MASTER THESIS
The effect of the entrepreneur’s personality on their success,
among entrepreneurs in the Netherlands.
Name: Imre Johannes Schurer
Student number: 6191096
Institution: UvA (University of Amsterdam)
Master: Business Administration
Track: Entrepreneurship & Innovation Thesis supervisor: Mrs Karin Venetis
Second supervisor: Mr Tsvi Vinig Hand-in date: 7th August 2016
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Statement of originality
This document is written by Imre Johannes Schurer who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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Table of content
Table of content……… 3 Abstract……… 4 1. Introduction………... 5 1.1 Background………... 5 1.2 Contribution……….. 61.3 Outline of the thesis……….. 7
2. Theoretical framework………. 9
2.1 - Success of an entrepreneur………. 9
2.2 - Personality traits (variables) drawn from scientific research………. 12
2.3 - Scientific research variable – Innovativeness………. 13
2.4 - Scientific research variable - Openness to experience……… 14
2.5 - Personality traits (variables) drawn from Venture Capitalists……… 15
2.6 - Venture Capital variable – Commitment………. 16
2.7 - Venture Capital variable – Trustworthiness……… 18
2.8 - Conceptual model………... 19 3. Methodology……….. 20 3.1 Research method………... 20 3.2 Research design……….……… 20 3.3 Procedure……….. 23 3.4 Participants………... 23 4. Results……… 25 4.1 Respondent analysis……….. 25 4.2 Data analysis………. 28 4.3 Hypotheses testing……… 32
5. Conclusion and discussion……… 39
6. Implications……… 41
7. Limitations and further research……… 42
Reference list……….……… 43
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Abstract
This paper examines the effect that personality traits have on the success of an entrepreneur. From the existing literature there were four personality traits identified to have a positive effect on the success of the entrepreneur; innovativeness, commitment, trustworthiness and openness to experience. Using an online questionnaire a quantitative research was done into the effect that these four personality have on the success of the entrepreneur. Using a factor analysis trustworthiness and openness to experience were combined into one variable. During the analysis the influence of the combined variable trustworthiness and openness to experience was significantly positively related to the success of an entrepreneur, measured by the revenue. The other personality traits however did not have a significant enough relationship with the success of an entrepreneur. This was probably caused by the low number of respondent and the large number of freelancers (Dutch; ZZP). It is very interesting to see which personality traits have a positive influence on the success of an entrepreneur and further research is definitely needed to explore the personality traits and there relation to success, also in combination with other predictors of success.
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1 - Introduction
1.1 - Background
People often wonder what it would be like to be a successful entrepreneur, because they have a certain status, money and seem to have a good life. The question however is what makes these people successful entrepreneurs. It seems like the holy grail in the business world, because if it is known why certain people become successful entrepreneurs it can be predicted and exploited. The underlying reasons for entrepreneurial success can be found in a large variety of areas, for instance education, size of network, luck, personality traits or experience.
The education that a person took could be a predictor for the success of an entrepreneur, because the person could have more knowledge and therefore an advantage over others. Robinson and Sexton (1994) conducted a study to find out if there is an effect between education and the success of an entrepreneur. In this study they found that there is a positively significant relationship between education and success of an entrepreneur, but there are some downfalls in this research. The variable chosen for education was the number of years that a person had an education, with a significant difference of one year between entrepreneurs and people working for companies. It can be challenged if this research took a good look at the type of education, the difference can for instance be explained that entrepreneurs often have a delay of one year in their education because they are working to build a large social network.
To illustrate that a high education does not make an entrepreneur more successful, I take a look at two successful Dutch entrepreneurs. The first entrepreneur is Bert Twaalfhoven (Isenberg & Rennella, 2009) who founded more than 50 companies and sold one of his companies for approximately 120 million Euro several years ago (he is now retired). This Dutch entrepreneur went to the U.S. to study and eventually graduated at Harvard, while becoming the head of Harvard alumni worldwide. Bert Twaalfhoven became a successful entrepreneur after his high education at Harvard with access to a global network of Harvard alumni.
Another successful Dutch entrepreneur is Hennie van der Most (Mulder & Ten Cate, 2006) who became successful in the amusement park industry. Hennie van der Most did not go to a high ranking university, in fact he did not even go to a university and probably got his
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knowledge from practice (an on the job education). But nonetheless Hennie van der Most became a successful entrepreneur with a net worth of approximately 36-40 million Euro in 2011, according to Quote magazine. By looking at these two entrepreneurs a case could be made that an education is not a mandatory aspect of a successful entrepreneur and neither is a network of highly educated people.
So what could be the cause of the success of an entrepreneur. An education may contribute to success, but it is not necessary for success. There are lots of successful entrepreneurs (for instance Hennie van der Most) that did not go to a University and most professors with high educations that do not have successful companies. From that a conclusion can be drawn that the cause of a successful entrepreneur is not solely something that can be taught or something that can be acquired during life, but that the cause might be something a person is born with or in other words their personality traits. In this thesis I want to explore if personality trait are a factor is the success of an entrepreneur and what are these personality traits that are the cause of the success of an entrepreneur.
In the scientific literature there is a lot to find about what determines success, with a lot of debate about which variables are important and which are not important plus the relative importance of a lot of different variables. In practice, companies that deal with determining whether an entrepreneur is or will be successful are often Venture Capitalists (VC). They have to see which entrepreneur is good to invest in and which investment will give the VC the highest return. These VCs are specialised in investments in entrepreneurs and have a lot of experience with determining which variables are important for the success of an entrepreneur. In my thesis I want to find out what the relative importance is of the two most important variables drawn from the scientific research as opposed to the two most important variables VCs (or other investors) use to determine what makes entrepreneurs successful. The variables will be explained in the literary review. The following research question is the main focus of this thesis.
‘To what extend can the personality traits of an entrepreneur predict its success as an entrepreneur?’
7 1.2 - Contribution
With this research I try to fill a research gap in the area of predicting the success of an entrepreneur. The scientific field has done extensive research on variables that can predict success and they have found a lot of variables that relate to success in all sorts of circumstances. On the other hand there has been a lot of research on which criteria VCs use to determine whether to invest or not in certain entrepreneur in order to predict the success. What has not been done is to combine these two areas in one study to see which criteria are the most important ones in relation to each other. In this study I will use the two most important ones of each two fields, because it is not feasible to research more variables. By doing this research the scientific community can be shown a practical view and what investors look for in entrepreneurs in order to get a better understanding in how to predict success in entrepreneurship.
The managerial use for this research is to better understand the criteria that can be used to predict the success of an entrepreneur. If there is a better understanding of what determines success this could mean that investors can invest better and gain a much higher profit. On the other hand this means that entrepreneurs have a better understanding of which variables are important in their own success. A person’s personality trait is not easily changed, according to some impossible, but if it is known which personality traits are important these traits can be improved in business schools or even high school.
1.3 - Outline of the thesis
To answer the main question of this thesis a couple of sub questions have to be answered first, in order to come to the hypotheses (that will be set in the following chapter: Theoretical Framework). The three following sub question will each give a better understanding, in order to try and answer the research question. These sub questions will all be answered in the following chapter in which the existing literary is review. The sub questions will not be specifically mentioned in the following chapter, but the content of the next chapter answers the sub questions.
SQ1: What does it mean to be a successful entrepreneur and how do you determine whether an entrepreneur is successful?
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SQ2: What does the existing literature say about the two main personality traits that Venture Capitalists use to predict whether an entrepreneur will be successful?
SQ3: What does the existing literature say about the two main personality traits that are identified in scientific research that predict the success of an entrepreneur?
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2 - Theoretical framework
The following sections will give an overview of the literature on the topic of ‘Successful Entrepreneurs’. In the first section the broad topic of the successful entrepreneur will be discussed, in which I will try to grasp the research that has been done on this topic to the best of my knowledge. In the second section I will review the scientific research on personality traits and identify the two most important personality traits. The third and fourth section will be comprised of these two most important personality traits drawn from scientific research.
The fifth section will identify the two most important personality traits from research into VCs. The sixth and the seventh section will describe the two most important variables drawn from the VC research. The eighth and final section of the theoretical framework will hold the conceptual framework. The hypotheses are mentioned in the section on which they are based on.
2.1 - Success of an entrepreneur
The personality traits of an entrepreneur are a strong predictor for the success of the entrepreneur’s business performance. There are various types of research being done on the personality traits of an entrepreneur, direct research where the entrepreneur is the subject of the research and indirect research in which companies/organizations are being researched that have to select successful entrepreneurs. The most successful companies that have to select successful entrepreneurs are VCs (Venture Capitalists). These VCs have a big area of scientific research that focuses on how a VC operates and why they make the investment decisions that they do. Because VC research is an important part of all the research in entrepreneurial success this will be captured in two of the four research variables. The more traditional scientific research, with the entrepreneur as the central point of research, will also be captured in two of the four research variables.
VCs are the most successful investors in start-ups (entrepreneurs)(Walske & Zacharakis, 2009) and a key tool for economic and technological development (Megginson, 2004), which must mean that they have a good way of predicting if an entrepreneurs is going to fail or if an entrepreneur is going to succeed. The way that these investment companies
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make these decisions is therefore very interesting, because they make these decisions very quickly; six minutes initial screening and twenty-one minutes in proposal assessment (Hall & Hofer, 1993). Both US and Dutch VCs value the entrepreneur himself as the most important attribute in a company, being more important as the product, market and financial situation (Vinig & de Haan, 2002).
VCs use a variety of criteria to determine if an entrepreneur will be successful or if they are going to fail, which will be put into a business plan by the entrepreneur itself. This business plan is then evaluated by the VC who can get a lot of information from a business plan, among other things the expertise of the entrepreneur in running a business. How a business plan is constructed says a lot of the capacity of an entrepreneur’s ability to predict the future of the company and if he understand what he is talking about. A business plan is a condition for a VC to invest in a company and is a very important document (Mason & Stark, 2004). A business plan can be seen as a ticket to compete for capital, since there is limited capital, the VC market can be seen as an auction like environment (Elitzur & Gavious, 2011). After a VC evaluates the business plan in multiple stages (Fried & Hisrich, 1994) the determining factor in investing capital are the entrepreneurs themselves.
If an entrepreneur is more experienced and capable of running a business, the risk of failing is reduced and the potential return is increased. This is more important than the projected returns and projected turnover (Dixon, 1991). It is proven that entrepreneurs with a successful track record are more likely to succeed than entrepreneurs that have failed in the past or are first-time entrepreneurs, since they make the right choices at the right time (Gompers et al. 2010). This also applies to the educational level of the entrepreneur which has a positive influence on the success of an entrepreneur (Robinson & Sexton, 1994). A VC wants to get the most return out of its investment as well as a quick return and an IPO (Initial Public Offering) is an ideal way of achieving these goals. To achieve an IPO the entrepreneur is very important, because some entrepreneurs prefer a quick IPO and others prefer to keep their company under their own control for as long as possible. The entrepreneur’s personality is very important in this decision making process and can help the VC in meeting their goals (Williams, Duncan & Ginter, 2006).
There are some differences between successful entrepreneurs across countries. A VC has to deal with the specific country in which they are operating and make an investment decision based on the specific entrepreneurial characteristics. Since VCs originate from the
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U.S. (United States) most of the literature is focused on VCs from the U.S.. These VCs are also the most developed in their investment approach (Wright, Pruthi & Lockett, 2005). U.S. based VCs value human capital as the most important factor, while European VCs use other determining factors that are more spread across the entrepreneur, the market conditions and the companies financial situation (Muzyka, Birley & Leleux, 1996).
VCs based in the U.S. are investing more in the initial phases of the business when it is still a start-up, while the investments of VCs in other countries are more spread across every stage of a privately owned company (Wright, Pruthi & Lockett, 2005). This causes U.S. VCs to look at the entrepreneur differently than a VC from another country, since a beginning entrepreneur is different than an entrepreneur with a company that is an established privately owned company. Every country has a different kind of entrepreneur, these are some examples;
In the Netherlands for instance it is found that the growth ambition of an entrepreneur (related to success) is driven by necessity, fear of failure and perceived opportunity (Verheul & Mil, 2008), depending on the type of company (start-up vs. established).
Russian entrepreneurs on the other hand are very different, most of them can’t even read a balance sheet (Hisrich & Grachev, 1995). This requires a different approach on determining whether to invest or not, the entrepreneurs themselves are more important.
In India there is a huge liberal IT industry which gives a lot of investment opportunities. But the entrepreneurs in India are relatively new to a ‘free’ market since India used to be a bureaucratically controlled country. (Dossani & Kenny, 2002).
In almost every scientific article that can be found concerning successful entrepreneurs and VC investment decision making, the entrepreneur itself is the most important factor (or one of the most important factors). In a survey held among 100 VCs five out of the top 10 criteria on deciding on investing in a company were related to the entrepreneur’s experience or personality (MacMillan, Siegel & Narasimha, 1985).
There are some improvements to be made on identifying successful entrepreneurs. For instance the decision of an entrepreneur to find capital from a VC could cause a ‘freerider’ effect in which the entrepreneur chooses money instead of success (Elitzur & Gavious,
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2003b). This is sometimes overlooked by a VC and could cause a VC not to invest in some companies. Making a decision to invest or not is a difficult process and could be improved. 20% of VC backed companies still fail and there are also successful companies who did not get an investment from VCs before becoming successful. This could be improved using an actuarial decision model in which components are assessed separately (the entrepreneur, the market conditions, the product) and combined to form a final decision, opposed to making one decision on the whole investment opportunity (Zacharakis & Meyer, 2000). This method is shown in other sectors (for instance in banks) to be more accurate than even the experts making the assessment on the components. VCs can also benefit from using bootstrap models as a decision-aid in order to better predict if an entrepreneurs is a good leader or not. This could cause a higher investment success rate (Zacharakis & Sheperd, 2005).
2.2 - Personality traits (variables) drawn from scientific research.
The research into personality traits of an entrepreneur and the effect of these personality traits used to be researched a lot, but the empirical research into the personality traits of an entrepreneur reached an empirical dead end (Rauch & Frese, 2007). Rauch & Frese (2007) conducted a meta-analysis into this topic and tried to give a new boost for a renewed interest into empirical research of personality traits of entrepreneurs. They researched specific personality traits and their effect on both business success and business creation. The following traits seemed to have a significant effect.
- Need for achievement - Generalized self-efficacy - Innovativeness
- Stress tolerance - Need for autonomy - Proactive personality
That personality traits (can) have an effect on the success of an entrepreneur is considered to be true by most researchers, but which personality traits have an effect and too which extend they have an effect is not clear and evidence for it is scarce (Schmitt-Rodermund, 2004). If we consider the above mentioned personality traits that can influence the business success, it can also be the case that some of the personality traits are not really about entrepreneurs but more about people in general. The personality traits ‘innovativeness’
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and ‘need for autonomy’ are considered to be strong predictors for entrepreneurial success, because innovation is a key driver in success. Companies without innovation are almost never successful. The need for autonomy is a specific trait that can be strong in entrepreneurs, because autonomy is one of the key aspects of being an entrepreneur. If someone wants to be autonomous and is an entrepreneur, they might have more to lose if they do not have success because they can lose their autonomy.
Another view on personality traits in relations to entrepreneurs is whether some personality traits lead to people becoming entrepreneurs, thus excluding the success factor and only focussing on the step from employed to self-employment. It has shown that the following personality traits have a significant positive effect on the entry and survival of entrepreneurs (Caliendo, Fossen & Kritikos, 2011).
- Locus of control - Risk attitude
- Openness to experience (one of the Big Five personality traits) - Extraversion (one of the Big Five personality traits)
Risk attitude is thought to have a strong positive impact on the success of an entrepreneur, because taking risks is an essential part of being an entrepreneur. Openness to experience means that a person wants to experience new things and is willing to do certain activities in which the outcome is uncertain. This is exactly what entrepreneurs are often doing, since it is almost never certain (especially in the early stages) if the company will be a success or a failure.
The two most important criteria found in this literature are the Innovativeness of an entrepreneur and the Openness to Experience. These two criteria are the most important ones, because they are expected to have the highest relationship with the success of an entrepreneur and they can be measured.
2.3 - Scientific research variable - Innovativeness
Innovativeness is closely linked to entrepreneurs and entrepreneurs are thought of as being innovators, since they continuously do things that have not been done before (Marcati, Guido & Peluso, 2008). People are more likely to become entrepreneurs if they are more innovative, but does that mean that the more innovative an entrepreneur is the more successful
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he is going to become? This is of course a question that is very interesting in order to predict if an entrepreneur will succeed in starting a company. If an entrepreneur has more tendency to innovate the company achieves more innovations and is more successful than companies that do not innovate as much (Marcati, Guido & Peluso, 2008). An innovative entrepreneur can better find business opportunities and is more successful (Chandler & Jansen, 1992).
The relationship between the entrepreneur and his company is stronger at small companies than it is at larger companies, meaning a small company with an innovative entrepreneur is probably more innovative than a larger company with an entrepreneur that is equally innovative (Miller & Toulouse, 1986). A high-tech start-up has entrepreneurs who are more innovative than a low tech start up and these entrepreneurs are technically more capable. Because the return in high tech companies is higher than it is at low tech companies, investors are more likely to invest in companies in the high tech industry which has entrepreneurs with a higher level of innovativeness (Tyebjee & Bruno, 1984). Thus making an innovative entrepreneur more likely to attract capital and become more successful than an entrepreneur who is less innovative.
Innovative entrepreneurs seek out capital from sources that can provide more than just monetary help. They are actively seeking parties that can provide aid with finding a management team and helping them with their credibility (Timmons & Bygrave, 1986). These entrepreneurs get more added value from their source of capital and are more likely to succeed than other entrepreneurs who are more focussed on monetary incentives. An entrepreneur’s personality traits have without a doubt a relation to the success of the company and the innovativeness of this entrepreneur is one of the more important variables (Rauch & Frese, 2007).
Based on the above mentioned the following hypotheses are created which can be tested in the research described in this thesis. Innovativeness has a positive effect on the success of an entrepreneur. I expect it to have a higher effect on the success of an entrepreneur than the other three personality traits, because it can add the most value to the success of the entrepreneur.
H1: Innovativeness positively influences the success of an entrepreneur. H2: Innovativeness has the most influence on the success of an entrepreneur
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Sometimes entrepreneurs can be to focused on their own company while that company is not going to succeed. Some famous entrepreneurs e.g. Bill Gates and Walt Disney who have been hugely successful started failed companies before they became successful. This shows that to be a successful entrepreneur you have to be open to new experiences and not completely focus on you your own company (Demers, 2014). Out of the well-researched ‘Big Five’ personality traits openness to experience has been found to have the most effect on the success of an entrepreneur and the entrepreneurial development (Caliendo, Fossen & Kritikos, 2011). High-growth-oriented entrepreneurs are not focussed on their own company, but are ambitious and look for opportunities (Gundry & Welsch, 2001).
A higher openness to new experiences indicates that the person has a higher entrepreneurial competence, which in turn results in a higher degree of entrepreneurial interest. People having a higher entrepreneurial interest are more likely to start a company at a younger age, causing them a higher change of being successful combined with the personality traits of the entrepreneur (Schmitt-Rodermund, 2004).
Being an entrepreneur is all about finding opportunities and taking advantage of these opportunities. This is largely based on prior information that the entrepreneur has (Shane, 2000), but if the entrepreneur is not open to cease these opportunities, the company will not be as successful as it can be. Having a higher openness to experience causes people to be more probable to enter into entrepreneurial activities and become self-employed (Caliendo, Fossen & Kritikos, 2011). The following hypothesis is created based on the literature that openness to experience has a positive effect on the success of an entrepreneur.
H3: Openness to Experience positively influences the success of an entrepreneur.
2.5 - Personality traits (variables) drawn from Venture Capitalists.
VCs are companies that invest money (and expertise) in other companies in order to get more money in return over time, this is their core business. This investment is usually made out of different steps of capital investments over time and is preceded by an extensive selection procedure (Elitzur & Gavious, 2003a). In this extensive selection procedure the VCs try to determine if the entrepreneur is the right choice to get the maximum capital return. Therefore VCs use various criteria to determine if an entrepreneur will be successful. There are four main criteria that seem to be used by a lot of VCs and a number of ‘less’ important
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criteria. The less important criteria for predicting success are: Openness to Challenges, Ambition, Risk Taking, Creativeness and Market Timing Skills (Gompers et al. 2010; Dvir, Sahed & Malach-Pines, 2010)
The first of these main criteria is the experience that an entrepreneur has in his previous companies and in leadership positions: ‘The more experience an entrepreneur has, the more successful he will become.’ seems to be the VC mindset (Gompers et al. 2010; Zacharakis & Shepherd, 2005). The second main criteria is whether the entrepreneur has the commitment it takes to become successful, if an entrepreneur is more committed he will spend more time and has more to lose (Dvir, Sahed & Malach-Pines, 2010; Kollmann & Kuckertz, 2010). The third main criteria is the trustworthiness that an entrepreneur has, if the VC can trust the entrepreneur he is more willing to invest and he is confident with the fact that the entrepreneur will succeed (Fairchild, 2011; Duffner, Schmid & Zimmerman 2009). The final main criteria is the progress that an entrepreneur makes, which means how fast his company is growing (Elitzur & Gavious 2011). The faster and more sustainable a company is growing, the more likely it will be that that entrepreneur will be successful.
The two most important criteria that VCs use in determining in which entrepreneur to invest are the Trustworthiness of an entrepreneur and the Commitment the entrepreneur has to his company and to achieving his goals.
2.6 - Venture Capital variable - Commitment
If someone has the feeling he/she is involved in making something into a success it is called commitment. When we talk about the commitment of an entrepreneur to his company it is mostly mentioned as organizational commitment, which means that the entrepreneur has a personal interest in the success of the company (the organization). It is well researched that a high organizational commitment of an employee or entrepreneur has a positive effect on the company (Jak & Evers, 2010). This is partly because when an entrepreneur is more committed to the company, the satisfaction level of the entrepreneur is higher with the same outcome as opposed to an entrepreneur who is less committed (Cooper & Artz, 1995). When the entrepreneur is more committed, he/she does work for the company because of noneconomic motives. The motivation is because they want to do it and not because they have to do it. Entrepreneurs who set up their own company are more committed to the company than entrepreneurs who inherit a company or buy a company, which causes start-ups to be
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more successful than established companies who are not owned by the founder (Brandstätter, 1997).
VCs view the entrepreneurs as the decisive factor to invest in a company, with commitment being one of the most important aspects of the entrepreneurs character (Kollmann & Kuckertz, 2010). When VCs invest in a company in a high novelty and high technology industries there are higher return than in other industries. Entrepreneurs who start a company in these high novelty and high technology industries are often more committed to their company as entrepreneurs in other industries (Dvir, Sadeh & Malach-Pines, 2010). These entrepreneurs love the challenge of starting a company and ambitious in succeeding in the industry. Besides the effect that commitment has on the success of the company, more commitment also increases the likelihood that an entrepreneur is seeking external capital. When an entrepreneur is committed to the success of the company, he views the company positively and is more likely to seek capital from a VC. The VCs in turn can provide the company with much needed capital and expertise, thus increasing the likelihood for success (Eckhardt, Shane & Delmar, 2006). VCs also have to be careful of how they are going to invest in the company, because if the VC invests in the wrong way, this can cause the entrepreneur to lose the commitment to his/her company. A straight debt contract would be the most optimal way of financing a start-up company (Elitzer & Gavious, 2002).
To sum up, commitment is a very important factor in achieving success as an entrepreneur. It is probably not the deciding factor because being an entrepreneur automatically implies that there is at least some level of commitment (Rauch & Frese, 2000). But commitment is necessary to achieve success, if this implies that more commitment will result in a more successful entrepreneur is something this article will research. Both social scientists and VCs agree that commitment/motivation is a significant link in entrepreneurial success (Khan, 1986). The following hypotheses were created based on the theory. Commitment should have a positive influence on the success of an entrepreneur, but because it is seen as condition to become an entrepreneur it is probably not the decisive factor in success. Hypothesis five is created, because I expect commitment to be the least predictor of success.
H4: Commitment positively influences the success of an entrepreneur. H5:Commitment has the least influence on the success of an entrepreneur.
18 2.7 - Venture Capital variable - Trustworthiness
VCs try to predict if a company is going to be successful or not as best as they can, but it is impossible to know for sure. It is also not possible to completely cover everything in a contract. The trustworthiness of an entrepreneur is therefore very important. If an entrepreneur is trustworthy it is more likely that his predictions of the company’s future are more accurate than if the entrepreneur is not trustworthy. When a VC trusts the entrepreneur this might also cause the entrepreneur to be more successful (Duffner, Schmid & Zimmermann, 2009). When an entrepreneur is looking for capital, trust is a decisive factor in choosing which kind of capital the entrepreneur will choose and from which VC/investor he/she will accept capital. Therefore it is very important for a VC to have a trustworthy relationship between the VC and the entrepreneur, trust goes both ways (Fairchild, 2011).
Trustworthiness is associated with various other factors, like the entrepreneurs ability, benevolence and integrity. These factors influence the trustworthiness positively and have a strong influence on the entrepreneurs relationship with its source of capital (VCs, banks or other lenders). If an entrepreneur is trustworthy the lender often charges lower interest rates, this giving the entrepreneur a more favourable source of capital and causes the entrepreneur to have a greater chance of success (Howorth & Moro, 2012). There are differences in the importance of the entrepreneurs trustworthiness between VC markets in different countries. In countries where having a network is more important (for instance France & Belgium) the focus is more on what information the entrepreneur provides as opposed to more mature VC markets (for instance the U.K. & the U.S.) where the VC rely more on their own analysis (Manigart et al. 2000). If a VC has to rely on information from the entrepreneur it is logical that the trustworthiness of the entrepreneur is more important than if the VC makes their own extensive analysis. Based on the literature it is expected that trustworthiness has a positive effect on the success of an entrepreneur, which will be tested in the following hypothesis.
19 Trustworthiness Commitment Openness to Experience Innovativeness VC Criteria VC Criteria
Scientific Research Criteria Scientific Research Criteria
Succes of an Entrepreneur
+
+
+
+
2.8 - Conceptual modelThe model that is accompanied by the research question and tries to answer the research question is the basis of this thesis (Figure 1).
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3 - Methodology
In this chapter an overview of the research is given, the reason for choosing a research method and how this method was applied. Firstly, the research method is explained after which the design of the questionnaire is motivated. Then the procedure of administering the questionnaire is described and the desired participants are described.
3.1 - Research method
Because the variables in the hypotheses are well defined variables and extensively researched, a quantitative method is chosen to research the hypotheses. With a quantitative research method, relationships between known variables can be researched and the influence that a variable has on the success of an entrepreneur can be measured. To achieve this method an empirical investigation via an online survey was used.
3.2 - Research design
Because the variables used in the hypotheses are well researched the questions for the questionnaire were taken from previously defined surveys found in the literature. This gives the advantages of having proven and reliable questions that measure the desired variable. The complete questionnaire is added in Appendix A.
Almost the entire questionnaire is in English because most of the questions drawn from the literature were in English and translating them might cause discrepancies in the reliability. Only the questions about commitment were in Dutch, because the questions in the literature were also in Dutch. Translating these into English might cause reliability discrepancies and since the targeted group is Dutch entrepreneurs they can understand Dutch as well as they can understand English. The only possible respondent from the targeted group who cannot fill in the survey are Dutch entrepreneurs who cannot understand English. This is an acceptable risk given the advantages this method gives.
As answers to the questions the well-used Likert scale is used in this questionnaire. The Likert scale is used in academic research and is thought of as very reliable. Using this scale means that respondents can give an answer to the question (a statement) in which the respondent can give an answer from 1 till 7. If the respondent fills in a score of 1 it means that he strongly disagrees and that the statement doesn’t apply on him/her. If the respondent
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replies with a score of 7 it means that he strongly agrees and that the statement applies on him/her. The score 2 till 6 means the following; moderately disagree, slightly disagree, neither disagree/nor agree, slightly agree and moderately agree (Aaker, 1996).
To measure openness to experience questions were taken from a paper written by Donnellan et al. (2006) in which they created the mini-IPIP. In this article four questions are given (three are reversed) and are almost as reliable as the larger IPIP-FFM scale which is often used to measure the ‘Big Five’ personality traits. The Cronbach’s Alpha of these questions is between 0.65 and 0.70, which is a strong Cronbach’s Alpha.
1. I have a vivid imagination. (Strongly disagree - Strongly agree)
2. I am not interested in abstract ideas. (Strongly disagree - Strongly agree) (R)
3. I have difficulty understanding abstract ideas. (Strongly disagree - Strongly agree) (R) 4. I do not have a good imagination. (Strongly disagree - Strongly agree) (R)
To measure innovativeness the questions were taken from a paper written by Marcati, Guido and Peluso (2008) with three reversed questions. The Cronbach’s Alpha is not mentioned, but it is mentioned that these questions are a strong predictor for innovativeness.
1. In general, I am among the last in my business sector to adopt an innovation within my company. (Strongly disagree - Strongly agree) (R)
2. If I heard that an innovation was available, I would be interested in adopting it within my organisation. (Strongly disagree - Strongly agree)
3. Compared to my competitors, I own few innovations (Strongly disagree - Strongly agree) (R) 4. I will adopt innovations, even if I have only heard of it yet. (Strongly disagree - Strongly agree)
5. In general, I am the last in my business sector to know the content of the latest innovation. (Strongly disagree - Strongly agree) (R)
6. I know the content of innovations before other people do. (Strongly disagree - Strongly agree)
To measure trustworthiness the questions were taken from a paper written by Howorth and Moro (2012) and contained no reversed questions. The Cronbach’s Alpha for the four questions and six others is 0.88, but in order to reduce the number of questions only the four strongest questions were put into this questionnaire.
1. I have a very good knowledge of the market in which my company operates. (Strongly disagree - Strongly agree)
2. I am very able in identifying the needed resources. (Strongly disagree - Strongly agree) 3. I am very able in managing resources. (Strongly disagree - Strongly agree)
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To measure commitment the questions were taken from a paper written by Jak and Evers (2010) and contained no reversed questions. The Cronbach’s Alpha for the five questions is 0.84, which is a strong Cronbach’s Alpha.
1. Ik ervaar de problemen van deze organisatie als mijn eigen problemen. (Sterk oneens - Sterk eens) 2. Ik heb het gevoel dat ik echt bij deze organisatie hoor. (Sterk oneens - Sterk eens)
3. Ik voel me emotioneel gehecht aan deze organisatie. (Sterk oneens - Sterk eens) 4. Ik voel me als ‘een deel van de familie’ in deze organisatie. (Sterk oneens - Sterk eens) 5. Deze organisatie betekent veel voor mij. (Sterk oneens - Sterk eens)
Measuring the success of an entrepreneur is a very difficult thing to do, because there is no agreed concept of the success of an entrepreneur. Some people say that the bigger the company, the more successful the entrepreneur is. But others say that a higher profit of a company, means the entrepreneur is more successful. VCs measure the success of a company by the rate of return that they receive on their investment (Duffner, Schmid & Zimmerman, 2009), but this cannot be asked of entrepreneurs (respondents) because not all of them have VC investment structures. In several articles the growth (profit/sales) and the revenue are described as a measurement of success, following questions are based on these articles with a scale that is present in appendix A (Chandler & Jansen, 1992,Rauch & Frese, 2000, Schmitt-Rodermund, 2004).
1. How much growth/decline did your company have in the previous 5 years in sales? 2. How much growth/decline did your company have in the previous 5 years in net profit? 3. What was your revenue last year? (EUR)
In order to gather statistics there are several control variables added in the questionnaire, these are the normal control variables that give general information but will not be used in testing the hypotheses.
1. Male or Female?
2. What is the size of your company? 3. What is your age?
23 3.3 - Procedure
To make the online questionnaire and to distribute it easily it was constructed using an online survey tool: http://www.thesistools.com/. With this survey tool a questionnaire could be made easily and a link could be mentioned in the invitation to fill in the questionnaire. Because the focus of this research was Dutch entrepreneurs (mentioned below in the section ‘participants’) the invitation to fill out the questionnaire was made in Dutch. It is difficult to find entrepreneurs to fill in the questionnaire, since entrepreneurs are busy people and are not likely to fill in a questionnaire send via e-mail. In order to reach Dutch entrepreneurs the method chosen to reach these entrepreneurs was LinkedIn and internet forums for Dutch companies. LinkedIn is an online network for professionals and companies. Since entrepreneurs are very present on LinkedIn it was thought of as an ideal tool to find entrepreneurs in order to get respondents for the questionnaire.
Invitation to fill out the questionnaire: Invitation Survey; ‘Successful Entrepreneur’.
Hello, I am working on a research into the personality traits of entrepreneurs and what the influence of these traits are on the success of their company. I would like to ask you to fill in this survey (maximum of 5 minutes) to help me in my research. Of course you would get the results of this survey send to you after filling in the survey, this will give a valuable insight into the decisive factors of investors and successful entrepreneurs. I am doing this research at the University of Amsterdam and the results are not used for commercial purposes. http://www.thesistools.com/web/?id=288337
LinkedIn groups in which the survey invitation was posted;
Amsterdam Inc., Business Model Generation, Economics and Business Network - University of Amsterdam, HvA Alumni Technische Bedrijfskunde, MKB Ondernemers Netwerken, MKB netwerkorganisatie, MKB-Amsterdam, MKB-Nederland, NL Startups, Technische
Bedrijfskunde TBK, Iedereen Ondernemer, Week van de Ondernemer 2012, ABN AMRO
Ondernemer & Onderneming, Ondernemers uit Nederland en Vlaanderen krijgen nu gratis leads, Ondernemen & Opdrachten, 100ondernemers, Maatschappelijk ondernemen?, Ondernemerssupport, Jong & Ondernemer, deOndernemer, Cultuur-Ondernemen
3.4 - Participants
In order to narrow the research and give a more valuable analysis on the outcome, the questionnaire will be distributed via a method in which only Dutch entrepreneurs will be able
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to fill in the questionnaire. This way the results will be specified to Dutch entrepreneurs, since only they would fill in a questionnaire with a Dutch invitation and (several) questions. The preferred respondents are a mix of successful entrepreneurs and unsuccessful entrepreneurs, since the difference between the two is what this research is investigating. It is likely that the majority of the respondents are male, since historically men are more prone to start a company. This is changing (or already has) but it will take some time until there are as many (or more) female entrepreneurs.
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4 - Results
In this chapter the results are given of the questionnaire. Firstly the analysis of the respondents is given with a descriptive overview of the data. Secondly the analysis of the data is presented to check if the variables are reliable and what the correlation is between the different variables. To conclude this chapter the hypotheses are tested. All of the analysis in being done in SPSS 22, a tool for statistical analysis.
4.1 - Respondent analysis
The questionnaire was distributed on LinkedIn forums, with the number of members ranging from 100 till 50.000, and on Dutch business forums on the internet. Out of the 118 respondents only 48 respondents filled in the entire survey, so the respondents that can be used in the analysis is 48. Because 48 is not enough to give a proper analysis, a second round of data gathering has been done. In this second round of data gathering 75 respondents filled in the entire survey. This means that the total number of respondents that can be used in the data analysis is 123. To get a better data set for analysis several respondents were removed from the data, because they were outliers or not suitable for this research. Twenty respondents were removed, because the respondents owned companies larger than the targeted respondent (thirteen Small and Medium, three Large companies and four Multinationals). One respondent was removed from the data set, because the revenue of the entrepreneur’s company was significantly higher than of the other respondents. The revenue of this respondent’s company was between 4,5 million EUR and 4,75 million EUR (19 on a scale of 1 till 21), while the second highest had a revenue between 2,5 million EUR and 2,75 EUR (a score of 11). Removing this one respondent meant that the scale of the variable could be decreased to a scale of 1 till 11 instead of 21, giving a better chance of a more valuable analysis. Nineteen respondents were removed from the data set because of the age of the respondent’s company, which was older than twenty years. By doing this the spread over the age of the company is more even an gives a better possibility of a reliable analysis. The remaining number of respondents used in further analysis is 83. Out of the 83 used respondents 36,1 % were female and 63,9 % were male and all of the respondents own companies employing between one and ten employees. The other control statistics are shown in figure 2 and 3, the descriptive statistics of all the variables are shown in table 1.
26 Figure 2 – Age of respondents
Table 1 – Descriptive statistics of all variables used in the analysis (1) value is 1 (Male) or 2 (Female).
(2) value is between 1 (younger than 20) and 6 (older than 60), with trances of 10 years. (3) value is always 1 (SOHO company, between 1 and 10 employees).
(4) value is 7 point Likert scale with 7 being highest score on that value. (5) value combines growth net profit and sales
(6) value is between 1 (the entrepreneurs company is 1 year old) and 20 (20 years old)
(7) value is between 1 (between 0 and 250.000 EUR) and 11 (between 2,5 million and 2,75 million EUR), with trances of 250.000 EUR.
(8) value is a combines value of the revenue and the two growth variables (net profit and sales growth).
(9) Value is between 1 (a decline between 50% and 25%) and 12 (an increase of more than 200%),with trances of 25%.
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The descriptive statistics show that there are more male respondents than that there are female respondents, which was predicted and is not surprising. There is an even spread of age among the respondents with the largest age group being between 50 and 60 years, which might be caused by being financially independent and being able to take the risk of starting a company and taking on the responsibility of owning your own company. The categories which have the least respondents are older than 60 (close to retirement age) and younger than 20 (only 2). Looking at the company age of the respondents there are three peaks of three, five and 12 years, the rest of the respondents are spread reasonably evenly. It would be preferable to have a larger group of respondents that own companies with a lower age, but this is not the case. This could be explained because there are a lot of freelance (zzp in Dutch) companies where one person is its own company.
In the variables Finance, Growth, CompAge, GrowthSales, GrowthProfit and Revenue there is a high maximum and (except Growth) a high standard deviation, this is caused by the number of possible answers used in the questions (the spread). The Cronbach’s Alpha of the Growth and the Finance variable is however good enough to be reliable (as is mentioned in the data analysis following after the respondent analysis). It is interesting to see that the mean of the variable commitment is significantly higher than the other variables to measure the personality traits. This might be explained by the fact that entrepreneurs own their own companies and there livelihood depends on the income of that company, meaning that they have to be committed to their company because they have nothing to fall back on. And people
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Commitment Innovativeness Trust_Openness Organizational commitment
Ik heb het gevoel dat ik echt bij deze organisatie hoor. .833
Ik voel me emotioneel gehecht aan deze organisatie. .902
Ik voel me als ‘een deel van de familie’ in deze organisatie. .913
Deze organisatie betekent veel voor mij. .934
Innovativeness
In general, I am among the last in my business sector to
adopt an innovation within my organization (R) .769
Compared to my competitors, I own few innovations (R) .553
I will adopt an innovation, even if I have not heard of it yet .691
In general, I am the last in my business sector to know the
content of the latest innovations (R) .765
I know the content of innovations before other people do. .778
Trustworthiness
I have a very good knowledge of the market in which my
company operates. .570
I am very able in identifying the needed resources. .636
I am very able in managing resources. .849
I understand the changing market conditions. .881
Openness to experience
I Am not interested in abstract ideas. (R) .894
Have difficulty understanding abstract ideas. (R) .870
Do not have a good imagination. (R) .923
might not be honest in filling in the questions about commitment, since they might like to be viewed as committed people.
4.2 - Data analysis
Factor Analysis
To determine if the questions regarding the independent variables can be combined into the variables related to the questions a factor analysis needs to done. By doing a factor analysis reliable variables can be created. All of the 19 questions for the independent variables were used in the factor analysis. The Kaiser-Meyer-Olkin value is 0.814, which is above the required 0.60. This means that the sample is large enough and the differences between the variables are large enough to go further in the analysis. There were four components identified which explained more than the required 60% (69%).
Three questions had a cross-load over multiple components which had to be removed from the analysis. The remaining 16 questions were divided over three components and had a
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Kaiser-Meyer-Olkin value of 0.803, which is higher than the required 0.60. All of the questions regarding commitment were associated with one component. All of the questions regarding innovativeness were associated with one component, plus one question regarding trustworthiness (I have a very good knowledge of the market in which my company operates). Because the content of this question can be related to innovativeness the question will be combined with innovativeness for further analysis. The rest of the questions regarding trustworthiness and openness to experience were associated with one component. This means that the respondents viewed the questions regarding trustworthiness and openness to experience as similar. For further analysis these two variables can’t be analysed separate and the questions will be combined into one new variable; trust_openness. The outcome of the factor analysis is shown in table 2 and the three question that are not used in further analysis are the following;
Commitment - Ik ervaar de problemen van deze organisatie als mijn eigen problemen.
Openness to experience - Have a vivid imagination.
Innovativeness - If I heard that an innovation was available, I would be interested in adopting it within my organization
Reliability of variables
To determine if the questions per variable are reliable the Cronbach’s Alpha has been calculated for all the variables. If the Cronbach’s Alpha is between 0.6 and 0.8 it is considered reasonable, if it is above 0.8 it is considered reliable and if the Cronbach’s Alpha is below 0.6 the variable is not reliable enough (Heus, Leeden & Gazendam, 2006). The reversed questions have been reversed so that all the questions measure the same thing (higher value meaning more). This means that the higher the score the higher the commitment/innovativeness/ openness to experience and trustworthiness of the entrepreneur.
Independent variables
The Cronbach’s Alpha for the four remaining questions of commitment is 0.920, this is reliable and it is not necessary to remove a question from the questions regarding commitment to increase the Cronbach’s Alpha. No question can be removed to increase the Cronbach’s Alpha to.
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The Cronbach’s Alpha for the six questions (five original questions and one question regarding trustworthiness) regarding innovativeness is 0.789, this is reliable because it is above the required 0.60. Removing one of the questions does not lead to a substantial increase of the Cronbach’s Alpha value, so all of the questions regarding innovativeness are used in the further analysis. Innovativeness had three reversed variables (lower meaning more) who were reversed to represent the same outcome (higher meaning more) before the Cronbach’s Alpha was calculated and before the factor analysis was performed.
The Cronbach’s Alpha of the six questions (three trustworthiness questions and three openness to experience questions) regarding trust_openness is 0.922, this very reliable since it is a lot more than the preferred 0.8. Removing one of the questions does not lead to a substantial increase of the Cronbach’s Alpha value and it is also not necessary, all of the questions regarding trust_openness are used in the further analysis. Out of the six questions three were reversed (lower score meaning more) and were switched to measure the same outcome (higher meaning more) before the Cronbach’s Alpha was calculated.
Dependent variables
If the two questions about the growth of the net profit and the growth of sales are combined with the revenue of the company a Cronbach’s Alpha of 0.681 is given. This is not the preferred value of above 0.8, but it is reliable enough to do further analysis. For further analysis the three questions are combined in the new value Finance. This variables captures the financial situation of the company in terms of growth and revenue.
If the questions of the increase in sales and the increase of profit of the past five years are combined it given a Cronbach’s Alpha value of 0.913. This value is higher than the preferred 0.8 value and gives a reliable measurement. It makes sense that these two questions are reliable, because the profit and the sales are often related to each other. For further analysis the two questions about the increase in profit and sales over the past five years will be combined into one reliable variable, to be named ‘Growth’.
Besides the two combined variables the individual questions can also be used to test the hypotheses, although the hypotheses can than only partly be rejected or accepted.
31 Correlation analysis
Furthermore the correlation between the eight variables in the conceptual model needs to be analysed to see if there are variables that are associated with each other or go together. In table 3 the results of the correlation analysis can be found. What can be seen easily in the correlation analysis is that there are some variables that are significantly correlated with each other. This means that when any of the variables has a higher score (or lower when negatively correlated) any of the other variables also has a higher score. Almost all of the relations between the variables in the conceptual model have a positive effect, except revenue on commitment. This could have been expected based on the conceptual model, since all of the four independent (now three) variables were expected to have a positive effect on dependent variables (the success of the entrepreneur). It is interesting to see that there is a significant correlations between two independent variables, innovativeness is significantly correlated with commitment. This correlation is not a problem in further analysis, because the value is not high enough to be a problem. Only 29,7% of a possible effect on the dependent variable is explained by both independent variables, which is not a big enough problem not to continue.
To asses if the variables are significantly correlated the Pearson Correlation is shown in table 3. If the Pearson score is below 0.05 the correlation between the two variables is significant, if this is not the case it means that the correlation is not significant.
Commitment is negatively correlated with Revenue (Pearson < 0.05). This could be explained by the lack in spread in the variables commitment, it has the highest mean of the independent variables of 6 and the lowest standard deviation of the independent variables Table 3 – Correlation analysis of the eight variables in the conceptual model
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(table 1). By having a lack of spread in the variable the analysis might not give a reliable correlation. That the mean of commitment is very high might be explained by the nature of entrepreneurs, they are more likely to be highly committed to their own company since they have a higher stake in the company. The respondents might also give a higher score on commitment because they themselves believe they are highly committed, while they might not be.
Trust_openness is positively correlated with revenue (Pearson < 0.05) with a reasonable correlation value of .766. This might give a significant result in the regression testing.
The correlations between Finance, Growth, Revenue, GrowthSales and GrowthProfit are expected and won’t give problems in the hypotheses testing, since they are comprised out of the same questions and in testing the hypotheses only one of the five dependent variables will be used per regression test.
4.3 - Hypotheses testing
In order to test the hypotheses a multiple linear regression test is needed with Finance as the dependent variable and commitment, innovativeness, trust_openness as the independent variables. In the regression test the first value to look at is the adjusted R2, this value tells how much the dependent variable is explained by the model. The second value to look at is the significance of the F value, the significance has to be lower than 0.05 which means that there is at least a 95% change that the models independent variables say something meaningful about the independent variable. Finally the standardized Beta and its significance are important, they will tell if the individual independent variables have a significant influence on the dependent variable. If everything is significant the zero hypotheses can be rejected and the alternative hypotheses can be accepted. The zero hypotheses means that there is no significant influence of the independent on the dependent variable. The alternative hypotheses means that there is a significant influence of the independent variable on the dependent variable.
Dependent variable ‘Finance’
In table 4 the important values of the multiple linear regression are shown with the dependent variable being Finance. The adjusted R2 tells that the model explains 2,3% of the
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dependent variable, which is low. The significance of the F value is 0.187, which means there is a 18,7% change that the model says nothing meaningful about the dependent variable. This is not enough and the model cannot be used to say anything meaningful about the influence of the independent variables on the dependent variable. Since the variable Finance is made out of three separate variables the next step is to run a regression test with Growth being the dependent variable and after that both of the variables that make up Growth as the dependent variable and revenue.
Dependent variable ‘Growth’
In table 5 the important values of the multiple linear regression are shown with the dependent variable being Growth. The adjusted R2 tells that the model explains 0,000% of the dependent variable, meaning is explains nothing. The significance of the F value is 0.394, which means there is a 39,4% change that the model says nothing meaningful about the dependent variable. This is not enough and the model cannot be used to say anything meaningful about the influence of the independent variables on the dependent variable. Since the variable growth is made out of two separate variables the next step is to run a regression test on both of the variables that make up Growth as the dependent variable.
Dependent variable ‘Sales Growth in the past five years’
The important values of the regression test, with the dependent variable being ‘Sales growth in the past five years’, are presented in table 6. In this regression test the independent
Table 5 – Outcome of the regression analysis with Growth as the dependent variable Table 4 – Outcome of the regression analysis with Finance as the dependent variable
34 Model** R R Square Adjusted R square Std. Error of the Estimate F Change Sig. F Change 1 .233* .054 .018 2.24 1.512 .218*
**Dependent variable: GrowthSales'
*Preditors: (constant), Trust_Openness, Innovativeness, Commitment
Model** R R Square Adjusted R square Std. Error of the Estimate F Change Sig. F Change 1 .142* .020 -.017 2.03 0.544 .653*
*Preditors: (constant), Trust_Openness, Innovativeness, Commitment **Dependent variable: GrowthProfit
variables explain 1,8% of the dependent variable, which is very low. The significance of the F value is higher than 0.05, which means that there is a 21.8% change that the model says nothing meaningful. This means that this regression model, as well as the previous two regression test, cannot be used for hypotheses testing.
Dependent variable ‘Profit Growth in the past five years’
The important values of the regression test, with the dependent variable being ‘Net profit growth in the past five years’, are presented in table 7. In this regression test the independent variables explain - 1,7% of the dependent variable, which is very strange but indicates that this regression test cannot be used. The significance of the F value is higher than 0.05, which means that there is a 65,3% change that the model says nothing meaningful. This means that this regression model, as well as the previous three regression tests, cannot be used for hypotheses testing.
There is one other two dependent variables which measures the success of a company in the dataset; ‘Revenue of the company’. To test if the independent variables have a meaningful effect on the variable revenue there is one more regression tests required to test the model.
Table 7 – Outcome of the regression analysis with ‘Net profit growth in the past five years’ as the dependent variable
Table 6 – Outcome of the regression analysis with ‘Sales growth in the past five years’ as the dependent variable
35 Model** R R Square Adjusted R square Std. Error of the Estimate F Change Sig. F Change 1 .490* .240 .211 1.70 8.308 .000*
*Preditors: (constant), Trust_Openness, Innovativeness, Commitment **Dependent variable: Revenue'
Standardized
Coefficients VIF
B Std. Error Beta t Significance
2.013 1.343 1.499 .138
-318 .195 -.171 -1.630 .107 1.137
.025 .189 .014 .134 .894 1.125
.510 .118 .435 4.326 .000 1.049
Trust_Openness
*Preditors: (constant), Innovativeness, Commitment, Trust_Openness **Dependent variable: Revenues
Model Unstandardizes Coefficients (Constant) Commitment Innovativeness
Dependent variable revenue
The important values of the regression test, with the dependent variable being revenue, are presented in table 8. In this regression test the independent variables explain 21,1% of the dependent variable, which is a good percentage and enough to examine further. The significance of the F value is lower than 0.01, which means that the change that the model says nothing meaningful is very low. This means that this regression model can be used for hypotheses testing, since it is significant.
Now the coefficients are important to see if there are one or more independent variables who significantly have an influence on the dependent variable, these outcomes are shown in table 9. The variable trust_openness is the only independent variable that has a significance under the 0.01, which means there is at least a 99% certainty that this independent variable has an influence on the dependent variable. The standardized Beta of openness to experience is positive, so it has positive influence on the dependent variable meaning a higher trust_openness results in a higher revenue. If trust_openness increases with 1 than the revenue increases with 0.435. The VIF values are low meaning there is no multi collinearity . The Darbin-Watson value is 1.969 which is good, because this needs to be between 1.5 and 2.5. The other variables don’t have a high enough significance, so it can’t be said with certainty that these variables say something meaningful about the dependent variable in the current regression model.
Table 9 – Coefficients of the outcome of the regression analysis with revenue as the dependent variable.
