Nathan Rose, author of the
book Equity Crowdfunding. The complete guide for startups and growing companies
(2016), for opportunistic reasons, the evaluation of the company uses to have a better
outcome in crowdfunding, than that one which could come out of a Venture Capital
evaluation. Proposing firms have to set their evaluation trade off, where higher pre-
money would be a signal of more stability and lower investor risk, while lower value
would show higher growth potential.
- Equity Target: this is the fraction of equity which is offered to crowd-funders
through the online campaign. In other words, it is the percentage of the minimum
target on the firm’s total evaluation. It is not the real amount of equity that the
investors will acquire at the end of the campaign, because that percentage apparently
would be higher due to the fact that successfully closed campaigns collect more funds
that the minimum required ones. This variable highlights the proposers’ equity
retention which is the most important element regarding one of our hypotheses.
Performance variables
During its publishing period the campaign collects pledged funds. Performance
variables are all those related to how the campaigns were funded in relation to signal
variables. During the discussion of the complete analysis, which and how the signal
variables influenced these were also studied.
- Total Pledgers: this is the total amount of crowd-funders who invested in each
successful campaign. Due to the fact that the Mamacrowd campaign’s web sites
reported both investors’ and pledgers’ data, while Crowdfundme included only
investors’ and also that, in the section ‘investment’, both platforms campaign’s web
sites reported the single fund pledges, the definition ‘pledge’ was used instead of
investment. The main difference between the two consists in the fact that the pledges
would turn into effective investments when crowd-funders would make monetary
transactions through the platforms, as pledge confirmation. As the data available

from the platforms’ web sites do not allow us to assess which pledge was confirmed
and which was not, the reported ones are considered as effective investments by the
way calling them pledges to remind the reader with this situation.
- Average Pledge: this is the average between the total pledges collected and the total
amount of crowd-investors that made them. This variable helps in comparing the
successful campaigns better in terms of the average contribution from single
investors. Calculating an average of funds collected would help in understanding the
pledger’s behaviors better. As shown in the previous variables group, every equity
online offer could have a different minimum required contribution, it could be
assumed that this would affect this variable. In addition, we expect that another signal
variable related to this one is the ‘top share pledge’.
- Pitch Length: this represents the duration of the pitch. CrowdfundMe and
Mamacrowd have a standard length proposed of 60 days but each proposer must set
this variable before the online bid’s launch. Due to this reason, this variable should
be classified as signal. However, it is not very common that successful campaigns
respect their expiry day. In fact, only one of the studied campaigns ended according
to platforms fixed length of 60 days, while on average they expire in 82 days (see
Table 5.2). There are no length limits fixed by law, however, it is considered
inappropriate to fix long ones (more than 60 days) or extend them too far. This is
mainly due to the fact that usually campaigns are launched to fulfill specific needs
and collecting more than the necessary could create problems. Usually founders, in
order to maximize their success, extend the expiry date of the pitch. They decide to
do so if their campaign is not fully funded, and they think that with more time it
would be, or if the pitch is already overfunded, but the pace of the investment does
not decrease. In the first case an extension is necessary, while in the second one, a
decision has been made to make a good campaign a greater one. Sometimes
campaigns expire when pledges reach the maximum target fixed by the proposing
firms, but, in this case as well, they could decide to postpone the end.

Table 5.1. Linear regression’s variables summary
Description Expected relation with success
Dependent y
% of overfunding Fund that exceed the 100% - how much successful is the campaign
Signal x
Business Age Difference between constitution date and pitch date Not so relevant Depend on investor risk attitude
Target Min (100%) Minimum investment required to consider the campaign successful Relevant Low value positive signal
Minimum pledge Minimum investment required to invest into the campaign Not so relevant Depend on investor risk attitude and level
Top share Pledge Amount of funds necessary to acquire proposal firm’s top valued share Not so relevant Depend on investor risk attitude and level
Day to Target Day from the first pledge day and the one when 100% is reached Relevant Low value positive signal
1 Week % € on 100% How much money respect to 100% in the first week (from pledge 1) Relevant High value positive signal
1 Week % # on Total # How much pledgers on total # in the first week (from pledge 1) Relevant High value positive signal
1 Month % € on 100% How much money respect to 100% in the first month (from pledge 1) Relevant High value positive signal
1 Month % # on Total # How much pledgers on total # in the first month (from pledge 1) Relevant High value positive signal
Early public investors % early investors (1st
month) with public profiles Not so relevant High value positive signal
Total public investors % investors with public profiles on total investors Not so relevant High value positive signal
Pre-money valuation Monetary evaluation of the firm at the launch day Relevant Depend on investor risk attitude
Equity Target % of the equity representing the Minimum Target Relevant Depend on investor risk attitude
Performance x
Total Pledgers (total #) Total amount of pledgers in term of numbers Relevant Positive correlation
Average Pledge Average between total capital pledges and total # Relevant Positive correlation
Pitch Length Duration of the campaign – difference between end and start date Not so relevant Neutral correlation

5.2. Descriptive statistics
Even before running the linear regression, it is possible to analyze roughly if there are
connections between the variables. This would be possible through extreme values’ study.
For instance, the ‘% of overfunding’ maximum value regards equity shares online offer
launched in 2017 by Graphene X-T, an Innovative startup, which studies and produces
eco-friendly and high-tech products using graphene as a raw material. Its huge success,
in terms of funds collected, was reached during the first day the first investor published
his pledge. In one week from the first pledge to the campaign’s website, they had already
collected 770% over the minimum target from 80% of total investors, and in one month
it achieved the total funds collected, 950% of the target, from the whole campaign’s
investors. These last values are the maximums for their variables as well (see Table 5.2).
In addition, it was noted that high early performances are related to early funded
campaigns. According to mean and median values regarding ‘Day from pledge 1 to
100%’, it can be assumed that early funded campaigns are those which achieve the
success in around 30 days. Furthermore, it can also be assumed that all these variables
have a connection with the dependent variable (y), and this hypothesis may be verified in
the regression outcome analysis.
Hypothesis 4: early high performances are related to early funded campaigns. They
are those funded in around 30 days. Early funded campaigns are related to higher
success rate.
As the literature and the previous data analysis suggest, the market is largely used
by startups and growing ventures and this is highlighted by the mean value of ‘Business
Age’ variable. It can be assumed that its maximum value is a consequence of the Italian
regulations changes which allow SMEs to finance through online crowdfunding
platforms. It could be argued that, in general, there are as many low investments,
‘Minimum pledge’ as there are high investments, ‘Top share pledge'. This could be notice
by the value of ‘Average pledge’ as well. Therefore, on average the public investors
percentage remains stable during the whole duration of the offers and, because of their
low variance, it can be presumed that most observations have the same variable value.
This trend appears to exist for equity retention as well and its value is stable around 94%.
Finally, ‘Pre-money valuation’ values vary a lot among campaigns.

Table 5.2. Variables descriptive statistics before and after two steps transformation
Variable descriptive statistics Transformed variables N(0;1)
Obs. Mean Median Std. Dev. Min Max Obs. Min Max
X
Business Age in Years 122 3.04 2.76 2.6274 0.15 20.09 113 -2.8833 2.4792
Minimum Target 122 160,831 100,000 128,448.2 45,000 650,000 113 -1.7549 2.6745
Minimum Pledge 122 844.7 498.5 2,564.801 100 20,000 113 -1.9236 4.9866
Top Value Share pledge 122 16,841 10,000 17,913.81 100 129,999 113 -3.9694 2.0845
Day from pledge 1 to 100% 122 31.86 28 29.91 1 153 113 -1.8926 1.5649
1 Week % € on 100% 122 0.8085 0.570 0.9931 0 7.70 113 -3.8839 2.2948
1 Week % # on Total # 122 0.2364 0.175 0.19368 0 1.00 113 -3.7326 1.9480
1 Month % € on 100% 122 1.3450 1.085 1.2276 0.03 9.50 113 -4.7146 2.4216
1 Month % # on Total # 122 0.4656 0.430 0.24121 0.02 1.00 113 -4.5399 1.4339
Early public Investors 122 0.6345 0.6700 0.1936 0 1 113 -7.1361 0.6678
Total public Investors 122 0.6240 0.6650 0.1659 0 1 113 -7.3991 0.6894
Pre-money valuation 122 5,169,515 2,350,000 13,983,408 1,000 119,500,000 113 -6.8234 3.3743
Equity Target 122 0.0630 0.0462 0.092129 0.000999 0.998004 113 -5.0216 4.0016
Total Pledgers 122 153.53 106 203.8323 2 2080 113 -4.7232 3.5284
Average Pledge 122 3,845.60 2,621.90 6,651.04 696.90 66,249.50 113 -1.9668 4.6192
Pitch Length in Days 122 81.42 79,5 29.11 13 219 113 -4.2394 2.5546
y
% of overfunding 122 1.5256 1.220 1.376695 0 8.4991 113 -5.9825 1.1626

6. Linear regression model
6.1. Methodology
6.1.1. Data transformation
Table 5.2 reports variables descriptive statistics before and after transformation. The
observed data are raw and the outcomes coming out of the OLS regression would not be
reliable, so they need to be transformed. First of all, some data are described as percentage
while others are integers. According to the values whereby they are defined, all variables
present range of numbers really high and wide differences. For example, ‘Pre-Money
valuation’ is reported in millions of euros and its standard deviation, about 13.9 million,
highlight huge differences within itself. Furthermore, ‘Business Age’ is listed in years,
with range of values between 0 and 20.09 and standard deviation equal to 2.6. Another
time variable ‘Day from pledge 1 to 100%’, is defined in days and it includes values from
1 to 153 with standard deviation around 30. One of the fundamental assumptions of linear
regression models, is the fact that the dependent variable (y) have to be normally
distributed. Then, we study the distribution of y using .R software, which is the
computational tool used over the whole thesis. Firstly, the distribution of y is plotted with
histograms, boxplot and normal distribution plots, that will show if our hypothesis of
normality is accepted or rejected. In both latter cases, plots structures would roughly
evidence the reasons why we would assume that answer.
Plot 1. Normal distribution analysis ylog

Equity crowdfunding in italy campaign success factors analisys manuel cristofaro

Equity crowdfunding in italy campaign success factors analisys manuel cristofaro

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