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Successful Crowdfunding: The Effects of Founder and Project Factors
Meng Hong Por One More Restaurant
#37 Street 315, Beoung Kak 1 Commune
Phnom Penh City, Cambodia +855-78-385-070
Sung-Byung Yang School of Management, Kyung Hee
University 26, Kyungheedae-ro, Dongdaemun-gu
Seoul, South Korea +82-2-961-9548
Taekyung Kim College of Business Administration,
The University of Suwon 17 Wauan-gil, Bongdam-eup Hwaseong-si, South Korea
+82-31-220-2149
ABSTRACT
Crowdfunding has been regarded as a novel way of collecting
money for innovators to launch products and services by opening
their ideas in online. This funding approach is differentiated from
a traditional fundraising alternative in terms of project evaluation
and risk management. In this paper, we question the reason why
some crowdfunding projects are more successful in the context of
a pre-ordering model, also known as a reward-based
crowdfunding. Data analysis results based on 704 Kickstarter
projects showed that founder’s prior experiences would influence
successful fundraising. User comments and update efforts have
positive effects on the increase of success rate. In addition, we
examined that the amount of funding goal had negative
association with fundraising success.
CCS Concepts
• Information systems ➝ Information systems applications ➝
Collaborative and computing systems and tools
• World wide web ➝ Web applications ➝ Crowdsourcing
Keywords
Crowdfunding; successful fundraising; crowdsourcing
1. INTRODUCTION One of the biggest problems of innovative projects is lack of
financial supports. This is true for scientific research projects, and
is also applicable for entrepreneurs who do not have credible
reputation. Traditional and even novice way to overcome this
issue is to borrow money from friends who know the project. Of
course, there are open chances to get financial supports from
banks and venture capitalists; however, proving potential values
about innovation is difficult for inexperienced founders. Moreover,
the idea is not usually validated in a test market, which means
backup data are lack of reality (Berger and Udell, 1998).
Thanks to collaborative technologies in the information system
domain, the desperate entrepreneur can have a new financial
supporting alternative, named by Crowdfunding. Crowdfunding
refers to a new way of collecting money from people in online
without personal contact (Fernandes, 2013). The process is simple.
An entrepreneur, known as a project founder in crowdfunding,
posts his or her business project on the Internet. Potential
investors (also known as backers) around the globe search or
browse projects to find out which one is interesting. A
crowdfunding platform helps entrepreneurs establish a semi-
structured webpage for advertising their idea, and it also provides
an opportunity for getting innovative products/services in advance
of marketization. The key idea behind crowdfunding is that
collective wisdom works well for evaluating a project. In
crowdfunding, entrepreneurs do not have to worry about losing
the control of a company while obtaining extra funds (Valanciene
and Jegeleviciute, 2013). In addition to raising fund,
crowdfunding has served as an indication whether or not there is a
market for a newly creative product (Mollick, 2014; Valanciene
and Jegeleviciute, 2013).
Although crowdfunding appears to be a winning strategy for
entrepreneurs, successfully reaching a funding goal is
challengeable. It should be noted that face-to-face communication
with project founders is replaced by computer-mediated
communication, which indicates that there are less social cues and
more ambiguity for judging quality of suggested project (Okdie et
al., 2011). Indeed, we should be aware that information sources
and investment experiences are limited in crowdfunding. There is
no guarantee that investors are specialists in funding innovative
idea. Returns of investment are settled down mainly by a founder.
Moreover, there are less physical evidences on credibility to the
business. Compared to buying an innovative product from a
matured company in online market, receiving goods or service
rights is not deterministic. Therefore, filtering out successful
projects in advance should be regarded as a key task for
improving fundraising quality.
In this study, we question why some of crowdfunding projects are
more successful than others. This research question is more
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DOI: http://dx.doi.org/10.1145/2971603.2971611
described by the following sentence: which factors influence the
possibility of success? We collected a real world crowdfunding
data in order to answer the question based on 704 cases from
Kickstarter. The following section starts with a background study.
The next section explains our hypotheses. The following part
includes data descriptions and analysis results. This paper
concludes with theoretical and practical implications. Future
research agenda will be added.
2. BACKGROUND
2.1 Crowdfunding From 2011, approximately 1.5 billion dollars were collected
through around 500 crowdfunding platforms worldwide.
Crowdfunding becomes a primary channel for introducing
innovative products/services (Giudici et al., 2013). Schwienbacher
and Larralde (2010) describes crowdfunding as 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 purpose.
Stakeholders in crowdfunding are categorized into two types:
founders and investors (also known as backers). Based on a
crowdfunding project, those different sides meet together. Their
cooperation aims to make the project real so that innovative
activities keep going (Gerber et al., 2012).
According to Belleflamme et al. (2014), initial capital requirement
influences a decision on crowdfunding. The decision made by
entrepreneur on which model of crowdfunding to pursue for their
venture is depended on initial capital requirement. In the case
when the initial capital requirement is relatively small,
entrepreneurs prefer a pre-ordering model. If the initial capital
requirement is higher, founders may prefer a profit-sharing
mechanism. Profit-sharing is a kind of traditional funding
strategies. Investors can make bigger money when a project is
successfully done. Since the share counts on the total amount of
sale in market places, the startup investors in crowdfunding
should have full responsibility on failure. To the contrary, a pre-
ordering model is unique in terms of responsibility and return. In
this model, a founder sets a target funding goal. If investors do not
comply to put money over the goal, the project is not funded. In
other words, this type follows an all-or-nothing scheme. Before
the project sells products/services in a real market place, a
crowdfunding platform provides an initial test market by placing
reward plans. For example, a founder can differentiate rewards for
different types of investors. If an investor decides to pay only 5
dollars, a product will be delivered. For an investor who pays 10
dollars, two products with a special gift will be given. This
rewarding process is complete before a founder goes into a mass
market.
Mollick (2014) reveals that personal networks of project founder
are significantly correlated with the success of crowdfunding.
Fernandes (2013) insists using video clips is crucial for
crowdfunding success. Ward and Ramachandran (2010) show a
crowdfunding project can be influenced by a similar prior project.
A prior study on risks in crowdfunding reveals mechanisms for
reducing uncertainty influences success possibility (Ahlers et al.,
2015). Based on semi-structure interviews, Gerber et al. (2012)
found that extrinsic motivation would play an important role for
crowdfunding success. Those prior studies provide insightful
ideas on crowdfunding success especially on a pre-ordering model,
also known as a “reward-based” model; however, they are lack of
a synthesized and simple structure to test effects of a founder
dimension and a project dimension on success rate.
2.2 Theory Base To develop a theoretical model considering both founder and
project dimensions in order to predict the success rate of
crowdfunding, we adopted the model of online review credibility
(Racherla and Friske, 2012), and the model of online trust
(Corritore et al., 2003).
Racherla and Friske (2012)’s model explains what makes online
reviews helpful for users. Based on persuasive communication
and source-related influential factor literatures, the model
indicates that review usefulness is influenced mainly by two
dimensions: messenger dimension and message dimension. The
relationships are moderated by different types of users’ decision
contexts.
The model of online trust explains external factors in an online
website influences trust levels. Specifically, Corritore et al. (2003)
studies online transactions to understand effects of website design
factors and prior experiences on using similar artifacts. The model
indicates that both individual factors in a perception level and
environmental factors in a design level should be considered to
understand how trust influences transaction performance in online
markets.
The abovementioned models commonly indicate that design
elements influence the success of crowdfunding. Moreover, those
should be rooted in both individual perception levels and project
characteristic levels. Project related information provides
information proxies for trust, credibility and functionalities (Qiu
et al., 2012). According to Metzger et al. (2010), cognitive
heuristics are useful in assessing information for successful
transactions in a computer-mediated environment. In this study,
we use design elements to predict a success ratio instead of using
self-reported survey items.
3. HYPOTHESIS A usual e-commerce website has information sources for
credibility. Company identity information plays an important role
that gives a clear image about business mission and customer
value. Corporate Identity (CI) provides a unified image to
customers and investors in a stock market. In the context of
crowdfunding, an external link for providing personal information
of founder has been adopted to achieve similar effects. Identity
information can be associated with credibility in online. Fogg et al.
(2001) reveals that identity disclosure (by showing name and
photo) strongly affects how consumer perceives trust.
H1. Identification information of founder increases the
possibility of success in crowdfunding.
Hsu (2007) finds in his study that entrepreneurs who have prior
founding experiences, especially those with financially successful
ones, are both more likely to acquire funding and have higher
valuations from venture capitalists. Similar finding is also
supported by MacMillan et al. (1986) in whose study indicates
that one of the most important criteria used by venture capitalists
to determine funding decision is entrepreneur’s experience.
Accordingly, the following hypothesis is derived.
H2. The level of prior experiences of collecting fund increases
the possibility of success in crowdfunding.
Shoppers are likely to listen to the others who are independent
with a company to get trustful information (Utz et al., 2012). In
the context of online crowdfunding, we expect that word-of-
mouth plays an important role to rule out biased decisions. It
should be noted that investors usually raise various questions
since a crowdfunding project is likely to be uncertain. A prior
study on the effects of user-generated reviews shows positive
association with sales and productive discussions (Chen et al.,
2004). Thus, we hypothesize:
H3. The number of comments increases the possibility of
success in crowdfunding.
It should be noted that a crowdfunding project requires progress
tracking. Projects displayed in a crowdfunding website, such as
Indiegogo, Kickstarter and Gofundme to name a few, are work-in-
progress in terms of lack of financial support, technical
incompleteness and marketization. Project Update can be useful in
distributing information about progress. The increase of
interactivity makes investors positively involved in project
development (Dwyer, 2007). In turn, we can assume that the
extent of efforts to interact with investors influence positively a
crowdfunding project. Thus, we hypothesize:
H4. The number of project updates is positively associated
with the possibility of success in crowdfunding.
Trustworthiness of a website is highly correlated with the extent
of elaborating information (Shelat and Egger, 2002). Elaborating a
description refers to an act of adding details about key information
sources for influencing an investment decision. In a crowdfunding
website, video clips, blueprints and interviews are likely to be
added to present more information. According to Mudambi and
Schuff (2010), depth of review descriptions in an online store
results in positive outcomes.
H5. The extent of elaborating descriptions influences
positively the probability of success in crowdfunding.
Investors cannot get a product or enjoy a service before a
crowdfunding project is complete. Simply, they should wait until
the project campaign reaches a finish line. Although long duration
of funding seems to be a safe choice for a founder, the possibility
of lagging product/service delivery can give a negative image to
investors. The traditional research stream about consumer
motivation reveals that time is a key for promotion success under
uncertainty (Belleflamme et al., 2014; Spears, 2001). Thus, we
hypothesize:
H6. Campaign period negatively impacts the probability of
success in crowdfunding.
Funding goal is suggested to be set at the minimum requirement
level of the startup requirement of a project (Cebulski, 2013).
High funding goal indicates high initial capital requirement for
project, which eventually gives signal of higher risk. This might
convey distrust on founder’s ability to complete the project. Thus,
we hypothesize:
H7. Increase of a funding goal influences negatively on the
probability of success in crowdfunding.
4. METHODOLOGY Data were collected from Kickstarter. At the moment of 2016,
over 9 million investors put money into more than 260,000
projects. The total amount of fundraising exceeds $2 billion. This
crowdfunding platform has been grown up rapidly so that
numbers should be read as proxies of its impact with caution.
There are fifteen types of project categories such as art, comics,
crafts, dance, design, fashion, film & video, food, games,
journalism, music, photography, publishing, technology, and
theater on this platform. Kickstarter adopts a reward-based
crowdfunding style, which means that an investor get a reward
defined in a funding contract in public. In addition, the reward
follows the all-or-nothing scheme. If a project fails to reach a
funding goal, investors lose the chance of getting a reward. Of
course, a founder cannot collect money from the failed project.
4.1 Data To avoid possible issues relating to live projects, we limited the
data set to 755 samples within 60 days which were completed in
January 2015. It should be noted that any failed projects can have
additional chances of redeploying slightly different products and
services in Kickstarter; therefore, one year lagged data can
provide chances for filtering out biased samples. Totally, 51
projects were discarded after inspection in this sense.
Descriptive statistics show that 79.4% projects are located in the
United States. Other regions include Australia, Canada, Denmark,
Great Britain, Ireland and New Zealand to name a few. As shown
in Figure 1, about 12 million USD were invested. Design and
technology were top-tier project categories with 37,150 USD and
45,361 USD in each on average (see also, Table 1).
Figure 1. Average investment by project category (US dollars)
Table 1. Descriptive statistics
Item Mean S. D.
Campaign period 33.34 11.59
Amount invested 17,442.04 36,615.96
Investors 175.49 278.92
4.2 Measurements In this study, we adopted multiple regression analysis in order to
validate hypotheses. Success Ratio, the dependent variable, is
defined as the extent of received fund over a funding goal. To
explain the variance of the dependent variable, seven dependent
variables as shown in Table 2 were defined. Since the distribution
of Success Ratio was skewed, we adopted log transformation to
adjust scales for better interpretation to results.
For identity disclosure, we used Facebook data. We create a
dummy variable which receives value one if there is a link to a
Facebook account; otherwise, zero. According to Fogg et al.
(2001), a person reveals his identity by using real name and photo.
For our study, we used the existence of personal photos as the
proxy of validating identity disclosure measurement. It should be
noted that a Facebook account for crowdfunding could be
artificial. We assumed that an account would belong to a real
person if actual and personal photos were uploaded at least three
times onto a Facebook profile page.
A study suggests there is correlation between geographic location
and decision to pledge the project (Agrawal et al., 2013). In order
to control the effect of regional proximity, we created a dummy
variable of Country. If a crowdfunding project was in the United
States, we put 1; otherwise 0.
Table 2. Measurements
Variable Measurement Description or Reference
Success Ratio Amount funded over funding goal The degree to which the amount of money received is
greater than a funding goal.
Identity Disclosure A dummy, takes 1 if there is a link to a
real Facebook account; otherwise 0.
Whether a person chooses to reveal his or her real identity
by providing a link to a personal Facebook page.
Experience Number of past projects Hsu, 2007
Comment Number of comments Chen et al., 2004
Update Number of updates The degree to which a founder puts effort in blogging the
progress.
Description Elaborateness Word counts Racherla and Friske, 2012
Funding Goal The amount of funding Mollick, 2014
Campaign Period Days for a crowdfunding project Mollick, 2014
Country A dummy, takes 1 if a project is in the
US; otherwise 0.
This variable indicates how much a project is affected by
regional characters (a control variable).
5. RESULT As shown in Table 3, all the variables could be discriminated so
that we could use adopted variables and developed ones to test
individual hypotheses.
Table 3. Discriminant validity
Item Factor Loading
1 2 3 4 5 6 7 8 9
DVar1 .977 -.057 .052 .096 -.046 .084 .025 .009 .146
IVar1 .023 -.012 -.023 -.011 .005 .034 .998 .041 -.016
IVar2 .093 -.038 .018 .988 -.072 .000 -.011 .035 .081
IVar3 .173 .263 .132 .100 .034 .135 -.020 -.009 .924
IVar4 .087 .090 .161 .000 .097 .966 .038 -.011 .120
IVar5 .053 .111 .969 .019 .076 .160 -.025 -.016 .116
IVar6 -.044 .102 .073 -.073 .983 .092 .005 -.018 .030
IVar7 -.065 .949 .117 -.045 .114 .094 -.013 -.010 .241
Cont1 .008 -.009 -.015 .034 -.017 -.010 .041 .998 -.008 * DVar1: Success Ratio (log), IVar1: Identity Disclosure, IVar2: Experience, IVar3: Comment, IVar4:
Update, IVar5: Description Elaborateness, IVar6: Funding Goal, IVar7: Campaign Period, Cont1: Country;
Principle Component Method, rotated by Varimax Kaiser Normalization
Correlation analysis results confirmed that Success Ratio would
be associated with dependent variables. Identity Disclosure was
exceptional (Pearson 𝜌 = 0.046, p-value = 0.223). We found that
the number of comments would be correlated with other
dependent variables. In addition, Update seemed to be a potential
cause of multicollinearity. Variance Inflation Factor (VIF) values
were relatively small (Identity Disclosure = 1.019, Experience =
1.097, Comments = 1.508, Update = 1.236, Description
0
10000
20000
30000
40000
50000
Elaboration = 1.225, Period = 1.120 and Goal = 1.439); therefore,
we concluded that the multicollinearity issue would not distort
results. In addition, we ran the Durbin-Watson test to understand
autocorrelation effects. The range of Durbin-Watson exists
normally from 0 to 4. If the value is close to 2, we accept it as no-
autocorrelation. The calculation result from our sample residuals
showed that autocorrelation would not be issue (DW = 2.003).
Fitness of regression model can be measured by an index for
coefficient determination. In our study, we used adjusted 𝑅2 to
understand how much the linear model was fitted into data. The
result was 20.3%.
Table 4. Correlation
Item Pearson Correlation
1 2 3 4 5 6 7 8 9
DVar1
IVar1 .046
IVar2 .204 -.020
IVar3 .315 -.034 .179
IVar4 .183 .066 .010 .304
IVar5 .124 -.044 .040 .301 .346
IVar6 -.085 .009 -.149 .095 .205 .171
IVar7 -.078 -.028 -.074 .489 .229 .266 .240
Cont1 .020 .081 .070 -.019 -.025 -.036 -.040 -.028 * Bold font refers to the Pearson correlation value is significant at 𝛼 = 0.05.
The regression model shows that H1 is not supported. Founder
Identity does not have significant effect on Success Rate (p-value
= 0.168). The first plausible explanation is that Facebook photos
are not adequate materials for identification, which does not give
significant clues for trustworthiness. The second explanation is
that a crowdfunding project has different characteristics that have
been reported in blog studies about the effect of Word-of-Mouth
on product sales (e.g., Jansen et al., 2009; Lee and Youn, 2009).
Social networking capabilities may not be correlated with the
success of crowdfunding since it does not deliver relevant
information on products or services (Giudici et al., 2013).
Hypothesis 2 is supported (p-value = 0.006). Experiences on prior
crowdfunding projects influence the next project. The historical
records of crowdfunding as a founder may give a positive signal
to potential investors about capability and competency. According
to Hu et al. (2005), reputation information increases trust with
reducing risks in a computer-mediate environment. Our result is in
line with the findings from the effects of prior experiences on
performance in the context of online shopping (e.g., Gefen et al.,
2003).
The number of comments is positively associated with Success
Ratio, which shows that H3 is supported (p-value < 0.000). User
participation has been studied as a key success factor in
information system research (Lin and Shao, 2000). The amount of
review comments can increase positive responses in terms of sales
(Ye et al., 2009). In the context of crowdfunding, the amount of
user-generated comment is a primary indicator to a possible
successful project.
The number of update is positively related with Success Rate (p-
value < 0.000). H4 is supported. According to Mollick (2014),
frequent update is considered as a positive indicator for quality.
Quick feedback to customer issues is required to recover service
failures (Zeithaml et al., 2010). Moreover, constant update gives a
good image on company’s innovation efforts (Xu et al., 2014).
Those can be good signals for project success; thus increasing
success rate.
H5 is not supported. The word count does not convey significant
meanings to explain the variance of Success Rate. The result
implies that variance of success and failure is not found in
quantity of explanation. We suspect that small quantity of
description can deliver key information sources for persuading
investors more successfully. However, this assertion was not
tested in this study. Further studies are needed to verify the effect
of various information cues that affect success.
H6 is supported. One plausible explanation is that time duration
affects project attractiveness. If a reward is expected several
months or even a year later, an investor may perceive a
crowdfunding project is uncertain. In addition, long duration
reflects the fact that a project is not mature enough for market
delivery. It gives a negative signal to investors about quality and
veracity. In line with H6, Funding Goal is negative associated
with Success Rate (p-value < 0.000), which shows that H7 is
supported. This result is in line with Mollick (2014). Increasing
goal is negatively correlated with success. Reward-based
crowdfunding projects usually have differentiated reward scheme.
For larger investors, a project founder promises bigger rewards. If
a person contributes only small money to the project, a reward is
small. The final goal is a sum of investment from different
schemes. It should be noted that even a big goal can have multiple
reward schemes that need to be supported by limited investors.
Since a return from participating in a crowdfunding project is
uncertain, small reward with small risk is naturally preferable. If
the pool of investors is limited, a large funding goal is probably
unrealistic; thus accelerating failure.
Figure 2. Analysis result
6. CONCLUDING REMARK Although crowdfunding provides a new approach for
entrepreneurs in funding innovative projects, how to make a
project being successful is not yet clear. The findings of this study
may contribute to knowledge accumulation in the research stream
of crowdfunding by offering clear insight on using design
elements. Our findings as also provide strategic insights to the
platform developers of crowdfunding. According to the analysis
result, prior successful stories in a founder dimension should be
highlighted to increase success rate. In addition, a searching tool
for discovering promising crowdfunding projects needs to
consider the amount of comments and updates. There should be
Identity Disclosure
Prior Experience
Country
Success Ratio
Comment
Update
Description Elaborateness
Campaign Period
Funding Goal
H1
H2
H3
H4
H5
H6
H7
Founder Dimension
Project Dimension
Control Variable
0.047
0.098**
0.393***
0.123***
0.050
-0.074*
-7.026***
0.010
clear guidelines for helping founders limit campaign period wisely
as shown in the analysis result.
Crowdfunding has become a competitive alternative in seeking
financial support. Although this study provides significant insights
for academic researchers and IS developers, we leave unmet
research needs for further work. We think the following
limitations should be answered for utilizing crowdfunding as an
important and useful financing tool for innovators. First, the
findings are rooted in one data source, Kickstarter. This probably
reduces the possibility of generalizability. Future study should
consider other crowdfunding sites equally including Indiegogo,
Crowdfunder, and Rockethub to name a few. Secondly, this study
only considers a pre-order type (i.e., reward-based crowdfunding).
It should be noted that other crowdfunding approaches are
emerging. Since our model is specialized in one of possible
crowdfunding alternatives, the explanation power of our model is
limited. Third, by combining review credibility model and on-line
trust model we developed our research model consisting of two
different dimensions. However, there are open chances to consider
hierarchical levels for both founder and project characteristics.
For example, comments by user can be separately investigated in
terms of gender, maturity of investing crowdfunding projects,
expertise and tastes. Interaction effects between our key
constructs and those variables should be interesting.
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