Thesis_Final_Zuure_Floris-Jan

Running head: STARTUP ENERGY AND INNOVATIVENESS 1
The Influence of Startup Energy on a Company's level of Radical Innovativeness
Floris-Jan August Zuure
Utrecht University School of Economics
Author Note
Floris-Jan August Zuure, Utrecht University School of Economics, Utrecht
University.
This paper is written as a bachelor thesis for the course Applied Economic Research
Course (ECB3OKVECO) and due on June 25, 2015.
Supervisor: Dr. Alex Klein
Correspondence concerning this paper should be addressed to Floris-Jan August
Zuure, Utrecht University School of Economics, Tolsteegsingel 5D, 3582 AC Utrecht, The
Netherlands.
E-mail: f.a.zuure@students.uu.nl

STARTUP ENERGY AND INNOVATIVENESS 2
Abstract
A lot of research has been done on startups in general and innovativeness of a company over
time, but there is no existing link between the influence of energy that is released by starting
up a new company and the innovativeness of an existing company. This paper defines the
concept of startup energy and investigates its link with radical innovativeness of a company.
Conducting a survey among 176 people with statements concerned with the relation between
startup energy and innovativeness is analyzed with regard to the age of the company. The
tests show no statistical significant evidence of a negative relationship between startup energy
and radical innovativeness and the age of a company. However, the negative relationship
between motivation and ambition with regard to the age of the company provides interesting
insights for future research.
Keywords: startup energy, innovativeness over time, motivation, ambition
The Influence of Startup Energy on a Company's level of Radical Innovativeness
Many startup firms come to existence every year with great product innovation and
new process innovation. Whereas companies that exist for a longer period of time constantly
experience the challenge to radically innovate, as they tend to devote most of their time to
small, incremental innovation and imitation (Klepper, 1996; Kuratko, Morris & Covin, 2011).
Numerous studies have been conducted on various aspects of both startups and
innovativeness over time. However, previous literature has not yet touched upon the link
between startups and the level of innovativeness of existing companies. Linking startups, and
especially the level of innovativeness in startup companies, to existing companies will help
these existing companies being more radically innovative.
This paper studies in what way a company can use the concept of startup energy to
increase the company's radical innovativeness. To this end, a new concept called startup

energy is introduced. Literature put forward several critical factors that help in defining the
concept of startup energy, referred to as determinants of startup energy. These determinants
are elaborated on and hypotheses are formulated. Followed by a literature review concerning
the company's radical innovativeness over time and a possible already existing link between
startup energy and radical innovativeness over time, the relationships between determinants of
startup energy and the age of the company and innovativeness over time are analyzed
empirically, based on a survey conducted among 176 employed people mainly located in the
Netherlands.
In the next sections an extensive literature review will be presented regarding the
concept of startup energy, which will be defined, and the company's innovativeness. Next,
hypotheses will be tested and the results will be presented. The discussion and concluding
remarks will be presented in the final section. The conceptual model shown below (see Figure
1) summarizes the construction of this research.
Figure 1. Conceptual model.
The concept and definition of startup energy
This paragraph will discuss and define the concept of startup energy. A large number
of researches have been done on startups in general (Bhide, 1992; Oviatt, McDougall &
Loper, 1995), but also on growth determinants of startups and critical success factors of
startups (Lasch, Le Roy & Yami, 2007), the financing of business startups (Cassar, 2002) and
sustainability of startups (Schick, Marxen & Freimann, 2002). But so far research has not
really elaborated on the concept of startup energy yet.

Startup
Energy

Radical
Innovativeness

Discussing the determinants of what it is that makes successful startups successful will
fill this gap in the literature. Combining several insights from previous literature on growth
and success factors of startups (Lasch et al., 2007) but also on the sustainability of these new
businesses (Schick et al., 2002) will contribute to the definition of the general concept called
startup energy.
A factor with great influence on success, innovativeness and sustainability of a new
business adventure is entrepreneurial orientation (Lasch et al., 2007). Entrepreneurial
orientation has been widely studied in previous literature and can be dealt with on both the
individual and organizational level. Lumpkin and Dess (1996) state several key criteria of
entrepreneurial orientation that are: 'a propensity to act autonomously, a willingness to
innovate and to take risks, and a tendency to be aggressive toward competitors and proactive
relative to marketplace opportunities' (Lasch et al., 2007, p. 64). Based on Miller's (1983)
view on the entrepreneurial firm: 'one that engages in product market innovation, undertakes
somewhat risky ventures, and is first to come up with "proactive" innovations, beating
competitors to the punch' (p. 771) several researches have agreed on the entrepreneurial
orientation being a combination of the three dimensions: innovativeness, proactiveness and
risk taking (Wiklund & Shepherd, 2005). Entrepreneurial orientation is one of the variables
used to explain the impact of human capital of the entrepreneur. Kuratko et al. (2011) argue
that several components that contribute to a higher entrepreneurial orientation—thus
entrepreneurial orientation as a whole—will fluctuate over time. Hence, the first hypothesis
(H1) to test is:
H1: The relation between the entrepreneurial orientation of the company and its age is
negative.

Other important determinants of the concept of startup energy are motivation,
ambition and intentional behavior of the entrepreneur. Lasch et al. (2007), who study both
individual and organizational factors that explain the sustainability (survival and growth) of
new ICT firms, assume that 'starting up an innovation and knowledge-based firm demands not
only a high level of qualification and particular technical skills, but also a strong motivation
and a positive intentional behavior' (p. 64). There are mutual relationships between
motivation and growth, or success of a company. An important finding by Delmar and
Wiklund (2003) is the positive effect of motivation to grow on actual growth of a business.
Since motivation clearly is one of the key criteria for starting up a new business, it can
be considered as an important determinant of startup energy. Furthermore, intentional
behavior and a clear mission (or purpose) will contribute to the motivation of the
entrepreneur. Once an entrepreneur or a new startup business has 'developed a picture of their
future business venture, they are determined to pursue it' (Schick et al., 2002). In contrast to
already existing firms, where it is more likely for the employees to get lost in the process of
maintaining current business practices. The next hypothesis (H2) presented is the following:
H2: The relation between ambition and motivation to achieve the company's
goals and the age of the company is negative.
Furthermore literature states that enthusiasm and dedication are key success criteria
for starting up a new business or as Lasch et al. (2007) mention: 'success belongs to those
who believe it in the strongest and the longest.' Blank (2013), who addresses the lean startup
method, describes the 'get out of the building' approach of startups. They go out and ask all
potential stakeholders for feedback on their business model, they rapidly assemble their
minimum viable products and use customers' input to revise the product in order to redesign

and make further adjustments. Startups seem to be more eager to deliver in comparison to
already existing companies. Therefore the third hypothesis (H3) presented will be:
H3: The relation between enthusiasm present within a company and the age of the
company is negative.
Taking the key determinants of startup energy—an entrepreneurial orientation,
motivation, ambition, intentional behavior, and enthusiasm—into account, startup energy can
be defined as the vivacity and increased willpower to achieve company's goals. With the
earlier formulated hypotheses in mind, it seems clear that the relationship between the general
concept of startup energy and the age of the company will also be negative. Hence, the final
hypothesis (H4) formulated concerning startup energy is the following:
H4: The relation between startup energy (and its determinants) and the age of the
Another critical notion in this study is innovativeness. Therefore the next section will
investigate several definitions and components in current literature of the company's radical
innovativeness in relation to the age of the company.
The company's level of radical innovativeness over time
This section is a literature review concerning one of the company's most fundamental
components to enter new markets, to increase market share, to create and sustain competitive
advantage and to be a successful organization in general: the company's innovativeness
(Gunday, Ulusoy, Kilic & Alpkan, 2008). Innovativeness has been studied widely in previous

literature. For this research it is relevant to discuss several definitions and aspects of
innovativeness in existing literature with a focus on radical innovativeness of an existing
company over time.
Innovativeness is regarded with the extent to which a company is doing things that are
new, unique, or different. Kuratko et al. (2011) define it as the 'relative emphasis on concepts
or activities that represent a departure from what is currently available' (p. 58). Nowhere near
all of the innovations are breakthrough innovations such as the automobile or the phone both
invented in the19th century, or more recent breakthrough innovations such as the World Wide
Web in the 20th century and even more recent electrical cars.
The concept of innovativeness applies to a wide range of options. These options vary
from simple, minor improvements such as new hiring methods, customer support programs or
employee training programs for existing products or services, to products or services that are
entirely new to our world. Furthermore it can also be 'a new production process technology, a
new structure or administrative system or a new plan or program pertaining to organizational
members' (Damanpour, 1991, p. 556).
Kuratko et al. (2011) state that innovativeness is one of the three dimensions (together
with the amount of risk-taking and proactiveness) of entrepreneurship, or entrepreneurial
orientation, discussed in the previous section. They claim that entrepreneurship is a variable
and that there is some level of entrepreneurship within every organization, even in the oldest
most bureaucratic and centralized firms in the world. Keeping the latter in mind, this
statement is also applicable to entrepreneurship's dimension of innovativeness. Hence, in this
study there will be assumed that every organization has some degree innovativeness.
This degree of innovativeness however, depends on several factors. Damanpour
(1991) studied the relationship between organizational determinants and the degree of
innovativeness. He used several independent variables such as specialization, functional

differentiation, professionalism, formalization and centralization with an expected positive or
negative influence on the level of innovativeness. Since it is not clear whether high levels of
innovation are sustainable in the long run, the age of the company is another important factor
in the degree of innovativeness.
Subramanian and Nilakanta (1996, p. 633) stated: 'Truly innovative organizations are
those that exhibit innovative behavior consistently over time', a situation that, in practice,
shows is hard to accomplish, especially in terms of new startup firms. The amount of startups
that come to existence every year is impressive. A large part of these startups however, tend
to disappear without existing more than a couple of years (Audretsch & Thurik, 2000). Many
of these new companies offer products or services that are not radically unique but rather
standard, they are innovative in other ways. They gain major competitive advantages by new
process innovations for instance (Kuratko et al., 2011). Nevertheless, with many of them
disappearing within a couple of years of existence it seems hard to sustain these competitive
advantages.
Literature indicates several reasons underlying the lack of implementing new ideas in
existing businesses. One could be that existing firms will not pursue a lot of new ideas simply
because they have different agendas or they simply do not recognize any potential value in
new ideas (Audretsch & Thurik, 2000). 'Winning in and of itself is difficult enough. To keep
on winning is much harder', Luca Cordero di Montezemolo once said, the former president of
Ferrari as quoted in Moenaert & Robben (2014). Clearly, vindicating leadership by
competitive advantage gained by radical innovativeness is amazingly difficult. Often
companies lose their competitive position by a lack of action i.e., a lack of radical
innovativeness (Moenaert & Robben, 2014). This can be clarified by the following
observation: 44 Companies out of the 100 largest industrial companies in the United States in
1980 disappeared altogether from that list in twelve years. Another 25 of these companies

sank on the ladder, 13 maintained and only 18 improved their position (Hodgetts, Luthans &
Lee, 1994).
A great example of a company that manages to sustain a given level of innovativeness
is 3M. The multinational, which was founded in 1902, currently has a catalogue of over
60,000 products that generate nearly $11 billion in sales. With its philosophy of innovation:
'innovation is often a numbers game; the more ideas a company has, the better the chances for
a successful innovation' (Kuratko et al., 2011, p. 178) the company is developing many new
products every year. Nevertheless, for many companies it still seems to be very hard to
sustain a certain level of radical innovativeness and sustainable competitive advantage.
During these times the frequency and degree of innovations decline, leading to smaller and
more incremental innovations. As mentioned before, radical innovation does not necessarily
have to be a new or unique product or service but it can also be concerned with radical
process innovation. However, for a company to survive existing literature assumes that radical
innovation, either by new, unique products or innovative processes, will lead to better
sustainable competitive advantages in comparison to rather small, incremental innovations.
Since we have seen that literature states it is hard to sustain a given level innovation (Kuratko
et al., 2011), the following hypothesis (H5) is presented:
H5: The relation between the level of radical innovations and the age of the
The next section will present some more insights on already existing literature
concerning the link between startup energy, or its determinants and a company's
innovativeness.

An already existing link between startup energy and radical innovativeness
This paragraph discusses an already existing link between startup energy and its
determinants and the degree of radical innovativeness of a company. Since the concept of
startup energy is newly introduced in this research, there is no clear link between this concept
and radical innovativeness in existing literature.
Yet, as stated before, startup energy has several important determinants such as
entrepreneurial orientation, motivation and ambition, and enthusiasm. These constituents of
the concept of startup energy form a causal relationship with growth and success of a
company, as we have seen in the previous sections (Lasch et al., 2007; Delmar & Wiklund,
2008). Furthermore, one of the dimensions of entrepreneurial orientation is the level of
innovation. Thus, there seems to be an already existing link between the determinants of
startup energy and innovativeness. However, there is no direct link between the vivacity and
increased willpower to achieve the company's goals and radical innovation of an already
existing company.
Methodology
In order to explore the relation between startup energy and its determinants and the
level of radical innovation over time empirically, a relevant questionnaire was developed and
an online survey was conducted among a sample of 176 employed people, mainly located in
the Netherlands. With 57% of the people between 20 to 29 years of age, this age group was
the largest out of the sample. Out of all participants 38% had less than five years of working
experience and 45% holds a bachelor level of education. The survey not only contained 11
statements (see Table 1) that are relevant to the relation between startup energy and
innovativeness, but also five demographical questions and 26 questions relevant to other
research related to internal marketing.

The survey, which related to a total of eight bachelor theses, was presented online and
shared through social media among employed friends, relatives and coworkers. Participants
were asked whether they agreed upon a certain statement and were able to answer a statement
on a one to five scale. Where one corresponded with 'very much disagree', two corresponded
with 'disagree', three with 'neutral', four with 'agree' and five with 'very much agree'. In case
the particular statement was not relevant to the participant there was also a sixth option,
namely 'not applicable'. After filling out the 37 statements, the participant was asked to
answer another five questions regarding gender, age, working experience, the age of the
company the participant works for and his or her level of education.
The survey was distributed on May 20, 2015 using online survey software and insights
platform Qualtrics. Data was collected a week later on May 27 and 116 respondents were
found. Hence, a follow up was decided upon in order to get more respondents. On June first,
the survey was closed and the data was collected to allow for enough time to process the
results in Stata (data analysis and statistical software). At that time, there were a total of 176
respondents. The combination of the results from the relevant statements presented to the
participants and the age of the company they work for determined whether there is a positive
or negative (multiple) linear relationship, which in turn can support or reject the hypotheses
mentioned earlier. Stata was used to conduct a simple, (multiple) linear regression analysis
that provides a relevant coefficient of the independent variable and a p-value.
Throughout this research a significance level of five percent (α = .05) will be used. All
p-values larger than the significance level of .05 used in this research indicate that at least five
percent of the result being due to chance, and therefore provide weak or no statistical
evidence.

Nr. Statement Variable
1 "At my work, I feel bursting with energy." Q1
2 "I am enthusiastic about my job." Q2
3 "I expect the company that I work for to develop radically new products in the coming five
years."
Q3
4 "I am motivated through management on a day-to-day basis." Q4
5 "I am proud of the work I do." Q5
6 "The ambition of the company that I work for is clear to me." Q6
7 "I feel motivated to achieve my company's goals." Q7
8 "The company that I work for has developed radically new products in the last five years." Q8
9 "When I get up in the morning, I feel like going to work." Q9
10 "I am motivated through my peers on a day-to-day basis." Q10
11 "Time flies when I am working." Q11
12 "What is the age of the company you work for?" age
Table 1. Relevant statements asked in the survey, with the variables used in Stata.
Results
The results show no statistical significant support for the hypotheses. The first
hypothesis stated (H1) is concerned with the entrepreneurial orientation present in a firm in
relation to the age of the company. The survey that was conducted was not able to encompass
any questions concerning the first hypothesis due to several reasons that will be further
elaborated on in the discussion section. Therefore, there is no reason to either support or reject
the first (H1) hypothesis.
The second hypothesis (H2) deals with the relation between motivation and ambition
to achieve the company's goals and the age of the company. In order to test this hypothesis
several individual variables were regressed concerning motivation (Q4, Q7, Q10) and
ambition (Q6) with the age of the company and varying results were found. The relation
between motivation through management on a day-to-day basis (Q4) and the age of the
company is not statistically significant for this research as p = .09 (larger than α = .05).
Nevertheless, with p < .10 and a coefficient of -.08985 there seems to be a quite strong non-
significant negative trend in the relationship. The same holds for the relation between
motivation to achieve company's goals (Q4) and the age of the company. Here, a strong
negative trend with a coefficient of -.08802 but p = .0529 was found, slightly above the
significance level of .05. Therefore, this negative relationship is not statistical significant

(with α = .05) in this research either. The third variable concerning motivation is Q10 and
deals with the motivation through the employee’s peers on a day-to-day basis. Here, no
negative relationship between the variable and the age of the company was found at all. The
final variable relevant to the second hypothesis is the following: 'The ambition of the
company that I work for is clear to me' (Q6). In relation to the age of the company this
variable showed another negative—though non-significant—trend. The negative relation with
a coefficient of -.08224 was not statistical significant since p = .051 is larger than the
significance level used in this research.
Besides looking at each variable individually, all four of the variables were also
combined into one new variable called mtvtn, which was regressed on the age of the
company. The result shows a negative relationship with a coefficient of -.04162 but a large p-
value (p = .25) and therefore is not statistically significant.
In the third hypothesis (H3) stated, only one dependent variable matters (Q2). It is the
statement concerned with the enthusiasm of the employee. A regression analysis found a
positive relationship between enthusiasm of the employee and the age of the company with a
coefficient of .06713. This relation is not statistically significant as p = .15. However, there
seems to be a positive trend in this relationship.
For the fourth hypothesis (H4), which is a collection of motivation and ambition,
enthusiasm and several other factors, several variables were used regarding the employee's
energy at work (Q1, Q5, Q9, Q11) in relation the age of the company they work for. For three
out of the four statements: 'At work I feel bursting with energy' (Q1), 'When I get up in the
morning, I feel like going to work' (Q9) and 'Time flies when I am working' (Q11), small
positive relations were found with the age of the company with extremely high p-values (p =
.82, p = .53 and p = .39 respectively) and therefore are far from statistically significant. For
the remaining statement 'I am proud of the work I do' (Q5) a non-significant negative relation

with a coefficient of -.01723 and p = .69 was found. Furthermore the relationship between all
the startup energy constituents (merged in a new variable called enrgy) and the age of the
company was investigated. The outcome was a positive trend with a coefficient of .19514 and
a large p-value, p = 0.58. Then, both variables mtvtn and enrgy were merged. Regression
analysis on the age of the company here yielded a very weak negative relation with a
coefficient of -.00526 and p = .88.
In order to test the final hypothesis (H5) two variables on the age of the company were
regressed individually. The first variable (Q3) concerned with the expected level of radical
innovation of the company in the coming five years and the other variable (Q8) that deals
with the level of radical innovation in the past five years. Both outcomes were a negative
relation with the age of the company, but far from statistically significant. Whereas Q8
regressed on the age of the company has a coefficient of -.06778 and p = .27, Q3 even shows
a weaker trend with a coefficient of -.00655 and an extremely high p-value, p = .99. Please
refer to Table 2 for an overview of the results.
Nr. Hypothesis Linear Function P-value
1 H0: The relation between the entrepreneurial orientation of the
company and its age is not negative.
Ha: The relation between the entrepreneurial orientation of the
company and its age is negative.
N.A. N.A.
2 H0: The relation between ambition and motivation to achieve the
company's goals and the age of the company is not negative.
Ha: The relation between ambition and motivation to achieve the
company's goals and the age of the company is negative.
Q4=-0.08985age + ɛ
Q6=-0.08224age + ɛ
Q7=-0.08802age + ɛ
Q10=0.0000age + ɛ
mtvtn=-0.041622age + ɛ
0.0905
0.0506
0.0529
1.0000
0.2494
3 H0: The relation between enthusiasm present within a company and
the age of the company is not negative.
Ha: The relation between enthusiasm present within a company and
the age of the company is negative.
Q2=0.06713age + ɛ 0.1453
4 H0: The relation between startup energy (and its determinants) and the
age of the company is not negative.
Ha: The relation between startup energy (and its determinants) and the
age of the company is negative.
Q1=0.00969age + ɛ
Q5=-0.01723age + ɛ
Q9=0.02962age + ɛ
Q11=0.04138age + ɛ
enrgy=0.19514age + ɛ
(mtvtn + enrgy)=-0.00526age + ɛ
0.8236
0.6948
0.5338
0.3866
0.5807
5 H0: The relation between the level of radical innovations and the age
of the company is not negative.
Ha: The relation between the level of radical innovations and the age
of the company is negative.
Q3=-0.0065536age + ɛ
Q8=-0.06778age + ɛ
0.9922
0.2733
Table 2. Results of OLS Analysis in Stata, all output is Stata output.

Discussion
This study addresses the contribution of startup energy on the innovativeness of a
company over time to fill a gap in the existing literature. None of the results in this research
are statistical significant and therefore cannot significantly fill the gap in literature regarding
startup energy and its influence on radical innovativeness.
The research had several limitations. It was primarily constrained by time due to the
academic calendar and as a result of that the sample size of the conducted survey was too
small. Since eight bachelor students distributed the survey mainly through social media and in
person, the participants were not evenly distributed. Ideally, participants would have been
more evenly distributed across age. The level of employed people in the main age group that
participated in the survey was lower. As all the questions asked applied to employed people,
results could be biased. Furthermore, since most participants in the main age group were
students and not full time employed or employed for a short amount of time only, it is likely
they did not have sufficient insights in the company that enabled them to properly fill out the
questionnaire. The narrow range of participants in terms of age and the small sample size
constrained the results.
The results could have benefited from a larger variety in age groups—especially full
time employed people, who are older in general—and more time to conduct the survey. Aside
from returning a higher sample size, more time would also have created the opportunity to
create a more extensive, detailed questionnaire and the possibility to distribute it to the right
participants to decrease possible bias. A more detailed questionnaire would also have made it
possible to test the first hypothesis (H1) stated in this research, which in turn could have
contributed to more significant results. Since entrepreneurial orientation seems to be an
important determinant from startup energy and innovativeness of a company (Lumpkin &
Dess, 1996; Lasch et al., 2007; Miller, 1983; Wiklund & Shepherd, 2005), its relation with

innovativeness of a company over time could be investigated in future research. In order to do
so, a more detailed and more explanatory survey is needed to obtain sufficient results.
Despite its limitations and lack of statistical significant evidence this study found a
few quite strong negative relationships of individual constituents of the introduced concept of
startup energy in relation to the age of a company. Although non-significant, the results
suggest that both motivation through management on a day-to-day basis and the motivation to
achieve company's goals decline as the company becomes older. Furthermore the ambition of
the company seems to become more vaguely as the company grows older. This relation could
be of great importance in building sustainable and innovative business. Nevertheless, future
research will have to show whether there is statistical significant evidence for these negative
relationships.
Other interesting research that could be done in this field is startup energy and
innovativeness in a comparative study. Where a similar, but more extensive questionnaire
could be conducted among employees of two different companies of which one has developed
radical innovations in the past years and is known for being progressive, and the other is
presumed to be more reliable on incremental innovations and imitation.
Conclusion & Recommendations
In this study, the main purpose was to deal with the way of the introduced concept
startup energy on the innovativeness of a company over time. In order to investigate in what
way a company can use startup energy to increase the company's innovativeness, several
hypotheses were proposed and tested by conducting a survey. The results from this survey do
not show any significant evidence and fail to reject any of the null hypotheses. Thus, this
study neither shows a negative relation between startup energy (and its determinants) and the
age of a company nor a negative relation between radical innovativeness and the age of the

company. Despite literature that suggests that determinants of the concept of startup energy
and the age of the company are negatively correlated (Kuratko et al., 2011; Schick et al.,
2002), in this research there is no statistical evidence that the concept of startup energy can
actually improve the radical innovativeness of an already existing company.
The negative relation between motivation and ambition and the age of the company
suggests that managers in existing companies should motivate their employees more and
make the ambition of the company clear in order to increase growth and success of the
company. But in order to significantly prove this, further research should be done in this field.
This important topic however, should be addressed in future research since it will contribute
to the sustainability of business and innovation in general.
Despite the lack of statistical significance, this research opens new doors for future
research in the field of startup energy. It addresses the problem of decreasing radical
innovativeness over time of a company, which is suggested in previous literature, and might
be able to solve this problem for existing companies by letting them use the energy that is
associated with smaller, newer companies.

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_cons 4.560899 .1456229 31.32 0.000 4.273461 4.848337
q12agec -.041622 .0360133 -1.16 0.249 -.112707 .029463
mtvtn Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 112.028736 173 .647564946 Root MSE = .80393
Adj R-squared = 0.0019
Residual 111.165438 172 .646310688 R-squared = 0.0077
Model .863297212 1 .863297212 Prob > F = 0.2494
F( 1, 172) = 1.34
Source SS df MS Number of obs = 174
. reg mtvtn q12agec
. gen mtvtn = max( q4motivation, q6ambition, q7mtvtgoals, q10mtvtpeers)
_cons 3.759755 .1852467 20.30 0.000 3.39409 4.12542
q12agec .0671331 .0458827 1.46 0.145 -.0234363 .1577025
q2enthusiasm Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 180.99422 172 1.05229197 Root MSE = 1.0224
Residual 178.756321 171 1.0453586 R-squared = 0.0124
Model 2.23789864 1 2.23789864 Prob > F = 0.1453
F( 1, 171) = 2.14
. reg q2enthusiasm q12agec
Appendix A
Here, a collection of Stata regression output with regard to the hypotheses is presented.
Stata Output 1. Concerning hypothesis H2.
_cons 3.47429 .2134488 16.28 0.000 3.052956 3.895624
q12agec -.0898459 .0527838 -1.70 0.091 -.1940376 .0143457
q4motivation Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 241.387283 172 1.40341444 Root MSE = 1.1782
Model 4.02177368 1 4.02177368 Prob > F = 0.0905
F( 1, 171) = 2.90
. reg q4motivation q12agec
_cons 4.28478 .168919 25.37 0.000 3.951359 4.618201
q12agec -.0822406 .0417746 -1.97 0.051 -.1646974 .0002162
q6ambition Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 152.948276 173 .88409408 Root MSE = .93254
Model 3.37044657 1 3.37044657 Prob > F = 0.0506
F( 1, 172) = 3.88
. reg q6ambition q12agec
_cons 4.185309 .1826213 22.92 0.000 3.824842 4.545777
q12agec -.0880185 .0451632 -1.95 0.053 -.1771641 .001127
q7mtvtgoals Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 178.689655 173 1.03288818 Root MSE = 1.0082
Model 3.86067548 1 3.86067548 Prob > F = 0.0529
F( 1, 172) = 3.80
. reg q7mtvtgoals q12agec
_cons 3.666667 .1626413 22.54 0.000 3.345637 3.987697
q12agec -5.85e-18 .0402221 -0.00 1.000 -.0793924 .0793924
q10mtvtpeers Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 138.666667 173 .801541426 Root MSE = .89789
Adj R-squared = -0.0058
Model 8.5265e-14 1 8.5265e-14 Prob > F = 1.0000
F( 1, 172) = 0.00
. reg q10mtvtpeers q12agec

_cons 3.47017 .1754933 19.77 0.000 3.123773 3.816568
q12agec .0096876 .0434004 0.22 0.824 -.0759784 .0953536
q1energy Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 161.494253 173 .933492791 Root MSE = .96884
Model .046767607 1 .046767607 Prob > F = 0.8236
F( 1, 172) = 0.05
. reg q1energy q12agec
_cons 3.56068 .1927595 18.47 0.000 3.180201 3.941159
q12agec .0413798 .0476705 0.87 0.387 -.0527146 .1354742
q11timeflies Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 195.632184 173 1.13082187 Root MSE = 1.0642
Model .853279757 1 .853279757 Prob > F = 0.3866
F( 1, 172) = 0.75
. reg q11timeflies q12agec
_cons 4.2042 .1425805 29.49 0.000 3.922768 4.485633
q12agec .0195135 .0352609 0.55 0.581 -.0500863 .0891134
enrgy Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 106.758621 173 .617101854 Root MSE = .78714
Model .189752406 1 .189752406 Prob > F = 0.5807
F( 1, 172) = 0.31
. reg enrgy q12agec
. gen enrgy = max( q1energy, q5proud, q9goingtowork, q11timeflies)
_cons 4.640003 .1359949 34.12 0.000 4.371569 4.908437
q12agec -.005259 .0336323 -0.16 0.876 -.0716441 .0611261
mtvtnenrgy Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 96.9655172 173 .560494319 Root MSE = .75078
Model .013782127 1 .013782127 Prob > F = 0.8759
F( 1, 172) = 0.02
. reg mtvtnenrgy q12agec
. gen mtvtnenrgy = max(enrgy, mtvtn)
_cons 3.611228 .2300476 15.70 0.000 3.157148 4.065308
q12agec -.0005536 .056892 -0.01 0.992 -.11285 .1117428
q3radicalf~e Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 277.425287 173 1.60361438 Root MSE = 1.27
Model .000152711 1 .000152711 Prob > F = 0.9922
F( 1, 172) = 0.00
. reg q3radicalfuture q12agec
_cons 4.024773 .2493637 16.14 0.000 3.532565 4.51698
q12agec -.0677784 .061669 -1.10 0.273 -.1895039 .053947
q8radicalp~t Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 328.258621 173 1.89744867 Root MSE = 1.3767
Model 2.28927495 1 2.28927495 Prob > F = 0.2733
F( 1, 172) = 1.21
. reg q8radicalpast q12agec
Stata Output 3. Concerning hypothesis H4
_cons 3.982816 .177266 22.47 0.000 3.632919 4.332713
q12agec -.01723 .0438388 -0.39 0.695 -.1037614 .0693013
q5proud Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 164.873563 173 .953026377 Root MSE = .97863
Model .147940734 1 .147940734 Prob > F = 0.6948
F( 1, 172) = 0.15
. reg q5proud q12agec
_cons 3.132616 .1920884 16.31 0.000 2.753462 3.51177
q12agec .0296163 .0475045 0.62 0.534 -.0641505 .1233831
q9goingtow~k Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 193.862069 173 1.12058999 Root MSE = 1.0605
Model .437095779 1 .437095779 Prob > F = 0.5338
F( 1, 172) = 0.39
. reg q9goingtowork q12agec

Total 174 100.00
2 88 50.57 100.00
1 86 49.43 49.43
participant Freq. Percent Cum.
sex of
. tab q38sex
Total 174 100.00
5 6 3.45 100.00
4 22 12.64 96.55
3 22 12.64 83.91
2 24 13.79 71.26
1 100 57.47 57.47
Q39 (Age) Freq. Percent Cum.
. tab q39age
Total 173 100.00
5 19 10.98 100.00
4 17 9.83 89.02
3 31 17.92 79.19
2 40 23.12 61.27
1 66 38.15 38.15
Q40 (Exper) Freq. Percent Cum.
. tab q40exper
Total 173 100.00
4 9 5.20 100.00
3 50 28.90 94.80
2 78 45.09 65.90
1 36 20.81 20.81
education Freq. Percent Cum.
level of
. tab q42educ
Appendix B
This appendix shows the demographics of the participants in Stata output.

Stata Output 5. Demographics of the participants.

Thesis_Final_Zuure_Floris-Jan

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