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KICKSTARTER Can crowdfunding countervail the Liability of Newness? Carozza Giacomo, Cipollone Michela, D’Urso Gianmarco, Ratzenberger Agnese

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Page 1: KICKSTARTER (1)

KICKSTARTER

Can crowdfunding countervail the Liability of Newness? Carozza Giacomo, Cipollone Michela, D’Urso Gianmarco, Ratzenberger Agnese

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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.

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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;