Informational asymmetries in crowdfunding

(1)

Informational Asymmetries in Crowdfunding

UNIVERSITY OF AMSTERDAM

AMSTERDAM SCHOOL OF ECONOMICS

BSc Economie en Bedrijfskunde

Bachelor Economics and Business

Author:

Q.D.J. Lont

Student number:

10803955

Thesis supervisor: Dr. J.J.G. Lemmen

Finish date:

31 January 2018

(2)

PREFACE AND ACKNOWLEDGEMENTS

This research would not have been possible without Oneplanetcrowd.

A thank you is in order for Dr. J.J.G. Lemmen for being my thesis supervisor and for H. Toxopeus for giving additional guidance.

Hierbij verklaar ik, Quentin Lont, dat ik deze scriptie zelf geschreven heb en dat ik de volledige verantwoordelijkheid op me neem voor de inhoud ervan.

Ik bevestig dat de tekst en het werk dat in deze scriptie gepresenteerd wordt origineel is en dat ik geen gebruik heb gemaakt van andere bronnen dan die welke in de tekst en in de referenties worden genoemd.

De Faculteit Economie en Bedrijfskunde is alleen verantwoordelijk voor de begeleiding tot het inleveren van de scriptie, niet voor de inhoud.

(3)

ABSTRACT

In this research there has been looked at differences in information search efforts, displayed by investors in crowdfunding campaigns. In crowdfunding campaigns there can be more informational asymmetries involved than compared to the institutional investment market. To gain a better

understanding of how investors in crowdfunding campaigns overcome the informational asymmetries, survey data has been combined with investor data. The survey data made it possible to distinguish between customers and non-customers. The results found in this thesis support the idea that customer investors exert a lower effort of information search than non-customer investors.

Keywords: Information asymmetries, crowdfunding, customer investors, entrepreneurial finance, risk aversion.

(4)

CHAPTER 1 Introduction

Finding external funds is difficult for starting enterprises. Venture capital institutions only invest in enterprises that have a significant turnover (Cosh, Cumming, and Hughes, 2009) and banks invest in enterprises that make a profit. This is not a given. Another reason that limits starting enterprises in attracting external financing is their ability to repay the financing. Banks and venture capital

institutions require certainty about regular the interest payments, which starting enterprises cannot give (Berger and Udell, 1998; Schwienbacher and Larralde, 2010).

To overcome these problems starting entrepreneurs looked for financing among their friends, family or own resources. This is called Angel investors (Freear, Sohl, and Wetzel, 1994; Berger and Udell, 1998) provide funding to start enterprises. For starting enterprises, crowdfunding finds its origin is this development.

1.1 Crowdfunding

Crowdfunding is a way to fulfill the financing need of starting enterprises. Crowdfunding is a method of financing for an enterprise or a project, whereby the funding comes from a group of individuals instead of from one institution (Schwienbacher and Larralde, 2010; Belleflamme, Lambert, and Schwienbacher, 2014). Belleflamme et al. (2014) describe the most important aspect of

crowdfunding as follows: “[…] raising funds by tapping a general public (or crowd).” As crowdfunding gained popularity, various online platforms were created on which entrepreneurs can place a call. There are multiple forms of crowdfunding that those online platforms offer entrepreneurs, namely: donation-based, reward-based, loan-based, and equity-based crowdfunding. In donation campaigns individuals from “the crowd” all donate to the entrepreneur and don’t expect anything in return. In reward-based crowdfunding campaigns, the entrepreneur offers the investors the chance to be the first customers of the enterprise. In both forms of crowdfunding described above there is no to little financial risk involved. For that reason, those forms of crowdfunding will be left out of this research.

In loan-based crowdfunding campaigns, the loan is created by multiple individuals who all contribute in the principal of the loan which is offered to the entrepreneur. For the entrepreneur, the loan works just like a loan from a bank. The only difference being that the interest is not paid to one institution but is distributed among the individuals who invested in the campaign.

In equity-based crowdfunding campaigns shares of the enterprise are offered to the investors. It is not possible to offer shares of an enterprise without making a valuation of the

(7)

to not yet make a valuation of their enterprise it is now also possible to offer convertible loans, which convert into equity under certain conditions. This delays the valuation moment.

The crowdfunding market is a growing market, which can be seen in the numbers of (Douw and Koren, 2017). In 2010 the total amount of capital invested through crowdfunding in the

Netherlands was €500.000. In 2016 the total amount of capital raised through crowdfunding was €170 million.

There has been research on the crowdfund market, but not yet every aspect of this market had been explored. Schwienbacher and Larralde (2010) give reason to expect that there is more informational asymmetry involved in crowdfunding, compared to the institutional investment market. On one side the investors are not as well educated as people who invest in the institutional investment market, so they do not know what type of information to look for when investing. Institutional investors, like VC’s and business angels, possess a certain degree of sophistication when it comes to investing in start-ups (Ahlers, Cumming, Günther, and Schweizer, 2015; Freear et al., 1994). This creates an incentive for the entrepreneur to disclose less information when doing a crowdfunding campaign, because he knows that the investors aren’t as well educated in finance therefor they would not know what kind of information is important.

The effects of informational asymmetries on product markets are described by Akerlof (1970). In this thesis, there will be looked for evidence of informational asymmetries in the crowdfund market and when they exist what affects those informational asymmetries.

Schwienbacher and Larralde (2010) go on to explain that not all investors require the same type of information. Investors who acquire equity will look for more information because the risk involved with equity is higher, than the risk involved in debt investments.

In this research, there will also be checked if these findings hold for the investors in a debt-based crowdfunding campaign and in an equity-based crowdfunding campaign. To research whether there is evidence of informational asymmetries and what the possible grounds are for those asymmetries, surveys have been sent to the investors in two crowdfunding campaigns on the platform of

Oneplanetcrowd. The first campaign is an equity-based campaign of a company that fabricates bicycles. The second campaign is a loan-based campaign of a company that produces sustainable cleaning products.

(8)

CHAPTER 2 Theoretical framework

This chapter will be structured as follows. First, theory of informational asymmetry will be explained. Second, the possible sources for informational asymmetry affecting the crowdfunding market, will be discussed. Finally, the potential factors influencing the different levels of informational asymmetries individuals are willing to accept will be explored.

2.1 Information asymmetry

Information asymmetry entails that the amount of information of two or more parties involved in a transaction is not the same. Akerlof (1970)explains information asymmetry by using the example of the secondhand car market. The buyer knows that there are two types of used cars being sold: cars of good quality, and cars of bad quality (lemons). The seller knows what kind of car he has, because the only way of knowing what type of car one owns is after driving around in it for a period of time. Since the buyer of the car cannot in advance find out what kind of car he is buying, both kinds will be sold at the same price. Therefore, bad cars drive the good cars out of the market.

Jaffee and Russell (1976) did research on the effect of information asymmetry in credit markets. In their research, they describe two types of borrowers, “honest” and “dishonest”. The “honest” type borrower “[…] refuses to default even if there are incentives to do so” (Jaffee and Russell, 1976). The “dishonest” type borrower is identical to the honest borrower, except for the fact that he defaults on his loan when it yields him a higher utility. Jaffee and Russell (1976) found that there are two possible equilibria in this market. The first is that the market reaches a stable

equilibrium. In this equilibrium, all individuals are limited in the amount they can borrow. The other equilibrium Jaffee and Russel (1976) found, was that the market can fluctuate unstably whereby lenders could make a short-term profit but have no other option than to leave the market in the long run.

The lemon problem (Akerlof, 1970) also occurs in the capital market. Healy and Palepu (2001) explain the problem of asymmetrical information for capital markets in the following way. In the capital market there are two types of participants. Savers and entrepreneurs. The entrepreneurs offer their business ideas to the savers and they consist of two types; good and bad. When savers at the time of investing cannot determine what kind of business idea they’re investing in, entrepreneurs with “bad” ideas will claim that their idea is worth as much as a “good” idea. Once the savers

discover this, they will value “good” and “bad” ideas the same, which leads to good ideas being undervalued. The good ideas, when not receiving enough money, won’t be able to succeed, which leads to value destruction. To prevent this from happening, it is necessary that funds are

(9)

appropriate distribution of funds is hard to accomplish. As mentioned above, entrepreneurs have an incentive to overstate the value of their business ideas. Furthermore, entrepreneurs have an

incentive to misuse the money. Since savers don’t play an active role in the management of the enterprise, they cannot monitor how the entrepreneur is spending the investment. This agency problem is called moral hazard. Healy and Palepu (2001) explain that the solution of these problems lies in reliable information but it is hard to accomplish that only reliable information is spread.

In the capital market, there are regulatory authorities that control the information that is being spread. Cohen and Sundararajan (2015) did research on self-regulation in the peer-to-peer sharing economy. Cohen and Sundararajan (2015) mention that the regulating authorities are in place to prevent the market from reaching inefficient or inequitable equilibria. In the markets of the peer-to-peer sharing economy there is no such form of regulation. The market for crowdfunding is one of those markets, in which information asymmetries plays an important role. Cohen and

Sundararajan (2015) name self-regulating organizations as the best solution for the regulatory issues involved in the peer-to-peer sharing economy. The role of the self-regulating organization is to find a solution to make participants aware that information about how they performed is visible to all participants, reducing informational asymmetries. The market for crowdfunding is a peer-to-peer lending market, and the platforms which enable the lending between the parties involved should be self-regulating organizations to prevent market failure. Feller, Gleasure and Treacy (2016) did research on information sharing in the peer-to-peer lending market. (Feller et al., 2016) found that the type of platform matters for the type of information the investors on that platform value before investing. The result of Feller et al. (2016) indicate that information asymmetry, information sharing, and the quality of the information shared still play an important role in the market for crowdfunding. This research investigates how investors in crowdfunding on the platform of Oneplanetcrowd

overcome these issues. 2.2 Effects on crowdfunding

Crowdfunding platforms offer funders different types of information on the page of the campaign. Those sources of information are used by the entrepreneurs to signal funders about the quality of the company and consist of a description of the project, an investment sheet, comments and identities of other funders, and a video made by the entrepreneur (Butticè, Colombo, and Wright, 2017; Colombo, Franzoni, and Rossi-Lamastra, 2015; Hornuf and Schwienbacher, 2015; Toxopeus and Polzin, 2018).

The rise of crowdfunding has created a new type of financer for entrepreneurs. People who are customer or user of the product of the enterprise can now become financer of the enterprise (Berglin and Strandberg, 2013). The innovation literature of von Hippel (1998), which explains how

(10)

product innovation shifts from experts to the users of the product, gives reason to believe that the experiences that customers or users have, create “local sticky” information. In turn the customer crowdfunders use this information to influence their investment decision, which leads them to search less information than non-customer crowdfunders. These results are backed by the research of Toxopeus and Polzin (2018).

H1. Customer crowdfunders search less information than non-customer crowdfunders.

Even when investors have gathered all the possible information there is always the problem of moral hazard. This lays on the entrepreneur-side of the transaction and is outside the scope of this research. One remark will be made on the topic of moral hazard, namely that investors can reduce the change of experiencing the negative effects of moral hazard by gathering as much information as possible. Schwienbacher and Larralde (2010) state that investors who acquire debt require less information than investors who acquire equity, due to the fact that investing in debt leads to a higher possibility of being refunded in the event the enterprise defaults. In this research will be expected that debt crowdfunders did less research before making their investment decision than equity crowdfunders.

H2. Debt crowdfunders search less information about the enterprise than equity crowdfunders. As mentioned before, Schwienbacher and Larralde (2010) stated that equity investors search more information than debt investors. To test if this also holds for customer investors, in this thesis will be looked whether there is also a significant difference in the information search of customer investors investing in debt, compared to customer investors investing in equity.

H3. Customer crowdfunders in debt campaigns search less information than customer crowdfunders in equity campaigns.

(11)

Chapter 3 Methodology

This chapter is structured in the following way. First the research context and how the data were gathered will be explained. Second, the design of the research will be handled. Third, the model will be explained and the independent, dependent and control variables will be mentioned.

3.1 Research context

When investors make an investment decision, they make a prediction on the unknown future performance of the company they’re investing in (Lin and Lee, 2004). To make a well-considered investment decision, it is therefore necessary to obtain as much information as possible on a company to make the best possible estimation. For established companies, there is strict regulation on what kind of information they need to publish every year in their financial reports (AFM, 2017). For small and medium sized enterprises, the regulation is less strict, but the investment decisions of the investors still are an estimation of the future performance of those small and medium sized enterprises. The only way investors can overcome informational asymmetries is to gather as much information as possible. In the research of Toxopeus and Polzin, (2018), the study was performed on a crowdfunding campaign for an online sharing platform. To test whether their results can be

generalized, in this research will be looked at the investors in two campaigns, both consumer brands. The first campaign was for a manufacturer of sustainable soap. The enterprise makes soap out of the peel of a certain type of fruit from Nepal. The second campaign was the campaign for a bicycle manufacturer. The enterprise makes normal bicycles as well as electric bicycles, which can be an alternative for cars in urban areas. The campaign for the soap manufacturer was a loan campaign, in which the investors all invest a small amount, which were then combined and equaled an amount of 300.100 EUR. In the campaign of the bicycle manufacturer, the investors invested in a convertible loan, which is either turned into certificates of shares after three years, or when a new outside investor invests at least 100.000 EUR in the company. At the moment of conversion, the investors become shareholders of the company. The amount raised in that campaign was 2.500.000 EUR. In both cases the crowdfunding campaign was first opened to just the in-crowd of the entrepreneurs, and when the campaign reached 20% of the target amount, it was opened for the public and anyone could invest. The target amount for the soap manufacturer was 200.000 EUR and for the bicycle manufacturer the target amount was 1.000.000 EUR. Both campaigns were started in October 2017 and finished in November 2017.

(12)

3.2 Research design

To obtain data on how much informational asymmetry an investor accepted before investing in either of the companies, a survey has been sent to the investors (see Appendix 4). The survey has been based on the survey used by Toxopeus and Polzin (2018), in order to check if the same results are found . To test the hypotheses, it is necessary to determine how to measure the amount of information an individual obtains before investing. Because information is not a numeric variable, in this research information gathered will be operationalized in two ways. The first way information is defined, is by making a score between 0 and 10 on how much information on the webpage of the campaign an investor looked at. The different options were weighted differently, for instance looking at the video doesn’t give investors as much information as reading the investment sheet.

The second way information search will be measured, is by looking at whether an investor searched information outside of the webpage of the crowdfunding campaign. In the surveys, the investors were asked what items on the crowdfunding page they read before investing and whether they looked for information outside of the crowdfunding page. The second variable needed to test the hypotheses, is a variable to determine the nature of the relation between the investor and the enterprise. In the surveys the investors were asked what kind of relation they had with the enterprise before investing in the crowdfunding campaign. When a pairwise correlation analysis was performed, there was found that customer has a negative correlation with both information looked at on the webpage as well as searching other information.

3.3 Model

To test the hypotheses, a model is derived which is tested statistically. Customer crowdfunders are expected to search less information than non-customer crowdfunders due to the information they obtained by using the product of the enterprise (H1). Secondly, debt investors are expected to gather less information than equity investors, due to the difference in risk involved (H2). Third, customer crowdfunders investing in debt are expected to search less information than customer crowdfunders investing in equity (H3).

3.3.1 Dependent and independent variables

The dependent variable that is tested in this research is the information an investor gathered before making his or her investment decision. Because information is not a numeric variable, in this research information gathered will be defined in two ways. The first way information is operationalized, is by making a score between 0 and 10 on how much information on the webpage of the campaign an investor looked at. In the surveys, investors were asked what items they looked at before investing in the campaign. The different options were weighted differently, for instance looking at the video

(13)

doesn’t give investors as much information as reading the investment sheet. The calculation of the grade on information search effort can be found in the codebook (see Appendix 5)

The second way information search will be operationalized, is by looking at whether an investor searched information outside of the webpage of the crowdfunding campaign. The investors were asked whether they looked for information outside of the crowdfunding webpage. The answers are categorized in no (0) and yes (1). Searching for additional information displays a higher

information search effort, which reduces the informational asymmetry (Toxopeus and Polzin, 2018). Expected is that non-customer investors will exert a higher search for information, so score high on information looked at on the crowdfunding webpage and search for additional information.

The independent variable used is a binary variable which captures whether the investor is a customer before the crowdfunding campaign (1) or not a customer of the company before the crowdfunding campaign (0). To test the differences in information search between debt

crowdfunders and equity crowdfunders, the binary variable VanMoof is included; (0) for investors in the debt campaign and (1) for investors in the convertible debt (equity) campaign.

3.3.2 Control variables

To eliminate other factors than being a customer that affect the information search of

customer crowdfunders, control variables have been added. The first control variable added

is the amount invested (amount). The amount invested affects the search for additional

information (Polzin, Toxopeus, and Stam, 2018; Vismara, 2016) because the higher the

amount invested, the more likely an investor is to do extensive research before investing.

Risk aversion is the next control variable that is added. Risk aversion is expected to influence

the information search, therefore a question about risk aversion (Kahneman and Tversky,

2013) has been put in the survey. The next control variable that is used is income since this

influences the relative size of the investment compared to the level of wealth (Riley and

Chow, 1992; Toxopeus and Polzin, 2018). In the survey, respondents were asked to make an

indication of their monthly income. This was asked in a multiple-choice question with

answer possibilities ranging from less than 1.000 EUR, between 1.000 EUR and 2.500 EUR to

more than 20.000 EUR. Each answer possibility has been categorized by taking the average

of the range in that group. The next control variable used is education (Graham, Harvey, and

Huang, 2009; Toxopeus and Polzin, 2018). Both papers find influences for the level of

education on investor behavior. Education has been measured on an ordinal scale ranging

from 1 to 5, with 1 being vocational education and 5 being an university degree.

(14)

Furthermore, investment experience has been added as control variable (Hodge and Pronk,

2006; Toxopeus and Polzin, 2018; Vismara, 2016). The investment experience is measured by

asking the investors about their previous investing experiences before investing in the

crowdfunding campaign. The crowdfunders were asked how many times they invested in:

investing on the stock market, investing in non-listed companies crowdfunding on other

platforms, crowdfunding on this platform. The answer options were: never (0 times), 1 time,

2 to 5 times, 5 to 10 times, 10 to 30 times, and more than 30 times. Of each option the

average has been used to quantify it and the score have been cumulated in the variable

exp_total. More than 30 times has been quantified as 40. The final control variables are age

and gender, because they are treated as common control variables in research on

crowdfunding (Korniotis and Kumar, 2011; Mohammadi and Shafi, 2018; Toxopeus and

Polzin, 2018).

3.3.3 Data analysis

First, a descriptive analysis is performed on the main dependent, independent and control

variables. Then, there was checked for pairwise correlations. Since the results of the

operationalization of information search on the webpage of the campaign is an ordinal

variable, first an ordered logistic regression was used to test the hypotheses. The results of

information search outside the crowdfunding campaign are operationalized in a binary

variable. To test the hypotheses on the binary variable (other_info), a logistic regression was

performed.

(15)

Chapter 4 Results

This chapter is built in the following way. First an overview will be given of the descriptive

statistics found in the sample. Than the results of testing for the different hypotheses will be

discussed. After that, a description of the control variables and their values will be given.

4.1 Descriptive statistics

The result of the descriptive statistics give insight in the main and control variables used.

From these results can be seen that, on average less than half of the investors in the sample

inspected looked for other information, outside of the campaign webpage. When looking at

the other dependent variable intended to be tested, time taken, it is possible to see that

investors spend on average take slightly more than one hour before investing in the

enterprise. When looking at the main independent variable, customer, it is seen that on

average less than a third of the respondents was already a customer of the enterprise before

investing in the venture through crowdfunding. Another observation that can be made is

that the investors in the campaigns are more or less equally

distributed in preferring financial return or the societal impact as main motivator for investing in either of the companies. Of the respondents 76% was male, and on average the respondents earn a higher income than the national average. The average amount invested was 1.880 euros, with a minimum of 250 euros and a maximum of 50.000 euros. The average age of the respondents is 48 years. A majority of the respondents indicated having completed some form of university education.

Table 1: Descriptive statistics

Variable Obs Mean Median Std. Dev. Min Max

other_info 377 0.32 0 0.47 0 1 grade_info 378 7.19 9 3.26 0 10 Customer 378 0.33 0 0.47 0 1 amount 378 1880.72 1000 3514.60 250 50000 Gender 360 1.23 1 0.42 1 2 Edu 361 4.44 5 0.85 1 5 Income 286 5944.93 3750 4349.11 500 25000 exp_total 371 33.69 24.5 31.22 0 160 Risk_aversion 367 0.60 1 0.49 0 1

(16)

Table 2: Definitions of the variables displayed

other_info Searching information outside campaign page

grade_info Score of items looked at on campaign page

Customer Binary variable on whether respondent is

customer

gender Gender of the respondent

Amount Amount invested by respondent

edu Level of education

income Income of respondent

Exp_total Total investment experience

Risk_aversion Binary variable on whether respondent is risk

averse or not

A pairwise correlation analysis was performed (see Appendix 1). It can be seen there that there is a negative correlation (-0.0917) between being a customer and information looked at on the crowdfunding page (grade_info). The correlation between being a customer and looking for other information, besides the crowdfunding page, is also negative (-0.2239). The significance level of the correlation between customer and grade_info is p<0.1, and the significance of the correlation between customer and other_info is p<0.01.

4.2 Information search

4.2.1 Information operationalized by information on the campaign webpage

To test the first operationalization of information search, info_grade, an ordered logistic regression is performed (Wooldridge, 2013). The results found in testing the first hypothesis, customer

crowdfunders search less information than non-customer crowdfunders, do not support the

hypothesis. The coefficient found is negative, but not significant. The second hypothesis on whether debt crowdfunders search less information than equity crowdfunders, is not supported by the results found. The coefficient of the binary variable VanMoof is negative but not significant. The coefficient is not significant which is reason to reject the hypothesis. The third hypothesis, whether customer-crowdfunders investing in debt search less information than customer-customer-crowdfunders investing in equity, is not supported by the results. The coefficient found for customer in a debt campaign is positive and the coefficient found for customer in an equity test is negative, which is the opposite of what was expected. This gives reason to believe that in these two campaigns the investors in the equity crowdfunding campaign were less likely of the information on the campaign webpage.

The likelihood ratio chi-square of the model used to test the first hypothesis equals 39.88 with a p-value of 0.0008, indicates that the model as a whole is statistically significant. The likelihood ratio chi-square is 40.06 with a p-value 0.0008 found for the model used to test the second

(17)

hypothesis, indicates that the model is statistically significant. The model used for testing the third hypothesis has a likelihood ratio chi-square of 40.59 with a p-value of 0.0017. This indicates that this model as a whole is statistically significant.

Table 2: Full model result; score information on campaign webpage

Variables H1 H2 H3 Customer -0.01889 (0.2469) Amount 0.0001** (0.0000) 0.0001** (0.0000) 0.0001** (0.0000) Risk_aversion -0.3272 (0.2419) -0.3128* (0.2440) -0.3237 (0.2445) Exp_total 0.0011 (0.0039) 0.0013 (0.0000) 0.0009*** (0.0039) Age -0.0329*** (0.0087) -0.0338*** (0.0089) -0.0336 (0.0090) Gender -0.6191 (0.2798) -0.6494 (0.2874) -0.6985** (0.2957) VanMoof -0.1209 (0.2768) VanMoof#customer Customer debt campaign 0.2534 (0.4529) Customer equity campaign -0.1471 (0.3735) Pseudo R2 Log Likelihood 0.0349 -551.93 0.0350 -551.84 0.0355 -551.57 Observations 285 285 285

Standard error in parentheses; ***p<0.01 **p<0.05 *p<0.1 (coefficients of income and edu see Appendix 2, table 5)

4.2.2 information operationalized by information outside the campaign webpage

A logistic regression is performed to test the second operationalization of information search (Wooldridge, 2013). In testing the first hypothesis, customer crowdfunders search less information than non-customer crowdfunders, the results show support for hypothesis 1. The next hypothesis that is tested is hypothesis 2 about whether debt crowdfunders search less information about the enterprise than equity crowdfunders. The coefficient found for VanMoof, measuring the difference in information search between crowdfunders in the convertible loan campaign and the regular loan campaign, is positive but not significant. The sign is in line with the expectations. The third

hypothesis that is tested, whether customer crowdfunders in debt campaigns search less information than customer crowdfunders in equity campaigns, is not backed by the results. The coefficient of the interaction variable VanMoof#customer measures the effect of a respondent being a customer-crowdfunder in a debt campaign or a customer-customer-crowdfunder in an equity. The coefficients found for

(18)

the interaction variable, are both negative. The coefficient for the interaction variable, when it symbolizes a customer-crowdfunder in an equity campaign is negative and has a significance level of α<0.05. This result does not support hypothesis 3.

Table 3: Full model results; searching for other information

Variables H1 H2 H3 Customer -1.4275*** (0.3869) Amount 0.0001*** (0.0000) 0.0001** (0.0000) 0.0002*** (0.0000) Risk_aversion -0.5172 (0.3222) -0.4538 (0.3033) -0.5690 (0.3295) Exp_total 0.0081 (0.0051) 0.0126** (0.0049) 0.0074 (0.0052) Age -0.0233* (0.0119) -0.0165* (0.0119) -0.0208 (0.0122) Gender -0.5364 (0.4129) -0.4371 (0.4125) -0.5560 (0.4299) VanMoof 0.3111 (0.3719) Customer debt campaign -0.8673 (0.6718) Customer equity campaign -1.2205* (0.5655) Constant 0.3938 (1.1438) -0.7114 (1.4829) -0.5826 (1.4149) Pseudo R2 Log likelihood 0.1611 -140.86 0.1163 -148.38 0.1655 -140.13 Observations 284 284 284

Standard error in parentheses; ***p<0.01 **p<0.05 *p<0.1 (coefficients of income and edu see Appendix 2, table 6)

4.3 Control variables

There have been found positive coefficients for the control variable amount. (Toxopeus and Polzin, 2018; Vismara, 2016) find that amount positively affects information search. There is reason to believe that when a higher amount is invested, a more extensive information search is performed. The control variable risk aversion has a negative coefficient in every model that was tested. Risk aversion has been measured with 1 for respondents who were not risk averse and 0 for respondents who were risk averse. This is in line with the findings of Kahneman and Tversky (2013). The control variable investment experience has a positive coefficient in every model that was tested, implying

(19)

that investors with more investment experience search for more information than investors with less experience. This is in accordance with the results of (Hodge and Pronk, 2006; Toxopeus and Polzin, 2018; Vismara, 2016). The control variable education has an ambiguous effect (see Appendix 2). In the first operationalization of information search, information on the webpage of the campaign, every coefficient of education is negative, but increasing in nearly every as the level of education increases. In the second operationalization of information search, other information, every

coefficient of education is positive and increasing as the level of education increases. Graham et al. (2009) found that investors with higher education are more likely to perceive themselves as competent investors. When this is true, investors with a higher education seem to score better on information looked at on the webpage of the campaign and are more likely to search for information outside of the webpage of the campaign, than investors with a lower level of education.

(20)

Chapter 5 Discussion and conclusion

This chapter is structured in the following manner. First a conclusion will be given on the results found during the research. Then, a discussion will be written on possible influences and limitations on the outcome of this research

5.1 Conclusion

The tests conducted on the first hypothesis: Customer crowdfunders search less information than non-customer crowdfunders, because of their experiences with the product, is not supported by the results found when testing information search operationalized as score of information looked at on the webpage of the campaign. In the test performed on the first hypothesis operationalized as information outside of the crowdfunding campaign, the results support the hypothesis. This gives reason to believe that of the respondents interviewed, customer crowdfunders were less likely to search for information outside of the crowdfunding webpage.

The tests performed to test the second hypothesis: Debt crowdfunders search less

information about the enterprise than equity crowdfunders, do not give significant results in either of the tests. In the model where information search was operationalized as information looked at on the crowdfunding webpage, the variable VanMoof capturing the investors in the equity campaign had a negative sign, which could indicate that the investors in the equity campaign looked at less information on the campaign page.

The models tested to test the third hypothesis: Customer crowdfunders in debt campaigns search less information than customer crowdfunders in equity campaigns, do not provide

significant results. When the results of testing the second hypothesis were observed, the expectation was that the third hypothesis would also not be supported by the result.

5.2 Discussion

A possible explanation for the findings in the testing for hypotheses 2 and 3, is that the investors in the sample had an above average level of education. Another explanation might be that the investors on average had some experience with investing, which might explain why the investors know that they need to look for more information than what is offered on the webpage of the crowdfunding campaign. Another remark that needs to be made is that the business ventures examined, both make a sustainable impact on the environment. This might create a bias in what type of investor decides to invest in the crowdfunding campaign.

(21)

5.2.1 Limitations

There has not been researched whether there are differences among customer investors. It is possible that customer investors who are long-time customers display other information search efforts than customer investors who only recently became customer.

Another limitation is that convertible debt is a different financial product than equity, since it starts its life as debt but is turned into equity after the passing of time, or when an external investor invests in the enterprise.

The next limitation is that the campaigns were both hosted on the same crowdfund platform, which means that it is not possible to make a generalization from the results to the entire

population. Feller et al. (2016) found that the type of platform the crowdfunding campaign is hosted on, matters for the type of information sought by the investors. The crowdfunders of

Oneplanetcrowd share at least one property, namely that they value sustainability and the society as a whole.

Another limitation is that the crowdfunding campaign of the cleaning products manufacturer was in cooperation with the ASN Bank. This could be interpreted by investors as a signal of the quality of the enterprise, therefore influencing information search behaviour.

The final limitation is that in testing the second hypothesis, debt crowdfunders search less information about the enterprise than equity crowdfunders, the significant independent variable customer has been removed, this causes a bias on the other variables. When the model for the information grade was tested with the variable customer put back in the regression, the coefficient for VanMoof was slightly smaller (-0.1213 vs. -0.1209) but still not significant. The same has been done for the model for information outside the webpage of the campaign. Here the coefficient was slightly smaller as well (0.2786 vs. 0.3111).

A suggestion for further research is to increase the number of campaigns as well as the number of platforms investigated. Also, the scope of financing products researched can be

broadened, because some crowdfunding platforms offer straight equity, instead of the convertible loan used for this research. The final suggestion for further research is to further explore the role of information search in the dynamics of investor decision making.

(22)

REFERENCES

AFM vraagt ondernemingen tijdig aandacht te geven aan invoering nieuwe verslaggevingsregels | December | AFM. (2017). Retrieved January 28, 2018, from

https://www.afm.nl/nl-nl/nieuws/2017/dec/invoering-nieuwe-verslaggevingsregels/

Ahlers, G. K. C., Cumming, D., Günther, C., & Schweizer, D. (2015). Signaling in Equity Crowdfunding. Entrepreneurship Theory and Practice, 39(4), 955–980. https://doi.org/10.1111/etap.12157 Akerlof, G. A. (1970). The Market for "Lemons" Quality Uncertainty and the Market

Mechanism. The Quarterly Journal of Economics, 84(3), 488. https://doi.org/10.2307/1879431 Belleflamme, P., Lambert, T., & Schwienbacher, A. (2014). Crowdfunding: Tapping the right crowd.

Journal of Business Venturing, 29(5), 585–609. https://doi.org/10.1016/J.JBUSVENT.2013.07.003

Berger, A. N., & Udell, G. F. (1998). The economics of small business finance: The roles of private equity and debt markets in the financial growth cycle. Journal of Banking & Finance, 22(6–8), 613–673. https://doi.org/10.1016/S0378-4266(98)00038-7

Berglin, H., & Strandberg, C. (2013). Leveraging customers as investors : The driving forces behind crowdfunding. Retrieved from

http://www.diva-portal.org/smash/record.jsf?pid=diva2%3A604272&dswid=article

Butticè, V., Colombo, M. G., & Wright, M. (2017). Serial Crowdfunding, Social Capital, and Project Success. Entrepreneurship Theory and Practice, 41(2), 183–207.

https://doi.org/10.1111/etap.12271

Cohen, M., & Sundararajan, A. (2015). Self-Regulation and Innovation in the Peer-to-Peer Sharing Economy. University of Chicago Law Review Dialogue, 82. Retrieved from

http://heinonline.org/HOL/Page?handle=hein.journals/uchidial82&id=116&div=9&collection=jo urnals

Colombo, M. G., Franzoni, C., & Rossi-Lamastra, C. (2015). Internal Social Capital and the Attraction of Early Contributions in Crowdfunding. Entrepreneurship Theory and Practice, 39(1), 75–100. https://doi.org/10.1111/etap.12118

Cosh, A., Cumming, D., & Hughes, A. (2009). Outside Enterpreneurial Capital. The Economic Journal. Wiley. https://doi.org/10.2307/40271400

(23)

Douw, S., & Koren, G. (2017). 2016 Topjaar voor crowdfunding in cultuursector - Douw&Koren. Retrieved January 30, 2018, from

http://douwenkoren.nl/2016-topjaar-crowdfunding-cultuursector/

Feller, J., Gleasure, R., Treacy, S., & Feller, J. (2016). Information sharing and user behavior in internet-enabled peer-to-peer lending systems: an empirical study. Journal of Information Technology Advance Online Publication. https://doi.org/10.1057/jit.2016.1

Freear, J., Sohl, J. E., & Wetzel, W. E. (1994). Angels and non-angels: Are there differences? Journal of Business Venturing, 9(2), 109–123. https://doi.org/10.1016/0883-9026(94)90004-3

Graham, J. R., Harvey, C. R., & Huang, H. (2009). Investor Competence, Trading Frequency, and Home Bias. Management Science, 55(7), 1094–1106. https://doi.org/10.1287/mnsc.1090.1009

Healy, P. M., & Palepu, K. G. (2001). Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature. Journal of Accounting and Economics, 31(1–3), 405–440. https://doi.org/10.1016/S0165-4101(01)00018-0

Hodge, F., & Pronk, M. (2006). The Impact of Expertise and Investment Familiarity on Investors’ Use of Online Financial Report Information. Journal of Accounting, Auditing & Finance, 21(3), 267– 292. https://doi.org/10.1177/0148558X0602100304

Hornuf, L. ;, & Schwienbacher, A. (2015). Funding Dynamics in Crowdinvesting. In Beiträge zur Jahrestagung des Vereins für Socialpolitik 2015: Ökonomische Entwicklung - Theorie und Politik - Session: Financial Economics II (pp. 1–27). Retrieved from http://hdl.handle.net/10419/112969 Jaffee, D. M., & Russell, T. (1976). Imperfect Information, Uncertainty, and Credit Rationing. The

Quarterly Journal of Economics, 90(4), 651. https://doi.org/10.2307/1885327

Kahneman, D., & Tversky, A. (2013). Prospect Theory: An Analysis of Decision Under Risk. In W. T. Ziemba & L. C. MacLean (Eds.), Handbook of the Fundamentals of Financial Decision Making, World Scientific Handbook in Financial Economics Series (pp. 99–127).

https://doi.org/10.1142/9789814417358_0006

Korniotis, G. M., & Kumar, A. (2011). DO OLDER INVESTORS MAKE BETTER INVESTMENT DECISIONS? Source: The Review of Economics and Statistics, 93(1), 244–265. Retrieved from

http://www.jstor.org/stable/23015932

(24)

Financial Services Review, 13(4), 319–332. Retrieved from

http://web.b.ebscohost.com.proxy.uba.uva.nl:2048/ehost/detail/detail?vid=0&sid=400537d1-

73e0-485f-9109-1bbfe1fbfd9d%40sessionmgr101&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3D%3D#db=bah&AN=1 6402447

Mohammadi, A., & Shafi, K. (2018). Gender differences in the contribution patterns of equity-crowdfunding investors. Small Business Economics, 50(2), 275–287.

https://doi.org/10.1007/s11187-016-9825-7

Polzin, F., Toxopeus, H., & Stam, E. (2018). The wisdom of the crowd in funding: information heterogeneity and social networks of crowdfunders. Small Business Economics, 50(2), 1–23. https://doi.org/10.1007/s11187-016-9829-3

Riley, W. B., & Chow, K. V. (1992). Asset Allocation and Individual Risk Aversion. Chow Source: Financial Analysts Journal, 48(6), 32–37. Retrieved from http://www.jstor.org/stable/4479593 Schwienbacher, A., & Larralde, B. (2010). Crowdfunding of Small Entrepreneurial Ventures. In D.

Cumming (Ed.), Handbook of Entrepreneurial Finance (pp. 369–391). NEW YORK: Oxford University Press. . https://doi.org/10.2139/ssrn.1699183

Toxopeus, H., & Polzin, F. (2018). Users as Funders of Sustainable Innovation (work in progress). Vismara, S. (2016). Information Cascades Among Investors in Equity Crowdfunding. Entrepreneurship:

Theory and Practice, n/a-n/a. https://doi.org/10.1111/etap.12261

von Hippel, E. (1998). Economics of Product Development by Users: The Impact of “Sticky” Local Information. Management Science, 44(5), 629–644. https://doi.org/10.1287/mnsc.44.5.629 Wooldridge, J. M. (2013). Introductory econometrics: a modern approach. (Erin Joyner, Joe Sabatino,

& Michael Worls, Eds.) (5th ed.). Mason: South-Western, Cengage Learning. Retrieved from http://economics.ut.ac.ir/documents/3030266/14100645/Jeffrey_M._Wooldridge_Introductor y_Econometrics_A_Modern_Approach__2012.pdf

(25)

(26)

APPENDIX 1 Pearson pairwise correlation

Table 4: Pairwise correlation analysis

Grade_

info Other_ info Custom er amount age gender edu income Exp_ total aversion Risk_ Grade_ info 1.00 Other_ Info (0.0000) 0.2244 1.00 Customer -0.0917 (0.0748) -0.2239 (0.0000) 1.00 Amount 0.0675 (0.19) (0.0052) 0.1435 (0.3998) 0.0434 1.00 Age -0.2742 (0.0000) (0.0218) -0.1188 (0.4864) -0.0359 (0.2135) 0.0641 1.00 Gender -0.1371 (0.00952) -0.1012 (0.0550) 0.0601 (0.2557) -0.1048 (0.0469) 0.1625 (0.0020) 1.00 Edu 0.1637 (0.0018) (0.0020) 0.1623 (0.0504) -0.1031 (0.6066) 0.0272 (0.0122) -0.1319 (0.0933) -0.0886 1.00 Income -0.0215 (0.7169) (0.7023) 0.0227 (0.0776) 0.1045 (0.0001) 0.2292 (0.5667) 0.0340 (0.0005) -0.2061 (0.0001) 0.2260 1.00 Exp_ Total (0.0266) 0.1151 (0.0000) 0.2618 (0.0000) -0.2367 (0.0368) 0.1085 (0.7965) 0.0134 (0.0003) -0.1914 (0.0073) 0.1409 (0.0020) 0.1824 1.00 Risk_ aversion (0.6887) 0.0210 (0.0845) -0.0902 (0.5878) -0.0284 (0.0116) 0.1316 (0.2410) -0.0614 (0.0005) -0.1823 (0.1993) 0.0677 (0.0002) 0.2216 (0.6092) -0.0268 1.00 The significance level in parentheses

(27)

APPENDIX 2 Coefficients of factor variables education and income

Table 5: Coefficients of factor variables education and income on information grade

Variable H1 H2 H3 Edu 1 -1.2720 (1.5960) -1.2887 (1.5861) -1.4680 (1.6196) 2 -0.4850 (0.8478) (0.8466) -0.4686 (0.8484) -0.5007 4 -0.4676 (0.6278) (0.6300) -0.4707 (0.6292) -0.4716 5 -0.1977 (0.6167) (0.6184) -0.1987 (0.6187) -0.2032 inc om e 500 0.5519 (0.5754) (0.5763) 0.5313 (0.5799) 0.5703 1750 0.3257 (0.4347) (0.4361) 0.3120 (0.4364) 0.3186 6250 0.3689 (0.2986) (0.2987) 0.3766 (0.2991) 0.3779 8750 -0.6613* (0.3483) -0.6379* (0.3520) -0.6359* (0.3536) 15000 -0.0047 (0.4298) (0.4278) 0.0173 (0.4363) 0.0499 25000 -0.6495 (0.8309) (0.8309) -0.6172 (0.8311) -0.5739 Standard error in parentheses; ***p<0.01 **p<0.05 *p<0.1

Table 6: Coefficients of factor variables education and income on other information

Variable H1 H2 H3

edu

1 0

(dropped) (dropped) 0 (dropped) 0

2 0.3939 (1.3999) (1.3793) 0.0964 (0.8484) -0.5007 4 0.5289 (1.1510) (1.1499) 0.5907 (0.6292) -0.4716 5 1.2347 (1.1313) (1.1301) 1.1526 (0.6187) -0.2032 in co m e 500 -0.0607 (0.8659) (0.7178) -0.0291 (0.5799) 0.5703 1750 -0.8659 (0.6790) (0.6728) -0.8003 (0.4364) 0.3186 6250 -1.0319* (0.4183) -0.9851* (0.4032) (0.2991) 0.3779 8750 -1.3616*** (0.5141) -1.3635*** (0.5111) -0.6359* (0.3536) 15000 -0.2982 (0.5727) (0.5419) -0.6547 (0.4363) 0.0499 25000 -0.1340 (1.1642) -0.4926 (1.0687) -0.5739 (0.8311) Standard error in parentheses; ***p<0.01 **p<0.05 *p<0.1

(28)

APPENDIX 3 Pictures of the crowdfunding webpages

Picture 1: crowdfunding webpage for VanMoof

(29)

APPENDIX 4 Survey sent to the crowdfunders

1. Wat was uw relatie tot VanMoof/Seepje voordat u meedeed aan de crowdfunding

campagne? (meerdere antwoorden mogelijk)

- Ik fiets zelf op een VanMoof fiets/Ik ben klant van Seepje

- Ik ben vriend of familielid van iemand bij VanMoof/Seepje

- Ik ben zakelijke relatie of bestaande investeerder van VanMoof/Seepje

- Ik ben (indirecte) kennis van iemand bij VanMoof/Seepje

- Ik werk bij VanMoof/Seepje

- Ik ben fan van VanMoof/Seepje

- Ik ben alleen funder

- Anders, namelijk:

2. Hoe lang rijdt u al op een VanMoof fiets? (alleen als bij 2 is aangegeven bestaande

klant)

- Minder dan een jaar

- Tussen 1-2 jaar

- 3-4 jaar

- 5-6 jaar

- 7-8 jaar

3. Hoe vaak gebruikt u uw VanMoof fiets? (alleen als bij 2 is aangegeven bestaande

klant)

- (bijna) nooit

- minder dan 1 per week

- 1-2 keer per week

- 3-6 keer per week

- dagelijks

[alleen voor investeerders die nog geen klant waren]

4. Heeft u sinds u crowdfunder bent geworden een VanMoof fiets gekocht of geleased?

- Ja

- Nee

-

5. Hoe belangrijk waren voor u de volgende redenen om in VanMoof te investeren?

[zeer onbelangrijk, onbelangrijk, neutraal, belangrijk, zeer belangrijk]

- Financieel rendement

- Maatschappelijke impact

- Ik wil VanMoof zelf (gaan) gebruiken

- Mijn relatie met de mensen achter VanMoof

- Onderdeel zijn van de VanMoof crowd

- De kwaliteit van VanMoof

- De kwaliteit van de uitbreidingsplannen

(30)

- Financieel rendement

- Maatschappelijke impact

7. Hoe lang heeft u zich verdiept in VanMoof (inclusief het voorstel) om uw

investeringsbesluit te maken?

- 0 – 15 min

- 15 min tot een half uur

- half uur tot 1 uur

- 1 tot 3 uur

- 3 tot 5 uur

- meer dan 5 uur

8. Wat heeft u op de crowdfunding pagina bekeken om uw investeringsbesluit te

maken?

- Video

- Projectomschrijving (deels)

- Projectomschrijving (helemaal)

- Investment sheet (PDF)

- Opmerkingen van andere crowdfunders

- Ander onderdeel, namelijk:

9. Heeft u buiten de crowdfunding website, andere informatie gezocht om uw

investeringsbesluit te maken?

- Ja, namelijk: [open veld]

- Nee

10. Hoe belangrijk was de volgende informatie voor uw investeringsbeslissing in

VanMoof/Seepje? Informatie over:

[zeer onbelangrijk, onbelangrijk, neutraal, belangrijk, zeer belangrijk]

- Het bedrijf VanMoof en zijn producten

- Doelstellingen van VanMoof

- De besteding van het opgehaalde bedrag

- De mensen achter VanMoof en hun ervaring

- Financiële planning en risico’s van VanMoof

11. Hoe risicovol schat u uw investering in VanMoof in? (Het gaat hier om het risico van

investeren in VanMoof/Seepje, waarmee wordt bedoeld dat u uw investering

gedeeltelijk of helemaal verliest)

- Niet risicovol

- Beperkt risicovol

- Vrij risicovol

- Zeer risicovol

- Kan ik niet goed inschatten

(31)

- 0 tot 20%

- 20 tot 40%

- 40 tot 60%

- 60 tot 80%

- 80 tot 100%

13. Hoeveel ervaring heeft u met de onderstaande activiteiten (los van uw investering in

VanMoof/Seepje): [geen, 1 keer, 2-5 keer, 5-10 keer, 10-30 keer, meer dan 30 keer]

- Investeren op de beurs

- Investeren in niet-beursgenoteerde bedrijven (buiten crowdfunding)

- Crowdfunding

- Crowdfunding bij Oneplanetcrowd

14. Wat zou u liever willen?

- 50 euro

- 75% kans op 100 euro

15. Stel dat u EUR 100 op een spaarrekening heeft staan tegen een rente van 2%.

Hoeveel geld heeft u na 5 jaar als u het geld plus de ontvangen rente op deze

spaarrekening laat staan?

- Minder dan EUR 110

- EUR 110

- Meer dan EUR 110

- Weet ik niet

- Ik wil deze vraag liever niet beantwoorden

16. Een aandeel in een bedrijf is meestal een veiligere investering in een beleggingsfonds

- Waar

- Niet waar

- Weet ik niet

- Ik wil deze vraag liever niet beantwoorden

17. Als een investeerder zijn geld spreidt over verschillende bedrijven, wordt het risico

van geld verliezen dan:

- Hoger

- Lager

- Blijft gelijk

- Weet ik niet

- Ik wil deze vraag liever niet beantwoorden

18. Neem aan dat de rente over uw spaarrekening 1% per jaar is en dat de inflatie 2% per

jaar is. Als u al het geld op de spaarrekening laat staan, hoeveel zou u over 1 jaar

kunnen kopen met het geld op de spaarrekening?

- Meer dan vandaag

- Precies hetzelfde als vandaag

- Minder dan vandaag

- Weet ik niet

(32)

19. Welk financieel instrument vertoont normaal gesproken de grootste waarde

schommelingen over tijd?

- Spaarrekeningen

- Obligaties

- Aandelen

- Weet ik niet

- Ik wil deze vraag liever niet beantwoorden.

[Niet van toepassing bij Seepje]

20. U heeft aan VanMoof een converteerbare lening verstrekt. Geef aan welke stelling

het meest op u van toepassing is.

Ik heb deze financiering verstrekt met het idee dat:

- Deze door VanMoof gedurende 5 jaar weer aan mij wordt afgelost

- Ik vervolgens aandeelhouder word in VanMoof

- Beide stellingen zijn niet op mij van toepassing.

[Niet van toepassing bij Seepje]

21. Geef aan of u het eens bent met onderstaande stellingen. (Erg mee eens/mee

eens/neutraal/oneens/ erg mee oneens:

- Het kan zijn dat VanMoof failliet gaat en u uw hele investering kwijtraakt

- Het rendement op uw investering in VanMoof is ongelimiteerd

- Als u aandeelhouder word in VanMoof heeft u ook stemrecht in het bedrijf

- Het is reëel dat de tijd tussen instappen en uitstappen als aandeelhouder in

VanMoof langer is dan 5 jaar.

- Het is reëel dat de tijd tussen instappen en uitstappen als aandeelhouder in

VanMoof langer is dan 10 jaar

22. Wat is uw hoogst genoten opleiding?

- Lager onderwijs/ basisonderwijs

- Lager beroepsonderwijs

- MAVO/ VMBO/ MBO

- HAVO/ VWO

- HBO

- WO(universitair)

23. Wat is uw geslacht?

- Man

- Vrouw

24. Zou u een indicatie willen geven van uw bruto maandinkomen?

- Minder dan 1000 EUR

- 1.000-2.500 EUR

- 2.500-5.000 EUR

- 5.000-7.500 EUR

- 7.500-10.000 EUR

- Meer dan 10.000 EUR

- Zeg ik liever niet

(33)

-

25. Hoe groot is deze investering ten opzichte van uw totale hoeveelheid beleggingen?

- 0 tot 5%

- 5 tot 10%

- 10 tot 15%

- 15 tot 25%

- 25 tot 50%

- 50 tot 75%

- 75 tot 100%

(34)

APPENDIX 5 Codebook for survey results

Wat is in uw investeringsbeslissing meer doorslaggevend geweest?

- maatschappelijk impact

1 - financieel rendement

2 - weet ik niet

0

Beweegredenen:

- zeer belangrijk

5 - belangrijk

4 - neutraal

3 - onbelangrijk

2 - zeer onbelangrijk

1

geslacht:

- Vrouw

2 - Man

1

Scholing

- Lager (beroeps)onderwijs

1 - MAVO/VMBO/MBO

2 - HAVO/VWO

3 - HBO

4 - WO

5

Welke informatie heeft u bekeken op de crowdfund pagina

- Video

(1-0)

- Gedeelte van de project beschrijving (1-0)

- Gehele project beschrijving

(1-0)

- Investment sheet

(1-0)

Grade_info is op de volgende manier berekend:

(35)

Klant geworden sinds campagne?

- Ja

2 - nee, wel van plan

1 - nee

0

Wat was doorslaggevend?

- Financieel

2 - Maatschappelijk

1 - Weet niet

weggelaten

Hoe lang heeft u over uw investeringsbeslissing gedaan?

Gemeten dmv gemiddelden van de groepen (0-15 min, 15 min tot half uur… meer dan 5 uur) Wat heeft u op de pagina bekeken?

- Video

(1-0)

- Projectomschrijving (deels)

(1-0)

- Projectomschrijving (helemaal)

(1-0)

- Investment sheet

(1-0)

- Ander onderdeel

(1-0)

Andere info gezocht (1-0)

Risico preferentie:

- Risico avers

0 - Niet risico avers

1

Ervaring met investeren

- Geen

0 - 1 keer

1 - 2 – 5 keer

3,5

- 5 – 10 keer

7,5

(36)

- 10 – 30 keer

15 - Meer dan 30 keer

40

Financial literacy vragen:

100 euro tegen 2% 5 jaar laten staan; aandeel in bedrijf veiliger dan aandeel beleggingsfonds; investeerder die geld spreidt; inflatie; grootste waarde schommelingen

- Als goed beantwoord 1

- Fout

0

Income:

Informational asymmetries in crowdfunding