29-06-2015 Study year 2014/2015
Group 25: Crowdfunding Dhr. J. Sol
Robin van Velthuizen 10464727
The influence of sharing behavior in social media on
crowdfunding success
2 Statement of Originality
This document is written by Robin van Velthuizen who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
3 Abstract
Social media can be seen as an important way for founders on crowdfunding platforms to promote their project. It is, however, unclear if this promotion tool can be used to increase the amount of money that investors are willing to invest. This study aims to find out whether sharing a crowdfunding project in social media has an effect on amount invested in that project. I hypothesize that equity-based crowdfunding projects with more shares in social media raise more money. This hypothesis was tested with a sample of 128 projects on two platforms, 78 from EquityNet and 50 from Crowdcube. Unfortunately, the hypothesis was not supported, suggesting that sharing in social media alone does not increase the amount
4 Table of contents 1. Introduction 5 2. Literature study 7 2.1. Crowdfunding 7 2.2 Equity-based crowdfunding 8 2.3 Social media 8
2.4 Crowdfunding and social media 10
3. Methodology 11 3.1 Design 11 3.2 Procedure 11 3.3 Analysis 11 3.4 Limitations 12 4. Results 13 4.1 Data 13 4.2 Regression 18 5. Discussion 20 5.1 Summary 20
5.2 Limitations & future research 21
5.3 Conclusion 21
5 1. Introduction
In 2015 Facebook, the biggest social media platform, reached 1.3 billion users (Statistic Brain, 2015). This amount of members illustrates the importance of social media nowadays. Social media is a group of internet-based applications that allow the creation and exchange of user generated content (Kaplan & Haenlein, 2010). According to Kaplan & Haenlein (2010), social media allow firms to engage in timely and direct end-consumer contact at relatively low cost and higher levels of efficiency than can be achieved with more traditional
communication tools. This makes social media not only relevant for large multinational firms, but also for small and medium sized companies, and even nonprofit and governmental
agencies. Accordingly, social media can be seen as an important tool for founders on crowdfunding platforms to promote their project (Gerber & Hui, 2013).
Crowdfunding is defined as an online request for resources from a distributed audience in return for a reward (Hui et al., 2014). Crowdfunding can take several forms so an
understanding of the founder’s choice of a particular form of crowdfunding and a particular project is important (Belleflamme et al., 2014). Gerber & Hui (2013) state that investors are not only motivated to support a certain project for financial reasons, but social reasons are also important and social media is a great way to connect with others. Founders seek both to expand awareness of their work and to make connections that benefit them professionally and socially: crowdfunding communities provide a receptive network for founders’ aims.
Investors find that supporting causes and helping others through crowdfunding gives a
powerful sense of community, satisfying a powerful human need for social affiliation (Gerber & Hui, 2013). Hui et al. (2014) found that crowdfunding relies on collaboration and that founders are creating communities to overcome difficulties, to get advice and to gain publicity. Therefore, it is valuable to study the influence of social media on the success of crowdfunding projects. With this information founders can implement social media in their crowdfunding campaign.
So far, some good qualities of crowdfunding products and motivations of founders have been studied. Mollick (2014) suggests that personal networks and underlying project quality are associated with the success of crowdfunding efforts, and that geography is related to both the type of projects proposed and successful fundraising. Furthermore, Hekman & Brussee (2013) studied 25 successful and 25 unsuccessful projects on KickStarter and used Facebook friends and the number of Bitly referrals to see whether there was a correlation between the two variables. They found that successful initiations on Kickstarter have more friends. Their analysis also shows that diverse networks are beneficial for the success of a
6 project (Hekman & Brussee, 2013). I want to do a similar study, but for sharing behavior of the projects on Facebook, Twitter and LinkedIn on equity-based crowdfunding platforms, named Crowdcube and EquityNet. In doing so, I investigate whether equity-based
crowdfunding combined with a good social media campaign is more profitable than a project where social media is less used. This thesis addresses the following question: “Does sharing in social media improve the success of an equity-based crowdfunding project?” In addition, I want to study whether there is a difference between projects available on crowdfunding platforms with a time limit. Crowdcube has a time limit of 45 days and the amount of days a project is available on EquityNet is without restrictions. Therefore, a sub question is: “Do time limits on crowdfunding platforms lead to different sharing behavior?”
7 2. Literature study
2.1 Crowdfunding
The concept of crowdfunding comes from the broader concept of crowdsourcing, crowdsourcing involves the crowd to obtain ideas, feedback and solutions to develop
corporate activities (Kleemann et al., 2008). As already described in the introduction, the term crowdfunding refers to an online request for resources from a distributed audience in return for a reward (Hui et al., 2014). A more expanded definition would be: “Crowdfunding
involves an open call, essentially through the Internet, for the provision of financial resources either in form of donations (without rewards) or in ex-change for some form of reward and/or voting rights in order to support initiatives for specific purposes" (Hemer, p.8, 2011). This means that crowdfunding is a phenomenon where a founder puts his project on a platform and investors can donate money to support this project. The founder begins the process by
publishing a request for funding on a crowdfunding platform. This request describes the business plan and the proposed product and it also describes what the investor gets in return (Bradford, 2012).
According to Hemer (2011), crowdfunding projects can take several forms, one of them is a donation. This is an altruistic act without any obligation for the recipient to give the donor anything in return. Another form of crowdfunding is where an investment takes place in exchange for the future product or some form of reward. This reward can be monetary or non-monetary (Belleflamme et al., 2014). Mollick (2014) states that these funders are treated as early customers, allowing them access to the products at an earlier date or they can buy the product for a better price. According to an industry report of Crowdsoursing.org (2012), these are the most popular ones. Additionally, there is a form of crowdfunding which is called “the lending model” in which funds are offered as a loan with the expectation of some rate of return on capital invested (Mollick, 2014). Finally, the fourth form of crowdfunding is equity crowdfunding. This form of crowdfunding is referred to the process where a group of
8 2.2 Equity crowdfunding
Crowdfunding platforms are similar to stock exchanges because in both market places equity is sold to a large number of investors. Because the project is supported by a large number of investors who invest a relative small amount of money, it is interesting for a large group of investors and not only the investors with a lot of money can contribute (Bradford, 2012). Nowadays small companies face challenges in the financial environment, due to their lack of credit, operating history and proven track record these companies often have a hard time pursuing financing through traditional avenues (Stemler, 2013).
The equity crowdfunding market is influenced by the legislative environment of its home country. While equity-based crowdfunding appears to be a simple and powerful
opportunity for entrepreneurs to raise capital, in some countries companies are unable to offer equity stakes in companies. This was also the case in the United States, this is because equity interests are likely to be classified as securities under the Securities Act (Stemler, 2013). Stemler (2013) also states that this act had the purpose to ensure full disclosure of truthful information regarding the character of securities. Furthermore, the act had the purpose to ensure market stability, market integrity and preventing and repairing damage caused by free market failures. As a consequence, companies must fully comply with the complex
registration requirements. Registration is relatively expensive, certainly for small businesses, with a range from $300,000 to $500,000 (Sjostrom, 2001). Fortunately, in 2012, Obama signed into law the Jumpstart Our Business Startups (Stemler, 2013). The act enables entrepreneurs to sell equity in their companies to a large number of investors via crowdfunding platforms ( Belleflamme et al., 2011).
2.3 Social media
According to Kaplan & Haenlein (2010) the term social media, what it should include and how it differs from Web 2.0 and User Generated Content is not clear. Web 2.0 is a term that is used to describe the way in which developers and end-users started to utilize the World Wide Web. At first, applications were developed by individuals, but nowadays they are
continuously modified by all users (Kaplan & Haenlein, 2010). The term User Generated Content can be described as the various forms of media content that are publicly available and created by end-users. Based on these concepts, it is now possible to give a more detailed definition of social media. According to Kaplan & Haenlein (2010), social media is a group of internet-based applications that build on the ideological and technological foundations of Web
9 2.0 and that allow the creation and exchange of User Generated Content. Within this
definition of social media there are various types of social media that need to be
distinguished. In this study Facebook, Twitter and LinkedIn are taken into account, because these social media applications fit well with the sharing behavior of entrepreneurs on crowdfunding platforms. Social networking sites, like Facebook, allow users to create personal pages, provide users with access to these pages and exchange with them instant messages and emails (Kaplan & Haenlein, 2010).
Social media also has several roles in the promotion mix of companies. According to Mangold & Faulds (2009), social media is an ideal way for companies to communicate with their customers. However, it is not only a tool to communicate with their customers, it is also a tool for customers to communicate with each other. This can be seen as an extension of traditional word-of-mouth communication (Mangold & Faulds, 2009). Social business is a concept which can be described as connecting your business with customers through social media, the key in this concept is customer engagement. Social media is a way to create customer engagement and is therefore important in the strategy of an entrepreneur (Evans, 2010). Furthermore, companies and entrepreneurs should recognize the importance of internet and social media, because consumers are turning more frequently to various types of social media to conduct their information search and make purchasing decisions (Mangold &
Faulds, 2009). Social media as information source is also seen as a more trustworthy source of information than corporate-sponsored communications (Mangold & Faulds, 2009).
An understanding of the concept social media is necessary for avoiding
mismanagement regarding the opportunities and threats of social media. According to Kietzmann et al. (2011), social media has seven functional blocks which allows managers to make sense of how different levels of social media functionality can be configured. These blocks are: identity, presence, relationships, reputation, groups, conversations and sharing. For this study the block “sharing” is important. This block represents the extent to which users exchange, distribute, and receive content (Kietzmann et al., 2011). Furthermore, sharing can be used to build relationships with other people. This is interesting for crowdfunding entrepreneurs because when these entrepreneurs evaluate what characteristics their investors have in common, they can build a sharing network. Kietzmann et al. (2011) states that it is difficult to build a network with people when there is nothing to connect them with.
10 2.4 Social media and crowdfunding
Connecting with others is an important reason to engage in crowdfunding. Hui et al. (2014) found that crowdfunding relies on collaboration and that founders are creating communities to overcome difficulties, getting advice and gain publicity. Social media could play a crucial role in creating communities. Although it is a good source to spread your ideas and keep the potential investors up-to-date, there are also some challenges to overcome. According to Hui et al. (2014), there are five different challenges to create and maintain online communities, including starting up the community, attracting members, motivating commitment, motivating contributions and regulating community health and wellness. Entrepreneurs can overcome these challenges by deciding what to post, communicating with members and offering feedback and rewards (Hui et al., 2014). Milgram (1963) states that when an entrepreneur wants people to join and stay in the community, the entrepreneur should reach out to potential members personally and act on messages to get status or people to join the community. If an entrepreneur is active on social media for example by sharing his project a lot or by
interacting a lot with social media followers, it could have a positive effect on the money that he will eventually raise.
Society ultimately decides whether a project is funded or not, the heavy reliance on community is beneficial for crowdfunding creators (Hui et al., 2014). The possibility to create and maintain a community could give the entrepreneur an advantage towards other projects, because investors find it important to be part of a community besides earning money (Gerber & Hui, 2013). Furthermore, Gerber & Hui (2013) state that investors find supporting causes and helping others through crowdfunding gives a powerful sense of community satisfying a powerful human need for social affiliation. Furthermore, Rick et al. (2007) states that
supporters are motivated to invest because of feelings of sympathy and empathy. This is why the first of the two hypotheses is as follows:
Hypothesis 1: Equity-based crowdfunding projects with more shares in social media raise more money.
There is no existing literature regarding the change in social media behavior under time pressure. The second hypothesis will therefore be explorative.
11 3. Methodology
3.1 Design
The research is an empirical oriented study, several variables that influence the crowdfunding project has been studied. I want to contribute to the theory by studying the sharing behavior and whether this variable has an influence on the crowdfunding project. The data needed to test these hypotheses are obtained through the use of a webcrawler and manually. EquityNet and Crowdcube are used as equity-based crowdfunding platforms to collect the data from. I chose these platforms because they show the sharing behavior of each project. The goal was to obtain 125 projects, 75 from EquityNet and 50 from Crowdcube. The difference between the two platforms is that EuityNet has no time limit for the projects on their site, where Crowdcube has a limit of 45 days
3.2 Procedure
The webcrawler gathered the following information: target amount, amount raised, investors, equity, days left, sector, shares on Facebook, shares on Twitter and shares on LinkedIn. These variables were transformed into the following variables to perform a hierarchal regression: percentage invested at t=1, total shares at t=1, change in amount of shares and change in percentage invested. After 45 days or 1 day before the project ends the amount raised, investors and the shares on Facebook, Twitter and LinkedIn were obtained again. This gives the opportunity to analyze the difference between the amount of shares in relation to the success of failure of a project.
3.3 Analysis
To test the data described before, I will use the OLS regression model. With this model it is possible to test whether two variables are linearly related and to calculate the strength of the linear relationship (Menard, 2002). The relationship can be described by an equation: Y= α + βx + e
Where Y is the variable being predicted, in this study that would be the money that is raised by the crowdfunding projects. X is a variable whose values are being used to predict Y, that would be the shares on social media, the platform or other control variables. Furthermore, the equation has an alpha, beta and an error. The alpha is called the intercept and represents the value of Y if X=0. The beta represents the change in Y associated with one-unit increase in X. The error term is a random variable that represents the error in predicting Y from X. The
12 alpha and beta can be estimated by the method of ordinary least squares estimation (Menard, 2002). The beta gives the coefficient of interest.
3.4 Limitations
The method to obtain data has some limitations regarding to the results. For example, the data that is obtained is suitable to run tests in SPSS, but there are other factors besides shares that contribute to the success of a project. This makes it difficult to draw a solid conclusion regarding to the research question.
Another limitation is the fact that the projects on EquityNet show little sharing in Social media. This makes it unreliable to pick 75 random projects, I decided to pick 30 projects that do show a reliable amount of shares and to pick 50 projects random. I picked the random projects by selecting the first and last projects on every page sorted by “near goal”. This filter makes sure that there are only projects in the data where there is a solid amount raised. EquityNet has a second limitation, the platform shows little activity. Projects that I picked at the beginning did not fund much. This means that there was little difference between the money that the project had raised at the beginning of the data collection process and the money it has raised at the end.
13 4. Results
4.1 Data
The sample exists of 128 projects, 78 from EquityNet and 50 from Crowdcube. The variables that are interesting to see whether the hypotheses should be supported or not are the amount invested in a project, the total shares at the begin of the data collection, the change in shares, the platform the project is on and the change in the amount invested. To make sure that there is no distinction in big or small projects, the amount invested is transformed into percentages. Table 1: Descriptive statistics
M SD
Percentage invested at t=1 39% 0.28 Change in percentage invested 0.15 0.32
Total shares at t=1 67 175.81
Change in amount of shares 28.85 75.09 Note: N=128
The descriptive statistics (table 1) show that there is a lot variation in the amount of shares. The standard deviation is high for total shares and the change in amount of shares. Therefore it is important to look at the skewness and kurtosis of the data.
14 Figure 2: Distribution of total shares at t=1 with skewness: 5.88 and kurtosis: 7.57
15 Figure 4: Distribution of percentage invested at t=1 with skewness: 1.59 and kurtosis 4.53
According to figures 1, 2, 3 and 4, the skewness and kurtosis of all variables is too high knowing that a skewness higher than one is considered substantial. The skewness and kurtosis can be explained by the difference between the sharing behavior and investing behavior of the projects on the different platforms. After the data collection was completed, I noticed that Crowdcube is a more active platform than EquityNet. This means that for many of the projects on EquityNet there was not a lot of difference between the shares and the amount invested at the beginning of the data collection and the end. Furthermore, the amount of shares at EquityNet is very little compared to the amount of shares at Crowdcube. To overcome this skewed dataset, I transformed the data using a natural logarithm.
Table 3 shows the descriptive data after the transformation and figures 5, 6, 7 and 8 show the new distributions. The data is now less skewed than before.
Table 3: Descriptive statistics, skewness and kurtosis after transformation
M SD
Percentage invested at t=1 31% 0.19 Change in percentage invested 0.11 0.21
Total shares at t=1 2.22 2.09
Change in amount of shares 1.35 1.90 Note: N=128
16 Figure 5: Distribution of change in amount of shares with skewness: 1.03 and kurtosis -0.42
17 Figure 7: Distribution of change in percentage invested with skewness: 2.30 and kurtosis 4.71
Figure 8: Distribution of percentage invested at t=1 with skewness: 0.74 and kurtosis 1.29
To test whether the platform available is able to predict the change in percentage invested a dummy variable is created where Crowdcube = 1 and EquityNet = 0. The dummy variable will be multiplied by the change in amount of shares to test whether the platforms have different sharing behavior.
18 Table 4: Descriptive statistics, skewness and kurtosis for change in shares controlled by platform
M SD
Change in shares controlled by platform 1.32 1.91 Note: N=128
4.2 Regression
Hierarchical multiple regression was performed to investigate the ability of the change in shares, the percentage invested in a project and the platform the project is available on to predict the change in percentage invested in a certain project.
In the first step of the hierarchical multiple regression the predictor change in amount of shares was entered. This model was statistically significant F (1, 126) = 85.421; p<0.001 and explained 40% of variance in the change in percentage invested. At Step 2 of the regression, the total amount of shares at t=1 and the percentage invested at t=1 were added. This model explained 39% of the variance and is also significant F (4, 123) = 21.755; p<0.001. After the introduction of the variable change in shares controlled by platform, the explained variance did not go up and instead remained the same. The model itself is still significant with F (5, 122) = 17.27; p<0.001. Where in the first two models the variable change in amount of shares was significant with Beta values of 0.63 (p<0.001) and 0.8 (p<0.001), in the last model none of the predictor variables were statistically significant. Although none of the predictor variables were significant, the variable change in amount of shares was still the variable with the highest Beta value (β=0.66). The beta value represents the change in variance of the variable change in percentage invested when the dependent variable goes up by one point.
There is no statistically significant result found in the final regression model. All of the t-values are not statistically significant and this means that none of the predictor variables is significantly relevant. In the first two steps the predictor variable is significant, so then the hypotheses would be supported and the change in amount of shares is statistically related to the change in percentage invested. However, when we put more variables into the model in the last step none of the predictor variables is significant.
19 Table 5: Summary for hierarchal regression analysis variables predicting change in
percentage invested
R R2 R2 change B SE β t
Step 1 0.63 0.4
Change in amount of shares 0.10 0.01 0.63 9.24***
Step 2 0.64 0.39 0.01
Change in amount of shares 0.13 0.02 0.8 5.78***
Total shares at t=1 0.0 0.01 -0.01 -0.17
Percentage invested at t=1 0.04 0.12 0.02 0.32
Platform dummy -0.11 0.09 -0.18 -1.2
Step 3 0.64 0.39 0.0
Change in amount of shares 0.11 0.14 0.66 0.79
Total shares at t=1 0.0 0.01 -0.01 -0.16
Percentage invested at t=1 0.04 0.12 0.02 0.32
Platform dummy -0.12 0.09 -0.18 -1.2
Change in shares controlled by platform
0.02 0.14 0.14 0.16
20 5. Discussion
5.1 Summary
The goal of this research was to examine whether sharing of the crowdfunding project in social media has a positive influence on the success of the project or not. Specifically, we tested data collected from equity-based crowdfunding platforms to see whether the change in amounts of shares has a positive relation to the change in percentage invested in the project. The expectation was that, indeed, the sharing behavior has a positive influence on the success of a crowdfunding campaign. The expectation was based on the fact that crowdfunding projects heavily rely on communities (Hui et al., 2014). Gerber & Hui (2013) state that creating and maintaining a community gives the entrepreneur an advantage towards other projects. Finally, investors find connecting with others an important reason to engage in crowdfunding. This leads to the research question of this research: “Does sharing in social media improve the success of an equity-based crowdfunding project?”
The first hypothesis was that equity-based crowdfunding projects with more shares on social media raise more money. In the first two steps of the regression model the variable change in amount of shares shows a stable statistically significant (p<0.001) beta with
respectively values of 0.63 and 0.67. However, in the last step of the hierarchal regression the beta is not statistically significant anymore and has a value of 0.66. The interaction variable does not help in the explanation of the change in percentage invested. Furthermore, only in the first step of the regression model the variable shows a statistically significant correlation of 0.39. Step 3 in the regression model shows that there is no difference in the amount invested in a project in relation to the amount of shares that project has. A possible
explanation can be the very little change in both shares and percentage change on EquityNet. As was mentioned in the results section, the distribution is skewed to the left. Which means there are a lot of zero values.
The second hypothesis was that time limits on crowdfunding platforms lead to different sharing behavior. The variable change in shares controlled by platform shows whether the Crowdcube platform shows more or less shares than EquityNet. According to the regression, the variable has a beta of 0.14 and is not significant. According to step 3 in the regression model, there is no difference in the effects of the sharing behavior between the platforms.
21 5.2 Limitations and future research
The main predictor variable in this study is the change in amount of shares, this variable should explain the change in percentage invested. The fact is, there are other variables possible that could explain this difference. For example, the quality of a crowdfunding product is important, I did not take this variable into account. The quality of a product is hard to measure and test in SPSS, this is the reason why I did not use this variable. It could be a good idea for future research to take quality as a control variable. The project industry, incentives and the location of the project could also be added as control variable.
The data collection of this research took 45 days, this made it impossible to follow every project for their whole lifetime. It would be better to follow the project for the whole time it is available on the platform. If this was the case, it was possible to test whether projects share more or raise more money at the end or not. Furthermore, 45 days made it impossible to only collect data from Crowdcube. Crowdcube shows more activity than EquityNet and it would be better for the study to test only projects with a certain amount of activity. Besides, data from these two sites gave a skewed distribution. For future research it would be good to follow projects on the Crowdcube platform, or maybe more, for a longer period of time and for the whole lifetime the project is available.
Finally, only the amounts of shares are collected in this study. The amount of likes of followers the project or the project owner has is not taken into account. These variables could be considered for future research.
5.3 Conclusion
The research question of this study was: “Does sharing in social media improve the success of an equity-based crowdfunding project?”. I expected to find a positive statistically significant relation between the change in amount of shares and the change in percentage invested. After the data collection and running a hierarchal regression, it can be said that we found no
positive answer to this question. Sharing in social media alone does not improve the success of an equity-based crowdfunding project. Furthermore, the sub question: “Do time limits on crowdfunding platforms lead to different sharing behavior?”, has also no positive answer. This means that there is no significant difference in sharing behavior between platforms with a time limit and platforms which has no time limit.
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