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Volume 2, Number 1
January - June 2018
pp. 29-42
https://doi.org/10.26784/sbir.v2i1.47
E-ISSN: 2531-0046
Received: 2017-11-16
Accepted: 2017-12-11
Small Business
International Review
Human and social capital as drivers of entrepreneurship
Capital humano y social como motores del emprendimiento
Carolina Madriz
Postgraduate student. Business School. Instituto Tecnológico de Costa Rica. Cartago, Costa Rica. E-mail:
krito.m.20@gmail.com
Juan Carlos Leiva
PhD Business Management at University of Valencia, Spain. Professor at Business School, Instituto Tec-
nológico de Costa Rica. Cartago, Costa Rica
E-mail: jleiva@itcr.ac.cr
http://orcid.org/0000-0001-9653-4629
Ralph Henn
Research Associate and PhD Candidate at Institute for Entrepreneurship, Technology-Management
and Innovation (EnTechnon) at the Karlsruher Institute of Technology, Germany
E-mail: ralph.henn@kit.edu
Abstract
The objective of this study is to determine whether human and social capital are drivers of entrepreneur-
ship. The methodology involves the estimation of descriptive and inferential statistical techniques such as
logistic regressions and correlations of variables. It is focused on information from the Global Entrepreneu-
rship Monitor database for 2012 from Germany and Costa Rica. The results demonstrate that human and
social capital, factors related to knowledge, have a positive statistical relationship with the propensity to
become an entrepreneur. Little difference exists among knowledge-related factors across countries. They
are mainly related to the cultural contexts, which affect the propensity to become an entrepreneur.
Keywords: knowledge; self-efficacy; entrepreneurship; human capital; social capital
Resumen
El objetivo de este estudio determinar si el capital humano y social son impulsores del emprendimiento. La
metodología involucra la estimación de técnicas estadísticas descriptivas e inferenciales como regresiones
logísticas y correlaciones de variables. El trabajo utilizó información de la base de datos del Global Entrepre-
neurship Monitor (GEM) para 2012 en Alemania y Costa Rica. Los resultados muestran que los factores de
capital humano y social, los cuales son relacionados con el conocimiento, tienen un impacto estadístico p osi-
tivo en la propensión de convertirse en emprendedor. Se hallaron pequeñas diferencias entre ambos países
bajo estudio. Estas se relacionan principalmente con los contextos culturales que afectan la propensión de
convertirse en emprendedor.
Palabras clave: conocimiento, auto eficacia, emprendimiento, capital humano, capital social.
Carolina Madriz ::: Juan Carlos Leiva ::: Ralph Henn
30
1. Introduction
With the prior literature, it is easier to identify
as a relevant issue whether human and social
capital (being in contact with people with
entrepreneurial knowledge) are drivers of
entrepreneurship. To identify the role of
knowledge in business start-up activities and in
giving support to different sectors, such as the
government and public sector, business sector
and academic sector, the previous research has
focused on factors that influence the formation
of building independent businesses (Davidsson
& Honig, 2003; Arenius & Minniti, 2005; Shane,
2012; Hsiao, Lee, & Chen, 2016).
Previous studies have established determinants
that influence the propensity of people to
become entrepreneurs, such as alertness to
opportunities, demographic characteristics,
the fear of failure, confidence in personal
skills (Arenius & Minniti, 2005), opportunities
in the entrepreneurial process (Eckhardt &
Shane, 2003), education level (Arenius & De
Clercq, 2005), or unemployment and the state
of the economy (Sternberg & Wennekers, 2005;
Ritsilä & Tervo, 2002; Arenius & Minniti, 2005).
Prior research reveals that factors related to
knowledge affect whether and how people
engage in entrepreneurship activities (Van
Praag & Cramer, 2001; Autio & Wennberg,
2010; Liedholm, 2002; Brüderl & Preisendörfer,
1998; Macpherson & Holt 2007). However, the
shortage of studies that could show the causes
of knowledge spillovers in the entrepreneurial
process (De Clercq & Arenius, 2006; Dencker,
Gruber & Shah, 2009; Ghio, Guerini, Lehmann,
& Rossi-Lamastra, 2015) display the need to
determine how factors based on knowledge
affect a person’s propensity to become an
entrepreneur.
This paper looks for advancing the literature
on the determinants that are based on the
knowledge to engage in a business start-up
activity.
Thus, transmitted knowledge (social capital)
and acquired knowledge (human capital) are
variables of strong impact for people who
make the decision to become entrepreneurs
(Davidsson & Honig, 2003). Similarly,
entrepreneurs discover opportunities related
to knowledge from the information they
already possess (Shane, 2000; Bayon, Lafuente,
& Vaillant, 2016).
Autio and Wennberg (2010) suggested in a study
that patterns of social groups could have three
times more influence on the probability to become
an entrepreneur, compared to the personal
attitudes that everyone has (human capital).
However, De Clercq and Arenius (2006)
determined that there are two factors based on
knowledge, and those have a great impact on
the decision of people to become involved in
starting a new business, which are human and
social capital (being in c ontact with people with
entrepreneurial knowledge).
The Global Entrepreneurship Monitor
establishes that some people decide to become
entrepreneurs out of necessity while others are
motivated by opportunities, mostly depending
on the country in which they live (Xavier et al.,
2012; Singer, Amorós, and Moska, 2015).
According to this finding, being aware of the
existence of factors that influence and encourage
people to conduct their own business, the
objective of this study is to determine whether
factors related to knowledge specifically human
and social capital (being in contact with people
with entrepreneurial knowledge) are drivers of
entrepreneurship. That´s why this research aims
to use estimation of descriptive and inferential
statistical techniques with information from the
Global Entrepreneurship Monitor database for
2012 from Germany and Costa Rica.
Comparing countries like Costa Rica and
Germany is useful because both have a national
strategy for competing in the knowledge base
sector (i.e. information and communication
technologies, biotechnology, medical device
cluster, among others.) (Schwab, 2016). The
analysis is worked with a representative
sample of the adult population from Germany
(N = 4300) and Costa Rica (N = 2041).
This article is composed of the following
sections: introduction, theory and hypotheses,
SBIR / Small Business International Review / Vol. 1 Nº 2 / July - December 2017 / AECA-FAEDPYME 31
methodology, results, discussion and
conclusions, finally the section of limitations,
future research and implications.
2. Theory and Hypotheses
As stated previously, the notion of self-efficacy
is characterized as the pillar in the development
of this study, which permits a relationship
among self-knowledge (human capital),
acquired (capital) knowledge and the decision
of individuals to engage in a new business. Self-
efficacy can be defined as self-confidence in
one’s own ability and skills to face a diversity of
circumstances and to perform a specific action
(Bandura, 1994, 2006). Investigations with a
focus on small businesses are increasing, and
they establish the importance of knowledge for
entrepreneurship and innovation (Zeng, Xie &
Tam, 2010; Gast, Werner, & Kraus, 2017). Self-
efficacy, knowledge, skills and abilities affect the
workload, the interest and level of difficulty of
the targets that are established for performance;
they also influence p ersistence (Kay & Moncarz,
2004). Studies have identified two important
characteristics that are positively related to
influencing one’s starting one’s own business
and to the business performance, which are
self-confidence in one’s knowledge and skills
and relationships with other people who
will transmit knowledge (knowledge-based
resources) (De Clercq & Arenius, 2006; Wiklund
& Shepherd, 2003; Lee, Lee & Pennings, 2001;
Arenius & Minniti, 2005; Autio & Wennberg,
2010).
2.1 Human Capital and Entrepreneurship
It has been revealed by previous research
that the knowledge and skills of people are
characterized as delimiting factors of their
behavior (De Clercq & Arenius, 2006), and also
that there is a positive relationship between
the ability to perceive entrepreneurial
opportunities and educational level (Arenius
& Minniti, 2005; Brixy & Hessels, 2010). There
are components of human capital that have a
representative positive effect on the likelihood
of a move into entrepreneurship, such as
education and work experience (Davidsson &
Honig, 2003).
In general, the literature of networks and capital
mentioned before demonstrates that there is a
positive correlation between entrepreneurship
and human capital. However, studies have
analyzed the intensity ratio between these two
factors, but the results have demonstrated that
the relationship is not strong enough (Davidsson
& Honig, 2003). Likewise, recent empirical
studies have shown results from a completely
different approach. They exhibit a nonlinear
relationship or insignificant impact between
education and entrepreneurship (Van der Sluis,
Van Praag & Vijverberg, 2008; Oosterbeek,
Van Praag & Ijsselstein, 2010; Brixy & Hessels,
2010), and the results even reveal that human
capital accumulation is not associated with the
initiative of business aspirations (Karaagac,
2014).
Moreover, the literature of psychology
establishes the importance of trust in
personal skills and the ability to behave
in a business fashion (Arenius & Minniti,
2005). The prediction of the study regarding
entrepreneurship is influenced by factors
such as the locus of control and intentionality
(Baron, 2000).
According to the prior findings, self-efficacy is
utilized on the assumption of a positive effect of
the probability between starting a business and
knowledge of people. Self-efficacy significantly
influences corporate behavior (Zhao, Seibert
& Hills, 2005; Townsend, Busenitz, & Arthurs,
2010); therefore, to achieve an increase in
entrepreneurship initiative, it is essential that
people believe in their personal abilities and
capabilities and thus discover courses of action
(Krueger, Reilly & Carsrud, 2000).
Entrepreneurial self-efficacy is defined as the
belief level of an individual in his personal
ability to perform successfully the duties
and responsibilities required of an employer
(Townsend, Busenitz, & Arthurs, 2010; Chen,
Greene, & Crick, 1998; Krueger & Brazeal, 1994).
From the theory of self-efficacy, it is derived
that people with higher human capital are
better at recognizing profitable opportunities,
and thus, they see entrepreneurship as an
attractive career choice because they believe
they have the required skills for success (Autio
Carolina Madriz ::: Juan Carlos Leiva ::: Ralph Henn
32
& Wennberg, 2010; Davidsson & Honig, 2003).
As a result, human capital plays a significant
role in economic activities. Previous studies
have shown the role of human capital to be an
engine for entrepreneurship (Morales & Roig,
2005; De Clercq & Arenius, 2006; Davidsson &
Honig, 2003, Autio & Wennberg, 2010).
The human capital approach in this study is
the knowledge that is directly related to a new
venture. The writings have paid more attention
to the business literature of knowledge focused
on performance results, growth and success
(Gruber, Kim, & Brinckmann, 2015; Macpherson
& Holt, 2007; Tsai, 2001; Lee, Lee & Pennings,
2001) and not in the monitoring of behavior
decisions, such as starting a business. (De Clercq
& Arenius, 2006). Therefore, the following
hypothesis is established:
Hypothesis 1: The level of human capital is
positively related to the propensity to become
an entrepreneur.
2.2 Social Capital and Entrepreneurship
Knowledge in business activities has a focus
on human capital but also on that transmitted
by other individuals. For this reason, the
importance of a type of knowledge about other
knowledge has been discussed (De Clercq &
Arenius, 2006; Morales & Roig, 2005). Through
the statistics of an empirical study, there were
found significant differences in social networks
between entrepreneurs and non-entrepreneurs
(Klyver & Hindle, 2007; Lamine 2017).
Knowledge focused on entrepreneurship
spirit should increase in areas with greater
knowledge (Audretsch, Bönte, & Keilbach,
2008), by geographic proximity to knowledge
sources generating more entrepreneurial
opportunities through a network approach to
the entrepreneurship spirit (Acs, Audretsch
& Lehmann, 2013). Indeed, empirical studies
support this statement. It was determined
that the aspect of social capital to be employed
to conduct models has a statistically positive
result for engaging in entrepreneurial activities
(Davidsson & Honig, 2003; De Clercq & Arenius,
2006; Klyver, Hindle & Meyer, 2008).
Persons who are in the same environment
with business people make that uncertainty
decrease, and they gain more confidence
to undertake entrepreneurial activities
successfully (Bandura, 1978; Indrawati et
al., 2015), decreasing the ambiguity in the
entrepreneurial process (Johannisson, 1996).
Social capital and networks literature have
shown the importance of external knowledge
to form individual knowledge, and thus, that
could provide input to those who aspire to
be entrepreneurs (Davidsson & Honig, 2003).
According to previous results, this study is
based on the importance of self-efficacy models
and the positive relationship between external
exposure to knowledge and entrepreneurship.
For this study, social capital will be the profit
obtained by accessing the knowledge of others
(De Clercq & Arenius, 2006). Despite claims
that the formation of families with their
own businesses has a positive effect on the
recognition of opportunities and the decision to
undertake entrepreneurial activities (Aldrich
& Cliff, 2003), there are studies with results
suggesting both direct and indirect effects to
this assertion (Carr & Sequeira, 2007).
A recent study demonstrates that the norms
of behavior of social groups can achieve a
greater impact of more than three times on
the likelihood of engaging in entrepreneurship
compared to individual attitudes (Autio &
Wennberg, 2010). Therefore, the following
hypothesis is established:
Hypothesis 2: The level of social capital is
positively related to the propensity of a person
to become an entrepreneur.
3. Methodology
3.1 Sample and Data Collection
This study focused on the Global
Entrepreneurship Monitor database from
Costa Rica and Germany for 2012. The analysis
is worked with a representative sample of the
adult population from Germany (N = 4300)
and Costa Rica (N = 2041). However, as a part
of this study there were used 3 filter questions
to determine whether the respondents were
nascent entrepreneurs, and after applying
SBIR / Small Business International Review / Vol. 1 Nº 2 / July - December 2017 / AECA-FAEDPYME 33
the questions to the first sample, there were
determined that the final samples that
participated in this study were N= 277 from
Costa Rica and N= 170 from Germany (nascent
entrepreneurs of the GEM databases).
Data were collected as part of the Global
Entrepreneurship Monitor (GEM) in 2012.
Private market survey firms conducted
telephone interviews with a standardized
questionnaire during 2012 with respondents
between 18-64 years old.
The GEM database is the most important
entrepreneurship research project in the world;
it is the result of academic efforts and interagency
coordination by almost 70 countries, according
to the GEM national report 2012.
The Global Entrepreneurship Monitor (GEM) is
an assessment of the entrepreneurial activity,
attitudes and aspirations of individuals in a
wide range of countries. It is a unique project
because it measures the behavior of individuals
related to the creation and management of a
company (Karaagac, 2014).
3.2 Measures
3.2.1 Dependent and Independent
Variables
Nascent entrepreneurs. As part of the analysis
people who were in the process of creating their
own business (nascent entrepreneurs1) at the
time of data collection have been identified to
determine the likelihood of engaging in business
start-up activities. To identify individuals
involved in the entrepreneurial process, the
GEM asked the following question: Are you,
alone or with others, currently trying to start a
new business, including any self-employment
or selling any goods or services to others?
1. A nascent entrepreneur was one who had taken
an action to be involved in an entrepreneurial
process. Established entrepreneurs were not con-
sidered (those who had paid wages for more than
three months, according to the GEM) to avoid the
bias of studying people who have already been
involved in the entrepreneurial process.
The database also asked two extra questions to
respondents who answered yes to this question to
identify people who had in mind being involved
in activities of self-employment and those who
were already involved in these activities, which
are as follows: “Over the past twelve months,
have you done anything to help start a new
business, such as looking for equipment or a
location, organizing a start-up team, working
on a business plan, beginning to save money,
or any other activity that would help launch a
business?” and “Will you personally own all,
part, or none of this business?”. In the study,
only respondents who answered “yes” to the
first question and to the second question “all” or
“part” were considered nascent entrepreneurs.
This dependent variable is a binary variable
that is classified in the following way: “1 = Yes”,
“0 = No”, attempting to identify whether the
individual was a nascent entrepreneur when
the survey was conducted.
Human Capital. Human capital was valued as
an independent variable and was divided into
two variables, which were “academic level”
and “personal skills” (Autio & Wennberg, 2010;
Arenius & De Clercq, 2005). Academic level
was divided into four categories: no university
degree, incomplete university degree, university
degree completed and higher than university
degree. The education variable was based on
two binary variables: ‘higher than university
degree’ and ‘university degree’ either complete
or incomplete (1 = Yes, 0 = No).
Moreover, to measure personal skills, the
concept of self-efficacy was applied, employing
the question of the GEM about whether “the
respondents had the necessary knowledge,
skill and experience to start a new venture”
(Autio & Wennberg, 2010). This question was
measured as a variable of dichotomous state,
with “1” indicating whether the individual had
the knowledge, skill and experience and “0”
indicating the absence of those features.
Social Capital. It has been confirmed that
knowledge of an employer has a positive
relationship that is statistically significant
to influence on the likelihood to engage in
entrepreneurial activities (Klyver, Hindle &
Meyer, 2008; Arenius & Kovalainen, 2006;
Carolina Madriz ::: Juan Carlos Leiva ::: Ralph Henn
34
Morales & Roig, 2005). Accordingly, social
capital is considered an independent variable.
Therefore, to assess the exposure of individuals
to external knowledge, the study was based
on the variable of “knowing an entrepreneur,”
which is a binary variable with the answers
“Yes” or “No” to the next question of the GEM:
“Do you know someone personally who started
a business in the past 2 years?”
3.2.2. Control variables. According to the study of
previous literature, the importance of including
some control variables in the research was
determined. Demographic variables influence
entrepreneurial activity (Runyan, Huddleston
& Swinney, 2006), so gender (Wilson, Kickul &
Marlino, 2007) and age (Klyver & Hindle, 2007)
were included. The GEM measured gender in a
binary way (“1” = female, “0” = male) and age in a
way indicating the number of years.
Moreover, “perspective of opportunities” in
the environment is related to the propensity
to create one’s own business (Klyver & Hindle,
2007; Klyver, Hindle, & Meyer, 2008). To measure
this factor, the following question established
by GEM was utilized: “In the next six months,
will there be good opportunities for starting a
business in the area in which you live? “with “1”
indicating “Yes” and “0” indicating “No”.
In addition, studies with entrepreneurial
approaches demonstrate that people with
more “fear of failure” are less likely to engage
in entrepreneurial activities (De Clercq &
Arenius, 2006). Therefore, the “fear of failure”
is considered a control variable. The question of
the GEM was as follows: “Would fear of failure
prevent you from starting a business?” with “1”
indicating “Yes” and “0” indicating “No”.
It was also considered that “what people of the
country think about entrepreneurship” is a factor
that measures entrepreneurial attitudes (Autio
& Wennberg, 2010). The GEM implemented the
following question of dichotomous nature (1 =
Yes, 0 = No): “In your country, do most people
consider starting a new business a desirable
career choice?”
According to the above theoretical
considerations, the conceptual model illustrated
in Fig. 1 was considered.
4. Results
First of all, it is important to mention that
after applying the three filter questions to
determine whether the respondents were
nascent entrepreneurs, the final samples that
participated in this study were N= 277 from
Costa Rica and N= 170 from Germany (nascent
entrepreneurs of the GEM databases).
Table 1 presents the intercorrelations of the
variables in the study utilizing the pooled
sample (from Germany and Costa Rica) and their
Source: Author’s elaboration.
Figure 1. Human Capital, Social Capital , and Nascent Entrepreneurs
Academic Level
Fear of failure
Age
Gender
Perspective of
opportunities
What people of the
country think about
entrepreneurship
Self- efficacy
Human Capital
Social Capital
Nascent
Entrepreneur
Knowing an
entrepreneur
SBIR / Small Business International Review / Vol. 1 Nº 2 / July - December 2017 / AECA-FAEDPYME 35
standard deviations and means. It indicates
that human capital (self-efficacy and academic
level) is partially positively correlated with
the propensity to become an entrepreneur.
However, it can be seen that social capital
(knowing an entrepreneur) and the propensity
to become an entrepreneur are completely
positively correlated.
The logistic regression analyses are presented
in Table 2, for a new variable called “EMPNAC”
was created, measured in a binary way, with
“1” indicating “Yes” and “0” indicating “No”. The
first and second columns present the pooled
samples from Costa Rica and Germany. To test
the hypotheses of the study, Table 2 exhibits
two models: analysis of just the control variables
and analysis of all of the variables included in
this study. The first model merely reveals the
control variables (first column, Table 2), and the
second one presents the control and predictor
variables, (second column, Table 2). In addition,
in Table 2, the same two models for each country
are presented to determine whether the results
differed for Costa Rica (third and fourth columns)
and Germany (fifth and sixth columns).
The statistical study from the pooled sample
demonstrates that the majority of the control
variables have a predictable result (first column,
Table 2). More specifically, when people have
more fear of failure, they are less likely to
become entrepreneurs. Additionally, those that
expect there will be good market opportunities
for a new venture are more likely to become
entrepreneurs. Moreover, the results suggest
that gender influences the decision to engage
in a new business, with males more likely to
being involved in a business start-up. Another
relevant finding from the control variables is
that younger individuals are more likely to
engage in new ventures.
To determine the variables related to knowledge
and to prove the hypotheses, the results of the
total variables from the two countries (column
2, Table 2) are shown. For Hypothesis 1, it can
be shown that the academic level presents a
nonlinear relationship or is insignificant to the
likelihood of starting a business. The “incomplete
university” category was considered the base
case. However, self-efficacy (perception of
having the knowledge and skills required
to start a new business) has a statistically
positive relationship with the propensity to
become a nascent entrepreneur. Furthermore,
giving support to Hypothesis 2, the statistical
results prove that the entrepreneurial
knowledge transmitted by others (knowing an
entrepreneur) is significantly positively related
to starting one’s own business.
In addition to the pooled sample study (first
and second columns, Table 2), a study was
Table 1. Correlations, Means and Standard Deviations
Fuente: elaboración propia con base en resultados de SPSS.
*** p < .001; ** p < .01; * p < .05
Variables Means S.D. 1 2 3 4 5 6 7 8
1. Entrepreneurship (start-up
activity)
2. Academic Level (completed or
did not complete university)
3. Self-efficacy
4. Knowing an entrepreneur
5. Fear of failure
6. Perspective of opportunities
7. Gender (woman)
8. Age
9. What people of the country
think about entrepreneurship
0.07
0.40
0.48
0.32
0.45
0.43
0.50
40.63
0.58
0.26
0.49
0.50
0.47
0.50
0.50
0.50
13.05
0.49
.038**
.075***
-.060***
.105***
-.010
-.051***
-.181***
.015
.213***
.196***
-.129***
.129***
-.075***
-.068***
.033
.224***
-.196***
.145***
-.147***
.049***
.016
-.084***
.149***
-.079***
-.101***
.020
-.125***
.101***
.020
-.055***
-.063***
-.056***
.044**
.
017
-.012
-.065***
36 Carolina Madriz ::: Juan Carlos Leiva ::: Ralph Henn
Table 2. Logistic Regression Analysis of the Likelihood of Being Engaged in a Business Start-up Activity
Source: Author’s elaboration.
*** p < .001; ** p < .01; * p < .05
2. Adjustment capacity (R2 = 0.092 - 0.220) means that there may be other variables that were not considered in the study and they may be important to the propensi-
ty to become an entrepre neur.
Two Countries Costa Rica Germany
Human Capital
Academic Level (completed or did not complete university)
Self-efficacy
Social Capital
Knowing an entrepreneur
Fear of failure
Perspective of opportunities
Gender
Age
What people of the country think about entrepreneurship
Constant
Nagelkerke R2 (2)
- 2 Log likelihood
-1.001
.785
-.523
-.016
.095
-1.022
.095
2508.622
(.368)***
(2.192)***
(.593)***
(.984)***
(1.099)
(.360)***
-1.017
.702
-.616
.001
-.112
-.927
.092
1401.423
(.362)***
(2.018)***
(.540)***
(1.001)
(.894)
(.396)**
.113
1.418
.669
-.907
.436
-.470
-.000
-.010
-2.515
.176
1286.749
(1.120)
(4.129)***
(1.953)***
(.404)***
(1.547)**
(.625)**
(1.000)
(.990)
(.081)***
-.952
.947
-.509
-.025
-.168
-1.084
.101
1043.497
(.386)***
(2.579)***
(.601)**
(.976)***
(.845)
(.338)**
.172
1.323
1.296
-.642
.683
-.251
-.032
-.093
-2.762
.220
922.326
(1.188)
(3.775)***
(3.656)***
(.526)**
(1.980)***
(.778)
(.969)***
(.912)
(.063)***
-.033
1.440
.946
-.820
.531
-.330
-.019
.127
-2.601
.199
2257.455
(.967)
(4.219)***
(2.575)***
(.440)***
(1.701)***
(.719)**
(.981)***
(1.135)
(.074)***
SBIR / Small Business International Review / Vol. 1 Nº 2 / July - December 2017 / AECA-FAEDPYME 37
conducted for each country to determine
whether the results from the pooled sample
differed in each country in term of the
hypotheses. Furthermore, to compare whether
there are differences between the results
obtained from each country, a statistical study
for each country was conducted. Interestingly,
making a comparison of the variables used for
the hypotheses, all of them were too similar
to the pooled samples of those countries, with
the perception of having the skills required
(self-efficacy) and the transmitted knowledge
(knowing an entrepreneur) being found
statistically significant with the propensity
to become an entrepreneur. In addition, the
level of education was not associated with the
entrepreneurial intention.
Furthermore, referring to the control variables
in the case of Costa Rica, the fear of failure,
the perspective of opportunities and gender
played a significant role in business start-up
activity (third column, Table 2); it is important
to mention that in the full model and the
pooled samples, too. For Germany, the control
variables model demonstrates that the last
three variables mentioned from Costa Rica
and the age remained significant even in the
control variables model (fifth column, Table 2).
However, in the German full model, only the
negative effect of gender disappeared (sixth
column, Table 2).
As a conclusion, through the statistical study
and the respective analyses, Hypothesis 1 is
partially accepted and Hypothesis 2 is fully
accepted. This is so for Hypothesis 1 because
self-efficacy has a statistically positive
relationship with the propensity to become
an entrepreneur; nevertheless, there is an
insignificant impact between the academic level
and entrepreneurship. Hypothesis 2 is fully
accepted because knowing an entrepreneur
significantly influences the propensity of
making a decision to become involved in a
start-up activity.
5. Discussion and conclusions
The present study proves there is a partial
positive correlation between human capital
and the propensity to become an entrepreneur
because there is a relationship with self-
efficacy but not with the academic level. In
addition, social capital is complete positively
correlated with the propensity to become an
entrepreneur.
This research demonstrates that self-efficacy
and knowledge are crucial for starting business
activity. It means that depending on the level
of human capital and transmitted knowledge,
the level of influence will decide whether
one becomes an entrepreneur. As a result, it
has been shown that the perception that an
individual has about having the skills required
for a new venture is relevant for making the
decision to engage in a business start-up. The
empirical study proves that someone who
thinks they have the skills required to manage
a new venture would be more likely to become
an entrepreneur (Morales & Roig, 2005; De
Clercq & Arenius, 2006; Davidsson & Honig,
2003; Autio & Wennberg, 2010).
In addition, it was proven that external
knowledge affects the propensity to engage in
business start-up activities. It could be because
if an individual has been in contact with people
who have established their own businesses,
those entrepreneurs transmit entrepreneurial
knowledge from their personal experiences
to the individual; in that way, the individual
would feel more sure (less uncertainty) and
confident in their abilities to undertake a new
business (Davidsson & Honig, 2003; De Clercq
& Arenius, 2006; Klyver, Hindle & Meyer, 2008).
People decide to become entrepreneurs by
different motivations. The GEM indicates
individuals who chose to have their
own businesses because of good market
opportunities, but others have no choice
because of necessity, according to GEM Global
Report (Xavier et al., 2012).
The difference in samples between the
countries (N = 277 for Costa Rica and N = 170
for Germany, although the total database of
Germany is basically twice as large as that
of Costa Rica) may occur because in Costa
Rica many people decide to undertake a new
business because it is the only option for work.
However, in Germany, most entrepreneurs
decided to engage in business start-up activities
Carolina Madriz ::: Juan Carlos Leiva ::: Ralph Henn
38
because there were good market opportunities
for entrepreneurship.
A very important fact from the statistical study
and its respective analysis from Costa Rica and
Germany is that there is not a relevant difference
between the respective relationships in the
statistics results (Table 2). In both countries,
the perception of having the skills required
to start a new venture has a statistically
positive relationship with the propensity to
become an entrepreneur. In addition, knowing
an entrepreneur is positively related to the
decision to start one’s own business. However,
focusing on control variables can suggest that
the contexts from an underdeveloped country
and a developed country may affect some
factors differently as to the likelihood to engage
in business start-up activities.
The results suggest that customized approaches
with a focus on exclusive cultural contexts are
essential for entrepreneurship in every country
(Lee et al., 2006). It could explain why the age
in Germany has a positive relationship with
the propensity to become an entrepreneur but
this age relationship is not significant in Costa
Rica. That could mean that the profile of people
varies according to the context in which they
are involved, and it could affect them to engage
in entrepreneurial activities.
Additionally, depending on environment
where people are located, the personal and
transmitted knowledge (human and social
capital) will change. As a consequence, the type
of business would be different depending on
the context.
6. Limitations, Future Research and
Implications
This study has some limitations, which are as
follows: First of all, in this study, correlations
were employed to give support to the causal
relationship for the hypothesis, to know the
change that one variable causes in another
variable. However, across-sectional study was
employed (logistic regression) to determine the
relationship of the factors related to knowledge
together with the propensity to become an
entrepreneur. It could be explained as follows:
the majority of respondents answered that
they have the skills required for a new venture
because they are already involved in the
entrepreneurial process. However, it may be
that people first experienced interactions with
entrepreneurs and that they subsequently
made the decision to engage in business start-
up activities. For that reason, although the
hypotheses were established with concrete
theory, it could be important to do a study
related to knowledge factors and in another
way, one focused on business start-up activities
to detect clear causality.
Similarly, there was a limitation for the study
in that there was only access to the questions
established by the Global Entrepreneurship
database; for that reason, only those questions
or variables were employed for analyzing
the social capital (knowing an entrepreneur).
Future research should investigate the social
capital with another variable that can help to
determine the relation. Furthermore, some
of those questions were limited by a period
of time, and sometimes they could not be
utilized to study a determined variable. A
recommendation for the GEM database is to pay
attention to the structure of how the questions
are limited by a period of time because it could
affect some potential studies.
Moreover, in this study, respondents from the
GEM database 2012 were employed, those
who conducted something for a new business
but were not involved in the business start-up
activity, that is, nascent entrepreneurs. It could
be important to do further research to know
whether these respondents continued with the
entrepreneurial process after the interviews.
It is important for future researchers to
study the principal reasons that cause the
positive relationship of human capital and
social capital with the propensity to become
an entrepreneur. To determine the principal
factors could help to improve entrepreneurship.
Furthermore, it could permit one to indicate
a positive relationship between social capital
and factors related to human capital (Gradstein
& Justman, 2000), for example, knowing
how an entrepreneur could improve his
skills and enhance human capital and vice
SBIR / Small Business International Review / Vol. 1 Nº 2 / July - December 2017 / AECA-FAEDPYME 39
versa. Future studies could present valuable
information to determine the reasons or nature
of the relationships between factors related to
knowledge and the reasons why they affect the
propensity to become an entrepreneur.
However, future researchers could explore
the effect of factors related to knowledge
with the propensity that one person engages
in various new ventures (Davidsson & Honig,
2003).
As a conclusion, one of the limitations to the
development of new businesses in the studied
countries is related to the factors that influence
knowledge, particularly self-efficacy and
transmitted external knowledge.
As far as recommendations to promote contact
with other entrepreneurs, one could plan
specific activities for entrepreneurs, such as
conferences for transmitting entrepreneurial
knowledge and obtaining good contacts from
entrepreneurs. These activities could be
promoted in public and private educational
centers. In addition, entrepreneurs could visit
high schools, colleges and universities to tell of
their successful experiences as entrepreneurs.
Correspondingly, students from educational
centers could create associations to encourage
and support business ideas, conducting
activities for the integration of different
careers, to engage in multidisciplinary teams.
In addition, teachers focused on that topic, or
if they had entrepreneurial experience, could
provide consulting support.
The educational centers may have incubators
that provide support and assistance to
students or graduates who want to start
their own businesses. Moreover, the state
could implement campaigns to promote
entrepreneurship, and the media might report
more cases of successful companies and the
experiences of their entrepreneurs.
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Madriz, C., Leiva, J. C., & Henn, R. (2018). Human and social capital as drivers of entrepreneurship. Small Business
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