The importance of preferences for autonomy in the decision to become an entrepreneur : differences in entry to entrepreneurship between individual and team sport athletes

The Importance of Preferences for Autonomy in the Decision to Become an Entrepreneur: Differences in Entry to Entrepreneurship Between Individual and Team Sport Athletes

MSc in Entrepreneurship

University of Amsterdam/Vrije Universiteit Thesis Advisor: Dr. J. Sol

17/06/2016

By:

Daniel A. Abbink

Student ID UvA: 11041404

2

Abstract

Selection and entry into entrepreneurship is a widely studied theme within psychology and

economics literature. The current literature examines psychological attributes and the many

different variables that relate to entrepreneurship. This thesis adds to the literature by examining

the link between the importance of preference of autonomy and entrepreneurship by looking at the

differences between individual sport athletes and team sport athletes. This thesis further

contributes to the literature by conducting an established questionnaire measure. These measures

examine the importance of several mechanisms (preference for autonomy, need for achievement,

risk aversion, and overconfidence) in the decision to become an entrepreneur. Using a sample of

individuals who are or have been participating in a sport. I suggest that people who participate in

an individual sport have a higher probability of preference for autonomy as opposed to those who

participate in team sports. This proxy indeed shows a positive correlation with established

questionnaire measures that gauge the preference for autonomy. The results show that there is no

direct relationship between preferences for autonomy and entrepreneurship. However, the risk

aversion measure suggest that the higher a person’s risk tolerance is, the more likely it is that that

the individual will enter into entrepreneurship.

Keywords: Entrepreneurship; preference for autonomy; need for achievement; risk aversion;

3

Acknowledgement

I would like to acknowledge and thank my thesis supervisor Dr. J. Sol for all of his valuable

feedback and guidance throughout this thesis process as well as throughout the entire joint

4

Table of Contents

1. Introduction………. 5

2. Literature Review………. 8

2.1 Preference for Autonomy……… 8

2.2 Need for Achievement………. 10

2.3 Risk Aversion……… 11

2.4 Controls……….. 12

3. Methodology……….. 14

3.1 Data Collection & Sample……….. 14

3.2 Measures……… 15

3.2.1 Dependent Variable Measures....……….. 15

3.2.2 Preference for Autonomy Measures……… 15

3.2.3 Need for Achievement Measures.………. 16

3.2.4 Risk Aversion Measures.……….. 16

3.2.6. Control Measures……….. 17

3.3 Data Description……… 18

4. Data Analysis & Results………. 20

5. Discussion & Conclusion……… 22

6. References……….. 25 List of Tables Table 1……….. 19 Table 2……….. 21 Table 3……….. 21 Appendix Appendix A (Questionnaire)……….. 29

5

1. Introduction

Selection and entry into entrepreneurship is currently a big theme in economics and

psychology literature. Within this theme, there is a large body of work on the psychological

attributes (as well as other variables) that are related to entry into entrepreneurship. One of the

most recent literature reviews that discusses these attributes has come from Astebro et al (2015).

According to Astebro et al. (2015), the fact that people enter into entrepreneurship despite low

risk-adjusted returns ‘suggests that standard theories of risk and return provide an incomplete basis

for entrepreneurship’ (p.50). Together with Moskowitz, Tobias and Vissing-Jorgensen (2002),

Astebro et al. (2015) highlight that because there is a low average of returns for entrepreneurs, the

possibility arises that there are nonstandard factors—such as the preference for control and

autonomy—that make individuals want to enter into entrepreneurship. Regular economic theories

see these particular job characteristics as a way to gain more nonpecuniary rewards (Astebro et al.,

2015). However, to some individuals, autonomy and control might be intrinsically valuable ends

by themselves (Astebro et al., 2015). The purpose of this thesis is to examine this mechanism in

more detail by making use of a new proxy for the preference for autonomy. To the best of my

knowledge, no study has used the difference between individual and team sport athletes as a proxy

for the preference for autonomy.

Another potential driver for entry into entrepreneurship is overconfidence (Astebro et al.,

2015). This implies that people become entrepreneurs because they tend to view the return

distribution more favourable than it might actually be. A good example of this would be a report

by Cooper, Woo and Dunkelberg (1988) in which they show that 33 percent of the 3000

6

companies a lower score. Astebro et al (2015) explain that overconfidence might appear to act like

a low level of risk aversion at first; however, it is different as it may arise from behavioural biases. An individual’s risk preferences could also play a role in a person’s willingness to become

an entrepreneur. According to Astebro et al (2015), ‘risk preferences are defined by the utility function over wealth in the standard expected utility framework’ (p. 55). A lot of individuals have

utility functions that imply risk aversion, meaning that they are more willing to hold a job with

regular and less-variable pay (Astebro et al., 2015). On the other hand, there are individuals that

are relatively less risk averse and, therefore, less deterred by the risks entailed in entrepreneurship

(Astebro et al., 2015). Furthermore, in an empirical analysis, Hvide and Panos (2014) provide

evidence that there is a link between risk tolerance and the decision to enter into entrepreneurship.

However, this thesis will examine the subject further.

Lastly, this paper considers the need for achievement as another driver for people to enter

into entrepreneurship. According to Hansemark (2003), the need for achievement includes certain

expectations of doing a task better and faster than others. It can also entail an individual’s need to better ones previous accomplishments (Hansemark 2003). A person’s need for achievement is

something that can be learned and will, therefore, develop according to how a person’s current frame of reference is compared to that person’s own desire to achieve (McClelland, 1990).

In order to understand which mechanisms are driving factors for individuals to enter into

entrepreneurship, this paper will use athletes’ involvement in sports as proxies to research a variety

of mechanisms. I argue that using athletes from both individual and team sports offers a good

proxy to study an individual’s preference for autonomy. In order to measure need for achievement,

I argue that using an individual’s highest level of sport played offers a solid proxy for this

7

measured by type of sport played; a sport where direct contact with the opponent is likely to occur

entails considerable more risk of injury than a sport where there is no contact with the opponent at

all. These dimensions will be discussed in further detail in the literature review.

This thesis will use a quantitative approach in order to analyse the importance of preference

for autonomy in the decision to become an entrepreneur. An established questionnaire measure

will be used as well as the differences between team sport athletes and individual sport athletes as

a proxy. The questionnaire uses sports related proxies in order to identify the mechanisms that may

play a role in the decision to become an entrepreneur. These mechanisms include: need for

achievement, preference for autonomy, and risk aversion. Moreover, this thesis will measure for

the control variables of parental entrepreneurship and overconfidence. By using these control

variables it becomes possible to assess the relationship between the other variables mentioned.

I hypothesize that people who participate in an individual sport have a higher probability

of preference for autonomy as opposed to those who participate in team sports. This proxy shows

a positive relationship with established questionnaire measures that gauge the preference for

autonomy. The results show that there is no relationship between preferences for autonomy and

entrepreneurship. However, the risk aversion measure suggest that an individual who is less risk

averse, is more likely to enter into entrepreneurship.

The structure of the paper is as follows: Section 2 reviews the literature of the topic; Section

3 explains the method used for research; Section 4 provides a data analysis of the results; Section

8

2. Literature Review

2.1. Preference for autonomy

Shane et al. (2003) argue, in a conceptual analysis, that autonomy is about an individual

taking the responsibility to use his/her own judgment rather than allowing decisions to be made

for them. However, it is important to note that autonomy is also about taking care of the responsibilities in one’s own life and not living through the efforts of other people (Shane, Locke

& Collins, 2003). In previous research it has been found that the need for autonomy is a necessity

for entrepreneurial activity. For example, Shane et al. (2003) explain that entrepreneurs first take

responsibility for chasing an opportunity that was not existent before; secondly, entrepreneurs are

responsible for all of their final results whether they are positive or negative. Another reason why

people might want to enter into entrepreneurship is because of their personal need for autonomy

(Hisrich, 1985). Hisrich (1985) came to this conclusion by conducting an interview study with

American female entrepreneurs in which it was discovered that independence was a major driver

for their entry into entrepreneurship.

In an empirical analysis, Hamilton (2000), observes that many entrepreneurs have lower

initial earnings as well as earning growth than people who are employed with the same set of

characteristics. The example Hamilton (2000) gives is that ‘the present value to the median

entrepreneur of a business lasting 25 years is over 25 percent less than the present value of a paid job of the same duration’ (p. 628). Using data from the 1984 panel of the Survey of Income and

Program Participation (SIPP), Hamilton (2000) constructs self-employment versus paid

employment earnings differentials. The assessment of the results provides empirical evidence that

is consistent with the idea that being self-employed offers highly valued nonpecuniary benefits

9

Frey, Benz and Stutzer (2004) review individual panel data from Switzerland, Germany

and the United Kingdom in which outcomes such as income level and working time are controlled

for. They discover that self-employed individuals have higher job satisfaction than employees do.

Therefore, Frey et al. (2004) argue that entrepreneurs enjoy autonomy as it raises their happiness

level. Hurst and Pugsley (2011) got survey evidence from the Panel Study of Entrepreneurial

Dynamics with a sample of 34000 individuals in 2005 and 2006. They find evidence that

entrepreneurs claim that nonpecuniary benefits such as autonomy are a major driver for them to

engage in entrepreneurial activity.

Although much of the evidence discussed above suggests that autonomy plays an important

role in entrepreneurship, there is much more that needs to become clear about the precise nature

of autonomy for being an entrepreneurship driver. There is a promising link between autonomy

and entrepreneurship but, in order to label it as a driver for entry more evidence and research is

needed. Moreover, autonomy is often studied in isolation, which is why this study controls for

other potential determinants. Therefore, this thesis will use the differences between team and

individual sports athletes as a proxy; allowing for a clear distinction between the preference of

working alone or in a team.

Hypothesis 1: Preference for autonomy is positively related to entry into entrepreneurship.

10 2.2. Need for achievement

The need for achievement is about a person’s expectations to perform better and faster than

any other person or better than one’s previous achievements (Hansemark, 2003). It is argued that

people who have a high need for achievement are more likely to engage in tasks that require

individual skills and effort, have higher degrees of individual responsibility for outcomes, and have

some level of risk, as opposed to individuals who have a low need for achievement (McClelland,

1961). As entrepreneurship is characterized as entailing most of these tasks compared to other

jobs; McClelland (1961) argues, in an empirical study, that individuals with high levels of need

for achievement are more likely to engage in entrepreneurial activity.

Based on a review of 23 studies with varying samples, measurements of need for

achievement as well as definitions of entrepreneurship, Johnson (1990) finds that need for

achievement sets entrepreneurs apart from other people; causing there to be a relationship between

need for achievement and entrepreneurship. Fineman (1977) conducted a very similar review of 19 different studies and discovered that ‘both projective and questionnaire measures of need for

achievement significantly predict firm founding’ (Hansemark, 2003, p. 9). Projective measures are

often used in personality tests and are designed to reveal hidden emotions an individual might have

(Hansemark, 2003).

Carrahar, Buchanan and Puia (2010) collected data from 249 entrepreneurs from USA, 173

from Latvia, and 220 from China in order to examine the relationship between need for

achievement and entrepreneurship. Their study had a focus on cross-cultural need for achievement

and its relationship with other demographic and psychological variables. From the results,

Carrahar, Buchanan and Puia (2010) argue that achievement motivation is a valuable factor in the

11

Need for achievement is a characteristic that can be learned and developed over time

(McClelland, 1990; Rotter, 1966), making it difficult to study and measure as it can also change

over time with changes in social context. (Hansemark, 2003). Hansemark (2003) argues that the

only way to research whether need for achievement has predictive validity is by performing

longitudinal studies where the independent and dependent variables are kept separate. It is also

important to not ignore the gender-specific differences that could act as possible discriminating

factors (Hansemark, 2003). Therefore, this thesis will examine the relation by using an established

questionnaire measure and by using the highest level of sport achieved as a proxy.

2.3. Risk aversion

It is a well-known fact that entrepreneurship often has been linked to risk bearing, which

is why a certain risk preference is thought to affect the selection of people who enter into

entrepreneurship (Cantillon, 1979; Cramer et al., 2002; Knight, 1971; Say, 1971). Cramer et al (2002) used the “Brabant Survey” containing a dataset of 5800 schoolchildren. They were each

interviewed in 1952 at the age of 12, which covers the family background variables, and they were

re-interviewed in 1983 and 1993 in order to cover labour market history as well as entrepreneurial activity. Cramer et al’s (2002) findings show that entrepreneurship is encouraged by low risk

aversion. However, an issue arises in their approach as it does not deal with the variations of risk

attitude that occur over the lifespan of a person (Cramer et al., 2002).

In a review of studies, Parker (2009) compares the measures between non-entrepreneurs

and entrepreneurs. However, he is not able to come to a clear conclusion as some studies find that

there is no relationship between risk preferences and entrepreneurial activity, while other studies

non-12

representative of the greater population of entrepreneurs and non-entrepreneurs (Astebro, et al.,

2015).

Hvide and Panos (2014) take a different approach to research whether there is a connection between an individual’s risk preferences and entrepreneurship. They reviewed Norwegian

government data on 400,000 Norwegian’s who started their own venture between 2000 and 2007.

In their findings, they are able to show that the people who were active in the stock market and

showed a higher risk tolerance, by investing large amounts of their wealth, were more a likely to

start a business. Furthermore, Hvide and Panos (2014) also argue that the results from their

empirical studies are in line with the self-selection theory that less risk averse people are more

likely to start a new venture. However, in the start-up phase, these companies tend to be of poorer

quality than those of risk averse individuals (Hvide & Panos, 2014).

Koudstaal, Sloof and van Praag (2015) attempt to better understand the behavioural

characteristics of entrepreneurs and the reasons behind the mixed results by performing a

“lab-in-the-field” experiment in which they compare entrepreneurs to managers and employees. The initial

results indicate that entrepreneurs consider themselves to be less risk averse than managers and

employees. However, after using incentivized measures, the results indicate that entrepreneurs are

only unique due to their lower degrees of loss aversion rather than risk aversion. Koudstaal et al.

(2015), therefore, argue that perceived risk attitudes are correlated to both risk aversion as well as

loss aversion.

In an empirical study, Lerner and Malmendier (2013), attempt to characterize risk attitudes

in order to address the suggestive literature on entrepreneurs being less risk averse. They use injury

13

This thesis will further examine the relation between risk aversion and entrepreneurship by using

the type of sport played as a proxy.

2.4. Controls: overconfidence and parental entrepreneurship

Overconfidence is defined by individuals who are confident in their own skills and,

therefore, overestimate their chances at success (Koellinger, Minniti & Schade, 2007). Koellinger,

Minniti and Schade (2007) use a large sample of surveys from the Global Entrepreneurship

Monitor (GEM) to study variables—such as overconfidence—that could influence a person’s

decision to become an entrepreneur. Their results suggest that there is a possibility that it is often overconfidence rather than good assessments of an individual’s own abilities that leads them to act

entrepreneurial (Koellinger, Minniti & Schade, 2007). Therefore, they also suggest that

overconfidence may be part of the reason that there is a high failure rate for new business owners.

In an incentive compatible market entry experiment, Camerer and Lovallo (1999) find that

individuals tend to overestimate their chances of being successful; even more so when they know

that success will depend on their own skills and abilities. Other important distinctions of

overconfidence are over-placement and over-precision. In the over-placement concept, individuals

tend to assess their skills too high relative to others (Astebro et al., 2015). Lastly, over-precision is when an individual has a high certainty regarding one’s own beliefs (Astebro et al., 2015).

Overconfidence may be a potential driver for entrepreneurship. However, the above studies

do not provide enough evidence to conclude this notion. Studies have also noted that when an individual’s knowledge about the comparison group is low, there is a higher likability for that

14

the studies are not directly related to entrepreneurship as overconfidence is often seen as a

personality trait that applies generally (Astebro, et al., 2015).

According to Darling (1988), parental entrepreneurship is another key factor that can

influence whether people decide to engage in entrepreneurial activity or not. In a Swedish adoptee

study by Lindquist, Sol and Van Praag (2015), they find higher rates of entrepreneurial activity in

adults who were adopted by self-employed parents as well as in those of whom the birthparents

were self-employed.

In an empirical study, Dunn and Holtz-Eakin (1996) use data from the National

Longitudinal Surveys (NLS) and find that there is a positive relation between parent

entrepreneurship and the probability that their children would eventually engage in entrepreneurial

activity. This probability was doubled when the individual had entrepreneurial parents as opposed

to the individuals who did not have entrepreneurial parents.

Research Question 1: Which mechanisms (preference for autonomy, need for achievement, risk aversion or overconfidence) drive individuals to enter into entrepreneurship?

3. Methodology and Data

3.1. Data collection and sample

Data used in this thesis was collected by using established questionnaire measures and by

using sports data as proxies for the possible relationship between entrepreneurship and the

mechanisms as described below. The sample comes from a population of team sport athletes,

individual sport athletes, and non-athletes across the world. The questionnaire measure was

15

distributed through e-mail and social media’s personal messages, 91 questionnaires were

completed and collected between April and May 2016. See Appendix A for the questionnaire with

comments on variable construction (provided with asterisk) and Table 1 for the description of

statistics.

3.2. Measures

3.2.1. Dependent variable

The dependent variable in this thesis is entrepreneurship. In order to determine if an

individual is entrepreneurial, which is defined as being self-employed and/or having started one’s

own company, this thesis uses the following questionnaire measure: “Have you ever started a

company or been self-employed? 1. Yes, 2. No.”

3.2.2. Preference for autonomy

This study also uses a set of questions developed by Burchardt, Evans and Holder (2012)

to measure preferences for autonomy. Their measures consider specific areas of life such as,

work/life balance, relationships, and household expenses. Each of these areas allow for autonomy

to be explored and, ultimately, reveal individuals who show limited levels of autonomy. This method is used because it taps into the individual’s personal need for autonomy, which Hisrich

(1985), in an interview study, found to be a key factor for people to enter into entrepreneurship.

Moreover, the sports data also offers a proxy for preference for autonomy by using the differences

between team and individual sports athletes.

The variable of preference for autonomy was constructed using the following questionnaire

16

(1-10 scale, 1 = low importance, 10 = high importance with regards to the question). The proxy for preference for autonomy was constructed by the following questionnaire measure: “Did you

participate in a team or individual sport? 1. Team Sport, 2. Individual Sport.”

3.2.3. Need for achievement

In order to measure an individual’s need for achievement, this thesis borrows questions

used by Hermans (1970), in which he is able to develop a scale for the achievement motive with ‘substantive validity, internal consistency, and discriminant validity’ (p. 355). Measuring need for

achievement is an important part of this thesis as it is often argued that the higher a person’s need

for achievement, the higher the chance is that this person will enter into entrepreneurship

(McClelland, 1961). The need for achievement variable is constructed as follows: “When I work,

the demands I place on myself are: 1. Very High, 2. High, 3. Pretty High, 4. Not so High, 5. Low,

6. Very Low.” (1-6 scale, 1 = very high, 7 = very low). In addition, the proxy variable is constructed as follows: “What is the highest level of sport you have played? 1. Regional, 2. National, 3.

International, 4. College/University, 5. Professional.”

3.2.4. Risk aversion measure

When measuring for risk aversion, questions from the SOEP survey are used. The SOEP

is a panel survey of residents of Germany. Dohmen et al. (2005) uses the SOEP survey as a

reference to create a similar English version of the questionnaire, which asks in multiple ways about a person’s risk preferences. This particular measure is used in this thesis in order to examine

whether there is a relation between certain risk preferences and the selection of individuals who

17

all of the measures contain some form of doubt as they allow the respondent to picture the stakes

and probabilities that are involved with risk-taking in a given period (Dohmen et al., 2005).

Following Lerner and Malmendier (2013), sports differ by their prevalence of injuries, I use the

type of sport played by the respondent as a proxy for risk aversion.

The variable for risk aversion has been set up with the following questionnaire measures: “On a scale from 1-10, how much do you consider yourself to be a risk-taking person?” (1-10

scale, 1 = not a risk taker, 10 = high risk taker). I also use “On a scale from 1-10, what is your risk tolerance with regards to your professional career.” (1-10 scale, 1 = low risk tolerance, 10 = risk

tolerance). For the proxy variable this thesis uses: “Which sport have you participated in or are currently participating in?” (Fill in the blank where direct contact sports were assigned the number

0, non-contact sports were assigned the number 1).

3.2.5. Control measures

The measures in the questionnaire consist of some demographic measures such as, gender,

age, education level, and current occupation. Furthermore, parental entrepreneurship is measured

by the question whether the individual’s parents have ever started a company or not. The

demographic measures in this thesis are used as control variables.

Lastly, the questionnaire measures for the controls of overconfidence and parental

entrepreneurship. The controls remain unchanged throughout the tests, which allows for a better

understanding of the relationship between the above mentioned variables that will be tested.

Overconfidence is measured by a procedure that is widely cited and used in studies

performed by Fischoff et al. (1977). An example of the procedure is given by Busenitz and Barney

18

most common cause of death in the world? 1. HIV, 2. Heart Disease.” (50%-100% scale, 50%

meaning that the respondent guessed, 70% meaning that there were 7 out of 10 chances that the

answer was correct, and 100% would indicate the highest level of confidence).

3.3. Data Description

The descriptive statistics presented in Table 1 show that the average age of the respondents

was 26 (M=26.22). After an initial look at the descriptive statistics, several interesting observations

can be made. First, preference for autonomy (“On a scale from 1-10 how important is it for you to

have control over your own work/life?”) appears to be of some importance as the respondents

scored an average of 8.45. The preference for autonomy proxy (“Did you participate in a team or individual sport?”), however, shows that there were almost as many individual athletes (40) as

there were team sport athletes (51). Furthermore, it can be observed that risk aversion (“On a scale

from 1-10, how much do you consider yourself to be a risk-taking person? On a scale from 1-10,

what is your risk tolerance with regards to your professional career”) bears some importance as

respondents scored an average of 7.06 (M=7.06) with a standard deviation of 1.38 (SD=1.38) when

measuring the statements together.

According to Field (2009) it is also important to check for multicollinearity, which may

appear when the levels of the correlations are high. Field (2009) also explains that the variance

inflation factors (VIF) are at a critical level when they have a value of 10 or tolerance below 0.2.

After examining the VIF values and the tolerance levels of the data, it is found that most of the

VIF values are around 1.3 with the exceptions of the preference for autonomy proxy (2.36) and

the risk aversion proxy (2.22) while most of the tolerance levels are between 0.7 and 0.9. This

Table 1

Descriptive statistics, means, standard deviations, and correlations

Variable Mean Std. Dev. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

1. Entrepreneur 0.51 0.50 1 2. Parent Entrepreneur 0.71 0.45 0.056 1 3. Gender 0.63 0.49 0.008 0.065 1 4. Age 26.22 3.11 0.170 -0.254* 0.239* 1 5. Higher Education 0.71 0.45 -0.090 0.138 0.014 -0.057 1 6. Overconfidence 73.76 17.48 0.076 0.079 0.436** 0.149 0.063 1

7. Preference for autonomy 8.45 0.96 0.099 0.197 0.055 0.123 -0.033 0.036 1

8. Preference for autonomy proxy 0.44 0.50 0.079 0.217* -0.186 -0.034 -0.077 -0.174 0.302** 1

9. Need for achievement -0.01 0.80 -0.020 -0.087 0.157 0.103 0.014 0.054 -0.032 -0.210* 1

10. Need for achievement proxy 0.46 0.50 -0.054 0.244* 0.077 -0.173 -0.098 0.188 -0.045 0.024 -0.314** 1

11. Risk Aversion 7.06 1.38 0.276* 0.161 0.034 0.076 -0.043 0.065 0.336** 0.130 -0.248* 0.096 1

12. Risk Aversion proxy 0.56 0.50 0.054 0.126 -0.181 -0.109 0.028 -0.113 0.163 0.695** -0.264* 0.198 0.031 1

4. Data Analysis Results

As described in section 2, I tested two hypotheses and address one research question. Hypothesis 1 (see section 2) is tested by computing Pearson’s correlation between the measure of

preference for autonomy (“On a scale from 1-10 how important is it for you to have control over your own work/life?’) and entrepreneurship. As discussed in section 2, a positive correlation

between preference for autonomy and entry into entrepreneurship was hypothesized. However,

opposing the initial hypothesis, the results presented in Table 1 show that no correlation was found

between preference for autonomy and entrepreneurship.

Hypothesis 1b (see section 2) was also tested by using Pearson’s correlation between the

items that measure preference for autonomy (“On a scale from 1-10 how important is it for you to have control over your own work/life?”) and the preference for autonomy proxy (team sport or

individual sport). Once again a positive correlation was hypothesized. The results gathered for this

hypothesis show that there is indeed a positive correlation between the two with a significant

p-value (p<0.01).

Research question 1 (see section 2) was conducted using a stepwise logistic regression

analysis with entrepreneurship as the binary dependent variable and all the variables listed in Table

2 as the predictors. For the analysis, the best fitting model was chosen (highest Cox-Snell R-square and report Wald’s Chi-square) with associated p-value as tests of significance for each of the

predictors.

Observation of the results showed only one variable to be predictive of entrepreneurship in

the logistic regression; risk aversion (“On a scale from 1-10 how much do you consider yourself

to be a person that takes risk?”, “On a scale from 1-10 what is your risk tolerance with regards to

21

the influence on the dependent variable entrepreneurship. Table 2 also shows B, the standard error,

and the associated p-value testing the hypothesis that the value of the effect of the predictor is zero

(0). Here it can be observed that only risk aversion has a significant effect on entrepreneurship.

In order to add to this thesis, I ran the same stepwise logistic regression using the

incorporated entrepreneur rather than the entrepreneur as the dependent variable. However, the

results presented in Table 3 show that none of the predictors have a significant effect on

incorporated entrepreneurship.

Table 2

The effect of the independent variables on the dependent variable Dependent variable: Entrepreneur

Independent variables (1) (2)

1. Preference for autonomy -0.073 (0.265)

2. Preference for autonomy proxy 0.019 (0.669) 3. Need for achievement 0.115 (0.321)

4. Need for achievement proxy -0.389 (0.511) 5. Risk aversion 0.444 (0.188)**

6. Risk aversion proxy 0.440 (0.662) 7. Gender -0.244 (0.537) 8. Age 0.104 (0.079) 9. Higher education -0.449 (0.512) 10. Overconfidence 0.012 (0.015) *p<0.1, **p<0.05, ***p<0.01 Table 3

The effect of the independent variables on becoming an incorporated entrepreneur

Dependent variable: Incorporated Entrepreneur

Independent variables (1) (2)

1. Preference for autonomy -0.453 (0.595)

2. Preference for autonomy proxy -0.741 (1.188) 3. Need for achievement -0.319 (0.973)

4. Need for achievement proxy 0.127 (1.296) 5. Risk aversion -0.027 (0.427)

6. Risk aversion proxy 19.499 (6045.376) 7. Gender -1.114 (1.316)

8. Age 0.159 (0.196)

9. Higher education -1.079 (1.108) 10. Overconfidence 0.005 (0.034) *p<0.1, **p<0.05, ***p<0.01

22

5. Discussion and conclusion

Entrepreneurship scholars have long discussed the importance of preference for autonomy

in the decision to become an entrepreneur (Frey et al., 2004; Hurst & Pugsley, 2011; Shane et al.,

2003). However, there is little literature that uses the differences between team sport athletes and

individual sport athletes as a measure to examine which mechanisms potentially cause entry into

entrepreneurship. Therefore, this thesis attempts to take a different approach with regards to

examining the four widely studied mechanisms, preference for autonomy, need for achievement,

risk aversion, and overconfidence, by using team sport and individual sport athletes as a proxy

measure.

In an attempt to fill a gap in the literature, this thesis provides data from established

questionnaire measures in which each measure specifically measures one of the four mechanisms

(preference for autonomy, need for achievement, risk aversion, and overconfidence). All of the

respondents were chosen by the criteria that they currently participate in a sport or have previously

participated in a sport. It was expected that preference for autonomy would positively relate to

entry into entrepreneurship as previous studies have shown (Hamilton, 2000; Hisrich, 1985; Shane,

Locke & Collins, 2003). However, the results gathered in the data analysis section of this thesis

show that there is no positive correlation between entrepreneurship and preference for autonomy.

This is not the result that was expected, which could be due to the fact that only a limited number

of surveys were completed during this study.

For future research, it would benefit the researcher to perform a longitudinal study, which

this study was not able to do in a limited amount of time. By performing a longitudinal study, the

researcher will be able to measure the mechanisms (need for achievement, preference for

23

become) an entrepreneur, allowing for the causality between the mechanisms and entrepreneurship

to be judged differently (Hansemark, 2003). It would be interesting to study the development of

these characteristics in young athletes and how they pertain to entrepreneurship in a broader sense.

This research tries to make a methodological contribution to the literature by exploring

whether individual sports versus team sports can be used as a proxy for the preference for

autonomy. As expected, the results show that individual athletes have a higher preference for

autonomy. It was also expected that individual athletes, because of their higher preference for

autonomy, would tend to engage in more entrepreneurial activity than team sport athletes.

However, the data analysis provides no evidence that this is the case.

Another limitation of this study is the usage of a high variety of established questionnaire

measures. It is often good to use established questionnaire measures, but when the measures are

very different from each other (i.e. using different scales of measurement), the Cronbach’s Alpha

will be too low to group them in the data analysis. Therefore, this limitation comes from a fault in

some of the established questionnaire measures. Future researchers of this subject should pay close

attention to the questionnaire measures that they are going to use and should focus on measures

with a high enough Cronbach’s Alpha, which will allow them to group each mechanism in order

to create a stronger data analysis.

Lastly, this thesis contributes to the current entrepreneurship literature with regards to

finding out which mechanism, if any (or multiple), could be a positive driver for entry into

entrepreneurship. Previous literature provides evidence that a high need for achievement plays a

positive role in the decision to become an entrepreneur (Hansemark, 2003; McClelland, 1961).

Hurst and Pugsley (2011) argue that individuals enter into entrepreneurship due to nonpecuniary

24

different evidence and show that two of the measures for risk aversion play a role in the decision

to become an entrepreneur. The measure shows that a high score on the risk aversion question

(high score = low risk aversion) has a significant effect on the decision to enter into

entrepreneurship. This is very much in line with the findings from Koudstaal et al. (2015) where

the results show that entrepreneurs consider themselves to be less risk averse than managers or

employees do. They also indicate that perceived risk attitudes are correlated to both risk aversion

and loss aversion. Therefore, it can be concluded that rather than preferences for autonomy, a person’s low levels of risk aversion as well as loss aversion could cause entry into

25

6. References

Arai, A., Ko, Y.J. and Ross, S. (2014) ‘Branding athletes: exploration and conceptualization of athlete brand image’, Sport Management Review, Vol. 17, No. 2, pp.97–106.

Arnold, R., Fletcher, D. and Molyneux, L. (2012) ‘Performance leadership and management in elite sport: recommendations, advice and suggestions from national performance directors’, European Sport Management Quarterly, Vol. 12, No. 4, pp.317–336. Åstebro, T., Herz, H., Nanda, R., Weber, R. A., Perspectives, E., & Weber, R. A. (2015).

American Economic Association Seeking the Roots of Entrepreneurship : Insights from Behavioral Economics Seeking Insights the Roots of Entrepreneurship : from Behavioral Ramana, 28(3), 49–69.

Burchardt, T., Evans, M., & Holder, H. (2012). Measuring inequality: autonomy: the degree of empowerment in decisions about one’s own life.

Busenitz, L. W., & Barney, J. B. (1997). Differences between entrepreneurs and managers in large organizations: Biases and heuristics in strategic decision-making. Journal of

business venturing, 12(1), 9-30.

Camerer, C., & Lovallo, D. (1999). Overconfidence and excess entry: An experimental approach. The American Economic Review, 89(1), 306-318.

Cantillon, R., 1979. In: Takumi, T. (Ed.), Essai sur la Nature du Commerce en General, 1st Edition. Kinokuniya Book-Store Co., Tokyo, 1755.

Carraher, S. M., Buchanan, J. K., & Puia, G. (2010). Entrepreneurial need for achievement in China, Latvia, and the USA. Baltic Journal of Management,5(3), 378-396.

Cooper, Arnold C., Carolyn Y. Woo, and William C. Dunkelberg. 1988. "Entrepreneurs' Perceived Chances for Success." Journal of Business Venturing 3(2): 97-108. Cooper, David

Cramer, J. S., Hartog, J., Jonker, N., & Van Praag, C. M. (2002). Low risk aversion encourages the choice for entrepreneurship: An empirical test of a truism. Journal of Economic

Behavior and Organization, 48(1), 29–36.

0

Darling, R. B. (1988). Parental entrepreneurship: A consumerist response to professional dominance. Journal of Social Issues, 44(1), 141-158.

26

Dohmen, T. J., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. G. (2005). Individual risk attitudes: New evidence from a large, representative, experimentally-validated survey.

Dunn, T., & Holtz-Eakin, D. (1996). Financial capital, human capital, and the transition to

self-employment: Evidence from intergenerational links (No. w5622). National bureau of

economic research.

Field, A. (2009). Discovering statistics using SPSS. Sage publications.

Fineman, S. (1977). The achievement motive construct and its measurement: where are we now? British Journal of Psychology, 68, 1–22.

Frey, B. S., Benz, M., & Stutzer, A. (2004). Introducing procedural utility: Not only what, but also how matters. Journal of Institutional and Theoretical Economics (JITE)/Zeitschrift

für die gesamte Staatswissenschaft, 377-401

Goldsby, M. G., Kuratko, D. F., & Bishop, J. W. (2005). Entrepreneurship and Fitness: An Examination of Rigorous Exercise and Goal Attainment among Small Business Owners*. Journal of Small Business Management, 43(1), 78–92. 627X.2004.00126.x

Gruber, J., & Poterba, J. (1994). Tax incentives and the decision to purchase health insurance: Evidence from the self-employed. The Quarterly Journal of Economics, 701-733. Hamilton, B. H. (2000). Does entrepreneurship pay? An empirical analysis of the returns to self‐

employment. Journal of Political economy, 108(3), 604-631.

Hansemark, O. C. (2003). Need for achievement, locus of control and the prediction of business start-ups: A longitudinal study. Journal of Economic Psychology, 24(3), 301–319. http://doi.org/10.1016/S0167-4870(02)00188-5

Hermans, H. J. (1970). A questionnaire measure of achievement motivation. Journal of Applied

Psychology, 54(4), 353.

Hisrich, R. D. (1985). The woman entrepreneur in the United States and Puerto Rico: a comparative study. Leadership and Organizational Development Journal, 5, 3–8. Hurst, E. & Pugsley, B. (2011). "What Do Small Businesses Do?" Brookings Papers on

Economic Activity 43(2): 73—142.

Hvide, H. K., & Panos, G. A. (2014). Risk tolerance and entrepreneurship. Journal of Financial

27

Katz, N. (2001). Sports teams as a model for workplace teams: Lessons and liabilities. Academy

of Management Executive, 15(3), 56–67. http://doi.org/10.5465/AME.2001.5229533

Kazemi, R. M., & Madandar, S. (2012). Identifying the Factors Affecting Entrepreneurial Attitude of Athlete & Non-athlete University Students. Retrieved March 28, 2016, from http://www.ifrnd.org/Research Papers/I4(6)6.pdf

Kenny, B. (2015). Meeting the entrepreneurial learning needs of professional athletes in career transition. International Journal of Entrepreneurial Behavior & Research, 21(2), 175– 196. http://doi.org/10.1108/IJEBR-07-2013-0113

Knight, F.H., 1971. In: Stigler, G.J. (Ed.), Risk, Uncertainly and Profit, 1st Edition. Chicago University Press, Chicago, 1921

Koellinger, P., Minniti, M., & Schade, C. (2007). “I think I can, I think I can”: Overconfidence and entrepreneurial behavior. Journal of economic psychology, 28(4), 502-527.

Koudstaal, M., Sloof, R., & Van Praag, M. (2015). Risk, Uncertainty, and Entrepreneurship: Evidence from a Lab-in-the-Field Experiment. Management Science.

Lerner, J., & Malmendier, U. (2013). With a little help from my (random) friends: Success and failure in post-business school entrepreneurship.Review of Financial Studies, 26(10), 2411-2452.

Lichtenstein, S., & Fischhoff, B. (1977). Do those who know more also know more about how much they know?. Organizational behavior and human performance, 20(2), 159-183.

Lindquist, M., Sol, J., and Van Praag, M. (2012). “Do Entrepreneurial Parents Have Entrepreneurial Children?,” IZA Discussion Paper No. 6740 (September)

Lumpkin, G. T., Cogliser, C. C., & Schneider, D. R. (2009). Understanding and measuring autonomy: An entrepreneurial orientation perspective. Entrepreneurship: Theory and

Practice, 33(1), 47–69. http://doi.org/10.1111/j.1540-6520.2008.00280.x

McClelland, D. C. (1961). The achieving society. Princeton, NJ: Van Nostrand.

McClelland, D. C. (1990). Human motivation. Cambridge: Cambridge University Press. Moskowitz, Tobias J., and Annette Vissing Jorgensen. (2002). "The Returns to Entrepreneurial

Investment: A Private Equity Premium Puzzle?" American Economic Review 92(4): 78.

Parker, Simon C. 2009. The Economics of Entrepre neurship. Cambridge University Press. Parris, D. L., Troilo, M. L., Bouchet, A., & Peachey, J. W. (2014). Action sports athletes as

28

entrepreneurs: Female professional wakeboarders, sponsorship, and branding. Sport

Management Review, 17(4), 530–545. http://doi.org/10.1016/j.smr.2013.12.005

Ratten, V. (2011). Sport-based entrepreneurship: Towards a new theory of entrepreneurship and sport management. International Entrepreneurship and Management Journal, 7(1), 57– 69. http://doi.org/10.1007/s11365-010-0138-z

Ratten, V. (2015). Athletes as entrepreneurs: the role of social capital and leadership ability. International Journal of Entrepreneurship and Small Business. Retrieved from http://www.inderscienceonline.com/doi/abs/10.1504/IJESB.2015.070217 Rotter, J. B. (1966). Generalized expectancies for internal versus external control of

reinforcement. Psychological Monographs, 80 (Whole No. 609).

Say, J.B., 1971. A Treatise o Political Economy or the Distribution and Consumption of Wealth, 1st Edition. Augustus M. Kelley, New York, 1803

Shane, S., Locke, E. A., & Collins, C. J. (2003). Entrepreneurial motivation. Human resource

management review, 13(2), 257-279.

Van Praag, C. M., & Cramer, J. S. (2001). The roots of entrepreneurship and labour demand: Individual ability and low risk aversion. Economica, 68(269), 45–62.

http://doi.org/10.1111/1468-0335.00232

White, R. E., Thornhill, S., & Hampson, E. (2006). Entrepreneurs and evolutionary biology: The relationship between testosterone and new venture creation. Organizational Behavior and

Human Decision Processes, 100(1), 21–34. http://doi.org/10.1016/j.obhdp.2005.11.001

Terjesen, Siri A. (2007) Passing the Torch: Athletic and Entrepreneurial Endeavors. Ultrarunning, 27(5).

29

Appendix A

*Q1 Please insert your gender.  Male (1)

 Female (2)

*Q2 Please provide your current age.

 Dropdown menu ranging from “18” – “65 and older” *Q3 Highest degree of education completed:

 High school (middelbare school) (1)  MBO (2)

 HBO (3)

 Some college/university courses (4)  Bachelor's degree (5)

 Master's degree (6)  Doctorate degree (7) *Q4 Current employment status:  Self-employed (1)

 Incorporated entrepreneur (2)  Employed (3)

 Looking for work (4)

*Q5 Have you ever started a company or been self-employed?  Yes (1)

 No (2)

*Q6 Have your parents ever started a company or been self-employed?  Yes, 1 (1)

 Yes, both (2)  No (3)

**Q7 Did you participate in a team or individual sport? (Please pick the sport you participate in the most)  Team Sport (1)

30

**Q8 What is the highest level of sport you have played?  Regional (1)

 National (2)  International (3)  College/University (4)  Professional (5)

**Q9 Which sport have you participated in or are currently participating in? (Please pick the sport you participate in the most)

-Fill in the blank-

Q10 Other people think that I :  Work very hard (1)  Work hard (2)  Work pretty hard (3)  Don't work very hard (4)  Don't work hard (5)

*Q11 When I work, the demands I place upon myself are:  Very High (1)  High (2)  Pretty high (3)  Not so high (4)  Low (5)  Very low (6)

Q12 If I have not attained my goal and have not done a task well, then:  I continue to do my best to attain my goal (1)

 I exert myself once again to attain my goal (2)  I find it difficult not to lose heart (3)

 I am inclined to give up (4)  I usually give up (5)

Q13 I tend to be influenced by people with strong opinions  Strongly agree (1)

 Agree (2)

 Neither agree nor disagree (3)  Disagree (4)

31

Q14 I judge myself by what I think is important, not what others think is important  Strongly Agree (1)

 Agree (2)

 Neither agree nor disagree (3)  Disagree (4)

 Strongly disagree (5)

*Q15 On a scale from 1-10, how important is it for you to have control over your work/life? 1= not important, 10= very important

______ Slide bar (1)

*Q16 On a scale from 1-10, how much do you consider yourself to be a risk-taking person?1= risk averse, 10= not risk averse

______ Slide bar (1)

*Q17 On a scale from 1-10, what is your risk tolerance with regards to your professional career?1= low risk tolerance, 10= high risk tolerance

______ Slide bar (1)

Q18 Imagine you have won 100,000 Euros in a lottery. Almost immediately after you collect, you receive a financial offer from a reputable bank, the conditions of which are as follows: There is the chance to double the money within two years. It is equally possible that you could lose half of the amount invested. What share of your lottery winnings would you be prepared to invest in this financially risky, yet lucrative investment?

 100,000 (1)  80,000 (2)  60,000 (3)  40,000 (4)  20,000 (5)  0 (6)

Q19 **IMPORTANT: Questions 19 - 24 are meant to measure a specific mechanism. Therefore, it is important that you do not look up the answers, but answer them using your own knowledge.**Luxembourg is considered to be the second richest country in the world. Please use your own knowledge to answer this question.

 True (1)  False (2)

32

*Q20 With regards to the previous question, please indicate how confident you are of your answer on a scale from 50% - 100% where 50% means that you guessed and 100% means that you were confident that your answer is correct.

______ Slide bar (1)

Q21 What is the most common cause of death in the world? Please use your own knowledge to answer this question.  HIV (1)

 Heart disease (2)

*Q22 With regards to the previous question, please indicate how confident you are of your answer on a scale from 50% - 100% where 50% means that you guessed and 100% means that you were confident that your answer is correct.

______ Slide bar (1)

Q23 Ukraine is the largest country in Europe. Please use your own knowledge to answer this question.  True (1)

 False (2)

*Q24 With regards to the previous question, please indicate how confident you are of your answer on a scale from 50% - 100% where 50% means that you guessed and 100% means that you were confident that your answer is correct.

______ Slide bar (1)