Crowdfunding Success and Capital
Structure Considerations
Abstract
The present paper builds a model characterizing the success rate of
online crowdfunding ventures dependent on a number of product,
campaign and platform specific parameters. In 70% of cases the model
is able to predict whether a reward -based crowdfunding campaign will
be able to reach its goal before the campaign has been launched.
Subsequently the paper makes propositions about the optimal
financing choice of entrepreneurs selecting among a variety of
financing options such as crowdfunding, bank loans, bonds and equity,
in the presence of various levels of taxation and transaction costs, by
extending the Modigliani–Miller framework to include crowdfunding .
Keywords: crowdfunding, entrepreneur finance, capital structure
1 Introduction
Crowdfunding is a method of financing non -profit and business
endeavors that has a lot in common with micro -finance and
crowdsourcing. It gives entrepreneurs the ability to request
investments from a large number of individuals usually in exchange
for interest payments, equity or the delivery of a product or reward at
a future date. This is often done through an online platform that grants
the creator of the crowdfunding campaign the ability to specify the
amount of capital he is seeking and the period of the campaign as well
as any information about the firm or product that he/she wishes to
present to potential investors.
1.1 Definitions
Giving a clear definition to crowdfunding is somewhat challenging as
this emerging field of finance takes several forms. The oldest and
most developed option is debt crowdfunding or peer -to-peer lending
which matches lenders directly with borrowers. Another o ption is
equity crowdfunding in which investors receive shares of the projects
they support. The present paper focuses on the reward -based form of
crowdfunding which offers investors the chan ce to buy a product or
receive a reward that will be delivered in the future.
Reward-based crowdfunding can be regarded as an over the counter
forward contract between the campaign creator and the buyer or a
constrained pre-order agreement. Only the prevalent in practice all -ornothing scheme of reward-based crowdfunding is considered. It
restricts the usage of the funds gathered through crowdfunding by
considering all projects that did not manage to reach their financing
goal in the period that they have set for the campaign as failed and
returning all investments. Nei ther the campaign creator nor investors
face any charges in case of failure. If the project succeeds a portion of
the gathered capital – usually less than 5% – is taken by the platform,
the rest is immediately transferred to the project creator.
1.2 Crowdfunding Research Motivation
Reward-based crowdfunding is a novel approach to financing and it
has some considerable weaknesses when compared with traditional
finance. They include lacking or ineffective legislation, poor fraud
control, reputation damages in case of a failed campaign, and lack of
public information. However, the field is worth examining due to a
number of factors which according to the phenomenal growth of
crowdfunding in recent years heavily outweigh the disadvantages .
Firstly, the unique opportunity for diversification that crowdfunding
provides is a crucial matching mechanism between consumers and
producers. The spread out campaign risk allocated among a large
number of buyers whose investments are similar in size allows the
successful development of projects which would have been rejected by
banks and venture capitalists.
Moreover, the uncommon characteristics of the crowdfunding
financing method allow for a lot of flexibility for both investors and
project creators. It assists the producer in adapting to the underlying
market demand at the early stages of production and acts as a market
testing mechanism more representative than a general market survey.
Additionally the all-or-nothing rule of crowdfunding enforced by the
minimum funding threshold is a market demand guarantee to the
producer and serves as a final demand check before the producer
enters the market. The active participation of consumers allows
producers to pursue only those product features which are in demand
and ultimately enables funders to shape the final product.
Year
Crowdfunding volume
in billion USD.
2009 2010 2011 2012 2013 2014
0.53
0.85
1.47
2.81
6.12
2015
16.23 34.4
Lastly, the rapid growth that crowdfunding has experienced in recent
years certainly cannot be ignored. The total yearly funding volume of
crowdfunding has expanded 13 times from 2012 to 2015 reaching over
$34 billion. A 2013 report of The World Bank predicts that
crowdfunding campaigns will reach $50 billion in China alone by
2025, and so far the actual results have surpassed this prediction. The
industry is projected to surpass venture capital investments as early as
2018 and to have raised more than $1 trillion by 2025.
1.3 Characteristics of Projects
The goals set by crowdfunding campaign creators vary greatly in size.
A large number of local projects seek small amounts of capital such as
cultural events that do not generate revenue, restaurants or other small
businesses. These campaigns usually have capital goals of less than
$3000 and are financed predominantly by regional investors. However,
there is an increasing interest from entrepreneurs looking for an
alternative of venture capitalists and traditional finance. T he control,
flexibility and speed that crowdfunding provides to entrepreneurs and
investors has resulted in a substantial number of large ventures like
the first commercially available 3D printer, the first virtual reality set,
several music albums, movies, and TV shows.
Financing ventures is not the only thing that businesses use
crowdfunding for. Platforms can be utilized to demonstrate consumer
demand like in the case of Pebble the first smart watch which was
initially rejected by venture capitalists. After qu ickly reaching and
even surpassing its funding goal on the crowdfunding platform
Kickstarter the product managed to attract a large amount of VC
capital. Unsuccessful campaigns give their creators reliable
information about the demand for their product at a very low cost.
Furthermore, crowdfunding is sometimes used for marketing purposes
in the early stages of product development. It allowed the creators of
the Ouya video game platform to attract the attention of game
developers before the product was relea sed and the success of the
campaign generated a lot of media coverage.
1.4 Characteristics of Investors
The motivations of buyers are just as diverse as the types of projects
seeking funding. It heavily depends on the platform that facilitates the
crowdfunding ventures. Platforms similar to Kickstarter or Indiegogo
allow project supporters to choose from one or more project rewards at
a different price – both the reward and the price are decided by the
project creator. Other platforms allow investors to become more
involved with the company or the product by using a crowdsourcing
approach – instead of or in addition to rewards contributors receive
the ability to change the product to their liking. Several online
platforms like Patreon focus on artistic creators and are built
exclusively on the donation model – the supporters of the campaign
receive either a small gift or nothing other than personal satisfaction
and warm-glow.
1.6 Literature Review
There has been little published peer-reviewed work to date on the
topic of crowdfunding. Schwienbacher and Larralde (2010) published
one of the first studies of crowdfunding, which included an analysis of
a French startup in the entertainment industry utilizing crowdfunding
techniques. There have been attempts to build a theoretical model of
when individuals would choose to crowdfund (Belleflamme et al.,
2012). However, the few recent studies on the topic, all in working
paper form, have tended to focus on the role of backers and investors
in crowdfunding. Kuppuswamy and Bayus (2013) examine how backer
support on Kickstarter varies depending on project success and timing.
Agrawal et al. (2010) used a market of musicians seeking
crowdfunding to understand whether crowdfunding relaxes geographic
constraints on fundraising that are typical of venture capital firms.
Finally, Burtch et al. (2011) examined how timing and exposure
affected 100 pitches for new journalism stories.
All these working papers offer valuable contributions, but no work to
date has provided a large-scale understanding of the empirical
dynamics of crowdfunding across a wide variety of projects, and they
have focused on backers, not on the project founders themselves.
Specifically, since crowdfunding is novel and potentially disruptive to
traditional approaches to funding, there are three research areas that
should be of interest to entrepreneurship scholars. First, it is important
to understand whether crowdfunding successes and failures are driven
by the same underlying dynamic as other forms of entrepreneurial
investment – that is, does the crowd fund projects that signal potential
quality, or is some other selection system at work? Second, since a
distinct feature of crowdfunding compared to other funding methods is
the removal of geographic limitations (Agrawal et al., 2010; Stuart
and Sorenson, 2003a), it is important to understand what role,
geography continues to play in new ventures in a crowdfunding
regime. Finally, it is critical to understand if crowdfunding “works”
do crowdfunded projects actually deliver results? In the next part of
this paper, I will attempt to introduce data into the discussion of these
three areas
1.7 Research Goals
Although crowdfunding receives a lot of media coverage there is a
lack of research and adequate regulation focusing on subject. This is
especially true when discussing the reward based form of
crowdfunding which unlike debt and equity based crowdfunding
cannot benefit from existing government policies. In many countries
contributions to reward-based crowdfunding campaigns are regarded
as donations and project creators ar e not held responsible for their
actions after their campaign has been successfully funded.
The lack of information is damaging for all parties involved as
entrepreneurs have to resort to less efficient financing opportunities
and contributors are left unaware of the dangers of crowdfunding
campaigns.
This paper builds upon existing financial theory and through adapting
existing research offers some insights to regulators and entrepreneurs
seeking finance into the opportunities that crowdfunding has to offe r.
2. Dataset Description
The data used in the development and analysis of the model that this
paper build was gathered from 4 global online crowdfunding
platforms, namely Kickstarter, Indiegogo, Rockethub and Fundrazer.
Platform
Kickstarter
Indiegogo
FundRazer
RocketHub
Date Range
05/2009-12/2016
04/2010-12/2016
10/2011-12/2016
04/2010-12/2016
Total Number Of Projects
422,392
247,820
114,952
45,640
The data features information about both successful and failed
projects. Each campaign is represented by a time series of 1000
observations taken at equal intervals depending on the duration of the
campaign. Additionally campaign information such as category,
location, description, currency, currency rate at the time and data
about the campaign creator is available. Contributions are
characterized by time, amount, currency, location and the registration
date of the platform user.
2.1 Campaign Data Relationships
Campaign characteristics of all Kickstarter projects were analyzed and
compared to determine their impact on project success. The following
variables were used in the regression:
i.
ii.
iii.
iv.
Project goal: The amount founders seek to raise using
crowdfunding.
Funding level: The percentage of a project's goal that is actually
raised by founders. Projects that raise at least their goal are
considered successful or funded projects, and they are paid the
total pledged to them by the crowdfunding site. Projects can
raise more than their goal, these projects are overfunded.
Backers: The number of funders supporting the project.
Facebook friends of founders (FBF) : Since many accounts in
Kickstarter are linked to Facebook, it is possible to determine
how many Facebook connections each founder has. Due to data
collection limitations, FBF is recorded as o f the time of data
v.
vi.
vii.
viii.
collection, rather than at the time of project initiation, which
suggests that project success may lead to increases in FBF.
Category: Projects are categorized by Kickstarter into one of 15
categories.
Updates: Founders are encouraged to post information, called
updates, about their projects during and after the fundraising
period. Updates represent efforts by founders to reach out to
current and potential funders, and to inform interested backers
about developments in a project.
Comments: Funders and potential funders can post comments
about projects. The data on comments includes details on the
number and timing of these postings.
Duration: The number of days for which a project accepts
funding. Although Kickstarter initially allowed projects to raise
funds for as many as 90 days, it now limits this time to 60 days,
but encourages 30 day funding windows.
The examination of campaign variables suggests that the leading
positive factors for success are the number of campaign updates, the
average contribution (pledge/backer). The leading negative factors for
successful projects are duration & goal.
This initial analysis suggests that on average successful projects had a
goal twice smaller than the mean . Additionally project creators were
twice as active in terms of campaign updates and comments. There
seems to be a big difference in the levels of activity of campaign
creators between categories with design and technology projects
performing well above the mean . The mean goal and contribution
(pledge/backer) also varies heavily with categories featuring higher
campaign goals receiving larger contributions. Ultimately, campaign
category seems to be an important success factor.
2.2 Location and Personal Connections Statistics
The success of traditional startups is often highly influenced by their
location due to positive externalities such as spillovers from
successful projects, industrial clustering and lower hiring costs. In
previous examinations crowdfunding ha s been found to lessen the
extent to which location dictates project success, however an analysis
of campaign location proves that it is an important factor.
The distribution of projects is uneven when compared to local
population. Some regions have a disp roportionate number of projects
in a specific category like Nashvile which has a high concentration of
successful music campaigns, Los Angelis which is dominated by film
and San Francisco which leads the technology and videogame
categories.
Local and distant investors are different. Local investors are more
likely to invest before the ratio of capital gathered over capital
threshold reaches 30% rather than later. In contrast, distant investors
contribute more heavily at the later stages of th e campaign when more
than 30% of the required capital is collected.
Additionally, although the total contribution of local investors towards
successful projects is much smaller than that of distant investors their
average investment is up to 4 times bigg er. There exists a clear
relationship between distance likelihood to invest and mean
investment.
This makes sense for projects aimed only at the local community,
however, the same is true for online products made available to the
whole world. This is perhaps due to friend and family connections
which are more likely to develop locally. Data from a survey
performed by the crowdfunding platform Kickstarter asked campaign
contributors about the reasons why they supported the project
immediately after they made a contribution. The results show that
friends and family are more likely to contribute at the start of the
campaign, moreover the share of the contributions of friends and
family falls as the campaign approaches its goal.
Moreover an abnormal percent of the contributions towards
unsuccessfully funded campaigns was from friends and family
members when compared to fully funded projects.
It is unclear whether both distance and personal connections are
factors weighted by contributors before they support a crowdfunding
campaign. Even if distance has no direct relationship on the likelihood
of a contribution to the campaign it seems to be a good predictor of
early investments.
2.3 The Likelihood to Invest Increases As Total Funds Raised Increase
Data collected from several crowdfunding platforms suggests that as
the share of capital collected over the target capital threshold
increases the rate at which new contributions are made also increases.
This becomes evident from the table below which sho ws the final
share of capital collected over the threshold for a large number of
campaigns with varying sectors and campaign thresholds.
Funds raised / K
Campaigns Percent
of Total
0% –
20%
55%
20% –
40%
6%
41% –
60%
2.5%
61% –
80%
0.9%
81% –
99%
0.05%
100%
36%
The data shows that disproportionately large share of the projects are
either successfully funded and reach at least 100% of their goal, or a
relatively small portion of the total threshold is achieved. Looking
even further into the initial 20% supports these observations.
Funds raised / K
Campaigns Percent of
Total
0% –
4%
62%
4% – 8% 8% –
12%
24%
9%
12% –
16%
3%
16% – 20%
2%
Projects that fail do so by large margins and those who succeed end up
with a little over 100% although the funders are able to contribute as
long as the campaign period has not finished.
2.4 Buyers Are Not Risk Neutral
Investors are well aware that not all crowdfunding campaigns succeed
and according to questionnaires filled by buyers they take a number of
campaign characteristics into account before contributing. Attributes
such as team size and experience, the feasibility of the product, its
current development stage and the time to completion are some of the
important qualities which buyers watch for. Unsurprisingly these are
to a large extent the characteristics which venture capitalists co nsider
when discounting their expected future returns. The table below shows
the average discount factor as a function of the stage of development
of the product.
Seed
80-100%
Angel
50-70%
Series A
40-60%
Series B
30-50%
Bridge
25-35%
Crowdfunding platforms often encourage campaign creators to utilize
these quality signals when creating new campaigns. For example
Kicksarter heavily promotes the use of videos in addition to project
description. Similarly, regular project updates and prom pt response to
user comments are another signal of quality. On the other side as saw
in the regression contributors are wary of campaigns with too
ambitious goals as this decreases the likelihood that the campaign will
be successful and although funders wi ll receive their money back
they’ll have to wait until the end of the campaign. The negate effect of
unusually long project durations can be explained in a similar fashion
– long campaign periods make investors wait for more for their reward
in case of success, or their money in case of failure.
3 Model
Combining the observation from the crowdfunding data we build a
model predicts the success rate of crowdfunding campaigns during any
stage of their development. The three major effects that we observed –
the increased likelihood of local investors to contr ibute early on, the
abnormal concentration of projects near the 0% and 100% financing
levels and the risk aversion of investors – are modelled separately and
combined in a unifying model.
3.1 Model Variables
i.
ii.
iii.
iv.
v.
vi.
vii.
viii.
ix.
x.
xi.
xii.
Campaign goal:
– the goal of each campaign is determined by
the project creator and cannot be changed after the start of the
campaign.
Current financing level:
– the amount of investment received
in this and all previous periods.
Contribution: – individual contribution to the campaign
Campaign duration: – the number of days after which the
campaign is either successful of failed.
Interest rate:
Reward waiting period: – the number of days that campaign
supporters will have to wait until they receive their reward.
Investor endowment: – a large number of small investments
are characteristic of crowdfunding campaigns. Each potential
contributor is endowed a different amount depending on the
mean income in the region.
Distance: – the distance between the campaign creator and the
potential contributor.
Nation: – a boolean variable that shows when the campaign
creator and the potential investor live in the same country.
Contribution threshold: – the minimum financing percentage
that a project must reach before a potential contributor cons iders
supporting it.
Campaign credibility: – dependent on category and creator
activity
Number of potential contributors:
xiii.
Project views: – the number of potential contributors that have
visited the campaign page
3.2 Initial investment propensity
According to the data on local investments a disproportional share of
them was done during the early stages of the project they supported.
Consumers are characterized by their individual endowment which
they allocate between consumption and contributions to the
crowdfunding campaign. Taking the initial location of the campaign
and their own location as given consumers maximize their utility
function with respect to how much they are willing to contribute to the
project.
Assumptions:
i.
ii.
iii.
Individuals are risk neutral
Individuals have perfect information about all active campaigns
from the moment of their launch
Individuals value current consumption, future consumption
dependent on their contribution to the campaign, the success of
local campaigns and the success of campaigns from their own
country
The endowment of each individual in the current period is distributed
as follows:
According to our assumptions the utility function of each individual
should look like this:
which can be simplified to
Taking the first order condition with respect to current contributions
and simplifying we end up with the following function for individual
and aggregate contributions for the current period:
3.3 Crowd investment propensity
The data suggests that the rate of contribution increases as campaigns
reach higher financing levels but few campaigns achieve levels that
are much higher than their initial goal. This can be attributed to the
crowd/herding behavior exhibited on crowdfundi ng platforms. To
model it we will use the notion of personal participation thresholds
developed by Granovetter to explain the participation in social events.
Granovetter assumes that participation is fully determined by the
decisions of other agents and th e individual participation threshold of
each agent.
Participation in the following period will occur only if current
participation surpasses the personal threshold of the individual.
The initial participation
is exogenous to the model. By treating time
as a discrete variable the model predicts that the participation in the
next period will be determined by the participation function and its
inputs the participation at the end of the current period and each
agent’s threshold.
An obvious limitation of the model is the initial participation.
Building upon the model proposed by Granovetter we define as the
minimum requirement of each potential investor who is willing to
invest only if the ratio of total funds rai sed and the minimum capital
requirement of the campaign surpass his investment threshold.
Assumptions:
i.
ii.
Individuals are risk neutral
Individuals have perfect information about all active campaigns
from the moment of their launch
iii.
iv.
Contributions are solely determined by crowd behavior. No
campaign characteristics are taken into account other than the
current level of contributions in relation to the financing target.
The participation thresholds of all individuals are normally
distributed
We end up with the following for the individual willingness to invest,
with being the mean and the deviation of all consumer thresholds
.
3.4 Discounting for risk
As data from the observed crowdfunding campaigns suggests investors
are wary of risk. They put a negative weight on project goal and
duration, the expected waiting period until they receive their reward,
and project risk factors such as low creator activit y.
Furthermore, even though contributors receive their money back in
case the project is not successful the value of the sum they receive
will decrease in case of inflation.
Assumptions:
i.
The decisions of individuals is affected by the interest rate,
campaign goal, duration, campaign quality and the time which
supporters will have to wait until they receive their rewards
The discount rate
of each individual can be represented by:
3.5 Traffic Increases Contributions
As the number of views that the campa ign receives increases
investments also increase. Thus increases in the ratio of views in the
current period over total potential investors correlate with higher
success rates.
3.6 Final Model
Combining all of these characteristics in one model we build a model
on the following assumptions:
i.
ii.
iii.
iv.
Individuals do not have perfect information about currently
active campaigns. Project views correlate with the number of
investments
Local investors are more likely to contribute at the early stages
of a project. Their contributions are larger than those of distant
investors.
Investors are more likely to contribute to projects that have
already seen support by others, thus exhibiting herd mentality
Investors are risk averse. They weight campaign risk factors such
as duration, goal and quality before they invest.
This leaves us with the following model for total investments in the
current period:
Total contributions at the end of the campaign can be computed as
follows:
4 Model Predictions
In order to configure model parameters 60% of the data was used as
training set 20% for validation and 20% for testing.
The model has only been tested at project launch before any
contributions have been made. It achieves 70% success rate in
predicting the outcome of the campaign.
5 Capital Structure Considerations
According to the Modigliani–Miller theorem under certain restrictions
capital structure is irrelevant to firm value. These restrictions are
quite unrealistic but they help us understand what factors make some
financing decisions better than others.
Modigliani–Miller assumptions:
i.
ii.
iii.
iv.
v.
there are no taxes
there are no bankruptcy costs
there are no agency or transaction costs
there is no information asymmetry
debt has no effect on the cost of capital before taxes
The Modigliani-Miller framework encompasses debt and equity
financing. Rewards-based crowdfunding does not fit, however on a
second look it involves varying levels of rewards that correspond to
pledge amounts delivered to the investors at a later date determined by
the creator of crowdfunding campaign. At the moment when the
investor contributes to the crowdfunding campaign , he enters a
contract with the entrepreneur to receive a good or service at a later
date. Therefore, we can regard financing through reward based
crowdfunding as a case of a forward contract traded over the counter.
The campaign creator designs the forward contract, taking the
creditworthiness of the issuer as given and optimizing for its maturity
date and yield in order to reach the minimum funding threshold . These
factors are taken into account by investor s in the crowdfunding
financing model and lead to a single equilibrium which determines the
number of contracts between the campaign creator and investors.
5.1 The presence of taxes
Taxation in most countries favors debt financing by taxing it at a
lower rate. Thus firms financed by debt enjoy a lower cost of capital
in comparison to those financed through equity.
Reward-based crowdfunding is taxed very differently around the
globe. It usually is subject to income taxes which makes it relatively
less favorable in comparison with debt and equity financing.
[table comparing tax rates]
5.2 The presence of bankruptcy costs
As the share of debt to equity in the capital structure of a firm
increases the bankruptcy costs that it faces also rise. Therefore there
is an optimal combination of debt and equity or debt and
crowdfunding for each firm.
[expand]
5.3 The presence of transaction costs
This is one of the main advantages of crowdfunding as it provides
financing with almost no fixed costs. However, the variable costs are
considerable as major crowdfunding platforms take anywhere from 3
to 8 percent of the gathered capital in the form of fees.
[compare with debt under different interest rates]
[compare fixed costs of issuing debt]