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Career choice intentions of students: Does entrepreneurship education matter?
Jiabao Li S2157993
University of Groningen
Faculty of Economics and Business
Small Business & Entrepreneurship Master (MSc BA)
Supervisor: Dr. H. Zhou Co-assessor: Dr. M. Olthaar
December 2014
Word count: 16,402
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Abstract
Drawing on the theory of planned behavior, this study attempts to identify the relationship between entrepreneurship education, entrepreneurial attitudes, perceived behavioral control, and career choice intentions for students from higher education. The data is drawn from GUESSS (2011) (Global University Entrepreneurial Spirit Students´ Survey, 2011). The sample for the tests of this study contains 40388 respondents across 193 universities. The results show that: 1) students with an entrepreneurship education background are more often intend to start their own business than non-participants (right after study and five years after their study); 2) students with entrepreneurship education background have higher entrepreneurial attitudes and perceived behavioral control; 3) entrepreneurship education indirectly influences entrepreneurial intention through attitudes and perceived behavioral control; 4) the three components of entrepreneurship education program which are learning, inspiration and resources all exert an effect on entrepreneurial intention through entrepreneurial attitudes and perceived behavioral control. The findings of this study contribute to the theory of planned behavior, theories about entrepreneurship education, and might help policy makers with making policies about entrepreneurial education.
Key words: entrepreneurship education, entrepreneurial intention, career choice intention,
entrepreneurial courses, entrepreneurial activities, incubation resources.
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Contents
1. Introduction ... 4
2. Literature review & Hypotheses ... 7
2.1 Career Choice Intention as Planned Behavior ... 7
2.1.1 Theory based intention models. ... 8
2.1.2 Ajzen’s theory of planned behavior. ... 10
2.1.3 Determinants of entrepreneurial intention. ... 14
2.2 Entrepreneurship Education ... 15
2.3 Entrepreneurship Education and Entrepreneurial Intention ... 19
2.4 Entrepreneurship Education, Theory of Planned Behavior and Entrepreneurial Intention ... 20
2.5 Effects of Different Content of Entrepreneurship Education on Entrepreneurial Intention ... 22
2.6 Conceptual Model ... 24
3. Data Description & Methodology ... 26
3.1 Data... 26
3.2 Sample ... 27
3.3 Measures ... 30
3.3.1 Entrepreneurial Intention ... 30
3.3.2 Mediators. ... 31
3.3.3 Participation in an entrepreneurship education program. ... 32
3.3.4 Control Variables... 33
3.4 Methodology... 34
3.4.1 Simple mediator model. ... 35
3.4.2 PROCESS. ... 37
4. Results ... 38
4.1 Entrepreneurial intention right after completing a study ... 38
4.1.1 Participation in entrepreneurship education program. ... 38
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4.1.2 Participation in entrepreneurial courses. ... 47
4.1.3 Participation in relevant entrepreneurial activities. ... 51
4.1.4 Usage of university resources. ... 55
4.2 Entrepreneurial intention five years after study ... 59
4.2.1 Participation in entrepreneurial education program. ... 59
4.2.2 Participation in entrepreneurial courses. ... 67
4.2.3 Participation in relevant entrepreneurial activities. ... 71
4.2.4 Usage of university resources. ... 75
5. Conclusion and Discussion ... 79
5.1 Contributions and Implications ... 82
5.2 Limitations ... 83
References ... 85
Appendix ... 94
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1. Introduction
Career choice intention is individuals’ intention to be an entrepreneur or to be an employee (Bae, et al., 2014; Zellweger et al., 2011). The intention of to be an entrepreneur is called entrepreneurial intention. Schumpeter, J. A, one of the most influential economists, mentioned the importance of entrepreneurship in early 20
thcentury. He believes that an entrepreneur is someone who innovates and brings new market conditions to induce economic growth.
Entrepreneurship is known as a vital stimulant for economic development, because of new job creation, technological innovation, and increasing economic efficiency (Shane &
Venkataraman, 2000). This positive effect of entrepreneurship on economic growth has been proved by Van Praag & Versloot (2007). Due to this vital position of entrepreneurship for economic growth and innovation, policy makers and scholars are paying tremendous attention towards the factors that influence individuals to choose to become an entrepreneur (Sanchez, 2013). In other words, what influences individuals’ entrepreneurial intention.
According to the European commission (2006), policymakers believe that entrepreneurial relevant education can increase the levels of entrepreneurship. In Europe, 42 percent of 164 important business schools have established specific centers for entrepreneurship (Wilson 2004). Moreover, in the year 2005/2006, a program called Junior Achievement Young Enterprise student mini-company (SMC) program has been organized by European secondary schools and colleges (Oosterbeek, vanPraag, & Ijsselstein, 2009). Therefore, it is not difficult to infer that policymakers and scholars believe that being an entrepreneur can be taught through entrepreneurship relevant education programs (Sanchez, 2013; Erikson, 2003).
To testify whether entrepreneurship relevant education accelerates the growth of
entrepreneurs, scholars have devoted attention to investigate the relationship between
entrepreneurship education and entrepreneurial intention (Ilouga et al., 2013; Sanchez, 2013;
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Zhang et al., 2013; Bae, et al., 2014). However, this relationship is still under exploration and lacks support from empirical tests (Peterman & Kennedy, 2003; Byabashaija & Katono, 2011;
Johansen & Schanke 2011; Zhang et al., 2013; Sanchez, 2013). In order to make a contribution for addressing this limitation, the purpose of this study is to investigate: how entrepreneurship education influences students’ career choice intention. The two research questions are: Does entrepreneurial education influences students’ career choice intention? And how does entrepreneurial education affects students’ career choice intention?
For the purpose of studying the relationship between entrepreneurship education and students’ career choice intention, this study draws on the theory of planned behavior (Ajzen, 1991, 2002). This theory proposed that intention is the antecedent of behavior, intention has three determinants, and these determinants are affected by exogenous factors (Ajzen, 1991; Krueger et al.
2000; Souitaris et al., 2006). Many researches have already applied this theory to study entrepreneurial intention. Yet, the investigation for entrepreneurial education (exogenous factors) on entrepreneurial intention through the three determinants is still limited and undergoing empirical tests (Gorman et al., 1997; Souitaris et al., 2006). Therefore, the theory of planned behavior is used for further investigation of this study.
In addition, Souitaris et al. (2006) proposed three components of entrepreneurship education, which are learning, inspiration and resources. For a more deep investigation, these three components are taken into account to check if each of them influences entrepreneurial intention.
The data of this study is drawn from “Global University Entrepreneurial Spirit Students ́ Survey, 2011” (GUESSS, 2011). The sample involves 40388 students of 7 countries in Europe.
The results show that participants of entrepreneurship education have a higher probability of having
entrepreneurial intention than non-participants. Entrepreneurship education indirectly influences
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entrepreneurial intention through attitude and perceived behavioral control. Learning, inspiration and resources affect entrepreneurial intention through attitude and perceived behavioral control.
Theoretically, this study contributes to 1) theory of planned behavior (by providing evidence of the relationship between entrepreneurship education and entrepreneurial intention);
and 2) the field of entrepreneurial education (by investigating the indirect effect of entrepreneurship education and components of entrepreneurship education). Practically, the empirical results provide evidence for policymakers (to establish useful policies and to provide effective help for stimulating entrepreneurship) and education institutions (to formulate more efficient entrepreneurship education programs).
This paper is organized as follows. Section 2 provides a literature review which concerns career choice intention, theory of planned behavior and entrepreneurship education, followed by hypotheses and conceptual models. Section 3 provides data descriptions and methodology.
Section 4 presents the results of hypotheses. Section 5 provides discussion and the conclusion,
which also contains contributions, implications, and limitations.
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2. Literature review & Hypotheses
2.1 Career Choice Intention as Planned Behavior
Career choice intention is usually defined as one’s desire to start one’s own business or to strive for organization employment (Bae, et al., 2014; Zellweger et al., 2011). The desire of starting one’s own business means an individual intends to found his/her own company. This intended behavior is known as entrepreneurial intention (Bird, 1988, Krueger & Carsrud, 1993;
Gelderen et al., 2008).
The influential factors of entrepreneurial intention which influence the decision of an individual to start one’s own business have drawn attention of many researchers. Those researchers are mainly focused on explaining one’s career choices by factors such as personality traits, demographics, personal history and social context. Linan (2004) proved that there are significant relationships between these factors and decisions for becoming an entrepreneur (behavior). However, some researchers criticize that these factors have low explanatory power, that it is difficult to develop more integrated explanatory models and that attention should be more focused on the processes before the entrepreneurial decision has been made (Bird, 1988; Krueger, 1993; Rauch & Frese, 2000; Gelderen et al., 2008). The “processes before the entrepreneurial decision” in psychology literatures means what influence one’s behavior (i.e. to be an entrepreneur).
Intention has been described, since a long history, as self-prediction of one’s behavior
(Ajzen, 1991; Ajzen & Fishbein, 1977), which means one’s actual behavior is expected when
one’s intention is formatted (Bae et al., 2014). The intention of to be an entrepreneur (to start
one’s own business), in many literatures, is considered as planned behavior (Katz & Gartner
1988; Krueger & Carsrud, 1993; Gelderen et al., 2008; Zhang et al., 2013). Intentionality, as
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defined by Bird (1988), is “a state of mind directing a person's attention (and therefore experience and action) towards a specific object (goal), or a path in order to achieve something (means)”. This process can be seen as an intentional behavior as well as a predictor of planned entrepreneurial behavior (Zhang et al., 2013). Therefore, entrepreneurial intention can be defined as one’s commitment (attention) to start own business (goal) (Krueger, 1993). Planned behavior can be predicted well by intentions towards that behavior since intentions are unbiased predictors of action where time lags exist (Bagozzi et al., 1989). In terms of entrepreneurial activities, a time lag exists between one’s interest to start a business and actual behavior of starting a business. Thus, planned (intentional) behavior is clearly representing entrepreneurial activities (Krueger & Carsrud, 1993). As Katz and Gartner (1988) studied, intentionality is a critical characteristic of emerging organizations. Therefore, the phenomena, which happen before the formations of organizations, and the decision to start an entrepreneurial career, are clearly important, and interesting (Krueger & Carsrud, 1993).
2.1.1 Theory based intention models.
To understand entrepreneurial intention, various comparable studies have emerged. In the 1990s, researchers started to use social psychological models, involving more proximal variables, to explain planned behaviors (Gelderen et al., 2008). Several theoretical models have been introduced, such as the Shapero’s model (Shapero & Sokol, 1982); Bird’s (1988) model;
Ajzen’s model (1988, 1991); Davidsson, (1995). There are two dominant models among these models---Shapero’s model and Ajzen’s model (see figure 1 and 2). For the reason that these two models present the basic cognitive linkage from the antecedents of entrepreneurial intention, and have been robustly tested and validated by existing literatures since 1990’s as well (Gelderen et al., 2008; Peterman & Kennedy 2003; Krueger et al., 2000; Kolvereid 1996;
Tkachev &Kolvereid 1999; Autio et al., 2001).
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Figure 1 Shapero’s model of entrepreneurial event
Figure 2 Ajzen’s model ---Theory of planned behavior
Shapero’s model (Shapero & Sokol, 1982) is called the entrepreneurial event model. This
model indicates that entrepreneurial intention is derived from perceived desirability, perceived
feasibility and the propensity to act upon opportunities (Krueger et al., 1993). Ajzen’s model is
named as theory of planned behavior (TPB), which describes intention by means of attitude
towards that behavior, subjective norm, and perceived behavioral control (Krueger et al., 1993).
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There are previous researches which provide evidence support that both models are competing and compatible (Gelderen et al. 2008; Zhang et al., 2013). For example, Krueger et al. (2000) finds that Shapero’s model is slightly better for assessing entrepreneurial intention;
Paço et al. (2011) concludes that Ajzen’s model is a proper tool for modeling the development of entrepreneurial intention through pedagogical processes. Moreover, these two models have large overlapping area. Perceived desirability and perceived feasibility of Shapero’s model correspond to the attitude toward the behavior and perceived behavioral control of Ajzen’s model (Krueger, 1993; Kolvereid, 1996b; Autio et al., 1997). Differences between these two models are that Shapero uses propensity to act instead of Ajzen’s subjective norm, and Shapero’s model mainly focuses on new organizational emergences than entrepreneurial behavior. Krueger et al. (2000) concludes that both models can be used for understanding the process of entrepreneurial intention and firm creation.
On account of this study, Ajzen’s theory of planned behavior is chosen to be the basic intentional model. For the reason that this study is investigating the antecedents of entrepreneurial behavior (career choice intention), and Ajzen’s model was robustness tested by different studies of various fields which includes career choice intention, as well as it is widely accepted by most scholars (Gelderen et al., 2008; Fayolle et al., 2006; Shook et al., 2003; Ajzen, 2001; Kolvereid, 1996).
2.1.2 Ajzen’s theory of planned behavior.
The theory of planned behavior introduces three conceptually independent determinants of
intention (Ajzen, 1991), as figure 3 shows. The first is attitude toward the behavior, which can
be explained as “the degree to which a person has a favorable or unfavorable evaluation or
appraisal of the behavior in question” (Ajzen, 1991, p.188). The second determinant is termed
subjective norm (perceived social norms), “this construct taps the subjects’ perception of what
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important people in their lives think about performing the behavior” (Krueger & Carsrud, 1993, p.325). The third predictor is named the perceived behavior control, which refers to “the perceived ease or difficulty of performing the behavior and is assumed to reflect past experience as well as anticipated impediments and obstacles” (Ajzen, 1991, p.188). The first two antecedents of intention measure subjective expectations about the personal attractiveness of the planned behavior (Krueger and Carsrud, 1993). The third antecedent represents the degree of optimism that the person perceives whether the target behavior is achievable or doable (Krueger and Carsrud, 1993).
The relation between these three constructs is, as Ajzen (1991) states “the more favorable the attitude and subjective norm with respect to a behavior, and the greater the perceived behavioral control, the stronger should be an individual’s intention to perform the behavior under consideration” (p.188). Besides, the predictive ability of these three antecedents on intention might be dependent on different behaviors and situations (Ajzen, 1991). Thus, researches may found various results of the impact of these three antecedents on intentions. For example, some researchers only found attitudes and perceived behavioral control have impact on intentions.
In a general way, intentions are assumed to indicate how hard a person is willing to try to
perform the behavior. The performance depends on how strong the intention causes an
individual to engage oneself in that behavior (Ajzen, 1991). However, perceived behavior
control likewise takes a pivotal position in this relationship. For example, a person has always
dreamt (attitude) to run an ice-cream shop (intention). He has been working in the ice-cream
shop of his uncle, which could have provide him a good experience --- which might be good
socializing to be a successful seller, or a bad experience --- which might be not able to handle
the stress of many customers (perceived behavioral control). These experiences will influence
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how hard this person tries to start an ice-cream shop (behavior). As Ajzen (1991, p.181) states
“a behavior intention can find expression in behavior only if the behavior in question is under volitional control”. The non-motivational factors (available resources and/or availability of the requisite opportunities) represent a person’s actual control over the intended behavior (Ajzen, 1991). Thus, the non-motivational factors display, to some extent, the likelihood of a person to achieve that intended behavior. For example, the person who dream to run an ice-cream shop of the former example cannot find affordable location suitable for his budget, hence he cannot turn his intention to behavior as his non-motivational factors is not under volitional control.
Moreover, the perceived behavioral control, together with behavioral intention can be used directly to predict behavioral achievement (Ajzen, 1991). This presumed impact is explained by two rationales. First, holding intention constant, the perceived behavioral control is likely to increase the degree of effort of an individual to achieve the behavior successfully (Ajzen, 1991, 2002). For example, two people with equally strong intention to learn ski, one may persevere to learn ski than the other, due to their self-confidences to master this activity. The person with a higher confidence may master how to ski, and the person who doubts about his/her own ability may give up learning skiing. The perceived behavioral control of this two people leads them to different effort expending, thus, different behavioral result. The second rational is that perceived behavioral control can often be used as a substitute for a measure of actual control.
This depends on the accuracy of the perception of information about the behavior. In other words, without familiar elements in that situation, perceived behavioral control may not be realistic (Ajzen, 1991, 2002).
Therefore, the perceived behavioral control, under certain condition, can be used to predict the
probability of a successful behavioral intention (Ajzen, 1985); and it is expected to be more decisive
for action, while social norms and attitudes towards that behavior influence intention (Autio et al.,
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2001).
Perceived behavioral control takes an important position in the theory of planned behavior.
Besides, the perceived behavioral control is most compatible with Bandura’s (1977, 1982) concept of perceived self-efficacy, which “is concerned with judgments of how well one can execute courses of action required to deal with prospective situations” (Bandura, 1982, p. 122).
Importantly, Ajzen (1991) has demonstrated that perceived behavioral control differs greatly from Rotter’s (1966) concept of perceived locus of control, which is a generalized expectancy that remains stable across situations and forms of action, i.e., a person may believe his/her outcomes are determined by his/her own behavior (inter locus of control) (Ajzen, 1991).
Whereas, perceived behavioral control usually varies across situations and actions, i.e., this person may also believe his/her chances of becoming a president of a country are very low (low perceived behavioral control). A more explicit interpretation from Ajzen (2002, p668) is “the term ‘perceived behavioral control’ should be read as ‘perceived control over performance of a behavior’ ”.
Recent studies have point out two components of perceived behavior control, which are
self-efficacy (dealing largely with the ease or difficulty of performing a behavior) and
controllability (the extent to which performance is up to the actor). These two components,
used together or each on itself, have a different impact on the prediction of intentions and
behaviors. For instance, the recent studies which use empirical tests show that perceived
self-efficacy improves prediction of intentions, but perceived controllability has no significant
effects on intentions. And only two cases showed that the perceived self-efficacy improves
prediction of behaviors, only one case shows that controllability improves the prediction of
behavior. Therefore, Ajzen (2002) states that “depending on the purpose of the investigation, a
decision can be made to aggregate over all items, treating perceived behavioral control as a
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unitary factor, or to distinguish between self-efficacy and controllability by entering separate indices into the prediction equation” (p.680).
With the understanding of the above sections, the interpretation of career choice based on theory of planned behavior is: the intention of an individual to become self-employed or employee is influenced by three factors—the first factor is the individual‘s attitude towards to becoming self-employed or an employee, which means the degree to which the individual has favorable or unfavorable evaluation towards to be self-employed or employee; the second factor is the perceived reaction/attitudes/opinion of the individual’s important people in his/her lives on self-employment.; the third factor is the perceived ease or difficulty of an individual to be self-employed or an employee.
2.1.3 Determinants of entrepreneurial intention.
Recent studies have examined several determinants of individual’s entrepreneurial intention, such as personalities and traits. Mathew & Moser (1996) have examined gender differences on entrepreneurial intention. The results show that males are more interested in owning a company than females. Zhao et al. (2005) investigated the effect of self-efficacy on entrepreneurial intention, they found a positive relationship. Krueger (1993) has found a positive relation between prior exposures to entrepreneurial activities and entrepreneurial intention. Among these determinants, it is not difficult for researchers to associate entrepreneurial education as one of the determinants as well, since education can promote individual’s skills, knowledge and motivation (Cho, 1998).
There are previous studies which show that entrepreneurial education has a connection with entrepreneurial activities (Galloway & Brown, 2002; Henderson & Robertson, 2000).
Dyer (1994) suggested that specialized entrepreneurial education may provide people with
confidence to start their own company. Peter & Kennedy (2003) proved that entrepreneurship
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education programs can encourage people to start their own business. Gorman et al., (1997) says that entrepreneurship can at least be encouraged through education. All these above statements are pointing at one direction that is entrepreneurial education may influence people’s psychological factors, thus influence people’s entrepreneurial intention. Consequently, the question--- what is entrepreneurship education? & how it can influence entrepreneurial intention? ---will be introduced in the following sections.
2.2 Entrepreneurship Education
There are different scholars who provide various definitions for entrepreneurial education.
In this study, four different definitions are provided below, for they have been cited in other researches.
i. Shepherd and Douglas (1997) propose a definition which says: “The essence of entrepreneurship is the ability to envision and chart a course for a new business venture by combining information from the functional disciplines and from the external environment in the context of the extraordinary uncertainty and ambiguity which faces a new business venture. It manifests itself in creative strategies, innovative tactics, uncanny perception of trends and market mood changes, courageous leadership when the way forward is not obvious and so on. What we teach in our entrepreneurship classes should serve to instill and enhance these abilities”
(Solomon, 2007, p. 169).
ii. Jones and English (2004) provide a definition as: “the process of providing
individuals with the concepts and skills to recognize opportunities that others have
overlooked and to have the insight, self-esteem and knowledge to act where others
have hesitated” (p. 416).
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iii. Politis (2005, p. 401) defined entrepreneurial education as ‘a continuous process that facilitates the development of necessary knowledge for being effective in starting up and managing new ventures’.
iv. Martinez et al. (2010, p. 11) define entrepreneurship education “as the building of knowledge and skills ‘about’ or for ‘the purpose of” entrepreneurship generally, as part of recognized education programs at a primary, secondary or tertiary-level educational institution”.
Through these definitions, we can conclude that entrepreneurship education is mainly about the entrepreneurial ability triggered by various, entrepreneurial relevant, learning program (i.e. lectures), inspiring activities, and necessary resources (Souitaris et al., 2006).
During the past 50 years, entrepreneurship education is growing rapidly from a single course offering to a varying range of educational program at more than 1,500 colleges and universities all over the world (Charney & Libecap, 2000; Solomon, 2007). For example, Solomon and Fernald (1991) show that in the United States, the number of new degree programs in entrepreneurship grew an increase of 428 percent, which is from 25 in 1979 to 107 in 1986.
In Europe, in order to encourage the move from the manager economy to the entrepreneurial economy (Thurik & Wennekers 2004), policy makers are arguing that entrepreneurship education must be at the core of any nation’s education policy (Sánchez, 2013). A recent survey also shows in 164 important business schools, 42 percent of them had established specific centers for entrepreneurship (Wilson 2004). As these facts show, entrepreneurship education raise the interests of the empirical world with no doubts (i.e.
Gorman et al., 1997; Peterman and Kennedy, 2003; Souitaris et al., 2006; Solomon, 2007;
Oosterbeek et al., 2009; Muofhe, et al., 2011; Zhang, et al., 2013; Sánchez, 2013; Bae, et al.,
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2014 ). Nevertheless, Kuratko (2005) doubts about whether entrepreneurship can be taught.
Solomon (2007), however, argues that entrepreneurship can be taught, the issue is that: what should be taught and how should it be taught.
Souitaris et al. (2006) did research on offerings in major universities and on descriptions of entrepreneurship programs in existing literatures. They suggest that a qualified entrepreneurship education program should offer activities which consist of four components---“1. a ‘taught’ component, with one or more modules; 2. a ‘business-planning’
component, which can include business plan competitions and advice on developing a specific business idea; 3. an ‘interaction with practice’ component, which can include talks from practitioners and can includes networking events; 4. a ‘university support’ component, which can include market-research resources, space for meetings, a pool of technology with commercial potential and even seed funding to student-teams” (Souitaris et al., 2006, p.574).
Further, Souitaris et al. (2006) proposed that entrepreneurship education consist of three parts:
learning, inspiration and incubation resources. This proposition has been applied by Sánchez (2013) to test impact of entrepreneurial education on entrepreneurial intention as well.
Following this line of logic, this study divides entrepreneurship education as following:
i. Courses
Basically, all education programs offer students different courses. So do entrepreneurship
educations. Solomon (2007) mentioned some facts about the fast growing speed of
entrepreneurship courses all over the world. For instance, in 1985, 253 colleges or universities
offered courses in small business management or entrepreneurship; in 1993, 441
entrepreneurship courses were available to interested students (Gartner & Vesper, 1994). So far,
many studies describe entrepreneurship education as relevant courses, which are offered by
colleges or universities (von Graevenitza et al., 2010). Therefore, courses are prerequisite
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components of entrepreneurship education.
ii. Inspiration
As Thrash & Elliot (2003), a psychology literature suggested: inspiration is characterized by evocation, motivation, and transcendence. Inspiration is evoked rather than initiated directly through an act of will or arising without apparent cause. It can be triggered by a person or idea.
Second, inspiration implies motivation which means it involves the energization and direction of behavior (i.e. a personal goal) (Elliot, 1997). Lastly, inspiration involves transcendence of the ordinary preoccupations or limitations of human agency. All three characteristics have been identified explicitly or implicitly by theorists across disciplines (Bowra, 1955; Bradley, 1929;
Carpenter, 1987; Hart, 1998). Thrash & Elliot (2003, p.872) suggested a definition for inspiration: “a motivational state evoked by a revelation (trigger) and directed toward the conversion of transcendent, revealed knowledge into a work of art, a text, or some other concrete form (target)”. Other researches revealed that inspiration can be understood and operationalize as what cause the inspiration (trigger) and what is inspired to do (target) (Souitaris et al., 2006). Therefore, in this research, entrepreneurial inspiration, which evokes students’ mind toward considering to becoming self-employed by events or inputs from successful entrepreneurs, can also be a component of entrepreneurial education.
iii. Incubation resources
Entrepreneurship education as a teaching program, which is offered by colleges or
universities, is a pool of resources that can help students to realize their business ideas
(Souitaris et al., 2006). For instance, students can ask their lecturers and classmates to evaluate
their business idea; or organize a competition for business planning. And through the
networking evens, students may get connect to investors or referrals. Moreover, resources like
laboratory, library and seed funding can even provide more help for student to reach their
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business idea (Souitaris et al., 2006). Therefore, resources related to support entrepreneurship which is offered by the university should be take into account for entrepreneurship education.
2.3 Entrepreneurship Education and Entrepreneurial Intention
According to the human capital theory, individuals with a higher level of competencies will achieve generally better results than those who have a lower level of competencies (Sanchez, 2013; Ployhart & Moliterno, 2011). Following this logic, many researchers have proposed that entrepreneurship education has impact on entrepreneurial intention. Though, results from these previous studies are still contradictory to each other. The impact of entrepreneurship education on people’s intention towards entrepreneurship is still in the exploratory stage (Byabashaija & Katono 2011).
Zhang et al. (2013) tested whether entrepreneurial education directly has impact on entrepreneurial intention among Chinese students, the result is confirmed. Students who had entrepreneurship education tend to have more favor to start their own business in the future. “In other words, taking entrepreneurship education can stimulate entrepreneurial intention and improve the probability of this intention-making” (Zhang et al., 2006, p.637). Sánchez (2013) used a pretest-posttest quasi-experimental design, drawn on the theory of planned behavior, they confirmed that students’ intention toward self-employment increases after taking an entrepreneurship education program. The same method has been used by Souitaris et al. (2006) to examine the attitudes and intention of students who followed entrepreneurship education.
Souitaris et al. (2006) concluded that taking an entrepreneurship education program increases
the overall intention and some attitudes toward entrepreneurship. Fayolle et al. (2006) also
conclude that there is a relationship between following an entrepreneurial education program
and entrepreneurial intention.
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However, there are recent studies, Oosterbeek et al. (2009) and von Graevenitza et al.
(2010), reject this relationship. Oosterbeek et al. (2009) analyzes the impact of the leading entrepreneurship education program, which is in the Netherlands, on entrepreneurial competencies and intentions. By using an instrumental variables approach in a difference-in-differences framework, they concluded that there is no intended effect after taking the program. Von Graevenitza et al. (2010) used data from a compulsory entrepreneurship course of a German University, to test ex-ante and ex-post-survey responses from students.
They found that intentions decrease after taking the course, but that self-assessed skills are significant positive.
The underlying result of the studies named above is that the impact of entrepreneurship education on entrepreneurial intention needs detailed further investigation, which may need more specific variables and a larger sample size. Peterman and Kennedy (2003, p. 130) suggest that “researchers need to develop credible methods of testing preconceived hypotheses, using control groups and large sample sizes” in order to provide convincing evidence to prove that entrepreneurship can be influenced by entrepreneurship education program (Peterman and Kennedy, 2003). From the above, Hypothesis 1 is developed below:
Hypothesis 1: Students, who participated in an entrepreneurship education program, are more likely to have entrepreneurial intention than non-participants.
2.4 Entrepreneurship Education, Theory of Planned Behavior and Entrepreneurial Intention
Based on the theory of planned behavior, entrepreneurial intention is proposed to be
determined by attitude toward entrepreneurship, perceived behavioral control and subjective
norms. Further these determinants are affected by exogenous influences, such as education.
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This proposition has been applied in the field of entrepreneurship for decades, it is based on a robust theoretical framework of the theory of planned behavior to assess the impact of entrepreneurship education on entrepreneurial intention (Fayolle et al., 2006). However, most previous researches have studied the relationship between entrepreneurial education and entrepreneurial intention. Krueger & Brazeal (1994) suggested that there is a positive effect from entrepreneurial education on perceived desirability by increasing knowledge and confidence. Souitaris et al. (2006) proposed that entrepreneurial education leads to higher attitude toward entrepreneurship, subjective norm, perceived behavioral control and entrepreneurial intention, but they only confirmed the relationship of entrepreneurship education (exogenous influence) on attitudes and intentions towards entrepreneurship. Gorman et al. (1997) confirmed that more empirical evidence for supporting these theoretical claims are needed. Therefore, this study is going to provide empirical testing on the relationship of entrepreneurship education, theory of planned behavior and entrepreneurial intention.
However, as discussed in section 2.1.3, the second factor of the theory of planned behavior is perceived social norms, which means that the perceived reactions/attitudes/opinions of the individual’s important people in his/her lives on self-employment. Entrepreneurship education, in this study, is the individual participated in relevant entrepreneurial courses, inspiration activities and used university resources. Thus, in this study, perceived social norm has no connection with individual’s entrepreneurship education. Therefore, the following hypotheses are proposed:
Hypothesis 2a: Students who participated in an entrepreneurial education program are more likely to have a higher perceived behavioral control than non-participants.
Hypothesis 2b: The higher the perceived behavioral control, the more the students are
likely to have entrepreneurial intention.
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Hypothesis 2c: Participation in an entrepreneurial education program indirectly influences entrepreneurial intention through perceived behavioral control.
Hypothesis 3a: Students who participated in an entrepreneurial education program are more likely to have higher attitudes toward entrepreneurship than non-participants.
Hypothesis 3b: The higher the attitudes toward entrepreneurship the more the students are likely to have entrepreneurial intention.
Hypothesis 3c: Participation in entrepreneurial education program indirectly influences entrepreneurial intention through attitudes toward entrepreneurship.
2.5 Effects of Different Content of Entrepreneurship Education on Entrepreneurial Intention
If entrepreneurship education can teach people entrepreneurship, then what should be taught and how should it be taught (Solomon, 2007)? As mentioned in section 2.2, Souitaris et al. (2006) has defined entrepreneurial education into three different categories, namely---courses, inspiration activities, incubation resources. The result of Souitaris et al.
(2006) only confirmed that inspiration activities correlated with an increase in entrepreneurial attitudes and intentions, all else are rejected. In order to further study about what should be taught and how entrepreneurship should be taught, this study is going to investigate whether these categories have impact on entrepreneurial intention through attitude towards entrepreneurship and perceived behavioral control. Therefore, hypotheses 4-9 are developed as below:
Hypothesis 4a: Students who have taken entrepreneurial courses are more likely to
have a higher perceived behavioral control than non-participants.
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Hypothesis 4b: Participation in entrepreneurial courses indirectly influences entrepreneurial intention through perceived behavioral control.
Hypothesis 5a: Students who have taken entrepreneurial courses are more likely to have higher attitudes toward entrepreneurship than non-participants.
Hypothesis 5b: Participation in entrepreneurial courses indirectly influences entrepreneurial intention through attitude toward entrepreneurship.
Hypothesis 6a: Students who have participated in entrepreneurial activities are more likely to have a higher perceived behavioral control than non-participants.
Hypothesis 6b: Participation in entrepreneurial activities indirectly influences entrepreneurial intention through perceived behavioral control.
Hypothesis 7a: Students who have participated in entrepreneurial activities are more likely to have higher attitudes toward entrepreneurship than non-participants.
Hypothesis 7b: Participation in entrepreneurial activities indirectly influences entrepreneurial intention through attitudes toward entrepreneurship.
Hypothesis 8a: Students who have used university resources of are more likely to have a higher perceived behavioral control than non-participants.
Hypothesis 8b: Usage of university resources indirectly influences the probability of having entrepreneurial intention through perceived behavioral control.
Hypothesis 9a: Students who have used resources offered by university are more likely to have higher attitudes toward entrepreneurship than non-participants.
Hypothesis 9b: Usage of university resources indirectly influences the probability of
having entrepreneurial intention through attitudes toward entrepreneurship.
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2.6 Conceptual Model
Figure 3 Conceptual Models Hypothesis 1
Hypothesis2a-2c
Hypothesis 3a-3c
Hypothesis 4a-4b
Hypothesis 5a-5b
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Hypothesis 6a-6b
Hypothesis7a-7b
Hypothesis 8a-8b
Hypothesis9a-9b
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3. Data Description & Methodology
3.1 Data
Global University Entrepreneurial Spirit Students´ Survey 2011(GUESSS, 2011) is taken as the secondary data for this study. GUESSS is an international research project which focuses on (1) entrepreneurial intentions and activities of students, (2) identification of antecedents and boundary conditions in the context of new venture creation and entrepreneurial careers in general, (3) observation and evaluation of Universities' activities and offerings related to the entrepreneurial education of their students (GUESSS, 2011)
1.
The survey of GUESSS (2011) covered 26 countries, 489 universities and 93,265 respondents. This study includes 7 west European countries, 193 universities and 40388 respondents (See table 1).
Table 1 Countries, universities and respondents
Country Number of Universities Respondents
Belgium 11 188
Luxembourg 2 444
France 17 1'498
Austria 17 4'553
Switzerland 44 8'115
Germany 46 12'469
Netherlands 56 13'121
TOTAL 193 40388
1 For more information about GUESSS (2011), refer to the GUESSS website: http://www.guesssurvey.org
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3.2 Sample
The average age of respondents in the sample is 24.8 years and the median age is 24 years.
Overall, 54.5% of the total respondents are female and 45.5% of all respondents are male. As shown in figure 4, the majority of respondents belong to the age group of “20-25 years”. This can be explained by figure 5 current level of study. Most respondents in the sample are undergraduate and graduate students, which cover more than 94% of all respondents.
Figure 4 Age distribution of the sample divided by gender
Figure 5 Current level of study
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
up to 19 years 20-25 years 26-30 years 31-40years 41+years
Female male
65,6%
29,2%
4,1%
0,8%
0,3%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Undergraduate
Graduate
PHD
Post doc
MBA
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Figure 6 Employment statuses of parents of respondents
In terms of current employment status of parents, see figure 6, 73% of all respondents have parents which are both employed by an employer, 27% of all respondents have at least one parent is self-employed or have majority ownership of a company. Zellweger et al. (2011) mentioned that families with business background may influence employment choice of their offspring.
Regarding of entrepreneurial intentions of students, right after their studies, about 6% of the respondents who did not participated in entrepreneurship education program have entrepreneurial intentions. Meanwhile, around 10% of the respondents who did participate in entrepreneurship education program intend to be self-employed (see figure7). To further check the differences, t-test is used (as table 2 shows), the mean of entrepreneurial intention of participants (M=0.1, SD=0.24) is significantly different and higher than the mean of the non-participants (M=0.06, SD=0.29, t(40388)= 12.67, p<0.000), which indicates there is a significant difference in entrepreneurial intention for participants and non-participants.
Moreover, the rate of entrepreneurial intention five years after studies grows to 39% with respect of respondents who participated in entrepreneurship education. 26% of all non-entrepreneurship education participants choose to become self-employed five years after
73%
15%
7%
5%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Employee
Father self employed
Both parents self-emplyeed
Mother self employed
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39%
26%
61%
74%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Participants Non-participants
Entrepreneurial intention No entrepreneurial intention
finishing their studies (see figure 8). Further, table 3 indicates there is a significant difference between entrepreneurial intention of entrepreneurship education participants (M=0.39, SD=0.487) and non-participants (M=0.26, SD=0.436, t(40388)= 27.84, p<0.000).
However, if participation in an entrepreneurship education program really contributes for entrepreneurial intention is still not convincing. Chapter 4 will provide clear knowledge about the relationship between entrepreneurship education and entrepreneurial intention.
Figure 7 Percentage of participants following an entrepreneurship program and non-participants who have entrepreneurial intention right after their studies
Figure 8 Percentage of participants following an entrepreneurship program and non-participants who have entrepreneurial intention 5 years after their studies
10%
6%
90%
94%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Participants Non-participants
Entrepreneurial intention No entrepreneurial intention
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Table 2 T-test for participants following an entrepreneurship education program (EEP) and non-participants who has entrepreneurial intention (EI) right after study
Mean Mean
difference
Standard deviation
Sig.
EI of non-participants 0.06 0.034 0.24 p<0.000
EI of participants 0.1 0.034 0.29 p<0.000
Table 3 T-test for participants following an entrepreneurship education program (EEP) and non-participants who have entrepreneurial intention (EI) five years after study
Mean Mean
difference
Standard deviation
Sig. (two tailed) EI of non-participants 0.26 0.132 0.436 p<0.000
EI of participants 0.39 0.132 0.487 p<0.000
3.3 Measures
23.3.1 Entrepreneurial Intention
Two dependent variables are constructed in this study, for the questions which measure entrepreneurial intention are: 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?” Along with each independent variable, there are four answers: (1) Employee, (2) Founder, (3) Successor, (4) others. As explained earlier in the theory section, entrepreneurial intention can be seen as business founder or owner. Therefore, both dependent variables are transferred into dummy variables, value 1 and value 0. Value 1 indicates respondents who chose founder or successor. Value 0 means respondents chose employee or others.
2 More information about variable description, please see Appendix 1.
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3.3.2 Mediators.
3.3.2.1 Attitude towards entrepreneurship
The measures of attitude toward entrepreneurship in GUESSS (2011) are inspired by the study of Linan & Chen (2009). Therefore, following GUESSS (2011), this study has measured attitude toward entrepreneurship by four items through a 7-point Likert-scale (from 1= strongly disagree to 7=strongly agree). Respondents were asked to indicate their level of agreement on four different statements. These statements evaluate their attitudes toward their own evaluation they feel it is to be an entrepreneur (i.e. founding a company, buying one, or succeeding in the parents' company). Cronbach’s alpha of this scale is 0.92, which is >0.60. Therefore, the variable is calculated as the average score of the four items.
3.3.2.2 Perceived Behavioral Control
GUESSS (2011) provides locus of control (belief of having a control over the behavior or
over the extent to which performing the behavior is up to the actor) and self-efficacy (ease or
difficulty of performing a behavior) as measurements for perceived behavioral control. As
discussed in chapter 2, studies can choose to use these two measurements alone or together. In
this study, perceived behavioral control is measured by self-efficacy, which shows the
individuals’ perception of the ease or difficulty of becoming an entrepreneur. Respondents were
asked to evaluate their level of certainty in twelve different tasks which related to their
perception of ease or difficulty for completing the tasks. The level of certainty is given as a
7-point Likert-scale ranging from 1=completely unsure to 7=completely sure. Cronbach’s alpha
of this scale is 0.87
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65% 35%
0% 20% 40% 60% 80% 100%
Participants Non-participants
3.3.3 Participation in an entrepreneurship education program.
According to GUESSS (2011), questions about whether respondents participate in an entrepreneurship education program is decided by a question asking if they have attended any entrepreneurship related university offerings. These offerings are divided into three categories, namely: lectures and seminars, networking and coaching offerings, provision of resources. And each of the categories has few options to choose, with answers “yes” or “no”. In this study, if the respondents attended at least one of the offerings of university, no matter which category, it is assumed that they have participated in entrepreneurship education program.
Specifically, the independent variable---participation in an entrepreneurship education program is analyzed as a dummy variable with value 0 and value 1. Value 0 takes the meaning that respondents did not attend any of the entrepreneurship related university offerings. The underlying meaning of value 1 is that respondents answered at least one “yes” among all the entrepreneurship related university offerings (see figure 9).
Figure 9 the percentage of participants in entrepreneurship education program
3.3.3.1 Participation in entrepreneurial courses.
In this study, participation in entrepreneurial courses is analyzed as a dummy variable with value 0 and value 1. Value 0 takes the meaning that respondents did not attend any of the courses. The underlying meaning of value 1 is that respondents answered at least one “yes”
among all the courses.
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3.3.3.2 Participation in relevant entrepreneurial activities.
In this study, participation in relevant entrepreneurial activities is analyzed as a dummy variable with value 0 and value 1. Value 0 takes the meaning that respondents did not attend any of the relevant entrepreneurial activities. The underlying meaning of value 1 is that respondents answered at least one “yes” among all the relevant entrepreneurial activities.
3.3.3.3 Usage of university resources
In this study, usage of university resources is analyzed as a dummy variable with value 0 and value 1. Value 0 takes the meaning that respondents did not used any of the resources offered by university. The underlying meaning of value 1 is that respondents answered at least one “yes” among all the resources offered by university.
3.3.4 Control Variables.
In this study, age, gender, parental employment status and nation are chosen as control variables. To examine how control variables affect entrepreneurial intention, the chosen variables can provide better understanding about the influencing factors of entrepreneurial intention.
Age is chosen to be one of the control variables, for the reason that researches have shown that “middle aged” people are more likely to set up their business than young people who lack experience (Taylor, 2004; Carrasco 1999). Age is measured as a continuous variable.
According to OECD (2008b), females are less self-employed than males. In this study gender is
measured by dummy variables--- 0 is male, 1 is female. Finally, the parental employment
status indicates that the intention of respondents to become an entrepreneur is influenced by
employment status of their parents. Previous studies have noted that people with self-employed
parents are more likely to become an entrepreneur, for the reason that they often have the
chance to inherit an existing business, they have more awareness of business and they have
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resources for starting a business. However, there are also negative views, such as having unhappy experiences about business and being too rich too have motivation to start a business.
This study is examined the influence of parental employment status by dummy variable value 0 means none of respondents’ parents is self-employed, value 1 means at least one of the parents of respondents is self-employed.
In terms of nation as control variables, in this study each nation is recoded into dummy variables: nation Germany (1=Germany, 0=other countries); nation Switzerland (1=Switzerland, 0=other countries); nation Austria (1=Austria, 0=other countries); nation Belgium (1=Belgium, 0=other countries); nation France (1=France, 0=other countries); nation Luxemburg (1=Luxemburg, 0=other countries). As noted, the Netherlands is not included in the dummies mentioned above. In this study, the Netherlands has been chosen to be the reference group, for the Netherlands has the most respondents among all 7 countries (see table 1).
Another reason is that if all 7 countries were included, this would create not only a situation of multi-collinearity, but also there is nothing with the value of zero to compare each of the other categories. Therefore, the Netherlands becomes the reference group which is used to assess the effects of the other nations. The results can be interpreted as the difference between each nation and the Netherlands.
3.4 Methodology
In this study, mediation methodology is applied. This is done for the reason that one of the main purposes of this study is to test if the independent variable (entrepreneurship education) influence the dependent variable (entrepreneurial intention) through mediators (attitude toward entrepreneurship and perceived behavioral control) or potential intervening variables (Preacher
& Hayes, 2008a). Moreover, in order to test the influence of mediators respectively, a simple
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mediation model has been chosen. In terms of statistical technique, linear regression and logistic regression have been applied in this study, and due to the character of dependent variables and the goal of this study. Additional, PROCESS macro, which was written by Hayes, A. F, has been applied to SPSS (Statistical Package for the Social Sciences) to run the tests.
3.4.1 Simple mediator model
3.
According to Preacher & Hayes, (2008a), mediation processes involving one mediating variable are called simple mediation. As figure 10A depicts, variable X is considered as causal variable which affects outcome Y. Path c represents the total effects of X on Y, this total effect can be measured by regressing Y on X alone (Hayes, 2012), see equation (1).
Figure 10B shows X can influence Y directly as well as indirectly through a single mediator M (Hayes, 2012). The direct and indirect effect of Variable X can be estimated by two models, one is X affects M through path a, see equation (2), and the other model is to estimating Y by regressing Y on both X and M, see equation (3) (e.g., Baron & Kenny, 1986;
Judd & Kenny, 1981; MacKinnon, Fairchild, & Fritz, 2007; Preacher & Hayes, 2004; Hayes, 2012). In equation (3), c’ is the direct effect of X on Y. The coefficient of path a multiply the coefficient of path b is called indirect effect, see figure 10B, equation (2) and (3). Path a represent the effect of X on M, path b is the effect of M on Y controlling for X. The perfect mediation effect is defined as c = c’ + ab, or ab = c – c’. Thus, the indirect effect of X on Y through M is the difference between total effect and direct effects of X. When c>c’, we can say partial mediation occurs.
In terms of this study, variable X represents 1) participation of entrepreneurial education program; 2) participation of entrepreneurial courses; 3) participation of relevant entrepreneurial
3 For more information about the simple mediator model please refer to Hayes (2012).
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activities; and 4) Usage of university resources. Variable Y represents 1) entrepreneurial intention right after study, 2) entrepreneurial intention five years after study. Mediator M represents 1) perceived behavioral control, 2) attitudes toward entrepreneurship.
Figure 10 Mediation process A
Y=
∗+ +
∗(1)
B
M = + + (2) Y = + + + (3)
Source: Mallinckrodt et al. (2006); Hayes (2012).
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3.4.2 PROCESS
4.
PROCESS is a computation tool for SPSS for statistical mediation and moderation, and conditional process analysis. It is written by Andrew. F. Hayes, Professor of Quantitative Psychology at the Ohio State University.
PROCESS is based on the path analytical framework which uses ordinary least square regression or logistic regression to compute direct and indirect effect in simple and multiple mediation models. It provides researchers an easy way to conduct tasks, for the reason that PROCESS encompass many capabilities of popular procedures and tools that already known, such as SOBEL, INDIRECT, MODPROBE, MODMED and RSQUARE, and MBESS (Hayes, 2012).
Besides, PROCESS not only provides all needed coefficients for regression analysis (see a, b, c’, c of equation 1, 2, and 3), but also directly provides coefficient of indirect effect with asymmetric bootstrap confidence intervals, which can provide the significant level of indirect effect and avoid the prediction of the mediation effect only based on the path test (Hayes, 2012).
To interpret the result from PROCESS, coefficient of a, b, c’, and c is needed as well as the upper level confidence interval and lower level confidence interval of indirect effect. The confidence intervals can be used to prove that the indirect effect ab is happening significantly, which is no zero included between both intervals.
4 For more information please check http://www.processmacro.org/.
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4. Results
Means, standard deviation and Pearson correlation of variables are presented in appendix 2 to 9. Since all the correlations of all variables are below the 0.6 cut-off, there is no suffering of shared variance of the data. Further, the VIF (variance inflation factor) is calculated. All values are below the critical cut-off of 10 (Hair et al., 2006), suggesting that multicollinearity is not a concern. For the mediation effect testing, the bootstrap sample for bias corrected bootstrap is 5000 with a 95% confidence interval.
Two main sections are made to provide results: 1) the results of entrepreneurial intention right after completing a study; 2) the results of entrepreneurial intention five years after completing a study. In each main section, sub-sections are written on the topic of each independent variable. The results are shown below. Tables with the SPSS results are presented at the end of each section.
4.1 Entrepreneurial intention right after completing a study
4.1.1 Participation in entrepreneurship education program.
As table 4 (page 35) indicates, the relationship between participation in entrepreneurship
education program and entrepreneurial intention right after study is positive and significant
(r=0.059, p<0.000). Table 5 also indicates that participation in entrepreneurship education
program has a positive and significant effect on the probability of having an entrepreneurial
intention right after finishing study (β=0.446, p < 0.000). In addition, exp(β)= 1.562>1, which
means the probability of respondents who participated in an entrepreneurship education
program and have entrepreneurial intention is about 1.6 times higher than of non-participants.
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