The effect of media tools on funding in
a Kickstarter campaign
Student: Alexander Esser
Student ID: 11894105
University: University of Amsterdam
Bachelor: Business Administration (BSc ECB) Supervisor: Dr. Abdulkader Kaakeh
Statement of Originality
This document is written by Student [Alexander Esser] who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are 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.
Table of contents
ABSTRACT. ... 4
1. INTRODUCTION... 5
2. LITERATURE REVIEW... 6
2.1. REWARD-BASED CROWDFUNDING. ... 6
2.2. THE FUNDING GOAL AND DURATION. ... 7
2.3. THE REWARD STRUCTURE. ... 9
2.4. KICKSTARTER COMMUNITY. ... 10
3. HYPOTHESIS FORMULATION. ... 11
3.1. PICTURES IN KICKSTARTER. ... 11
3.2. VIDEOS IN KICKSTARTER. ... 11
4. DATA AND METHOD. ... 12
4.1. VARIABLES: ... 12
4.2. DATA ANALYSES. ... 14
5. RESULTS ... 15
5.1. THE EFFECTS OF PICTURES AND VIDEOS. ... 15
5.2. THE EFFECT OF VIDEOS FOR CERTAIN CATEGORIES. ... 17
6. DISCUSSIONS. ... 20
6.1. IMAGES. ... 20
6.2. VIDEOS. ... 21
6.3. THE REWARD STRUCTURE AND THE DURATION OF THE CAMPAIGN. ... 23
6.4. VIDEOS IN THE TECHNOLOGY CATEGORY. ... 24
6.5. LIMITATIONS AND FURTHER RESEARCH. ... 25
7. CONCLUSION. ... 26
8. REFERENCES. ... 27
Abstract.
Crowdfunding has emerged as a new alternative for entrepreneurs to get funded. As crowdfunding is done completely via digitalized platforms communication between entrepreneurs and investors may become difficult. Communication is a key aspect of pitching and thus is an important contributor to the success of a crowdfunding campaign. Although, crowdfunding platforms have different means of facilitating communication the use of videos and pictures and their contribution to funding percentage have been understudied. Especially, this paper aims at providing a more comprehensive view of the effect of videos and images on funding percentage while controlling for other means of success, such as the reward structure and the duration of the campaign. Drawing on a dataset of 11,534 Kickstarter projects this paper finds that videos and pictures positively affected funding percentage with pictures increasing funding percentage with 5.87% and videos increasing funding percentage with 26.55%. These results shed light on the importance of pictures and videos within Kickstarter campaigns and allow entrepreneurs to further optimize their Kickstarter campaigns to achieve optimal success.
1. Introduction.
Entrepreneurs are always struggling to receive funds in order to get started on their product idea. Traditionally, entrepreneurs would turn to family and friends and in later stages turn to venture capitalists, angel investors, or private equity firms when trying to acquire funds. However, in recent times crowdfunding has emerged as a new way for entrepreneurs to raise the needed capital (Belleflamme, Lambert, & Schwienbacher, 2014; Schwienbacher & Larralde, 2010). Crowdfunding works on the principle of presenting your business idea to the crowd and receiving relatively small donations from a large number of individual people to finance your product (Freedman & Nutting, 2015; Mollick, 2014). Individuals donate a certain amount of money in return for a reward, voting right or in some cases nothing such as charity products (Schwienbacher & Larralde, 2010). Most crowdfunding is done on online platforms which have reduced barriers for being an entrepreneur by finding investors quicker and easier (Heminway & Hoffman, 2010).
Although crowdfunding has paved the way to attract many investors from different regions, entrepreneurs often still fail as they were unable to successfully influence an online crowd (Hui, Greenberg, & Gerber, 2014). In the absence of face-to-face exchanges, communication tools become crucial to facilitate interaction between potential investors and entrepreneurs. Many forms of communication exist within crowdfunding platforms, yet a popular interaction practice is the use of comments which have been associated with increasing the chances of successfully getting funded (Kromidha & Robson, 2016). An alternative way of communication is through, the use of videos and images, and are for an online environment the closest substitutes to a face to face interaction. However, the use of pictures and videos within a Kickstarter campaign has been understudied. Videos and pictures are a great tool that entrepreneur’s frequently use to address themselves directly to investors, yet enable investors also to meet the people or team behind the product (Chan, Parhankangas, Sahaym, & Oo, 2020; Frydrych, Bock, & Kinder, 2016). Moreover, entrepreneurs who use crowdfunding platforms are often in the midst of developing products that are unfinished, investors may thus rely heavily on perception elements to determine if they provide monetary support (Davis, Hmieleski, Webb, & Coombs, 2017; Maxwell, Jeffrey, & Lévesque, 2011; Parhankangas & Ehrlich, 2014) Alternatively, videos and images are signs of preparedness which has been found to increase the chance of successfully getting funded (Mollick, 2014). However, videos and images are not the only factors that contribute to the success of a crowdfunding campaign. Many other factors such as the crowdfunding platform, the duration of the campaign, and the use of certain phrases can all increase the probability of becoming successfully funded
(Cordova, Dolci, &, Gianfrate, 2015; Hui, Greenberg, & Gerber, 2014). Therefore, this paper aims at providing a more comprehensive view of the effect of videos and images on funding percentage while controlling for other means of success, such as the reward structure, the duration of the campaign, and the funding goal of the campaign. Specifically, find an answer to the question: “To what extent do videos and images further increase funding percentage of a Kickstarter campaign after rewards and duration have been optimized for success?”
Due to the rising popularity of Kickstarter, entrepreneurs must understand how to optimize their campaigns to get the most funds. Videos and images are a great way to interact with the investors and could thus be important in receiving more funds. However, as making a video and pictures can be labor intensive and most likely will take up which valuable time, it is important to comprehend if these interaction tools truly are an advantage to a Kickstarter campaign. If choosing the right reward structure or the right duration of the campaign can achieve the same, entrepreneurs can better focus their resources on other tools which could increase the funding of their campaign. Alternatively, it is important to realize if videos and images have other valuable contributions than just increasing the chance of gaining funds. Thus, this study contributes to the existing literature of crowdfunding by helping entrepreneurs optimize their Kickstarter campaign by choosing the right resources to become successful.
The paper will in the next section asses what previous scholars have highlighted as ways that entrepreneurs can optimize their campaigns in becoming more successful. Emphasis will be placed on the funding goal, the duration of a campaign, the rewards structure, and the crowdfunding community. From these previous suggestions, the hypotheses are formulated and tested using an OLS regression. Thereafter the results will be discussed, were the main findings are that videos and pictures positively affect the funding percentage of a Kickstarter campaign. Finally, the paper will discuss why videos and pictures positively affect a Kickstarter campaign ending at the conclusion which indicates how entrepreneurs can benefit from this research.
2. Literature review.
2.1.Reward-based crowdfunding.
Reward-based crowdfunding is the most popular way of crowdfunding. In reward-based crowdfunding, entrepreneurs set up a campaign in which they try to persuade individuals to invest in their project in exchange for a reward. The reward is typically the product the entrepreneurs want to raise money for, but it can be anything from a t-shirt to being credited in
a movie. Reward-based crowdfunding can be distinguished into two different structures either being a ‘All or Nothing’ (AON) or ‘Keep it All’(KIP) structure. In the AON model, entrepreneurs set a capital goal they want to raise in a predetermined amount of days. Only if they reach that capital goal in set time, do entrepreneurs get to keep that money and are then deemed successful (Cumming, Leboeuf, & Schwienbacher, 2015). Thus from here on, every time successful is mentioned it means that entrepreneurs have raised their capital budget in time. Alternatively, KIP structures are not as strict, because the entrepreneurs get the funds whether or not they reach the budgeted capital goal in the predetermined time (Bi, Geng, & Liu, 2019). The AON structure is generally more successful and better suited for larger projects because entrepreneurs are triggered to be more committed and only undertake the project if enough capital is raised which represents a cost to the entrepreneur reducing the risk for the crowd (Cumming et al., 2015).
This paper uses Kickstarter data because it is one of the most popular reward-based crowdfunding platforms and has large datasets available, including different success factors. Kickstarter is a crowdfunding platform that makes use of the AON structure. Entrepreneurs, use the platform to pitch their product idea. Usually, this pitch consists of information about the product combined with a video and some kind of reward structure designed to attract individuals and convincing them to invest. A campaign is successful when funding is reached in a set time, entrepreneurs are determined to attain this as only then do they get to keep the money. There are different ways to create a successful Kickstarter campaign, however, the funding goal, the duration, and the reward structure within a campaign are three distinct factors that have been researched extensively and have shown to continuously be important to achieve success. Since its existence in 2009, Kickstarter has seen an increase in the number of users and has helped 181,870 products to become backed with $4,972,670,256 raised in total through its projects.
2.2.The funding goal and duration.
The funding goal is the amount an entrepreneur wants to collect during his crowdfunding campaign to start production. By lowering it a campaign can increase its chance of success (Cordova et al., 2015; Kunz, Bretschneider, Erler, Leimeister, 2017). A lower capital budget means that fewer investors have to be convinced to invest, thus it seems logical that a lower capital goal increases the chances of success. Forbes and Schaefer (2017) recommend to lower the funding goal no matter what and thereby reducing the risk of not receiving any funds. The
authors go on to say that in case that the raised capital goal is not enough entrepreneurs rather than creating one campaign with a high capital goal, they should launch a smaller second campaign using the momentum of the first one. This is advantageous especially as entrepreneurs opt for crowdfunding not only to raise capital, but also to indicate demand for a proposed product, or use crowdfunding as a form of marketing to eventually secure funding in a more traditional way via a venture capitalist or angel investor (Mollick, 2014). Thus, opting for a lower capital goal reduces the risk of not reaching the target and can simultaneously increase the chance of getting funded via a different mean, yet it also makes sure that investors, in general, have positive affiliations to the product. Another reason why lowering the funding goal can increase the chance of success is that it can deceive investors. The reason being is that Kickstarter’s way of displaying funding progress is in the form of percentages of funds received. It is deceiving because investors can think a campaign that has a higher percentage funded, has raised more money even though the actual amount of money might be lower (Forbes & Schaefer, 2017). Investors, who are more likely to invest in projects that are nearly completely funded (Agrawal, Catalini, & Goldfarb, 2011; Moysidou & Spaeth, 2016), might think that a project with a higher percentage is doing better and thus invest in that project even though it might not be the case. Investors are influenced by this as it seems more people have invested in that project because the percentage funded is higher, which is an example of the peer effect, where investors use the action of others to solidify their decision to invest themselves (Ward & Ramachandran, 2010).
The funding duration, which is the number of days a Kickstarter campaign is running for, also has an impact on success. More specifically, a shorter campaign leads to more success (Devaraj & Patel, 2016; Frydrych, Bock, Kinder, & Koeck, 2014; Kunz et al., 2017). Surprisingly, a longer duration decreases the chance of success as it highlights a lack of confidence in the product, lack of urgency, and overall procrastination (Cumming et al., 2015; Mollick, 2014; Kunz et al., 2017). Moreover, longer-lasting campaigns have more trouble maintaining project momentum, as support on crowdfunding platforms fades quickly (Ward & Ramachandran, 2010). Kuppuswamy and Bayus (2018) have found that backing behavior on Kickstarter is bathtub shaped as initially there is much interest in a project which is quickly followed by a decrease of support over most of the cycle, yet at the end, some excitements return so that the project gets funded. Therefore, a longer duration causes an extension in the non-funding period, which increases the chance that investors forget or even back out which could explain why increasing the duration might hurt funding (Chen, Thomas, & Kohli, 2016). Kickstarter allows projects to be anywhere from 1-60 days and even recommends that
entrepreneurs set the length of the campaign to 30 days or less (Kickstarter, 2020). Nevertheless, Buttice, Colombo, & Wright (2017) have found that entrepreneurs that use Kickstarter for the first time should opt for 33.33 days and more experienced users should opt for 31.78 to achieve the greatest success. So in general, campaigns should be shorter rather than longer and entrepreneurs should aim for setting their campaign around the 30 days mark to increase their chances of success.
2.3.The reward structure.
Kickstarter is a reward-based crowdfunding platform thus the rewards naturally play an important role within campaigns. Belleflamme et al. (2014) have highlighted that the rewards are beneficial for entrepreneurs because it allows them to pre-sell their product, enabling them to start production. The authors go on to say that it allows entrepreneurs to take advantage of price discriminating by discriminating between two groups of consumers namely the ones that pre-order the product and the regular customers (Belleflamme et al., 2014). Moreover, price discriminating can also take place between pledgers as different prices are paid for the same products (Kunz et al., 2017). An example of this is that many campaigns offer a certain reward in limited form early on to attract investors. If the limit is reached investors can still get the reward, yet now paying a higher price for it. The ability to price discriminate is an explanation of why increasing the reward levels increases a campaign’s chance of success (Kunz et al., 2017; Kuppuswamy & Bayus, 2018; Lin, Lee, & Chang, 2016). Limiting rewards can also increase funding by creating a sense of urgency for investors to back a campaign and thus increasing investments, yet it can also work adversely as rewards that individuals wanted are sold out making it less appealing to invest (Kunz et al., 2017; Lin et al., 2016) Alternatively, increasing rewards can confuse the investor and is known to lead to overfunding which can cause troubles for campaigners by complicating their production (Chen et al., 2016; Koch, 2016; Mollick, 2014).
Although entrepreneurs benefit from the reward structure, one of investor’s main motivations for participating on a crowdfunding platform are the rewards they get in exchange for their monetary investment (Duvall, 2014; Gerber, Hui, & Kuo, 2012). Moreover, as rewards are often tied to the donation level (higher donations lead to bigger rewards), they can be persuasive as investors increase their investments to get a certain reward they are interested in (Gerber & Hui, 2013). The recommended number of rewards is debatable with Kickstarter recommending 9 rewards, yet scholars highlighting that projects having 6 rewards up until a
maximum of 12 achieve the highest chance of success (Chen et al., 2016; Forbes & Schaefer, 2017; Kickstarter, 2020). Thus, entrepreneurs can use the rewards system to their advantage by limiting the rewards thereby increasing their chance of success (Weinmann, Tietz, Simons, & vom Brocke, 2017).
2.4.Kickstarter community.
Crowdfunding investors are not typical investors as they do not necessarily expect to gain a monetary reward from their investment (Belleflamme & Lambert, 2014). They are also motivated by human need for belonging, which they get through platforms such as Kickstarter as supporting a product allows them to be part of a special community (Gerber & Hui, 2013). Kickstarter also highly emphasizes this sense of community and praises frequent investors and tries to connect backers that have supported the same product (Gerber & Hui, 2013). Entrepreneurs are also motivated to participate and become part of the community as they can learn much from the community and gain many tips and knowledge along with investments (Gerber, 2011; Gerber & Hui, 2013). Although, campaigns usually run for a short time entrepreneurs are encouraged to build long-lasting relationships with their supporters and appreciating them with special rewards or letting them be a part of the decision-making process (Belleflamme, & Lambert, 2014; Hemer, 2011; Hui et al., 2014). Besides, entrepreneurs should attempt to involve the investors throughout the campaign and showing them that their contributions matter and are important which creates momentum and can increase the chance of success (Colistra & Duvall, 2017). The entrepreneurs that are involved within the community also attract frequent backers who are especially important to the platform as they tend to be the first ones who support a project and are in charge of 72% of the pledges on the platform (Inbar & Barzilay, 2014). The initial funding is crucial for a campaign because projects often experience tipping points which, when a certain target is reached, sends a positive signal to other backers that they should invest (quality signal of being a good project) (Kim & Viswanathan, 2013). Inbar and Barzilay (2014) have found that on Kickstarter, this tipping point is typically when 40% of the funds have been reached as this results in 97% of the projects reaching their funding goal. The Kickstarter community is facilitated by both entrepreneurs and investors and it is thus important to understand both sides of the motivational aspects that draw them to the platform. It turns out it is much more than just a platform where entrepreneurs can raise money, it is a platform whereby emotion, empathy, and collectiveness come together.
3. Hypothesis formulation. 3.1.Pictures in Kickstarter.
Entrepreneurs who use Kickstarter to get funds have a difficult task persuading investors just with the product description. Communicating all relevant information in a short, effective construction and presented as a story can increase financial investment (Martens, Jennings, & Jennings, 2007). An important way to achieve that is through the use of visuals. Visuals can often communicate more than texts (Jiang, Wang, & Benbasat, 2005) and the use of pictures can increase an individual’s apprehension of information and help with decision making (Glenberg & Langston, 1992; Lindgaard, Fernandes, Dudek, & Brown, 2006). Moreover, visuals can grab the attention of individuals evaluating business proposals and have a significant influence on the duration individuals spend on a webpage (Chan & Park, 2015; Danaher, Mullarkey, & Essegaier, 2006; Koch & Siering, 2015; Parhankangas & Renko, 2017). As individuals generally spend only about 4-5 minutes on a website the additions of pictures within a campaign can increase the time an investor spends on a page giving investors a longer interval to familiarize themselves with the whole product (Gerber et al., 2012). Thus this paper hypothesizes:
Hypothesis 1: The funding percentage of a Kickstarter campaign increases when a Picture is added.
3.2.Videos in Kickstarter.
A video is also a great way to gain the attention of investors because of the possibility to include dynamic scenes and sound effects (Jiang & Benbasat, 2007). Videos are advantageous because they display information dynamically which makes them more effective than the static information portrayed by images (Park & Hopkins, 1992). Including a video in a campaign also reduced barriers for getting informed, investors do not need to read the entire project, rather they can watch the video and get the information they need (Koch & Siering, 2015). Parhankangas and Renko (2017), have found that different linguistic styles have no impact on the success of a campaign and explain that this occurs because videos and images go a long way in clarifying the mind of crowdfunding investors, which undermines the use of linguistic styles. Mollick (2014) and Kickstarter (2020) have also highlighted that including a video is a sign of quality and preparedness which is often associated with more funding. Moreover,
investors who watched a video of high-quality associate these qualities with the project itself (Chan et al., 2020). A project can also illustrate organizational legitimacy by providing additional information about the founding team (Kotha & George, 2012; Zhao, Song, & Storm, 2013). Research has highlighted that more traditional investors such as venture capitalists see information about the founding team as critical for the decision-making process (Zimmerman & Zeitz, 2002; Baum & Silverman, 2004). Frydrych et al. (2014), have found that reward-based crowdfunding investors look at the team composition as well, to assess whether or not to invest. Videos are often addressed directly to the crowd and allow investors to get to know the team and gain a much better insight into the product (Chan et al., 2020; Kunz et al., 2017). Despite this, Frydrych et al. (2014) and Cordova et al. (2015) have found that videos do not influence funding, emphasizing that videos have become a necessity instead of being a sufficient criterium for successful funding. Thus it seems that scholars are divided whether videos are important or not, therefore, this paper hypothesizes that:
Hypothesis 2: The funding percentage of a Kickstarter campaign increases when videos are added.
4. Data and method.
To test the hypotheses, Kickstarter data were selected starting from May 2009 till November 2016. Kickstarter is used because it is the largest reward-based crowdfunding platform which has also been used by many other studies (Chan et al., 2020; Parhankangas & Renko, 2017). The data set is compiled of 29,788 Kickstarter campaigns before any transformations.
4.1.Variables:
Dependent variable: Throughout our hypotheses, the funding percentage attained during the Kickstarter campaign is the dependent variable. As this variable was not originally in the dataset this variable had to be created. For this, the amount raised in dollars and the funding goal in dollars were needed. The funding percentage was calculated by 𝐴𝑚𝑜𝑢𝑛𝑡 𝑟𝑎𝑖𝑠𝑒𝑑 $
𝑓𝑢𝑛𝑑𝑖𝑛𝑔 𝑔𝑜𝑎𝑙 $ and was
called Pfunded (percentage funded). To calculate the funding percentage, extreme values had to be removed. For the funding goal, the same approach as Mollick (2014) was used to remove the extreme values. Thus, all values below 100$ (90 values) and above a million dollars (86 values) were removed. Moreover, for the variable amounts raised all projects that raised less
then 10$ (1543 values) were removed. 10$ was used as the cutoff value as this made sure that all canceled products and unrealistic products were removed from the sample which would skew the results.
Independent variables: The independent variable for the first hypothesis was Nimages. This variable indicated how many images were presented during a campaign and is a numerical variable. The second independent variable is Dvideo (Dummy video) which is a dummy variable which was coded as 1 being that a video was included in the project and 0 representing that no video in a campaign was included. The dummy variable for video was used rather than the numerical variable because the numerical variable for video was inconsistent and inaccurate as many projects that had a video were somehow not included in the variable.
Control variables: The control variables used to test the two hypotheses are Rewards, Duration, and Comments. Rewards are the number of rewards that are offered during a Kickstarter campaign and are represented numerically. As rewards affect funding and thus could influence the results obtained for our hypothesis, in this paper, it was decided to restrict the rewards to minimize the effect that rewards could have on the funding percentage. As a benchmark to the restrictions, we took what previous scholars have said that projects with 6-12 rewards have a higher probability of success (Chen et al., 2016; Forbes & Schaefer, 2017; Kickstarter, 2020). In this paper, the rewards were restricted to 4 and 14. This was chosen as the range entailed the mean (8.5 rewards), increased the sample size so that the majority of the dataset (66.7%) was included while also staying relatively close to what previous scholars have suggested. Within this range of rewards, one data point gave an error this data point was removed.
The second control variable is the duration of the project. This variable represented the number of days a campaign ran for (numerically). Again, it has previously been highlighted that the duration of a project could also affect percentage funding, which again this study wants to minimize thus the duration of projects was also restricted. Kickstarter recommends that entrepreneurs set their campaign to 30 days or less and scholars have hinted that opting for a slightly higher number increases the chance of success (Buttice et al., 2017). It was thus decided to opt for a range of days of 24 up until 36 days. A cut off value of 24 days was chosen as only 9.2% of the projects chose a duration less than 24 days. In contrast, the upper boundary of 36 days was chosen because the mean number of days was 35.7 in the dataset. Overall the range again entailed the majority of the projects 61.8%.
The last control variable is the number of comments a project entailed (numerical variable), which typically are investor’s questions or updates about the product. Although comments have
also been found to affect funding (Kromidha & Robson, 2016), the dataset used for this paper did not include any information about what the comments entailed. By not knowing if the comments entailed updates or answers to questions that investors might have had, it was decided to not transform the comment variable so that the sample size stayed bigger. Thus, the comment variable is used without any transformation.
Thus, after all the alterations the final data sample contains 11,534 values (29,788 – 11535 = 18253 data point removed). From this sample, 5075 projects were successful which brings the success rate up to 44,00%. This is an improvement to the success rate that Kickstarter themselves observe (37.44%), which is logical as many extreme values have been removed. In the sample 9283 project (80.48%) included a video in their campaign and 6522 (56.54%) included a picture.
4.2.Data analyses.
The hypotheses were tested by doing a multiple regression, model 1 was Pfunded regressed on Nimage with Comments, Duration, and rewards as control. Model 2 was Pfunded regressed on Dvideo with Comments, Duration, and rewards as control. The last model was Model 3 which was another regression with Pfunded being regressed on both Dvideo and Nimage with the same control variables. The three models are summarized in Table 2.
The means standard deviations and the correlations for all variables used within the models are summarized in Table 1. All variables were checked for multicollinearity with the help of the correlation matrix. High correlation values of approximate 0.7 between independent variables indicate multicollinearity (Draper, 2014; Menard, 2002). The greatest value of the correlation matrix is 0.2237 which is smaller than 0.7 thus multicollinearity is not a problem in this analysis. A scatterplot of the residuals indicated that heteroscedasticity was present
Table 1. Means (M), Standard deviations (SD), Pearson correlation for all variables
Variables M SD 1 2 3 4 5 6 1. Pfunded 1.1386 .0317 (-) 2. Nimage 5.8807 .0882 0.1918 (-) 3. Dvideo .80484 .0037 0.0452 0.1093 (-) 4. Comments 33.4844 3.9284 0.2195 0.1317 0.0284 (-) 5. Duration 30.2709 .0188 0.0067 0.0617 0.0283 0.0055 (-) 6. Rewards 8.2470 .0260 0.0611 0.2237 0.1867 0.0544 0.0641 (-)
(Appendix I). Thus, all regressions were done using heteroskedasticity robust standard errors which eliminate worries if heteroskedasticity is present (Stock & Watson, 2015).
5. Results
5.1.The effects of pictures and videos.
Hypothesis 1 predicted that images have a positive effect on the funding percentage. As can be seen from Table 2 (model 1) the coefficient for images (variable Nimages) is both positive and statistically significant (model 1; Nimage: 𝛽 = 0.0587, p < 0.01), thus lending support to Hypothesis 1. Specifically, the results indicate that the addition of images within a Kickstarter campaign increases funding by 5.87%. Similarly, hypothesis 2 which predicted that videos have a positive effect on funding percentage also received support (model 2; Dvideo : 𝛽 = 0.2655, p < 0.01). Thus, including videos in a Kickstarter project has a positive effect of 26.55% on funding percentage compared to projects without a video. The third model had both the independent variables Dvideo and Nimages included in the regression to check for omitted variable bias. As we can see from Table 2 (model 3) both variables are still significant and are both positive (model 3; Nimage: 𝛽 = 0.0582, p < 0.01, Dvideo : 𝛽 = 0.1725, p < 0.01) yet their effect on percentage funded changed (coefficient). Especially for videos, this difference is large as the coefficient decreased by 9.3% compared to model 2 meaning that when images and videos are both included within a Kickstarter project, videos have a smaller effect on percentage funding. Moreover, from Table 2 we can also see that the constant (𝛽0) for P-funded is relatively high in model 1 and 3 (0.8718 and 0.7873) and significant (p < 0.1), this means that when these variables are used in the regression, projects generally tend to have a funding percentage of 87.81% and 78.73%. What is surprising is that the inclusion of the variable Dvideo causes the constant (𝛽0) to drops, an explanation could be that if videos are of great quality and investor’s enjoy them funding percentage increases, however, if the quality of the video is low and investors do not enjoy the video, it causes the effect of videos to be negative.
Further, from Table 2 it can be noted that in almost every regression the control variables are insignificant. It seems a bit strange that comments do not have any influence on the percentage funded. Especially, after research has indicated that comments affect funding positively (Hornuf & Schwienbacher, 2018; Kromidha & Robson, 2016). It could be that there are many irrelevant comments posted and thus using the variable without filtering for relevant information, which could influence investors, such as questions answered by entrepreneurs makes the variable insignificant. Moreover, the variable duration is also insignificant
throughout all three regression. This could be a sign that restricting the duration to 24 to 36 days works in making campaigns more optimized.
Thus if entrepreneurs adjust the duration of their campaign to around 30 days the duration of the campaign will have no impact on funding percentage. Lastly, the variable rewards is insignificant in two regressions (model 1 & 3), yet is significant in model 2. Rewards, could in this case be significant because videos often visualize rewards and thus making certain rewards
Table 2. regressions (1) (2) (3) Variables Model 1 (Image) Model 2 (Video) Model 3 (Image, video) Pfunded .8718* (.4159) .3363 (.4256) .7837* (.4168) Nimage .0587*** (.0104) .0582 *** (.0104) Dvideo .2655 *** (.0604) .1725 *** .0572 Comments .0016 (.0010) .0017 (.0011) .0016 (.0010) Duration -.0091 (.0134) .0031 (.0135) -.0095 (.0134) Rewards .0174 (.0129) .0530 *** (.0139) .0132 (.0130) Observations 11,534 11,534 11,534 R2 0.0754 0.0515 0.0758 F- value 16.51 *** 14.75*** 16.36***
Heteroscedasticity SE is in the parenthesis *** p<0.01, ** p<0.05 , * p<0.1
more favorable, which could lead to investors increasingly choosing that reward thereby increasing the funding percentage. Alternatively, the variable rewards could be significant, because the selected range of keeping rewards between 4 and 14 might not be the optimal range. It is possible that by increasing rewards, a higher percentage of funding might be achieved. However, this effect is minimal as it accounts for about 5.3% of the funding percentage.
5.2.The effect of videos for certain categories.
Although videos, in general, have a large effect on percentage funding it might not be the same case for every category. Kickstarter has 15 different categories and each project is labeled within a certain category. The most popular categories in this data set were Design, videos & films, games, music, and technology. It would make sense that different categories benefit more from a video than other categories. For example, it could be that for music projects, videos might have a relatively low effect on percentage funded but for design products, it might be more important. To test the interaction effect of how videos influence funding percentage per category a couple of things need to be done. Firstly, a dummy variable was made for each category and coding them each with a different number. So Art which is alphabetically the first category was coded with a 1 and comics were coded with a 2 and so on for all categories (how all categories were coded can be found in appendix II).
In Table 3 the results are summarized. Model 4 is a double interaction to find if the different categories are affected by a video with respect to percentage funding. This was done as follows. A new variable was created called Categorycoded which interacted every category to the first category ‘Art’. Thus Art * Technology, Art*Design etc. Then a regression was done where Dvideo (dummy variable video) interacted with Categorycoded on Pfunded. The results of the most popular categories within this dataset are summarized in Table 3 (the rest can be found in the appendix III ). As can be seen from Table 3 Technology is the only significant category (p<0.01). This highlights how much bigger the effect on Pfunded is when a video is included in a project if that project falls under the technology category in comparison to the art category. As the coefficients in model 4 are difficult to interpret, another regression was done where the coefficients are represented in margins this is also summarized in Table 3 under model 5. This highlights that Pfunded increases by 196.68% when a video is included in a project of the technology category compared to the art category. This highlights that technology
is the category where further analysis is needed as this category indicates that videos have a bigger effect on the percentage funded.
Table 3. Interaction model
Model 4.
Interaction with popular
categories
Model 5.
Interaction with popular categories (margins)
Variables Coefficient model Margins model
Art .8217 (.0938) .8217 Dvideo × Categorycoded Art ×Technology 1.0460 (.3400)*** 1.9668*** Art × Design -.1859 (.4470) 1.8556
Art × film & video -.0951 (.1315) .4576 Art × games -.2706 (.3192) 1.7225 Art × music .01574 (.1336) .9516 Observation 11,534 F-value 19.13 *** R-squared 0.0227
first number is coefficient
in parentheses is the heteroscedasticity SE *** p<0.01, ** p<0.05 * p<0.1
So a follow-up regression was done. This time the only category that was used in the regression was technology, this variable was used as a dummy variable where 1 represents that the project was within the technology category and 0 indicated that the project was in any other category. Thus, Pfunded was regressed against another interaction effect of Dvideo on Dtechnology (Dvideo × DTechnology). The results are summarized in Table 4 and from the table we can see that Dtechnolgy is still significant (p<0.01). Moreover, to make interpretation easier again another regression was run to find the margins (gives us the expected value) which are summarized from in Table 5. Thus, from Table 5. we can identify that the effect on Pfunded is 196.68% greater when a video is included in a project that is labeled as a technological project compared to a project that is labeled as any other project. Moreover, Table 5 also illustrates what the effect is on Pfunded when a project within the technology category does not include a video (60.14%).
Table 4. interaction model with only technology Variables Model 5 Pfunded .8385 .0496 1.Dvideo .3180 .0606 1.Technology -.2371 .1765 Dvideo×Dtechnology 1 1 1.0474 .3227 Observations 11,534 F-value 15.42 R-squared 0.0051
Parentheses is the heteroscedasticity SE *** p<0.01, ** p<0.05 * p<0.1
Table 5. interaction model with only technology (margins) VARIABLES Dvideo×dDtechnology Model 6 Margins 0 0 .8385 *** 0 1 .6014 *** 1 0 1.1565 *** 1 1 1.9668 *** OBSERVATIONS 11,534 *** P<0.01
A reason why Pfunded increases by such a large percentage (196.68%) when a video is included within the technology campaign is due to the extreme differences of funding within the sample. In the sample few technological projects have no videos (120) and these same projects tend to have low funding. Alternatively, technological projects with videos are much more frequent (663) and if they succeed tend to succeed by large margins (mean of Pfunded for technology projects that succeed = 565.10%). These large differences in funding are also reflected in the results. Although, videos might have a large effect is seems unlikely that videos are solely responsible for this increase thus this value (196,68%) gives us an indication that videos are important contributors to Pfunded, but the actual percentage might in actual fact be lower.
So, overall these tests have highlighted that the use of videos is more important for the technology category than any other category. Surprisingly, other categories did not have a significant effect, especially the category film & video, and games were expected to be significant, as individuals might want to know what style of film is being made and how it is going to look. The same can be said for games, individuals might be interested in how a game is going to look or visualize the playing experience before investing.
6. Discussions.
Crowdfunding has emerged as a new way of getting seed capital breaking barriers to becoming an entrepreneur. The reward-based model has become popular under entrepreneurs, but also under individuals who enjoy backing projects they believe in, in exchange for rewards. Yet, the online pitching environment has made it difficult to establish a trusted relationship while also allowing the entrepreneurs to successfully persuade investors. The use of visuals can help in increasing trust and enables entrepreneurs to convey emotion and increases communication via the web. This paper has found that the addition of images and videos within a Kickstarter campaign has a positive effect on the funding percentage of a campaign even though the duration of the campaign and the rewards of a campaign were optimized for success.
6.1.Images.
The results from this empirical study are in line with previous studies, highlighting that the addition of pictures increases funding percentage of a crowdfunding campaign (Buttice et al., 2017; Koch & Siering, 2015). Pictures, effect funding positively as research has found that vividness in a product presentation is a sign of quality (Jiang et al., 2005). As pictures are not
present in every campaign the inclusion of them can indicate that entrepreneurs have put in more effort to convince investors, which investors could perceive as a quality signal which increases the chances of success (Mollick, 2014). Moreover, pictures aid in apprehension and help investors assess projects’ main intentions and functionalities (Glenberg & Langston, 1992; Kunz et al., 2017). Aside from pictures attracting investors they also increase investor’s trust in the campaign if the pictures contain the founders or the team members (Boeuf, Darveau, & Legoux, 2014; Di, Sundaresan, Piramuthu, & Bhardwaj, 2014). The pictures of the founders have an even stronger effect if the facial expressions are happy, as this makes investors feel welcoming and increases the chances of success (Rhue & Robert, 2018).
Nevertheless, in this study images had only a small effect on funding percentage (5.82%) indicating that investors enjoy them, yet they are not crucial to the success of a campaign. It could be that because pictures just demonstrate a small snapshot they express insufficient information for investors to completely understand the product and convince them of funding (Koch & Siering, 2015). On the other hand, as crowdfunding is still relatively new entrepreneurs might not use pictures in their optimal way to increase funding percentage which could be an indication as to why the positive effect was low during this study. A way that entrepreneurs could optimize the use of pictures is if their project permits it, is to portray sadness through the campaign’s pictures as this creates empathy and increase the chances of getting funded (Hou, Zhang, & Zhang, 2019; Liang, Chen, & Lei 2016; Small & Verrochi, 2009). Moreover, pictures that include a child or more people can also increase the rate of success (Rhue & Robert 2018). Therefore, pictures are a contributor to percentage funded, yet entrepreneurs could further optimized pictures to enhance project success rate.
6.2.Videos.
The results of the study also indicated that the inclusion of videos has a positive effect on percentage funding. This is in line with what Mollick (2014) has found, highlighting that videos are signs of quality and thus increase the chance of success. Crowdfunding investors are in that sense similar to normal investors as they base their decisions to invest on quality signals. Alternatively, videos also help entrepreneurs to differentiate themselves from other projects by being able to be creative. Creativity helps with attracting and convincing investors as it demonstrates quality, great potential, and high passion (Davis et al., 2017; Szymanski, Kroff, & Troy, 2007; Ward, 2004). Besides, videos are an efficient and easy way to convey information to investors and many investors base their decision to invest purely on the
information that is conveyed throughout the video (Koch & Siering, 2015; Parhankangas & Renko, 2017), which could explain videos persuasive power.
The importance of videos also has to do with how Kickstarter designs the campaign pages, where videos are typically the first thing investors are confronted with. This has the advantage that if the video is of great quality and all the necessary information is presented investors have a positive perception of the product and can be more inclined to invest. However, if the video is of poor quality investors strongly criticized the campaign, doubt the ability of the entrepreneur, and interpret this video as a sign of unprofessionalism (Dey, Duff, Karahalios, & Fu, 2017), which thus could be fatal for the campaign. Therefore, videos have to be extremely well designed so that investors are convinced to invest after watching them. In order to do that entrepreneurs should, to the best of their ability realize what kind of people they especially want to attract and in what way they want to do that. Campaigns that offer intangible products such as movies or musical projects can increase their success by directing themselves to consumers by using a more emotional approach (Manning & Bejarano, 2017). In general, using an emotional approach throughout videos can be effective as crowdfunding investors join platforms to become part of a community, thus emphasizing that investors can become part of the journey and the team through their investments can be very persuasive and increase investments. (Gerber & Hui, 2013; Manning & Bejarano, 2017). On the other hand, projects that are more compilated and ask for more money should highlight more factual information to justify their need for money and often approach potential investors in a more transactional manner (Dey et al., 2017; Manning & Bejarano, 2017). Although, different projects might have different ways to attract more individuals the most important aspect is that the right information is communicated effectively. Investors are often interested in previous progress, future development, and how a project differentiates itself from other projects to decide if they want to invest (Manning & Bejarano, 2017). To convey all of this information in 4 to 5 minutes which is the average time people spend on a webpage is a difficult task (Gerber et al., 2012). A video can be the perfect way to communicate all that information, especially if done in a narrative way which brings everything into context so that future plans and objectives can be assessed as plausible in light of previous accomplishments and which can have a big positive effect on funding (Navis & Glynn, 2011; Teece, 2010). If done correctly the videos can enable entrepreneurs to showcase professionalism and experience which can lead to investors associating these qualities with the project itself (Chan et al., 2020; Joenssen, Michaelis, & Müllerleile, 2014; Tirdatov, 2014). Thereby, making videos an effective tool and are reasons that explain why videos have such a high positive effect on funding percentage. However, as
videos only aid a campaign when they showcase quality entrepreneurs are inclined to spend more time to professionalize videos. This in turn could suggest that projects that have solid videos have an overall higher quality as more time is spent creating the campaign. Therefore, investors might be more inclined to invest in a project not necessary because a video is included, but because the overall quality of a campaign is greater, which might also be a reason why videos are found to be so effective throughout this study.
Unexpectedly, this study has found that when videos and images are combined together in a campaign the positive effect of videos is decreased from 26.55% to 17.25%. This strangely indicates that images have a large negative effect on video’s effective power. An explanation could be that pictures are included in the product title and videos are not. Thus if the picture that is contained in the title is not appealing, individuals might never click on the campaign page and thus never get to see the video. Another reason might be that individuals compare the video quality to the image quality, as less time might be spent on images as their contribution to funding is not so important, it could give a bad quality signal. As most Kickstarter investors are less experienced than normal investors with 69% of investments being done by first-timers (Davis et al., 2017), they base their decision to invest often on quality signals such as the number of other backers and the funding percentage at the time of investments rather than on pure factual information (Kim & Viswanathan, 2013). Therefore, seeing that the quality of the images does not match the quality of the pictures could reduce investment. Thus, it is important for entrepreneurs to realize that using pictures can be beneficial but if the pictures are of bad quality, including them into a campaign can decrease the effectiveness of the videos by more than pictures themselves add (9% compared to 5%). This indicated that entrepreneurs should only include images if they truly help the campaign and are of good quality.
6.3.The reward structure and the duration of the campaign.
The reward structure and the duration of campaigns were in this study optimized for success. The rewards were set to a range of 4 – 14 and the duration of the campaign were set to a range of 24 -36 days. The rewards variable was only significant in model 2 (Table 2) which was the regression that only included videos. The significance of the result illustrates that rewards even within the range of 4-14, had a positive effect on funding. This highlights that increasing the rewards structure could positively affect the funding percentage and indicates that that the chosen range (4-14) for rewards could be further optimized when a campaign only entails a video. These results could thus be in line with what Chen et al. (2016) and Forbes and
Schaefer (2017) have found, that the optimal reward structure is in the range of 6 – 12. In contrast, the duration of the campaign was in none of the regressions significant which could indicate that optimizing the duration of a project to around the 30 days mark is effective in optimizing a campaign. Overall though most projects had the rewards structures and the duration of their projects set to what Kickstarter recommended (rewards set around 9 and duration less than 30 days) which indicates that most entrepreneurs take on the advice of Kickstarter. This means that as most of the projects adapt the same number of rewards and number of days a campaign runs for, these tools become less important for funding as all projects will eventually have nearly the same values. This indicates that the use of videos and images which are important ways to differentiate yourself can become even more important in the near future.
6.4.Videos in the Technology category.
The findings of the interaction regression, highlighting which category benefits the most from the use of video, is the technology category. Videos in that category are crucial as they increase the percentage funded by 196,68%. Technological firms often make use of crowdfunding platforms to start production on their product, yet having a successful campaign might provide these projects with extra funding via more traditional ways. Thus, to make projects interesting for venture capitalists or angel investor’s market demand and potential must be illustrated which is better achieved with big projects that succeed (Roma, Petruzzelli, & Perrone, 2017). To achieve this, high quality has to be represented which is difficult to portray as technological campaigns often produce intangible products, which prohibits investors to be able to judge the quality of the product. Therefore, professional investors rely on observable attributes to inform themselves on the overall quality of the project (Ahlers, Cumming, Günther, & Schweizer, 2015; Baum & Silverman, 2004; Shane & Cable, 2002; Stuart, Hoang, & Hybels, 1999). Videos play an important role in this, as they are known elements that signal quality, but also because the number of pictures does not influence the success of technological projects (Joenssen et al., 2014; Mollick, 2014). Therefore, this might explain why such a high impact of videos within technological projects was found in this study. However, the fact that other categories are not significantly affected by the presence of videos might emphasize that videos in some categories can be seen as a necessity for projects that without them a project cannot be taken seriously and thus are not necessarily a tool that increases the chance of success (Frydrych et al., 2014; Cordova et al., 2015).
6.5.Limitations and further research.
The present study has several limitations that should be taken into account. Firstly, the dataset used in this study is from 2009 to 2016. This means that the data and the results might not be completely applicable to Kickstarter today, as entrepreneurs could have learned a lot since then and could have been able to optimize more aspects of campaigns that lead to more success. Likewise, due to the increasing popularity of crowdfunding the platform might have attracted different investors who might not value the importance of video and pictures to the same extent anymore. Furthermore, this study was limited to which control variables could be included that were relevant to the dependent variable (Pfunded) and not inconsistent. This might also be a reason why the 𝑅2(the overall fit of the model) was relatively low and thus might not be a good predictor for the population. It would have been interesting to include other control variables such as social media’s effect on a campaign. Social media might play an important role in the effectiveness of videos, especially because when a campaign is shared the video is shared instead of the whole campaign, which could enhance the power videos have. Moreover, as social media is becoming increasingly important in society especially for younger people, which most crowdfunding investors are (Davis et al., 2017), it would have been interesting to include social media as a control variable which would give a more accurate prediction of the effect of videos and pictures on percentage funding. Moreover, it would have been meaningful to assess what made videos so effective, was it the emotional messaging that convinced investors or rather that they received relevant information in a short and comprehensive manner or a combination of both. This study was also mainly focused to benefit potential entrepreneur’s on Kickstarter, thus these results might not be valid for other platforms such as GoFundMe or Indiegogo. Moreover, the perspective of investors was barely touched upon in this paper thus it would have benefited the study if an additional qualitative study was done, focusing on what investors enjoyed from a video pitch and what kind of pictures persuade them. This would make for good future research as little is known about what investors enjoy seeing within a video or a picture. To be more precise it would be interesting to know what the ideal length of a video would be if including a different kind of background music would change the attitude of investors or that including more animations would have an effect. It would also be beneficial for entrepreneurs to know what the typical ages are of crowdfunding investors as this would allow entrepreneurs to optimize the videos and pictures so that they would most likely attract that age and thus could increase the success rate of campaigns.
Moreover, the interaction between videos and pictures would be curious to investigate further. As this study highlighted that the combination of both pictures and video’s in a campaign decreased video’s effect on percentage funding, it would be important to better understand why this occurs and how pictures and videos could optimize each other so that their effectiveness would increase. Lastly, it would be curious to see if platforms such as Crowdfunder and Crowdsupply, which appeal more to technological projects experience the same importance that videos have on percentage funded.
7. Conclusion.
This study highlights that videos and images have a positive effect on funding percentage even though the number of rewards and the duration of projects was optimized for success. It is important that entrepreneurs make use of pictures, but especially videos in their Kickstarter campaign to increase their chances of getting funded. However, entrepreneurs should only include videos and images when the quality is sufficient otherwise, it can harm the success rate of a campaign. Videos and pictures can be made more efficient by using emotions throughout them and are in general important communication tools that can help investors better understand the product in a short time, increasing the likelihood of investments. Additionally, the use of videos within technological projects is extremely important and entrepreneurs should include them at all times to increase their funding percentage. Lastly, it is expected that entrepreneurs will continue to optimize the use of pictures and videos so that they stay relevant for the years to come and scholars are encouraged to further delve into the topic to highlight new findings and thereby increase the success rate for Kickstarter projects.
8. References.
Agrawal, A. K., Catalini, C., & Goldfarb, A. (2011). The geography of crowdfunding (No. w16820). National bureau of economic research.
Ahlers, G. K., Cumming, D., Günther, C., & Schweizer, D. (2015). Signaling in equity crowdfunding. Entrepreneurship theory and practice, 39(4), 955-980.
Baum, J. A., & Silverman, B. S. (2004). Picking winners or building them? Alliance, intellectual, and
human capital as selection criteria in venture financing and performance of biotechnology startups. Journal of business venturing, 19(3), 411-436.
Belleflamme, P., & Lambert, T. (2014). Crowdfunding: Some empirical findings and microeconomic underpinnings. Available at SSRN 2437786.
Belleflamme, P., Lambert, T., & Schwienbacher, A. (2014). Crowdfunding: Tapping the right crowd. Journal of business venturing, 29(5), 585-609.
Bi, G., Geng, B., & Liu, L. (2019). On the fixed and flexible funding mechanisms in reward-based crowdfunding. European Journal of Operational Research, 279(1), 168-183.
Boeuf, B., Darveau, J., & Legoux, R. (2014). Financing creativity: Crowdfunding as a new approach for theatre projects. International Journal of Arts Management, 16(3).
Buttice, V., Colombo, M. G., & Wright, M. (2017). Serial crowdfunding, social capital, and project success. Entrepreneurship Theory and Practice, 41(2), 183-207.
Chan, C. R., Parhankangas, A., Sahaym, A., & Oo, P. (2020). Bellwether and the herd? Unpacking
the u-shaped relationship between prior funding and subsequent contributions in reward-based crowdfunding. Journal of Business Venturing, 35(2), 105934.
Chan, C. S. R., Park, H. D., 2015. How images and color in business plans influence venture investment screening decisions. Journal of Business Venturing, 30(5), 732–748.
Chen, S., Thomas, S., & Kohli, C. (2016). What Really Makes a Promotional Campaign Succeed on a
Crowdfunding Platform?: Guilt, Utilitarian Products, Emotional Messaging, And Fewer But Meaningful Rewards Drive Donations. Journal of Advertising Research, 56(1), 81-94.
Colistra, R., & Duvall, K. (2017). Show me the money: importance of crowdfunding factors on backers’ decisions to financially support kickstarter campaigns. Social Media+ Society, 3(4),
2056305117736942.
Cordova, A., Dolci, J., & Gianfrate, G. (2015). The determinants of crowdfunding success: evidence from technology projects. Procedia-Social and Behavioral Sciences, 181, 115-124.
Cumming, D. J., Leboeuf, G., & Schwienbacher, A. (2015). Crowdfunding models: Keep‐it‐all vs. all‐ or‐nothing. Financial Management.
Danaher, P. J., Mullarkey, G. W., & Essegaier, S. (2006). Factors affecting web site visit duration: A cross-domain analysis. Journal of Marketing Research, 43(2), 182-194.
Davis, B. C., Hmieleski, K. M., Webb, J. W., & Coombs, J. E. (2017). Funders' positive affective reactions to entrepreneurs' crowdfunding pitches: The influence of perceived product creativity and entrepreneurial passion. Journal of Business Venturing, 32(1), 90-106.
Devaraj, S., & Patel, P. C. (2016). Influence of number of backers, goal amount, and project
duration on meeting funding goals of crowdfunding projects. Economics Bulletin, 36(2), 1242-1249. Dey, S., Duff, B., Karahalios, K., & Fu, W. T. (2017, February). The art and science of persuasion: not all
crowdfunding campaign videos are the same. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 755-769).
Di, W., Sundaresan, N., Piramuthu, R., and Bhardwaj, A. 2014. Is a Picture Really Worth a Thousand Words? – On the Role of Images in E-Commerce, presented at the International Conference on Web Search and Data Mining.
Draper, N. R. (2014). Ridge Analysis in Experimental Design. Wiley StatsRef: Statistics Reference Online.
Duvall, K. M. (2014). Active consumerism: Measuring the importance of crowdfunding factors on backers' decisions to financially support Kickstarter campaigns.
Forbes, H., & Schaefer, D. (2017). Guidelines for successful crowdfunding. Procedia CIRP, 60(1), 398-403.
Freedman, D. M., & Nutting, M. R. (2015). Equity crowdfunding for investors: A guide to risks, returns, regulations, funding portals, due diligence, and deal terms. John Wiley & Sons.
Frydrych, D., Bock, A. J., & Kinder, T. (2016). Creating project legitimacy–the role of entrepreneurial narrative in reward-based crowdfunding. International perspectives on crowdfunding: Positive, normative and critical theory, 99-128.
Frydrych, D., Bock, A. J., Kinder, T., & Koeck, B. (2014). Exploring entrepreneurial legitimacy in reward- based crowdfunding. Venture capital, 16(3), 247-269.
Gerber, E. (2011). Innovation self-efficacy: Fostering beliefs in our ability through and by design. core77.
Gerber, E. M., & Hui, J. (2013). Crowdfunding: Motivations and deterrents for participation. ACM Transactions on Computer-Human Interaction (TOCHI), 20(6), 1-32.
Gerber, E. M., Hui, J. S., & Kuo, P. Y. (2012, February). Crowdfunding: Why people are motivated to
post and fund projects on crowdfunding platforms. In Proceedings of the international workshop on design, influence, and social technologies: techniques, impacts and ethics (Vol. 2, No. 11, p. 10). Northwestern University Evanston, IL.
Glenberg, A. M., & Langston, W. E. (1992). Comprehension of illustrated text: Pictures help to build mental models. Journal of memory and language, 31(2), 129-151.
Hemer, J. (2011). A snapshot on crowdfunding (No. R2/2011). Arbeitspapiere Unternehmen und Region. Heminway, J. M., & Hoffman, S. R. (2010). Proceed at your peril: crowdfunding and the securities act of
1933. Tenn. L. Rev., 78, 879.
Hornuf, L., & Schwienbacher, A. (2018). Market mechanisms and funding dynamics in equity crowdfunding. Journal of Corporate Finance, 50, 556-574.
Hou, J. R., Zhang, J., & Zhang, K. (2019, January). Can Title Images Predict the Emotions and the Performance of Crowdfunding Projects?. In Proceedings of the 52nd Hawaii International Conference on System Sciences.
Hui, J. S., Greenberg, M. D., & Gerber, E. M. (2014, February). Understanding the role of community in crowdfunding work. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing (pp. 62-74).
Inbar, Y., & Barzilay, O. (2014). Community impact on crowdfunding performance. Available at SSRN 2524910.
product understanding. Mis Quarterly, 475-500.
Jiang, Z., Wang, W., & Benbasat, I. (2005). Multimedia-based interactive advising
technology for online consumer decision support. Communication of the ACM, 48(9), 93–98.
Joenssen, D., Michaelis, A., & Müllerleile, T. (2014). A link to new product preannouncement: Success factors in crowdfunding. Available at SSRN 2476841.
Kickstarter. 2020. Creator Handbook. Retrieved from https://www.kickstarter.com/help/handbook Kim, K., & Viswanathan, S. (2013). The Experts in the Crowd: The Role of Reputable Investors in a
Crowdfunding Market (SSRN Scholarly Paper No. ID 2258243). Rochester, NY: Social Science Research Network. Retrieved February, 26, 2014.
Koch, J. A. (2016). The phenomenon of project overfunding on online crowdfunding platforms–Analyzing the drivers of overfunding.
Koch, J. A., & Siering, M. (2015). Crowdfunding success factors: The characteristics of successfully funded projects on crowdfunding platforms.
Kotha, R., & George, G. (2012). Friends, family, or fools: Entrepreneur experience and its implications for equity distribution and resource mobilization. Journal of business venturing, 27(5), 525-543. Kromidha, E., & Robson, P. (2016). Social identity and signalling success factors in online
crowdfunding. Entrepreneurship & Regional Development, 28(9-10), 605-629.
Kunz, M. M., Bretschneider, U., Erler, M., & Leimeister, J. M. (2017). An empirical investigation of signaling in reward-based crowdfunding. Electronic Commerce Research, 17(3), 425-461. Kuppuswamy, V., & Bayus, B. L. (2018). Crowdfunding creative ideas: The dynamics of project
backers. In The economics of crowdfunding (pp. 151-182). Palgrave Macmillan, Cham. Liang, J., Chen, Z., & Lei, J. (2016). Inspire me to donate: The use of strength emotion in donation
appeals. Journal of Consumer Psychology, 26(2), 283-288.
Lin, Y., Lee, W. C., & Chang, C. C. H. (2016, August). Analysis of rewards on reward-based crowdfunding platforms. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 501-504). IEEE.
Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention web designers: You
have 50 milliseconds to make a good first impression! Behaviour & Information Technology, 25(2), 115–126.
Manning, S., & Bejarano, T. A. (2017). Convincing the crowd: Entrepreneurial storytelling in crowdfunding campaigns. Strategic Organization, 15(2), 194-219.
Martens, M. L., Jennings, J. E., & Jennings, P. D. (2007). Do the stories they tell get them the
money they need? The role of entrepreneurial narratives in resource acquisition. Academy of management journal, 50(5), 1107-1132.
Maxwell, A. L., Jeffrey, S. A., & Lévesque, M. (2011). Business angel early stage decision making. Journal of Business Venturing, 26(2), 212-225.
Menard, S. (2002). Applied logistic regression analysis (Vol. 106). Sage.
Mollick, E. (2014). The dynamics of crowdfunding: An exploratory study. Journal of business venturing, 29(1), 1-16.
Moysidou, K., & Spaeth, S. (2016, September). Cognition, emotion and perceived values in crowdfunding decision making. In Open and User Innovation Conference, Boston, USA.
Navis, C., & Glynn, M. A. (2011). Legitimate distinctiveness and the entrepreneurial identity: Influence on investor judgments of new venture plausibility. Academy of Management Review, 36(3), 479-499. Parhankangas, A., & Ehrlich, M. (2014). How entrepreneurs seduce business angels: An impression
management approach. Journal of Business Venturing, 29(4), 543-564.
Parhankangas, A., Renko, M., 2017. Linguistic style and crowdfunding success among social and commercial entrepreneurs. Journal of Business Venturing, 32(2), 215-236. Park, O. C., & Hopkins, R. (1992). Instructional conditions for using dynamic visual
displays: A review. Instructional science, 21(6), 427-449.
Rhue, L., & Robert, L. P. (2018, April). Emotional delivery in pro-social crowdfunding success. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-6).
Roma, P., Petruzzelli, A. M., & Perrone, G. (2017). From the crowd to the market: The role of reward-based crowdfunding performance in attracting professional investors. Research Policy, 46(9), 1606-1628.
Schwienbacher, A., & Larralde, B. (2010). Crowdfunding of small entrepreneurial
ventures. Handbook of entrepreneurial finance, Oxford University Press, Forthcoming. Shane, S., & Cable, D. (2002). Network ties, reputation, and the financing of new
ventures. Management science, 48(3), 364-381.
Small, D. A., & Verrochi, N. M. (2009). The face of need: Facial emotion expression on charity advertisements. Journal of marketing research, 46(6), 777-787.
Stock, J. H., & Watson, M. W. (2015). Introduction to econometrics.
Stuart, T. E., Hoang, H., & Hybels, R. C. (1999). Interorganizational endorsements and the performance of entrepreneurial ventures. Administrative science quarterly, 44(2), 315-349.
Szymanski, D. M., Kroff, M. W., & Troy, L. C. (2007). Innovativeness and new product success: Insights from the cumulative evidence. Journal of the Academy of Marketing Science, 35(1), 35-52.
Teece, D. J. (2010). Business models, business strategy and innovation. Long range planning, 43(2-3), 172-194. Tirdatov, I. (2014). Web-based crowd funding: Rhetoric of success. Technical Communication, 61(1), 3-24. Ward, C., & Ramachandran, V. (2010, December). Crowdfunding the next hit: Microfunding online
experience goods. In Workshop on computational social science and the wisdom of crowds at NIPS2010 (pp. 1-5).
Ward, T. B. (2004). Cognition, creativity, and entrepreneurship. Journal of business venturing, 19(2), 173-188. Weinmann, M., Tietz, M., Simons, A., & vom Brocke, J. (2017). Get it before it’s gone? How limited
rewards influence backers’ choices in reward-based crowdfunding.
Zhao, Y. L., Song, M., & Storm, G. L. (2013). Founding team capabilities and new venture
performance: The mediating role of strategic positional advantages. Entrepreneurship Theory and Practice, 37(4), 789-814.
Zimmerman, M. A., & Zeitz, G. J. (2002). Beyond survival: Achieving new venture growth by building legitimacy. Academy of management review, 27(3), 414-431.
