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Theoretical framework
The analysis starts from the theoretical studies among the explanation of the “struggle of survival”
by Charles Darwin in 1859, between newborn and older firms. Darwin structural approach was to
consider the process of variation of the genotype, selection of the associated phenotype and
retention of the underlying genotype for understanding, over the long term, the evolution (in term of
birth and death rates) of organizational populations. Starting from Darwinian legacy, numbers of
scholars tried to construct biological theories for firms.
In 1965 Arthur Stinchcombe’s debate about the “liability of newness” played an important role in
management studies. The liability of newness predicts that firms at the very beginning of their life
cycle are very likely to be selected out by the environment. This means that start-up’s failure rates
are high in the first years of its organizational life. Stinchcombe identified a number of internal and
external drivers among the explanation of the struggle of survival of the newborn organizations.
The most important factor is that creating a new organization generally involves creating new roles,
which have to be learned and also have high costs in time, conflict and temporary inefficiency.
Moreover, relations of trust are much more precarious in start-ups than in older organizations. The
mortality rate drops with time, when the firm “learns”, how to operate. If the new-born firms are
able to successfully face all these problems they might survive, but the rate of early mortality is still
very high.
Although there are numbers of different interpretations of the Darwinian “struggle of survival”
theory and many integrations to the liability of newness, to date 64% of the works among this
matter support Stinchcombe’s propositions: new-born firms die young. Which means that nowadays
the debate isn’t any more on the validity of his theory but the scholars’ focus is directed to the
factors that can be determinant in contrasting early death. This newer perspective has been focusing
on discovering what firm-specific or environmentally related factors can counteract the age effects
themselves. In this view, numbers of scholars have demonstrated the existence of different factors
that strongly influence the way in which the early evolution of the new-born firm is shaped.
We have analysed the Kickstarter crowdfunding platform as a possible external factor that can help
start-ups to countervail the liability of newness. We started from the Pfeffer and Salancik (Pfeffer
and Salancik, 1978) consideration about the importance to face the environmental uncertainty
through “reductioning” or “restructuring” the dependence from resources and to achieve these goals
through specific strategic actions. Crowdfunding platforms as Kickstarter can be seen as a new way
to support start-ups in the first troubled years of their life by giving them not only tangibles sources
(i.e., money) but also intangible capabilities like massive exposure on the internet. As Lambert and
Schwienbacher (2010, 6) define: “crowdfunding involves an open call, essentially through the
Internet, for the provision of financial resources either in form of donation or in exchange for some
form of reward and/or voting rights in order to support initiatives for specific purposes.” In simpler
words, crowdfunding means that a project or a venture is financed by a group of individuals (a
“crowd”), not by a professional source (e.g., a venture capitalist or a bank). But the influence of
crowdfunding on a company should not be considered only from the financial perspective. This
type of fundraising has also other purposes such as marketing, promoting and testing the company's
product(s), gaining better knowledge regarding customers' preferences or development of ideas.
Thus, crowdfunding can be treated as a promotion tool, a way to get to know the consumers, a basis
for mass customization and so on (Belleflamme et al. 2011, 25–26.).
Already using a crowd as a helping force has a positive impact on a company. First of all, according
to Kleemann et al. (2008), it enables a cost-reduction as users create a value for the company while
taking part in designing and improving the product. Also the product’s development time is shorter
and the costs are reduced (Larralde & Schwienbacher 2010, 6.). Moreover, a “crowd” may be more
efficient than individuals in solving problems bothering the company. Finally, Belleflamme et al.
(2011, 3) accentuates that by using crowdfunding a company offers to some of its customers an
enhanced experience. A crowdfunder can understand better the features and the quality of the
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product by following the project on a platform and through the interactions with other investors.
The flow of information of the line “organization – customers” is improved. Customers gain also a
better perception of the product’s newness. Customer acceptance is enhanced as investors
participate in the development of the product (Larralde & Schwienbacher 2010, 6.). Additionally, a
crowdfunder who receives part of the profit from the venture may want to promote the product.
Case Introduction
KICKSTARTER: The science of crowdfunding
Kickstarter is a new way to fund creative projects. It’s a starting point for everything from films,
games and music, to art, design, and technology. This independent company of 71 people is based
in Greenpoint, Brooklyn. Kickstarter is full of projects of different sizes, that are brought to life
through the direct support of people. Since the launch in 2009, 5.5 million people have pledged
$938 million, funding 54,000
creative projects. Kickstarter is one
of a number of crowdfunding
platforms, which give project leaders
an option on how to raise the needed
money. Project creators choose a
deadline and a minimum funding
goal; if the goal is not met by the
deadline, no funds are collected, a
provision point mechanism.
Kickstarter collects a 5% fee from a
project’s funding total only if a
project is successfully funded. Unlike
many forums for fundraising or
investment, Kickstarter claims no ownership over the projects and the work they host. The website
keeps online all the launched projects.
Kickstarter’s mission is to help bring creative projects to life: “We believe that creative projects
make for a better world, and we’re thrilled to help support new ones. Building a community of
backers around an idea is an amazing way to make something new”.
Each project is independently created. The filmmakers, musicians, artists, and designers on
Kickstarter have complete control over and responsibility for their projects. Kickstarter is a platform
and a resource; there is no involvement of the website in the development of the projects
themselves. Anyone can launch a project on Kickstarter as long as it meets the guidelines.
Project creators set a funding goal and deadline. If people like a project, they can pledge money to
support it. Funding on Kickstarter is all-or-nothing — projects must reach their funding goals to
receive any money. All-or-nothing funding might seem as a waste of time, but it has worked
extremely well in obtaining the public’s attention and in advertising the projects. To date, 44% of
projects have reached their funding goals.
“There’s just something magical about Kickstarter... You immediately feel like you’re part of a
larger club of art-supporting fanatics.” — Amanda Palmer, who rallied 25,000 backers to support
her album, book, and tour.
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Creators keep 100% ownership of their work. Backers are supporting projects to help them come to
life, not to profit financially. Instead, project creators offer rewards to thank backers for their
support. Backers of an effort to make a book or film, for example, often get a copy of the finished
work. A bigger pledge to a film project might get one into the premiere — or to a private screening
of the movie. For example, one artist raised funds to create a wall installation, then gave pieces of it
to her backers when the exhibit ended.
PRESENTING THE RESEARCH
1. Objective and Methodology
1.1 Objective
The objective of the research is to study all the data recorder in order to define an index that is
suitable to remarkably differentiate the survived firms by the failed ones: An index that may be used
to forecast firms’ odds of survival, when funded through a crowdfunding platform.
1.2 Sampling Method
All the firms took in consideration in the research are firms that overcame the minimum goal set for
the funds needed to launch the project. It means that all the firms got the funds, produced the
product and sent it to the backers. So all the firms achieved at least the 100% of the required funds.
We decided to set two criterions: both criterions singularly are sufficient but not necessary to label
as “survived” the firm born by a fundraising campaign on Kickstarter:
Is the original product still available on the market? If it is, we can be sure that the firm is
succeeding in selling the crowdfunded product.
Are there other products produced by the firm available on the market? Even if the original
product is no-longer on the market, the firm may have succeeded in extending its life-cycle
by changing its product.
Due to the impossibility to know if the co-founders of a project launched on the platform wanted to
originally create a firm, and in order to respect a prudence principle, we decided to assume the
following axioms:
All the projects that actually evolved to a survived firm were supposed to evolve in a real
firm. And those would be defined as “survived”.
We will assume that all the projects that are not a firm, were supposed to become one. In
this way the final proportions will be as prudent as possible.
In order to study if crowdfunding, and Kickstarter in particular, can actually provide a valuable set
of assets to start-ups, we started a statistical analysis following the following rules:
All the projects selected were randomly picked up between the 1st and the 20th of January.
All the projects selected were picked up in the following fields: Fashion, Product Design,
Food, Video Games, Tabletop Games and Hardware.
We selected only projects that could become a product firm (no services, music CDs,
theatrical performances etc.).
Only projects that ended between 2010 and 2011 were taken in consideration: In this way
the firms born by the funded projects would have already passed at least their second year of
existence.
All the projects selected can be reorganized as follows:
Requested Funds (R.F.)
o The first 10 projects asked from 500$ to 3.500$;
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o The next ten projects asked from 3.501$ to 10.000$;
o The last group, raised asked from10.001$ to 55.000$.
Obtained Funds (O.F.)
o The first 10 projects raised from 1.500$ to 7.600$;
o The next ten projects raised from 7.601$ to 20.500$;
o The last group, raised from 20.501$ to 350.000$.
% of funds asked and funds raised. (%)
o The first 10 projects raised between 101% and 115% of the required funds;
o The next ten projects raised between 115% and 315% of the required funds;
o The last group, raised between 315% and 14600% of the required funds.
Number of backers (N.B.)
o The number of backers for the first 10 projects is between 170 and 1.100;
o The number of backers of the next ten projects is between 1.100 and 2.450;
o The number of backers for the last group is between 2.450 and 21.100.
The projects are distributed among the different product categories as follows:
The distribution of the firms among the two years’ time span is:
o 2010: 15 projects
o 2011: 15 projects
2. First Approach: looking at requested funds
2.1 Method & Clusters
When bringing business ideas on a crowdfunding platform like Kickstarter, firms, start-ups or
single entrepreneurs must preliminarily set a precise and quantitative goal. An effective evaluation
of the budget is by far the most important step for any business to take off, independently from the
way it is going to be funded. Acknowledging this relevance, we decided to start considering our
sample basing on the amount of money that, according to the minds behind each single project, was
necessary in order to start the production. Before exploring the clusters, we need to specify that in
case this achievement was not satisfied, the Kickstarter campaign fails, backers are not charged, and
no further actions are made available on the platform.
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During this approach, our sample of thirty
elements is split in three clusters of funding
goals divided as such: Cluster A: 500-3.500$,
Cluster B: 3.501-12.000$, Cluster C: 12.001-
55.000$. Each cluster consists of ten elements
belonging to different product categories1
.
2.2 Survival Rate
According to the parameters explained before,
we observe that:
- 60% of entities survived among Cluster A:
3 of 3 entities survived in Hardware category (100%), 2 of 4 in Board Games (50%), 1 of 2 in Food
(50%). No other entities survived in the other categories.
- 40% of entities survived among Cluster B: 2 of 5 entities survived in the Design category
(40%), 1 of 2 Food (50%). No other entities survived in the other categories.
- 30% of entities survived among Cluster C: 2 of 4 entities survived in the Design category
(50%), 1 of 3 in Hardware (33%). No other entities survived in the other categories.
2.3 Observations
One first assumption that stands out from the data mentioned above is that smaller projects (Cluster
A) have the highest survival rate, while most ambitious ones are likely to perish in the short term.
Another observation about the categories taken in consideration, is that Hardware and Design
projects seem to be the most expensive to fund, while the Food and Board Games ones range from
mid to low production costs.
The final consideration we should do is about the entities who did not survive in the short-term: it is
possible that some of them failed to face the market and start mass production simply because they
misjudged in setting their goal.
3. Second Approach: measuring total raised funds
3.1 Method & Clusters
Even after a project successfully reaches the funding goal, if the Kickstarter campaign time is not
expired it is possible for the producers to raise more money. How this additional money is managed
is completely up to the firm. Many of them, in order to encourage people who did not fund their
project to participate or backers who have already pledged a certain amount of money to increase
their pledge, set customized advanced goals that, once reached, could unlock previously, not
expected, features of the product and services available for every backer (independently from the
pledged amount).
1
In all the tables the orange coloured projects have survived, while the purple coloured ones haven’t.
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As explained, this kind of survey becomes relevant if we think that there are no limits to funds and
backers for a single project and even cheaper products can potentially raise a huge amount of
money turning the tables previously shown over. This raw observation will be extremely important
when we will attempt to calculate the success of each single campaign in the following chapter.
On the base of what we did for the previous
approach, we split our sample of thirty
elements in three clusters depending on the
total of raised funds divided as such: Cluster
D: 1.500-7.600$, Cluster E: 7.600-20.500$,
Cluster F: 20.500-350.000$. Each cluster
consists of ten elements belonging to different
product categories.
3.2 Survival Rate
According to the parameters explained before, we observe that:
- 80% of entities survived among Cluster D: 3 of 3 entities survived in Hardware category
(100%), 2 of 3 in Food (66%), 1 of 2 in Fashion (50%), 1 of 1 in Board Games (100%), 1 of 1 in
Design (100%).
- 10% of entities survived among Cluster E: 1 of 4 entities survived in the Design category
(25%). No other entities survived in the other categories.
- 30% of entities survived among Cluster F: 2 of 4 entities survived in the Design category
(50%), 1 of 4 in Hardware (25%). No other entities survived in the other categories.
3.3 Observations
The survival rate seems somehow to confirm what we have seen in the previous paragraph: the
higher the costs of the project, the lower the chances to survive for the entities. That’s because the
amount of funds received, as one of the basic assumptions of this research, is always higher than the
funding goal. But, at this stage, the only relevant thing we can add, deducing it from the data, is that
entities seem to suffer the higher responsibility deriving from managing high amounts of money.
Products in Hardware and Design categories seem to attract more money than the ones in Food.
4. Third Approach: evaluating the success
4.1 Method & Clusters
This approach could be considered a natural continuation of the two previous ones. While looking
for the funding goal in the first step, and then moving our attention to total raised funds we are now
trying to measure the success of each campaign. Although this “success” does not apply necessary
to firm’s actual possibilities to overcome the liability of newness, it could be a good starting point.
Of course, the success of the fund raising campaign may depend on various elements such as the
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product itself, the promotional effort of the producer outside the Kickstarter website and the
category to which the project belongs to.
This time we calculated the percentage of
money raised (see Clusters D, E, F) dividing
by the minimum sum requested in order to
start producing (see Clusters A, B, C). Our
sample is hereby partitioned in three more
clusters containing ten elements each:
projects funded between Cluster G: 101%
and 115%, Cluster H: 116% and 315%,
Cluster I: 316% and 1460%.
4.2 Survival Rate
According to the parameters explained before, we observe that:
- 30% of entities survived among Cluster G: 1 on 3 entities survived in Design category (33%), 1
on 4 in Food (25%) and 1 on 1 in Board Games (100%). No other entities survived in the other
categories.
- 50% of entities survived among Cluster H: 1 on 4 entities survived in Design category (25%), 3
on 3 in Hardware (100%) and 1 on 2 in Fashion (50%). No other entities survived in the other
categories.
- 50% of entities survived among Cluster I: 1 on 4 entities survived in Hardware category
(25%), 1 on 3 in Board Games (33%), 2 on 2 in Design (100%) and 1 on 1 in Food (100%).
4.3 Observations
Although it seems difficult to find any trend related to the percentage of extra money received we
notice slight increase of survival rate with the increase of “success” of the related Kickstarter
campaign.
Hardware products and Board Games should be considered the most successful categories in
attracting more funds than the original goal set.
5. Fourth Approach: focusing on backers’ impact
5.1 Method & Clusters
A final and different attempt to evaluate the success of a project is of course the number of backers
who participated. As for all other parameters analysed so far, some clarifications are needed. In fact,
each funding campaign has several “pledges”, which are basically the amount of money that people
may offer in exchange of rewards or products, and they usually may vary from a symbolic amount
of 1-2$ until thousands of dollars: this means that a huge number of backers of small pledges have a
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lesser impact than the same number with higher pledges, when we consider the total amount of
collected money.
Following the path drawn so far, we took into
account the raw number of backers and
divided the sample in three clusters as such:
Cluster J: 17-110, Cluster K: 111-243,
Cluster L: 248-2106.
5.2 Survival Rate
According to the parameters explained
before, we observe that:
- 60% of entities survived among Cluster
G: 3 of 4 entities survived in Hardware
category (75%), 1 of 2 in Food (50%), 1 of 1 in Board Games (100%), 1 of 1 in Design (100%).
- 30% of entities survived among Cluster H: 1 of 5 entities survived in Design category (20%), 1
of 2 in Food (50%) and 1 of 2 in Board Games (50%). No other entities survived in the other
categories.
- 20% of entities survived among Cluster I: 1 of 3 entities survived in Hardware category
(33%), 1 of 3 in Design (33%). No other entities survived in the other categories.
5.3 Observations
Watching these results, it appears clear how the number of backers influences the chances to
survive. In fact, entities with less total backers seem to be more likely to survive.
As a last observation, we can confirm how Hardware, Design and Board Games seem to be the
most popular categories among the seven taken into consideration.
READING THE RESULTS
1. Merging Data
Remarkable are the aggregated data [Figure 1].
A first unexpected behaviour is observable among the “Number of Backers” index: on the average,
failed start-ups had been supported by 30% more backers than the survived ones.
A fact that has to be remarked: the product isn’t the unique pledge that a backer can obtain founding
a project, there are also offerings (when the pledge, usually 1$, is exchanged for a gratitude email).
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Also the statistics about
“Raised Funds” do not seem to
match the expectations. On the
average, the start-ups failed
raised 28% more than the
survived ones, even the top
raiser picked up in our
selection (a wearable device
that raised more than 33.000$)
failed.
About this index we should
keep in our mind that the
presence of this outlier,
mentioned before, heavily
influenced the average
calculation for the index.
The third index, Required
Funds, shows how on average
firms who failed asked around
27% less funds than successful
firms.
The last main index taken in consideration is the percentage of raised funds compared with the
required funds. Here again failed start-ups detain the higher average score, 25% higher.
Figure 2
Classifying all the data in a chart with the projects sorted by category on the horizontal axis and a
logarithmic scale on the vertical one (reporting for each index: dollars for “R.F.” and “O.F.”,
percentages for “%”, and natural numbers for “N.B.”) allows us to do the following observations:
• The “Hardware” and “Product Design” clusters are the most active both from the “Number
of Projects” point of view and from the amount of funds and % achieved (visible also by the
gap between the O.F. and R.F. curves). Those categories contain also both the upper and
lower outliers.
Figure 1
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• The category “Food” is the most supported in terms of number of backers.
• The most stable categories are the Table top and Video Games, these register the minimum
variance among all the indexes.
2. The Key Factor
Analysing both the statistical indexes and the main fundamentals of the
dynamics of how start-ups evolve, we decided to analyse deeper the
combination of “Obtained Funds” and the “Number of Backers”.
Both the indexes, picked individually, do not seem to describe much
statistically and theoretically, however, their combination seems to be
suitable for this task.
The new combined index is the ratio of the Obtained Funds and the
Number of Backers. This way the funds raised are weighted per the
number of people that gave their money to the projects. This index, due to
the way it is built, also muffles the influence of the outliers.
On average, between failed and survived firms, there is a 68% gap, the
widest gap recorded among all the indexes until now. For this reason we
decided to assume this index to try to understand how Kickstarter provides
assets to the teams that want to launch their start-ups.
So, for the data and the analysis carried on in this research, we can assert
that a project, in order to obtain good assets that could be exploited in the
CONCLUSIONS
This case study tries to understand if starting a firm through crowdfunding could be a determinant
factor in reducing the liability of newness in start-ups.
We started by considering Pfeffer’s and Salancik’s (Pfeffer and Salancik, 1978) studies on the
importance of managing the uncertainty of a new-born firm by reducing the firm’s dependence on
external sources. Considering that every new enterprise needs funds, we think that the possibility of
obtaining these funds also by “non-traditional” sources, such as crowdfunding platforms, increases
the chances of success. We have then analysed the platform Kickstarter and took our dataset from
their website. For every project we studied 4 different variables: the amount of requested funds, the
amount of obtained funds, the ratio of the obtained funds on the requested ones (in percentage) and
the number of backers. Furthermore we considered in which category the project was set (e.g.,
Video Games, Food etc.) and, lastly, we created an index from the ratio between obtained funds and
number of backers.
From our research on the single clusters we can see that projects who have requested less funds and
also those who have received less funds have had in comparison to the clusters who have required
and obtained a larger amount of funds the highest survival rate. The difference between obtained
and requested funds doesn’t seem to affect in a significant way the success of a project. By contrast,
if we consider all the dataset, the failed firms have, in average, requested less funds, even though
they have obtained 25% more funds than the projects that have survived. The most surprising result
is that the successful projects have, in average, had a lower number of backers, which invested a
larger amount of money in the single product. We supposed this outcome is due to the fact that the
fewer backers support projects in which they have more confidence. This could derive from a better
understanding of the project itself and of the consequent feasibility of it, as well as the capability of
the project to attract a larger number of buyers once the product is on the market.
12. References:
G. Abatecola, 2012 a, Organizational Adaptation: an update;
G. Abatecola, 2013 a, Research in organizational evolution. What comes next?, European
Management Journal;
G. Abatecola, R. Cafferata, S. Poggesi, 2012, Arthur Stinchcombe’s “liability of newness”:
contribution and impact of the construct, Journal of Management History;
R. Cafferata, G. Abatecola, S. Poggesi, 2009, Revisiting Stinchcombe’s “liability of
newness”: a systematic literature review;
Belleflamme, P., Lambert, T., Schwienbacher, A. 2011. Crowdfunding: Tapping the Right
Crowd. Core discussion paper 2011/32,;
Lambert, T., Schwienbacher, A. 2010. An Empirical Analysis of Crowdfunding.;
Larralde, B., Schwienbacher, A. 2010. Crowdfunding of Small Entrepreneurial Ventures,
Oxford University Press;
www.kickstarter.com;
