The Influence of Entrepreneurship Education and Family Status
on Entrepreneurial Intention
Final version
Author
Aldrich A. Croes
S2386542
A.A.Croes@student.rug.nl
0031654345520
Master: Small Business and Entrepreneurship
Poelestraat 40 A, Groningen
University of Groningen
Faculty of Economics and Business
Abstract
Entrepreneurship is a widely studied topic, however, the conditions that need to be met for a person to become an entrepreneur are not yet fully understood. In this study entrepreneurial intention, a vital precondition for becoming an entrepreneur is researched. Two main factors are investigated that likely influence entrepreneurial intention of a person: Entrepreneurial family status and entrepreneurial education. Drawing on the theory of planned behavior, it is investigated how these two factors influence entrepreneurial intention via influencing attitudes, subjective norm, and perceived behavioral control. The sample consisted of students in higher education in the Netherlands. Data was drawn from the “Global University Entrepreneurial Spirit Students ́ Survey” (GUESSS). The results show that students who participate in entrepreneurial education are more likely to have higher intention (five years after their studies have been completed) to found their own business. Family entrepreneurial status has a positive effect on entrepreneurial intention right after graduation and also five years after completion of study. Practical implications of the findings as well as directions for future research are discussed.
Keywords: Entrepreneurial Intention, Theory of Planned Behavior, Entrepreneurial Family Status, and Entrepreneurship Education.
Acknowledgements
Table of Contents
ABSTRACT 2
ACKNOWLEDGEMENTS 3
1. INTRODUCTION 5
2. THEORETICAL BACKGROUND 7
2.1THEORY OF PLANNED BEHAVIOR 7
2.2THEORY OF PLANNED BEHAVIOR IN THE CONTEXT OF ENTREPRENEURSHIP 8 2.3ENTREPRENEURSHIP EDUCATION AND ENTREPRENEURIAL INTENTION:MEDIATING ROLE OF ATTITUDE AND PERCEIVED BEHAVIORAL CONTROL 9 2.4FAMILY ENTREPRENEURIAL STATUS AND ENTREPRENEURIAL INTENTION:MEDIATING ROLE OF ATTITUDE,SUBJECTIVE NORM AND PERCEIVED BEHAVIORAL CONTROL 11
CONCEPTUAL MODEL 14
3. METHODOLOGY 15
3.1.RESEARCH STRATEGY 15
3.2DATA COLLECTION 15
3.3SAMPLE SELECTION AND DESCRIPTION 16
3.3MEASURES 17
3.3.1ENTREPRENEURIAL INTENTION 17
3.3.2ENTREPRENEURIAL FAMILY STATUS AND ENTREPRENEURSHIP EDUCATION 18
3.3.3MEDIATORS 19
3.3.3.1ATTITUDE TOWARD ENTREPRENEURSHIP 19
3.3.3.2SUBJECTIVE NORMS 19
3.3.3.3PERCEIVED BEHAVIORAL CONTROL (PBC) 19 3.3.4CONTROL VARIABLES FOR ENTREPRENEURIAL INTENTION 20
3.4METHODOLOGY APPROACH 22
3.4.1MULTIPLE BINARY MEDIATION MODEL 23
4. RESULTS 25
4.1ENTREPRENEURIAL INTENTION RIGHT AFTER STUDIES 26
4.2ENTREPRENEURIAL INTENTION FIVE AFTER STUDIES 31
5. DISCUSSION 37
6. LIMITATIONS, FUTURE RESEARCH 39
6.1IMPLICATIONS 40
7. CONCLUSION 40
REFERENCES 41
APPENDIX 46
1. Introduction
state that the effects coming from entrepreneurship education are still poorly understood. Similarly, researchers have hardly focused on family background and its influence on the development of entrepreneurial intensions. Krueger, Reilly, and Carsrud (2000) state that teachers, consultants, advisors, and entrepreneurs can benefit from a better general understanding of how intentions are formed. Furthermore, understanding intentions offers sizable diagnostic power, like entrepreneurship educators can use this model to better understand the motivations and intentions of students and to help students understand their own motivations and intentions. As Krueger, Reilly, and Carsrud (2000) state: “Understanding intentions helps us to better understand where ideas for a business venture come from and how the venture becomes a reality” (p.426)
For the present study secondary data has been drawn from the “Global University Entrepreneurial Spirit Students ́ Survey” (GUESSS). This survey is an international research project that investigates the entrepreneurial spirit of students from all over the world. The remainder of this paper is organized as follows: the theoretical background describes the previous research regarding theory of planned behavior in the entrepreneurial context, followed by the methodology section in which focus on the method and data description, that is used to test the formulated hypotheses. Subsequently, the empirical results are depicted and discussed. In the final section, the discussion and conclusion, a summary of the major findings, limitations and implications are presented.
2. THEORETICAL BACKGROUND
2.1. Theory of Planned Behavior
Furthermore, Ajzen (1991) states that intention is formed as a result of three factors that are included in the theory of planned behavior. The first factor is attitude, were an individual has a positive or negative personal valuation about the intended behavior (Ajzen, 2001). The second factor is subjective norms that illustrate the perceived social support of performing the intended behavior. The last factor is perceived behavioral control. Perceived behavioral control is more than just the feeling of being able, it rather includes the perception of control ability regarding the intended behavior. This perception is concerned not with the skills one has but with an individual’s judgments about what can be done with those skills (Kickul, Gundry, Barbosa, and Whitcanack, 2009).
2.2. Theory of Planned Behavior in the context of entrepreneurship
2.3. Entrepreneurship Education and Entrepreneurial Intention: Mediating role of Attitude and Perceived Behavioral Control
Entrepreneurship education complies with broad definitions of entrepreneurship (Rauch and Hulsink 2014; Gibb, 2002). A more narrow definition of entrepreneurship is that entrepreneurship is concerned with the discovery and exploitation of profitable opportunities (Shane and Venkataraman, 2000). The main purpose of entrepreneurship education and entrepreneurship programs is to inspire entrepreneurs to start a business (Gorman et al., 1997; Von Graevenitz, Harhoff, and Weber, 2010). Nevertheless, entrepreneurship education also prepares individuals to successfully administer growing, profitable businesses and in so doing enhancing the welfare of society (Hood and Young, 1993). It is obvious that entrepreneurship education influences perceptions about entrepreneurship, however it seems to have less effects on actual behaviors related to entrepreneurship (Rauch and Hulsink, 2014). Research of Franke and Luthje, (2004) shows that education in entrepreneurship encourages graduates to start their own businesses. Research by Clark, Davis and Harnish (1984) claims that entrepreneurship courses appeared to attract students with strong interests in entrepreneurial activities. Some empirical studies confirm the positive impact of entrepreneurship education courses or programs at universities on individual preference for self-employment (Tkachev and Kolvereid, 1999). Only students who have strong confidence in their entrepreneurial skills have a high intention to become an entrepreneur (Chen et al. 1998). Nevertheless, according to Fayolle, et al. (2006) there is a debate in the entrepreneurship education literature as to whether the actions of starting up a business is a suitable outcome of entrepreneurship education.
Hypothesis 1a: Participation in entrepreneurship education has a positive effect on
entrepreneurial intention right after studies.
Attitude towards entrepreneurship may be influenced by educational channel (Krueger, 1993; Von Graevenitz, Harhoff, and Weber, 2010). For example, students of universities that do not offer entrepreneurship education are less likely to become entrepreneurs, causing for a lower level of entrepreneurial intention (Lima, Lopes, Nassif and Silva, 2014). Rauch and Hulsink (2014) found that “entrepreneurship education has a positive effect on attitudes, perceived behavioral control, and the intention to become an entrepreneur” (p.199). Entrepreneurship education affects attitudes and consequently affects peoples’ intentions (Rauch and Hulsink, 2014). Moreover, emotions and passion that are associated with entrepreneurship can enhance one’s attitudes (Souitaris et al., 2007). However, attitudes are also affected by external influences such as organizations and institutions (Ajzen, 1991).
Hypothesis 2a: The positive relationship between entrepreneurship education and
entrepreneurial intention is mediated by attitudes right after studies.
Hypothesis 2b: The positive relationship between entrepreneurship education and
entrepreneurial intention is mediated by attitudes five years after studies.
Perceived behavioral control is known as the perception of the difficulty of becoming an entrepreneur, something that can be influenced by entrepreneurship education (Liñ ´an et al., 2011). Rauch and Hulsink, (2014) also support this statement, perceived behavioral control might be modified by changing people’ s believes and their ability to engage in entrepreneurial behavior by participating in entrepreneurship education.
Hypothesis 3a: The positive relationship between entrepreneurship education and
entrepreneurial intention is mediated by perceived behavioral control right after studies.
Hypothesis 3b: The positive relationship between entrepreneurship education and
The research of Rauch and Hulsink, (2014) states that entrepreneurship education does not affect subjective norms because the belief of friends and family cannot be influenced directly by entrepreneurship education. To summarize, the main objective of entrepreneurial education is to create a positive attitude towards entrepreneurship by influencing attitudes and perceived behavioral control (Rauch and Hulsink, 2014).
2.4. Family Entrepreneurial Status and Entrepreneurial Intention: Mediating role of Attitude, Subjective Norm and Perceived Behavioral Control
This paper defines Family entrepreneurial status as a family business, governed and/or managed by one or both parents (Chua et al., (1999). According to Sørensen (2007), this definition suggests that family’s exposure to self-employment is an important source of the transmission of self-employment, and can affect young people’s occupational choices such that they perceive self-employment as desirable and achievable. However, according to Sørensen, (2007), there is little evidence to suggest that children of the self-employed parents enter self-employment because they have superior entrepreneurial abilities or because they have privileged access to their parent’s financial or social capital. In previous research it has been shown that parents’ entrepreneurial background can instigate entrepreneurial intentions in their children (Scherer et al., 1989). In the research of Dunn and Holtz-Eakin (2000) data on young men in the United States was used and it was estimated that parental self-employment significantly increases the probability of entry into self-employment during the early career.
Hypothesis 4a: Family Entrepreneurial Status has a positive effect on entrepreneurial
intention right after studies.
Hypothesis 4b: Family Entrepreneurial Status has a positive effect on entrepreneurial
intention five years after studies.
subsequently parents who are active in a family business will affect their children’s future entrepreneurial intentions by modeling attitudes and beliefs (Krueger et al., 2000). Moreover, the family background significantly influences the attitudes and subjective norms related to career choice (Carr and Sequeira, 2007).
Hypothesis 5a: The positive relationship between family entrepreneurial status and
entrepreneurial intention is mediated by attitude right after studies.
Hypothesis 5b: The positive relationship between family entrepreneurial status and
entrepreneurial intention is mediated by attitude five years after studies.
Greve and Saleff, (2003) state that a family business background may present lower barriers to entrepreneurial entry, subsequently those with such backgrounds may be able to profit on their social ties and social capital. Students with a family business background seem to see the doubtful part of being in control but nonetheless; they see the optimistic part about their capabilities and resources to pursue an entrepreneurial career, too (Zellweger, Sieger and Halter, 2011). Furthermore, family support offers the subjective norms that potential entrepreneurs may use to determine if their goal is to start a business (Carr and Sequeira, 2007).
Hypothesis 6a: The positive relationship between family entrepreneurial status and
entrepreneurial intention is mediated by subjective norm right after studies.
Hypothesis 6b: The positive relationship between family entrepreneurial status and
entrepreneurial intention is mediated by subjective norm five years after studies.
Hypothesis 7a: The positive relationship between family entrepreneurial status and
entrepreneurial intention is mediated by perceived behavioral control right after studies.
Hypothesis 7b: The positive relationship between family entrepreneurial status and
2.5. Conceptual model
3. METHODOLOGY
In this chapter the specific methodology that was used in this paper will be described. The strategy, sample selection and description, data collection and analysis will be presented. Furthermore, this study was making use of secondary data, a factor analysis will be presented as well and reliability test.
3.1. Research strategy
In this study, entrepreneurial intention is being investigated by applying theory of planned behavior. The intention of a behavior depends on attitude, subjective norm, and perceived controlled behavior.Correspondingly, this research will be concentrated on the intention part of the theory, while including the two additional contextual determinants: Family entrepreneurial status and entrepreneurship education.
3.2. Data collection
For this study, secondary data is drawn from the “Global University Entrepreneurial Spirit Students ́ Survey” (GUESSS). This survey investigates the entrepreneurial spirit of students worldwide, a total of 26 countries have participated in this survey. The Netherlands has joined this survey in 2011 for the first time. The collection of the data took place among students in higher education in different fields of study and at different education levels in the Netherlands. According to the Netherlands report of 2011 the data collection was conducted through an online survey that was distributed by institutional representatives at 14 Universities and 24 Schools of Applied Sciences between March and June 2011. Table 1 presents the participating educational institutions in the Dutch GUESSS survey as well as the number of addressed students, response rate and through which method the students were contacted. The complete GUESSS data set for 2011 includes from across 26 countries from more then 93,000 respondents, a total of 13,121 are from the Netherlands.
Table 1 Educational Institution WO and HBO
Universities (WO) Method Population Reponses Response
rate
Rotterdam Nyenrode Business University Direct mail 4,045 315 7.79 Radboud University Nijmegen Direct mail 1,500 86 5.73
University of Groningen Direct mail 25,000 1,627 6.51
Eindhoven University of Technology
Direct mail 1,494 132 8.84
Maastricht University Direct mail 14,500 449 3.1
University of Twente Direct mail 8,416 731 8.69
Utrecht University Direct mail 30,000 3,115 10.38
VU University Amsterdam Direct mail 5,000 253 5.06
Tilburg University Direct mail 1,000 282 28.2
University of Amsterdam Intranet 30,825 76 0.25
Universities of Applied Sciences (HBO)
Method Population Reponses Response
rate Hanze Univ. of Appl.
Sciences Direct mail 23,320 814 3.49
InHolland Univ. of Appl.
Science Direct mail 33,000 996 3.02
Univ. of Appl. Sciences Utrecht
Direct mail 38,000 1,738 4.57
The Hague Uni of App
Sciences Direct mail 200 55 27.5
The Hague Univ. of Hospitality Mgt
Direct mail 1,900 78 4.11
HAN Univ. of Appl.
Sciences Newsletter 1,400 60 4.29
Amsterdam Univ. of Appl.
Sciences Intranet 41,779 332 0.79
Zuyd Univ. of Appl. Sciences
Intranet 13,200 30 0.23
Breda Univ. of Appl.
Sciences Intranet 7,000 29 0.41
Others (1) 247
Total 13121
Note: (1) Other educational institutes (with no systematic data collection and ≤ 20 responses) Source: Global University Entrepreneurial Spirit Students’ Survey 2011 Netherlands Report
3.3. Sample selection and description
students (Master students). Furthermore, only 39 % from the students, one or both of the parents are self-employed. With regarding gender 56,2 % of the total sample size is female. The average age of students is 23.97 years. Figure 2 shows the total age distribution in percentage.
Figure 2: Age distribution.
3.3. Measures
3.3.1. Entrepreneurial Intention
In previous empirical papers the dependent variable “entrepreneurial intention” has been measured in various ways. In this paper, the respondents were asked: ‘Which
career path do you intend to pursue right after completion of your studies, and which career path five years after completion of your studies?’ The respondents had to
choose one out of four options: (1) Employee, (2) Founder, (3) Successor, (4) Others. The focus of this research is on the founders ‘foundation of own firm”. The respondents also had to state how likely they are considering owning their own firm in right after or five years after finishing their studies. Therefore two dependent variables are constructed. The dependent variable is entrepreneurial intention right after studies and entrepreneurial intention five years after studies. Dummies variables were created to indicate whether the student has the intention to be a founder.
6%
74% 14%
6%
Age
3.3.2. Entrepreneurial Family Status and Entrepreneurship Education
The two independent variables are “Entrepreneurial Family Status and Entrepreneurship Education”. For entrepreneurial family status the following question was used: ‘Are your parents currently self-employed or do they have majority
ownership in a company’? Dummy variable 1 represents the respondent that has one or
both of their parents self-employed, 0 for the parents are not self-employed.
For entrepreneurship education the respondents had to answer if they attended lectures or participated in seminars regarding the topic entrepreneurship. Furthermore, if a respondent participated in the networking and coaching workshops/events that have been offered by the educational intuitions, these were considered as entrepreneurial education. Respondents who attended an entrepreneurship education program had at least to attend one of the taught components by the educational intuitions. Table 2 presents the 13 taught components that have been taken in consideration to be entrepreneurship education. From these 13 taught components one entrepreneurial education dummy variable was created. Dummy variable for entrepreneurial education: takes value 1 if respondent attended an entrepreneurship education program, respondent had to attended at least one of the taught components and/or one business-planning component (networking and coaching offering), otherwise, it takes value 0 if respondent did not attend the program.
Table 2: Entrepreneurship Education Taught Components Lectures and seminars about (taught components) Entrepreneurship in general
Family firms
Financial entrepreneurship ventures Technology entrepreneurship Social entrepreneurship Entrepreneurial marketing Innovation and idea generation Business planning
Networking and coaching offering (business-planning component) Workshops/networking with experience entrepreneurship
Contact platforms with potential investors Business plan contest/ workshops
3.3.3. Mediators
Attitude towards entrepreneurship, subjective norms, and perceived behavioral Control are hypothesized to mediate the relationship between entrepreneurial family status and entrepreneurship education and entrepreneurial intentions. A factor analysis was conducted in order to describe variability among observed and correlated variables and potentially lower number of unobserved variables (Pallant, 2001). For all the three mediators towards entrepreneurial intention has been measured through a seven-point likert scale (from 1=strongly disagree to 7=strongly agree). The reliability of the scale confirmed by Cronbach’s alpha as can be seen in table 3.
3.3.3.1. Attitude Toward Entrepreneurship
Attitude towards entrepreneurial intention has been measured with four items; this is according to the research of Linan and Chen (2009). The respondents were asked to indicate their level of agreement on the four different statements referring their attitude towards entrepreneurship. The four statements are as follow: ‘Being an
entrepreneur implies more advantages than disadvantages to me’. Second one: ‘A career as entrepreneur is attractive for me’. Third: ‘If I had the opportunity and resources, I would become an entrepreneur’. And the last one: ‘Being an entrepreneur would entail great satisfactions for me’. The scale was found to be reliable
(Cronbach’s alpha > α= 0.936) as can be seen in table 3.
3.3.3.2. Subjective norms
Subjective norm was measured with three items, these three items are according to the research of Linan and Chen (2009). To measure the reaction of the respondent environment, the respondents were asked ‘if you would pursue a career as
an entrepreneur how would people react in your environment?’ The respondents’
environment consists of three groups: parents / other family members, friends / fellow students, and people that are important to them in general. Furthermore, the scale was found to be reliable (Cronbach’s alpha is > α= 0.719 (see table 3).
Perceived behavioral control for this paper was measured with three items, these three items are part of the multidimensional locus of control Levenson, (1973). The first item is: When I make plan I am sure that the planned will come reality. Secondly: I myself can determine very much of what’s going on in my life. And the last item: If I get what I want it is the result of endeavor and personal commitment.
Moreover, reliability of the scale was found to be reliable (Cronbach’s alpha is > α= 0.642) (see table 3).
Table 3: Mediators Cronbach’s alpha
Mediators Number of items Cronbach’s
alpha
Attitude toward entrepreneurship 4 α= 0.936
Subjective Norms 3 α= 0.719
Perceived Behavioral Control 3 α= 0.642
3.3.4. Control variables for Entrepreneurial Intention
Table 4: Variable Description
Variable Measurement
Dependent variables Entrepreneurial intention right after studies
Dummy variable: 1 if respondent has the intention to be a founder right away after their studies, 0 if respondents intend to be an employee.
Entrepreneurial
intention five years after studies
Dummy variable; 1 if respondent has the intention to be a founder in five years after their studies, 0 if respondents intend to be an employee
Main independent variables
Entrepreneurship
education program Dummy variable: 1 if respondent attended an entrepreneurship education program including at least one of the taught components, one business-planning component (networking and coaching offering), Otherwise, it takes value 0 if respondent did not attend the program.
Family Entrepreneurial Status
Dummy variable 1 represent the respondent that has one or both of their parents self-employed, 0 for the parents not self-employed.
Mediators
Perceived Behavioral Control α= 0.642 Levenson, (1973).
When I make a plan I am sure that the plan, will become a reality.
I myself can determine very much of what’s going on in my life.
If I get what I want it is the result of endeavor and personal commitment.
Subjective Norms α= 0.719
Linan and Chen (2009)
Your close family Your friends
Your fellow students Attitude toward
entrepreneurship α= 0.936
Linan and Chen (2009)
Being an entrepreneur implies more advantages than disadvantages to me.
A career as entrepreneur is attractive for me If I had the opportunity and resources, I would become an entrepreneur.
Being an entrepreneur would entail great satisfactions for me.
Control variables
Age Continuous variable, reveals the age of respondents
Gender Dummy variable: 1 if respondent is female, 0 if
Business and Economics Dummy variable: 1 if respondent’s field of study is business and economics, 0 if field of study is natural science, social sciences or other
Bachelor Dummy variable: 1 if respondent level of study is
undergraduate (bachelor), 0 if it is graduate, (master) PhD.
University Institution Dummy variable: 1 if the institution is university
(WO), 0 if it is university of applied sciences (HBO)
3.4. Methodology approach
Cronbach’s coefficients above .6 suggesting high reliability. This test is applied to the QUESSS (secondary data) in order to assess the reliability of this study.
3.4.1. Multiple binary mediation model
The mediation model illustrates how the independent variables (X), family entrepreneurial status and entrepreneurship education affect the dependent variable (Y), entrepreneurial intention through one or more mediators (M) (Preacher & Hayes, 2008a). In this paper, the relationship between family entrepreneurial status (X) and entrepreneurial intention (Y) and is being mediated by attitude toward entrepreneurship (M1), subjective norm (M2) and perceived behavioral control (M3). Furthermore, the relationship between entrepreneurship education (X) and entrepreneurial intention (Y) mediated by attitude toward entrepreneurship (M1), and perceived behavioral control (M3). Because of the three mediators in this model, a multiple mediator model is applied; this is illustrated in figure 2 and 3. To investigate multiple mediation different paths is created: “Path A” represents the effect of family entrepreneurial status/entrepreneurship education on the mediators. Furthermore, “Path B” represents the direct effect of three mediators (attitude toward entrepreneurship, subjective norm and perceived behavioral control) on entrepreneurial intention. And “Path C” is the direct effect between (X) and (Y) and “(path c’)” present the indirect effects of the independent variable on the dependent variable through the three mediators. There is partial mediation, when so called “path A” as well as “path B” is significant. Full mediation between (X) and (Y), is when so-called “path A” and “path B” are to be significant, controlling for M (path c') should be zero, not significant (Pallant, 2001).
24 B α1 b1 ć α2 b2 α3 b3
Figure 3: Multiple mediator model Entrepreneurship Education A c B α1 b1 ć α3 b3
(A) X affects Y (total effect).
(B) X is hypothesized the indirect effects on Y through Mediator 1,2 and 3. Source: Adaption of Preacher & Hayes, (2008a)
4. Results
This chapter presents the results from the statistical analysis. Due to the substantial amount of hypothesis the result part will be present in two parts, the first part is the result on entrepreneurial intention right after studies and the second part is five years after the studies. Table 6 presents the means the standard deviations and the Pearson correlations in order to measure of the degree of linear dependence between the variables. The dependent variable is presented on the top of the table and follow the three mediators and control variables.
Table 6: Descriptive statistics and Pearson correlations of variables
Variable Mean Sd EI 1 EI5 ATE SN PBC
Entrepreneurial intention right after studies (EI1)
.08 .276
1.0000
Entrepreneurial intention five year after studies (EI5)
.30 .460 .150** 1.0000 Attitude (ATE) .00 1.001 .206** .435** 1.0000 Subjective Norm (SN) .00 .999 -.046** -.002 .038** 1.0000 Perceived Behavioral Control (PBC) .00 .999 .046** .061** .151** .066** 1.0000 Family Entrepreneurial status (FES) .39 .487 .051** .087** .152** .026** .044** Entrepreneurship Education (EE) .61 .488 -.024** .022* .046** .016 .042** Age 23.97 4.939 .082** .047** .032** -.094** .013 Gender .56 .496 -.079** -.098** -.239** .112** -.030** Business & Economics .36 .480 .038** .138** .318** .030** .073** University Institution .69 .461 -.080** -.078** -.069** .020* .024** Bachelor .30 .457 -.036** -.037** -.035** .004 .040**
Variable FES EE Age Gender BE UI Bachelor
University Institution (UI)
-.007 .149** -.069** .008 -.031** 1.0000 Bachelor -.009 .033** .275** -.022* -.030** .361** 1.0000 Sd: Standard Deviation
*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
As can be seen from the table 6, participation in an entrepreneurship education program is negatively significantly correlated with entrepreneurial intention directly after studies (r=-.024**, p<0.005) and (r=-.022* p<0.010) five years after studies. For Family entrepreneurial status (r=. 051**p<0.005) positively significantly correlated
with entrepreneurial intention directly after studies and (r=. 087**p<0.005) after five
years after studies.
4.1. Entrepreneurial intention right after studies
Table 7: Logistic regression: effect of participation in Entrepreneurship Education (EE) on entrepreneurial intention right after studies
Entrepreneurial Intention
B Standard Errors Sig Odds ratios
Entrepreneurship Education (EE) .009 .082 .911 1.009 Control Variables Age .043*** .006 .000 1.044 Gender .526*** .081 .000 1.693 Business & Economics -.205** .081 .012 .815 University Institution .351*** .090 .000 1.421 Bachelor .238** .097 .014 1.269 N 9830 Log-likelihood 5030.326 Nagelkerke R Square .035
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Entrepreneurship
Education (EE), Gender: 1= female, Business Economics: 1= business and economics;0= social sciences and
natural sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University Institution: 1= WO; 0= HBO.
The logistic regression model was statistically significant χ2 (6,N=9830)= 139.957 p<0.000), indicating that the model was able to predict entrepreneurial intention. The model as whole explained by 35% Nagelkerke R squared of the variance entrepreneurial intention right after studies and correctly classified 92.6% of the cases. Test of Hypothesis 1a
The result indicated that participation in entrepreneurship education has no significant effect on entrepreneurial intention right after studies. Therefore, hypothesis 1a is not supported.
Table 8: Logistic regression: effect of participation in family entrepreneurial status (FES) on entrepreneurial intention right after studies
Entrepreneurial Intention B Standard Errors Sig Odds ratios Family Entrepreneurial status (FES) -.487*** .078 .000 .614 Control Variables Age .044*** .006 .000 1.045 Gender .535*** .081 .000 1.707
Business & Economics -.176** .081 .029 .839 University Institution .361**** .089 .000 1.435
Bachelor .241** .098 .014 1.272
N 9826
Log-likelihood 4991.351 Nagelkerke R Square .044
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Family Entrepreneurial
status (FES) Gender: 1= female, Business Economics: 1= business and economics;0= social sciences and natural
sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University Institution: 1= WO; 0= HBO.
model was able to predict entrepreneurial intention. The model as whole is explains by 44% Nagelkerke R squared of the variance entrepreneurial intention right after studies and correctly classified 92.6% of the cases.
Test of Hypothesis 4a
The results showed that family entrepreneurial status has a significant effect on entrepreneurial intention right after their studies. Although the direction of the effect differs from hypothesis 4a. Therefore, hypothesis 4a being is supported.
Table 9: Multiple binary mediation model Entrepreneurship Education (EE) on Entrepreneurial intention right after studies
OLS regressions (Path a1, a2, a3): effect of Entrepreneurship Education (EE) on two mediators.
Logistic regression (Path c): total effect of Entrepreneurship Education (EE) on entrepreneurial intention right after studies
Logistic regression (Path c’): direct effect of Entrepreneurship Education (EE) on entrepreneurial intention right after studies
Logistic regression (Path b1, b3): effect of each mediator on entrepreneurial intention right after studies Path A1 Path A3 Path C Path C’, b1, b2, b3
ATE PBC EI EI Entrepreneurship Education (EE) .020 .069*** .009 -.007 Mediators Attitude (ATE) .982*** Perceived Behavioural Control (PBC) .081* Control Variables Age .006*** .000 .043*** .041*** Gender -.407*** -.030 .526*** .177** Business & Economics .584*** .138*** -.205** .294*** University Institution -.063*** -.006 .351*** .340*** Bachelor -.040* .097*** .238** .269***
N 9830 9680
Log-likelihood 5030.326 4499.622
Pseudo R2 .035 .147
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Entrepreneurship Education (EE), ATE: attitude towards entrepreneurship, SN: subjective norm, PBC: perceived behavioral control, EI: entrepreneurial intention right after studies, Gender: 1= female, Business Economics: 1= business and economics;0= social sciences and natural sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University
Institution: 1= WO; 0= HBO.
appeared, (B-std=. 020 p=. 333). It can be concluded that attitude does not mediate the positive relationship between entrepreneurship education and entrepreneurial intention. Test Hypothesis 2a
The positive relationship between entrepreneurship education and entrepreneurial intention was not found to be mediated by attitudes right after studies. Hypothesis 2a is not supported.
Path A3 of the mediation model, which tested the regression of family entrepreneurship education (EE) on perceived behavioral control, is significant, (B-std=-.069, p<0.000). Path B showed that the logistic regression of the mediator perceived behavioral control on the dependent variable entrepreneurial intention, while controlling for age, gender, field of study, level of study and types of educational institutions, is significant B-std= .081, p<0.10). As such, there is full mediation, whereas the direct relationship between independent variable and dependent variables is not significant. Last, controlling for age, gender, level of study, field of study and types of educational institutions are significant predictors for entrepreneurial intention. Furthermore, the positive relationship between entrepreneurship education and entrepreneurial intention is mediated by perceived behavioral control, right after studies. As can be seen in table 9. As such, there is full mediation.
Test Hypothesis 3a
The positive relationship between entrepreneurship education and entrepreneurial intention is fully mediated by perceived behavioral control right after studies. Hence, hypothesis 3a is supported.
Table 10: Multiple binary mediation model family entrepreneurial status (FES) right after studies
OLS regressions (Path a1, a2,a3) effect of Family Entrepreneurial status (FES) on three mediators.
Logistic regression (Path c): total effect of Family Entrepreneurial status (FES) on entrepreneurial intention right after studies
Logistic regression (Path c’): direct effect of Family Entrepreneurial status (FES) on entrepreneurial intention right after studies
Logistic regression (Path b1, b2,b3): effect of each mediator on entrepreneurial intention right after studies
b2,b3
ATE SN PBC EI EI
Family Entrepreneurial status (FES) .285*** .022 .080** -.487*** -.238*** Mediators Attitude (ATE) .981*** Subjective Norm (SN) -.143*** Behavioral Control (PBC) .081* Control Variables Age .006*** -.018*** .000 .044*** .042*** Gender -.411*** .241*** -.035* .535*** .188** Business & Economics .568*** .107*** .142*** -.176** .294*** University Institution -.061*** .008 .005 .361**** .346*** Bachelor -.041* .070*** .097*** .241** .259
N 9830 9676
Log-likelihood 5030.326 4494.376
Pseudo R2 .035 .148
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Family Entrepreneurial
status (FES), ATE: attitude towards entrepreneurship, SN: subjective norm, PBC: perceived behavioral control, EI: entrepreneurial intention right after studies, Gender: 1= female, Business Economics: 1= business and
economics;0= social sciences and natural sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University
Institution: 1= WO; 0= HBO.
As can be seen in table 10, path A1 of the mediation model, which tested the regression of family entrepreneurial status (FES) on attitude, is significant,
(B-std=-.285, p<0.000). Path B showed that the logistic regression of the mediator attitude on the dependent variable entrepreneurial intention, while controlling for age, gender, field of study, level of study and types of educational institutions, is significant, B-std=. 981, p<0.000). As such, there is partial mediation. Last, controlling for age, gender, field of study and types of educational institutions are significant predictor for, entrepreneurial intention is mediated by attitude right after studies. As can be seen in table 10. As such, there is partial mediation.
Test of Hypothesis 5a
The positive relationship between family entrepreneurial status and entrepreneurial intention is partial mediated by attitude right after studies. Therefore hypothesis 5a is supported.
Test of Hypothesis 6a:
The positive relationship between family entrepreneurial status and entrepreneurial intention is not being mediated by subjective norm right after studies. This implies that hypothesis 6a is not supported.
Path A3 of the mediation model, which tested the regression of family entrepreneurial status (FES) on perceived behavioral control, is significant, (B-std=. 080, p<0.05). Path B3 showed that the logistic regression of the mediator perceived behavioral control on the dependent variable entrepreneurial intention, though controlling for age, gender, field of study, level of study and types of educational institutions, is significant, B-std=. 081, p<0.01). As such, there is no mediation.
Test Hypothesis 7a
The positive relationship between family entrepreneurial status and entrepreneurial intention is not mediated by perceived behavioral control right after studies. This implies that hypothesis 7a is not supported.
4.2. Entrepreneurial intention five after studies
Table 11: Logistic regression: effect of participation in entrepreneurship education (EE) on entrepreneurial intention five years after studies
Entrepreneurial Intention B Standard Errors Sig Odds ratios Entrepreneurship Education (EE) -.126*** .048 .009 .881 Control Variables Age .022*** .005 .000 1.022 Gender .386*** .046 .000 1.471
Business & Economics -.531*** .047 .000 .588
University Institution .269*** .054 .000 1.308
Bachelor .113* .055 .040 1.120
N 9830
Log-likelihood 11572.649
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Entrepreneurship
Education (EE), Gender: 1= female, Business Economics: 1= business and economics;0= social sciences and
natural sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University Institution: 1= WO; 0= HBO.
Entrepreneurship education (EE) has a significant effect on entrepreneurial intention five years after studies, as was indicated by the performed logistic regression. The results show that there is a significant negative relationship between family entrepreneurial status (FES) on entrepreneurial intention (B-std=-.126, p<0.000). Additionally, all control variables also had an effect on entrepreneurial intention among the students. Only “field of study” had a significant negative relationship as can be seen in table 11. The logistic regression model was statistically significant χ2
(6,N=9830)= 331.763 p<0.000), indicating that the model was able to predict entrepreneurial intention. The model as a whole explained by 47% Nagelkerke R squared of the variance entrepreneurial intention right after studies and correctly classified 70.6% of the cases.
Test Hypothesis 1b
Participation in entrepreneurship education has a significant effect on entrepreneurial intention five year after studies, but the effect differs from our hypothesis 1b. Therefore, hypothesis 1b is supported but the direction of the effect differs.
Table 12: Logistic regression: effect of participation in family entrepreneurial status (FES) on entrepreneurial intention five years after studies
Entrepreneurial Intention B Standard Errors Sig Odds ratios Family Entrepreneurial status (FES) .346*** .046 .000 1.414 Control Variables Age .022*** .005 .000 1.022 Gender .398*** .046 .000 1.490
Business & Economics -.528*** .047 .000 .590 University Institution .249*** .054 .000 1.283
Bachelor .114** .055 .039 1.121
N 9826
Log-likelihood 11517.690 Nagelkerke R Square .054
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Family Entrepreneurial
sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University Institution: 1= WO; 0= HBO.
As shown in table 12, a logistic regression was performed to indicate that family entrepreneurial status (FES) has a significant effect on entrepreneurial intention five years after studies. The results show it that there is a positive significance relationship between family entrepreneurial status (FES) on entrepreneurial intention (B-std=. 346, p<0.000). Furthermore, nearly all control variables had a positive significantly related to entrepreneurial intention five years after studies only “field of study” has a negative significant relationship. The logistic regression model was statistically significant χ2
(6,N=9826)= 139.957 p<0.000), indicating that the model was able to predict entrepreneurial intention. The model as whole explained by 54% Nagelkerke R squared of the variance entrepreneurial intention right after studies and correctly classified 70.5 % of the cases.
Test of Hypothesis 4b
The result shows that family entrepreneurial status has a positive effect on entrepreneurial intention five years after studies. Therefore, hypothesis 4b is supported. Table 13: Multiple binary mediation model Entrepreneurship Education (EE) five after studies.
OLS regressions (Path a1, a2, a3): effect of Entrepreneurship Education (EE) on three mediators.
Logistic regression (Path c): total effect of Entrepreneurship Education (EE) on entrepreneurial intention right after studies
Logistic regression (Path c’): direct effect of Entrepreneurship Education (EE) on entrepreneurial intention right after studies
Logistic regression (Path b1, b2, b3): effect of each mediator on entrepreneurial intention right after studies
Path A1 Path A3 Path C Path C’, b1, b2,
Economics University Institution -.063*** -.006 .269*** .259*** Bachelor -.040* .097*** .113* .107* N 9830 9680 Log-likelihood 11572.649 9453.536 Nagelkerke R Square .047 .296
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Entrepreneurship Education (EE), ATE: attitude towards entrepreneurship, SN: subjective norm, PBC: perceived behavioral control, EI: entrepreneurial intention five year after studies, Gender: 1= female, Business Economics: 1= business and economics;0= social sciences and natural sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University
Institution: 1= WO; 0= HBO.
From table 13 paths A1 of the mediation model, which tested the regression of family entrepreneurial status (FES) on attitude, is not significant, (B-std=. 020, p<. 333). Intrinsically, there is no mediation
Test Hypothesis 2b
The positive relationship entrepreneurship education and entrepreneurial intention is not mediated by attitudes five years after studies. This implies that hypothesis 2b is not supported.
Path A3 of the mediation model, which tested the regression of entrepreneurship education (EE) on perceived behavioral control, is significant, (B-std=. 069, p<0.000). Path B3 showed that the logistic regression of the mediator perceived behavioral control on the dependent variable entrepreneurial intention, while controlling for age, gender, field of study, level of study and types of educational institutions, is not significant B-std=. -.033p=. 215). As such, there is no mediation.
Test Hypothesis 3b
The positive relationship entrepreneurship education and entrepreneurial intention is not being mediated by perceived behavioral control five years after studies. Hypothesis 3b is not being supported.
Table 14: Multiple binary mediation models family entrepreneurial status (FES) five after studies
OLS regressions (Path a1, a2, a2 effect of Family Entrepreneurial status (FES) on three mediators.
after studies
Logistic regression (Path c’): direct effect of Family Entrepreneurial status (FES) on entrepreneurial intention right after studies
Logistic regression (Path b1, b2, b3): effect of each mediator on entrepreneurial intention right after studies
Path A1 Path A2 PathA3 Path C Path C’, b1, b2, b3 ATE SN PBC EI EI Family Entrepreneurial status (FES) .285*** .022 .080** .346*** -.056 Mediators Attitude (ATE) 1.265*** Subjective Norm (SN) -.040 Perceived Behavioural Control (PBC) -.031 Control Variables Age .006*** -.018*** .000 .022*** .019*** Gender -.411*** .241*** -.035* .398*** -.044 Business & Economics .568*** .107*** .142*** -.528*** .047 University Institution -.061*** .008 .005 .249*** .229*** Bachelor -.041* .070*** .097*** .114** .105*
N 9826 9676
Log-likelihood 11517.690 9456.823
Nagelkerke R Square .054 .295
Notes: ***: p-value less than 0.01; **: p-value less than 0.05; *: p-value less than 0.10, Family Entrepreneurial
status (FES), ATE: attitude towards entrepreneurship, SN: subjective norm, PBC: perceived behavioral control, EI: entrepreneurial intention five years after studies, Gender: 1= female, Business Economics: 1= business and
economics;0= social sciences and natural sciences, Bachelor: 1=bachelor; 0= Master, PhD, or other, University
Institution: 1= WO; 0= HBO.
Path A1 of the mediation model, which tested the regression of family entrepreneurial status (FES)on attitude, is significant, (B-std=. 285, p<0.000). Path B1 showed that the logistic regression of the mediator attitude on the dependent variable entrepreneurial intention, while controlling for age, gender, field of study, level of study and types of educational institutions, is significant B-std=1.265<0.000). As such, there is partial mediation. Last, controlling for age, level of study and types of educational institutions is significant predictor for, entrepreneurial intention is mediated by attitude five years after studies. As can be seen in table 14. As such, there is partial mediation.
The positive relationship between family entrepreneurial status and entrepreneurial intention is partially mediated by attitude five years after studies. Consequently, hypothesis 5b is supported.
Path A2 of the mediation model, which tested the regression of family entrepreneurial status on subjective norm, is not significant, (B-std=. 022 p=. 279). Therefore there is no mediation.
Test Hypothesis 6b
The positive relationship between family entrepreneurial status and entrepreneurial intention is not being mediated by subjective norm five years after studies. This indicates that hypothesis 6b is not supported.
Path A3 of the mediation model, which tested the regression of family entrepreneurial status (FES)on perceived behavioral control, is significant, (B-std=. 080, p<0.05). Path B3 showed that the logistic regression of the mediator perceived behavioral control on the dependent variable entrepreneurial intention, while controlling for age, gender, field of study, level of study and types of educational institutions, is not significant B-std=-.031 p =0.000). Basically, there is no mediation.
Test Hypothesis 7b
The positive relationship between family entrepreneurial status and entrepreneurial intention is not mediated by perceived behavioral control five years after studies. This implies that hypothesis 7b is not supported.
5. Discussion
In this chapter, the findings of the statistical analysis will be discussed. The following table (15) presents a summary of the six hypotheses that was measured in different time periods, right after the studies and five years after the studies. The hypotheses were developed according to the conceptual model, which is inspired by the theory of planned behavior.
Table 15: Summary of the hypotheses
Hypotheses Right after
studies (a)
Five years after studies (b)
H1: Participation in entrepreneurship education has positive effect on entrepreneurial intention.
Not Supported
Supported
H2: The positive relationship entrepreneurship education and entrepreneurial intention is mediated by attitudes.
Not Supported
Not Supported H3: The positive relationship entrepreneurship education and
entrepreneurial intention is mediated by perceived behavioral control.
Supported Not supported H4: Family Entrepreneurial Status has a positive effect on
entrepreneurial intention.
Supported Supported
H 5: The positive relationship between family entrepreneurial status and entrepreneurial intention is mediated by attitude.
Supported Supported
H6: The positive relationship between family entrepreneurial status and entrepreneurial intention is mediated by subjective norm.
Not supported
Not supported H7: The positive relationship between family entrepreneurial status and
entrepreneurial intention is mediated by perceived behavioral control.
Not supported
Not Supported
before and in a later stage of their career path, to consider founding their own company.
The expected mediation effect of perceived behavioral control between the entrepreneurial education and entrepreneurial intention is only significant right after the students finishing their studies. This full mediation is in line with the research of Souitaris et al. (2007) that measured entrepreneurial behavior right after completion of student’s studies, this study reports significant relationships between entrepreneurial education and intention.
Attitude towards entrepreneurship was found to have no mediation effect on the relationship between entrepreneurship education and entrepreneurial intention. This is contrary to the research of Rauch and Hulsink (2014) that states that there is a mediation effect, attitude towards entrepreneurship acts as mediator between entrepreneurship education and entrepreneurial intention. These results were not expected because attitudes usually affect people’s intentions. An explanation for this is unpredictable mediation is when the direct effect is even larger than the total effect.
Family entrepreneurial status has a remarkable influence on entrepreneurial intention (Sørensen (2007). Family entrepreneurial status has a positive effect on entrepreneurial intention right after graduation and also five years after completion of study. This finding is consistent with the paper of Scherer et al., (1989) which states, parents entrepreneurial background instigates entrepreneurial intentions in their children. Moreover, Sørensen (2007), that family’s exposure to self-employment is an important source of the transmission of self-employment on their children.
The positive relationship between family entrepreneurial status and entrepreneurial intention is being partially mediated by attitude. Furthermore, indicating that attitudes usually affect people’s intentions, this is inline with the study of Krueger et al. (2000) who noted that having a family background in entrepreneurship, that indirectly influenced entrepreneurial intentions through the effect on attitude.
could be one of the reason why subjective norm does not mediates the relationship between the dependent and independent variables. It could also be that the direct relation is so strong that is the mediation effect of the subjective norm and perceived behavioral control becomes invalid.
6. Limitations, Future Research
As every other study, this research does not come without limitations. The data used in this study was collected only at a single point in time and not across different time periods. Across time data could provide a better impression, especially to investigate if respondents will act on their entrepreneurial intention. Additionally, because secondary data was used, meaning that the data was not collected for the main purpose of this study, secondary data sources may provide a vast amount of information but not always the quality that is needed. Furthermore, to have a more complete overview of the national entrepreneurial intention in the Netherlands, it would be ideal to have all academic institution taken into account, as opposite to only 20 institutions in this data set. Furthermore, respondents had to fill in which career path they will take right after studies as well as for five years after graduation, their latter entrepreneurial intention could be influenced by different factors that have not been taken into account in this research.
On schooling level, the objective of teaching entrepreneurship in business school is not the soul purpose to start your own business, but many graduates are also indirectly involved with entrepreneurship, either academically or as consulting (Kolvereid and Moen 1997).
6.1. Implications
The findings of this research offer several implications for students, universities, politicians, policy makers and researchers in the Netherlands. Universities and other organizations should be aware of the benefits of entrepreneurial education and understand that the characteristics of the programs may create potential entrepreneurs or emphasize entrepreneurship as a career option in the future. Moreover, universities are potential places where students can find a partner for future business ventures. For the economy it is also important to have students with entrepreneurial intention in addition students should be encouraged pursue these intentions. For politicians and policy maker’s entrepreneurial intention is valuable because main entrepreneurship is on of the driver for economic growth, development and employment generation in many countries worldwide (Al-Harrasi,Al-Zadjali and Al-Salti, 2014).
7. Conclusion
Entrepreneurial intention is important in the entrepreneurship field of study. This paper was set to explore the influence of entrepreneurship education and family status on entrepreneurial intention. The findings showed that the framework is built on the theory of planned behavior model and can be used to explain entrepreneurial intention. Participation in education has positive effect on entrepreneurial intention only five years after their studies. In the case of family entrepreneurial background, there is significant relationship on entrepreneurial intention right after and five year after graduating. These significant relationships are important in entrepreneurship. Furthermore, investigating entrepreneurial intention among students seems to be relevant to new business creation, subsequently economic growth and generates new jobs, and confidently helps maintains employment levels.
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