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The effect of business and economics education programs on

students’ entrepreneurial intention

Justo De Jorge-Moreno Business Science Department, University of Alcalá, Madrid, Spain

Leopoldo Laborda Castillo Institute of Latin American Studies, University of Alcalá, Alcalá de Henares,

Spain, and

Marı́a Sanz Triguero Business Science Department, University of Alcalá, Madrid, Spain

Abstract

Purpose – This paper aims to evaluate the effect of participation in business and economics education programs on the student’s entrepreneurial intention in terms of perceptions of the desirability and personal feasibility of starting a business.

Design/methodology/approach – The methodology used to measure the student’s entrepreneurial intention is the data envelopment analysis (DEA). This approach involves mathematical programming and as a new tool in this field has permitted enrichment of the results achieved.

Findings – Results reveal that the explanatory factors for both types of students are different. This could be explained because the students choose one career or another according to their expectations of employment. In this sense, the student’s entrepreneurial intention decreases in the business students when they progress in their studies and they are closer in contact with the business reality. However, the student’s entrepreneurial intention increases in the case of business students when they choose a future work option different to work in public administration.

Research limitations/implications – Although the work reaches conclusive findings, further research is required in a longitudinal way.

Practical implications – The article provides new methodology and results in the field of entrepreneurship and employability in higher education in Spain.

Originality/value – In the context of the theory of planned behavior, the article is innovative on a methodological level in arguing for “connected” perceptions of the desirability and personal feasibility of starting a business with an approach toward employability and enterprise development for students. The authors think that the understanding of the sources of “entrepreneurial intention” at the students’ level is crucial for policymakers to develop appropriate educational polices to improve entrepreneurship performances.

Keywords Entrepreneurial intention, Education programs, Students, Self-employment

Paper type Research paper

1. Introduction Some studies have shown that entrepreneurship education plays a significant role in cultivating entrepreneurship spirit among graduates. Based on a study done by Kolvereid and Moen (1997), it is shown that those students who have taken a major in

The current issue and full text archive of this journal is available at

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Received 29 April 2011 Revised 16 September 2011 Accepted 14 November 2011

European Journal of Training and Development

Vol. 36 No. 4, 2012 pp. 409-425

q Emerald Group Publishing Limited 2046-9012

DOI 10.1108/03090591211220339

entrepreneurship have revealed greater interest in becoming entrepreneurs; and these students act more entrepreneurial than other students in taking up the challenge to start up a new business. Thus, it is suggested that although it may not be possible to develop entrepreneurship from education exclusively, to a certain extent, education has an effect to alter and contribute to the formation of entrepreneurship.

Nevertheless, the extent to which entrepreneurship is teachable, or even worth teaching, is a matter of debate among scholars (Fiet, 2000). Recently it has become clear that entrepreneurship, or at least certain elements of it, can be taught – entrepreneurs are not just born but can also be made (Henry et al., 2005a, b). Therefore, this leaves room for entrepreneurship education and training attempting to develop and promote those “reachable” facets associated with entrepreneurship.

In general terms, the contribution of entrepreneurship to the world economy is well recognized; nevertheless, there is still debate about if we can teach students to become entrepreneurs (Fiet, 2000; Moro et al., 2003). The European Commission (2004) posits that entrepreneurship is one of the key components to be included in current educational systems in order to prepare people for successful participation in society.

The change that is occurring in the EHEA (European Higher Education Area) could be a good opportunity to advance in the creation of leaders with the skills and attitudes to be entrepreneurial in their professional lives. In this context, the primary purpose of entrepreneurship education should be to develop entrepreneurial capacities and mindsets. But, entrepreneurship education programmes can have different objectives, such as:

. developing entrepreneurial drive among students (raising awareness and motivation);

. training students in the skills they need to set up a business and manage its growth; and

. developing the entrepreneurial ability to identify and exploit opportunities.

If so, questions that need to be answered are: What should be taught? How should it be taught? How should entrepreneurship education be assessed? (Fayolle, 1998; Moro et al., 2003).

From one side, the debate addresses the problem of a lack of uniformity in course content and lack of theoretical rigor (Falkang and Alberti, 2000; Fiet, 2000a). Authors such as Sexton and Bowman (1984) point out that there is a lack of accepted theories of entrepreneurship and training. Certainly, entrepreneurship is considered a complex subject to study in the context of teaching and learning because it depends on the individual’s self-regulated actions and on characteristics that may not be easy to influence (Pihkala and Miettinen, 2002). However, it is believed that entrepreneurship can be taught, or at least certain features of it, through socialization and formal training as opposed to something genetically conceived (Kirby, 2002).

On the other side, the debate is still in place due to a lack of well-defined methods for assessing the effectiveness of entrepreneurship education (Moro et al., 2003; Falkang and Alberti, 2000). Most of the research has focused on course contents, pedagogical and audience characteristics.

To reduce this theoretical and methodological gap, we adopt the theory of planned behavior like an appropriate framework to develop our methodological approach, in order to achieve the objectives of this study. These objectives are twofold. First, we

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analyze the perceptions of the desirability and personal feasibility of starting a business using the concept of “entrepreneurial intention”. In particular, our goal would be to conduct a comparative analysis between students (considering the degree and career) to detect which students gain higher levels of “entrepreneurial intention” considering their intention to start a business and their motivation to carry out this action. Our hypothesis is that “entrepreneurial intention” probably decreases when the students progress in their studies and they are closer in contact with the business reality.

Second, the relationship between “entrepreneurial intention” measures and relevant socioeconomic variables by means of a Truncated regression analysis are explored. The understanding of the sources of “entrepreneurial intention” at the students’ level is crucial for policymakers to develop appropriate educational polices to improve entrepreneurship performances.

This paper is organized as follows; in section 2 we focus in the relevant literature entrepreneurial intention in order to have a theoretical background about this issue. In section 3 we show the methodology for evaluation of “entrepreneurial intention”, variables and data. We then present the estimation methodologies and results in section 4. We finish with the conclusions, limitations and extensions in section 5.

2. Theoretical background: assessing entrepreneurial intentions amongst students The classical empirical literature suggests that individuals’ attitudes are determined by “external or contextual factors” and “personality characteristics or personal background”.

Scott and Twomey (1988) analysed the ambitions of university students and the results of the study identified parental influence and work experience as significant factors. Parnell et al. (1995) in a cross-cultural study compared the entrepreneurial propensity of American and Egyptian university students and found that entrepreneurial propensity of American students was greater than Egyptian students (the entrepreneurial propensity was taken as a function of self-confidence, perceived level of education, and perceived opportunities). Begley et al. (1997) compared the role of socio-cultural factors in a four-dimensional model. This study indicated that only social status of entrepreneurs could be predicted as a factor to start a business. Autio et al. (1997) analyzed the entrepreneurship of university students through a process-based approach, the study checked the robustness of entrepreneurial intention in various cultural contexts and indicated that the image of entrepreneurs and encouragement from university environment affect the entrepreneurial conviction of university students. Lee et al. (2005) investigated in a cross-cultural study the differences in the attitudes of university students towards venture creation in four countries, the study revealed that each country should provide a customized entrepreneurship education to foster entrepreneurship considering their unique cultural contexts. The study of Lüthje and Franke (2003) revealed that the impact of attitude towards self-employment might be linked to two personality traits (risk-taking propensity and internal locus of control) and two contextual factors (perceived barriers and perceived support), the study also considered the impacts of both internal factors (motivation and self-confidence) and external factors (perceived level of education, opportunities and support) on entrepreneurial propensity of university students (the

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study found that two internal factors and perceived level of support were statistically significant factors). Veciana et al. (2005) tested the desirability, feasibility, and intentionality for entrepreneurship according to gender and entrepreneurial history of students in Spain and Puerto Rico.

Ang and Hong (2000) compared entrepreneurial spirits of university students in Hong Kong and Singapore. These authors concentrated specifically on the role of some personality characteristics (risk-taking propensity, tolerance for ambiguity, internal locus of control, innovativeness, and independence) and motivational factors (love for money, desire for security, and desire for status), rather than the differences in the contextual factors. Other interesting study was made by Henderson and Robertson (2000). These authors provided a useful insight into perception of young adult on entrepreneurship and show that the respondents perceived entrepreneurs mostly with their innate characteristics. Wang and Wong (2004) explained entrepreneurial interest of students in Singapore based on personal background. The study of these authors also reveals that gender, family business experience, and education level are significant factors in explaining entrepreneurial interest.

Turker and Selcuk (2009) combining personality characteristics and external factors, tested on a sample of 300 university students in Turkey. The entrepreneurial support model considers predominantly the impact of contextual factors on entrepreneurial intention. In the model, entrepreneurial intention is taken as a function of educational, relational, and structural supports. The results of the survey show that educational and structural support factors affect the entrepreneurial intention of students.

However, according to Basu and Virick (2008), the role of education in affecting attitudes, norms, perceptions of controllability, and behavior are not adequately explored in this variety of empirical studies.

In the context of Entrepreneurial intentions amongst students, Basu and Virick (2008) propose the theory of planned behavior like a more appropriate framework. The theory of planned behavior[1] argues that entrepreneurial intention is dependent on an individual’s attitude toward the desirability of an entrepreneurial career, subjective norms including perceived family expectations and beliefs to perform the behavior, and perceived behavioral control or the perceived ability to execute the intended behavior of entering entrepreneurship.

Using this framework, previous research indicates that: . entrepreneurship education can enhance an individual’s level of self-efficacy

(Wilson et al. 2007); . entrepreneurship education is strongly related to entrepreneurial intention, with

entrepreneurship majors expressing higher intentions to start their own businesses (Noel, 1998);

. entrepreneurship education can also increase students’ interest in entrepreneurship as a career (Dyer, 1994), and finally; and

. entrepreneurship programs significantly raised students’ subjective norms and intentions toward entrepreneurship by inspiring them to choose entrepreneurial careers (Souitaris et al., 2007).

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3. Methodology: research design, data and variables 3.1 Research design In the light of the theory of planned behavior, we proposed a new methodological approach to analyze the entrepreneurial intention of starting a business of university students. This methodology consists in three phases:

(1) In the first phase multivariate techniques are used, specifically factor analysis (FA), in order to simplify the data reducing the number of variables without a great loss of information and, at the same time, identifying the structure or dimensionality of the data. The first factor analysis allows us to capture information on the student’s perceptions of the desirability of starting a business (FA No. 1) while the second one obtains student’s perceptions of personal feasibility of starting a business (FA No. 2).

Questions based on the studies of Brockhaus and Nord (1979); Brockhaus (1980) were used. The four questions reflect: desire, intent to start their own business, and the effort they are willing to make for this purpose in terms of time and effort as well as savings involved in the project. The analysis was performed separately because the analysis of entrepreneurship intention efficiency in the next step will examine both groups of students together and separately.

(2) In the second phase, a frontier analysis is used to determine the “entrepreneurship intention efficiency frontier” using non-parametric DEA (Data Envelopment Analysis), based on the factors extracted in the first phase (FA No. 1 and FA No. 2) as outputs and the constant value input ( ¼ 1). The advantages of this technique, among others, lie in the possibility of making comparisons between students, high flexibility since there are no functional forms imposed on the data, and easy interpretation of results.

We made a model of Entrepreneurship intention efficiency based on Lovell and Pastor (1999). We specified the set of variables obtained by factor analysis FA No. 1 and FA No. 2 and the input equal to unity. In line with these authors we applied an output-oriented BCC model (Banker et al. 1984) with single constant input that shows that all that matters are the output values, i.e. the model can be considered as a pure output model. Each student wish to maximize their entrepreneurial attitude and psychological traits (motivation) y ¼ (y1, yr, . . . , yM) based on the level of the endowment of individual inputs, which in our case is constant and single unity (x ¼ 1) for all students. In this context, the measurement of technical Entrepreneurship intention efficiency with which students work under variable returns to scale can be estimated as follows:

Maxf

f; l

s:t: Yl $ Yofi

eTl ¼ 1;

l $ On

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Where e is an n £ 1 vector o 1s. Yo ¼ (Yo1. . .Yom) is an m x 1 output vector of the unit being evaluated, Y is an m x n matrix of outputs vectors (AF No. 1 and AF No. 2) of the n units (students) in the sample, l ¼ (l1 . . . .ln) is an n £ 1 vector of intensity variable, and n is the number of units in the sample. In this context, from a production perspective (benchmark) we argue that each student is by itself “the input” and, therefore, a single constant input was at hand (Lovell and Pastor, 1999, p. 49). These authors further proved that output-oriented BCC model with a single constant input are equivalent to an output-oriented BCC model without inputs. In these special circumstances scale Entrepreneurship intention efficiency is not a major issue. The above model describes a production process where if Ø ¼ 100 (best practice), the student is considered efficient.

(3) The third phase consists on applying a Truncated regression to find the influence of explanatory factors in terms of socioeconomic characteristics of the entrepreneurship intention efficiency (u) estimated in the second stage.

Having analyzed the Entrepreneurship intention efficiency by degrees, the next step is to study the determinants of the entrepreneurship intention efficiency. Since the Entrepreneurship intention efficiency indicator is a truncated variable, following the recommendation of Simar and Wilson (2007) we have estimated a truncated regression model to analyze the determinants of the Entrepreneurship intention efficiency of students. From the one proposed in equation 2 we can identify the variables not directly related to production that influence the educational level of Entrepreneurship intention inefficiency of the students and can make a prediction of what the Entrepreneurship intention inefficiency of each student should be.

fi ¼ f ðZ i; biÞ þ 1i

Where fi is the Entrepreneurship intention efficiency of the student obtained in a second step. Z is a vector z ¼ (z1, zl . . . , zL) of certain individual socioeconomic variables, not directly related to the production affecting the entrepreneurial learning process.

The dependent variable is the indicator of the Entrepreneurship intention efficiency score, estimated in the first step. The explanatory variables reflect the different characteristics of the students. First, average time/course captures the number of years that the students spend in passing the academic year. Students with higher entrepreneurial vocation might relate to minor difficulties in passing the courses. Gender is a dummy variable that takes value 1 if the respondent is male and 0 otherwise. Sometimes the stereotypes associated with entrepreneurs can affect women’s intentions, curtailing their entrepreneurial activity. However, there is a lot of research supporting the fact that the new trends and organizational demands are starting to be more favorable for women, and accepting that they have the qualities more consistent with the management style required for the immediate future (Burke and Collins, 2001). Therefore, the idea of social stereotype, defined by Deaux and Kite (1987) as “a set of beliefs formed following a series of attributes and behavior expected of a person or a category specifically of sex” must be rejected. Course is a dummy variable that indicates in which course the student is studying (In our case we made the

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decision to group students into two groups (group 1 courses 1 to 3, group 2 courses 4 and 5) because of the different simulations carried out and results achieved in the first stage). Family tradition is a dummy variable that takes value 1 if the respondent has some entrepreneur in the family and 0 otherwise. Many studies confirm that the presence of entrepreneurs in the family has a positive impact on the decision to create a company (Kolvereid and Moen, 1997). Family businesses allow a more direct way to know both the risks and benefits of establishing and conducting a business (Cromie et al., 1992). Finally, the dummy variables of intents; the intent of building a company measured on the respondent intensity and preference for future work.

3.2 Data and variables The empirical analysis was conducted by a questionnaire, on a sample of university students from five courses in the degree of Economics and Business Administration. The population has been chosen previously in the literature by authors like Autio et al. (1997); Krueger et al. (2000); Fayolle and Gailly (2004).

The sample comes from one of the oldest public universities in Spain. The fieldwork was conducted during April and May of 2009. The students were briefly explained the main purpose of the research and the importance of carefully and honestly answering all items.

The final sample was composed of 426 respondents. In this way, there was a sufficiently large sample. The structure of the sample is shown in Table I.

Table II shows a descriptive analysis of the variables used. As it can be seen, the average time to pass the course is greater for students in Economics with the mean at 1.79 (SD ¼ 1.80) years. There is also a family tradition with 52.34 percent of the students. Of the students in business administration, 55.52 percent preferred to work in the private sector in large companies. In total 72.24 percent and 50.78 percent of students in business administration and economics, respectively, are seriously considering to set up a business or are already entrepreneurs.

4. Empirical analysis and results 4.1 Factorial analysis First a factorial analysis (FA no. 1) is carried out to measure the student’s perceptions of the desirability of starting a business, see Table III. To validate the internal consistency of the scales used to measure the variables we performed the reliability

Business administration Economics

Course no. Students registered Sample

Percent over/ population

Students registered Sample

Percent over/ population

1 224 69 30.80 93 18 19.35 2 211 74 35.07 73 16 21.92 3 175 73 41.71 48 24 50.00 4 298 40 13.42 234 39 16.67 5 172 43 25.00 191 31 16.23 Total 1080 299 27.69 639 128 20.03

Source: Author’s calculation

Table I. Sample by education

programs

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Cronbach Alfa test, in which we obtained good values of 0.888 and 0.914. The statistical significance of Bartlett’s test indicates that the variables are related, while the KMO test sample shows a correct simple adequacy. Analysis of the results obtained is summarized in Table III.

In both groups of business and economics students, there was only one factor with eigenvalues greater than 1, explaining 75.03 and 79.7 percent of the variance respectively. The factor loadings and order in relation to these items are very similar.

In a similar way, we carried out the second factor analysis (FA no. 2) to capture the student’s perceptions of personal feasibility of starting a business.

Among the authors who have used these concepts in the literature, the following can be identified. In relation to internal control or locus of control Rotter (1966), Brockhaus

Business administration Economics

Question Variables Mean SD Mean SD

Average time in passing a course 1.49 1.18 1.79 1.18 Age 21.21 2.82 22.42 3.12 Gender (women) 54.85 52.34

Family tradition? 1 ¼ Yes 43.10 50.39

Which work would you prefer to realize in the future?

Public sector 16.02 22.66 Private sector SME 12.04 18.75 Private sector big firm 55.52 35.94 Self-employed 7.36 7.81 Continue studying 9.03 14.84

Do you intend to start a business? No 17.73 25.78 Yes (seriously) 72.24 50.78 Yes (I am starting one, I am a entrepreneur) 10.03 23.44 No. of observations 299 128

Source: Author’s calculation

Table II. Descriptive analysis by education programs

Business administration Economics Variables Factor 1 Factor 1

Item no. 1. Idea of creating a company 0.802 0.851 Item no. 2. I plan on having my own business 0.892 0.892 Item no. 3. Dedication of time and effort 0.900 0.924 Item no. 4. Investment savings 0.867 0.899 Kaiser-Meyer-Olkin test (KMO) 0.790 0.812 Barlett test 716.8 * 370.8 *

Percent of variance explained 75.03 79.70 Cronbach alpha 0.8885 0.9142 No. of observations 299 128

Note: *p , 0.01 Source: Author’s calculation

Table III. II. Rotated factor matrix for student’s perceptions of the desirability of starting a business (Factor loadings retained after varimax rotation) and test

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and Nord (1979), Miller and Toulouse (1986) can be cited. McClelland (1961) is the author of reference in relation to the need for achievement, and others have considered this in their own work such as Hornaday and Bunker (1970); Carland et al. (1989) or Lee and Tsang, 2001). In relation to tolerance for ambiguity, the work of Gupta and Govindarajan (1984) or Carland et al. (1989) can be cited. Finally, in the propensity for risk, Brockhaus and Nord (1979), Brockhaus (1980) among others are included. The questions were selected from the Entrepreneurial Attitude Orientation (EAO) scale (Robinson et al., 1991)

Table IV shows the results and test. The Cronbach alpha, Bartlett and KMO values for both degrees are adequate. The percentages of explained variance for Business and Economics students are 65.1 and 63.6 percent respectively.

The results obtained after varimax rotation are three factors for the two degrees to identify the factors through factorial loads considered equal to or greater than 0.5 (Hair et al., 1999). Factor no. 1 for business students (factor no. 2 economics students) relates to the items that define the need for achievement and less intensity on internal control. Factor no. 2 (factor no. 1 economics students) relates to the items that define the tolerance for ambiguity. Finally, factor no. 3 for both degrees is related to risk.

4.2 Entrepreneurship intention efficiency frontier measurement We use the model of Charnes et al. (1981) in the evaluation of the Entrepreneurship intention efficiency in relation to the degrees. The result of this test confirms that we should work with the two degrees separately.

Business administration Economics Variables F 1 F 2 F 3 F 1 F 2 F 3

No. 1. I like to be recognized in my work or studies 0.752 0.708 No. 2. I am very meticulous in the work I do 0.759 0.788 No. 3. I always like to work to be among the best 0.740 0.533 No. 4. If I do not take risks I will become stagnant 0.748 0.804 No. 5. People who take risks are more likely to succeed 0.824 0.827 No. 6. I handle confusing situations and unclear definitions well 0.879 0.873 No. 7. I handle uncertain situations well 0.869 0.839 No. 8. I like to plan activities ahead of time 0.739 0.595 No. 9. I never put off situations for a better time 0.526 0.573 KMO 0.730 0.696 Barlett test 695.1 * 310.4 *

Percent of variance explained 29.04 48.57 65.16 35.03 51.68 63.68 Cronbach alpha 0.731 0.761 No. of observations 299 128

Note: *p , 0.01 Source: Author’s calculation

Table IV. Rotated factor matrix for student’s perceptions of personal feasibility of

starting a business psychological traits

(factor loadings retained after varimax rotation)

and test

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Tables V and VI show the results of Entrepreneurship intention efficiency for both Business and Economics degrees by course.

The Entrepreneurship intention efficiency for students of business degree of the second and third course is higher with 90.49 and 89.56 percent respectively. This means that it is possible to increase the Entrepreneurship intention efficiency in 9.51 and 10.44 percent (entrepreneurship intention inefficiency level), respectively, while maintaining the input level constant. The concept of Entrepreneurship intention inefficiency suggests wasteful existing resources for carrying out a productive activity. Entrepreneurship intention inefficiency appears when one or more of the stakeholders: students, teachers, head of department/university, educational policy authorities, etc. does not adequately fulfill their role.

The sources of university Entrepreneurship intention inefficiency would be different. First, teachers of a university are facing a legal framework that is limited and largely determines the organization of educational resources. Thus, a university law which is diffuse in its objectives and with limited teacher incentives can create a poor organization in terms of sizes of the classrooms, staff recruitment, division of groups, greater rewards for the best teachers or the use of the repeated year mechanism in the university system. Secondly, the teaching system used by the teacher may be wrong, which could lead to lack of motivation and lack of guidance that would affect student performance. Finally, other aspects of self-management of the university related to the margin of discretion to make decisions concerning teacher recruitment, student selection and funding may also influence the productive mechanisms of the university.

Continuing with Table V, students in the fourth and fifth courses have the lowest level of Entrepreneurship intention efficiency with 87.93 and 85.99 percent respectively. These students have the highest values of standard deviation and therefore more dispersed values.

Business Efficients/obs Mean Std dev. Min Max

Course no. 1 9/69 88.78 9.57 50.21 100 Course no. 2 9/74 90.49 7.39 66.29 100 Course no. 3 8/73 89.56 9.30 59.92 100 Course no. 4 4/40 87.93 10.17 54.64 100 Course no. 5 4/43 85.99 10.68 55.60 100 Total 299 88.88 9.32 50.21 100

Source: Author’s calculation

Table V. Entrepreneurship intention efficiency score by course – Business students

Economics Efficients/obs Mean Std dev. Min Max

Course no. 1 0/18 75.86 10.59 54.19 89.61 Course no. 2 1/16 75.24 11.43 54.73 100 Course no. 3 1/24 77.06 9.42 52.73 100 Course no. 4 0/39 72.44 10.61 41.64 98.36 Course no. 5 1/31 75.08 11.77 48.91 100 Total 128 74.78 10.76 41.64 100

Source: Author’s calculation

Table VI. Entrepreneurship intention efficiency by course – Economics students

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In relation to the economics students, it is the third course that has the highest Entrepreneurship intention efficiency level with 77.06 percent and the students of first, second and fifth have similar values of Entrepreneurship intention efficiency around 75.00 percent.

Finally, the first and fourth courses have no efficient students and therefore do not reach the maximum value 100 percent.

4.3 Determinants of entrepreneurship intention efficiency The results of the truncated model estimated for both degrees are shown in Table VII. On one hand, the entrepreneurial decreases as students progress through their studies and are closer in contact with the reality for business students (first three years versus the last two). Perhaps personal pressures, family or the opportunity costs involved in setting up a company might deter students from this option. However, students who expressed the intention to create a company are more efficient in both degrees. In the case of business students for the option “Yes (seriously)” and “Yes (I’m starting one, I’m an entrepreneur)”, and in the case of the economics students for the last option mentioned.

On the other hand, students who have expectations to work in private sector SME and big f are more efficient than those who have expectations to work in the public sector. In the case of students of economics, no option is statistically significant. The variable’s coefficient increases with the option of self employment and continuing studying. These latter options seem logical given the situation of high unemployment that exists in Spain. However, in the case of economics students, no choice is statistically significant.

Finally, family tradition is not explanatory of Entrepreneurship intention efficiency in the case of business students, but for economics students it has a negative effect, indicating that students with family tradition are more efficient.

Business Ad. Variable Coef. est. E. Estand. Coef. est. E. Estand.

Constant 63.31 * * * 5.600 67.977 * * * 8.650 Average time/course 21.172 * * 0.561 20.047 0.688 Gender 2.487 * 1.401 4.179 * * * 1.581 D_course 24.125 * * * 1.528 22.657 1.698 Intend to start a business Yes (seriously) 3.722 * * 1.728 2.726 1.838 Yes (I’m starting one, I am a entrepreneur) 10.456 * * * 2.177 10.461 * * * 2.196

Prefer work in the future Private sector SME 12.675 * * 5.600 27.057 8.859 Private sector big firm 17.810 * * * 5.317 1.061 8.359 Self-employed 24.629 * * * 5.400 4.788 8.378 Continue studying 39.187 * * * 6.455 7.344 8.486

D_family tradition (1 ¼ yes) 0.390 1.433 23.261 * 1.559 log likelihood 2845.833 2433.017 Chi2 90.02 * * * 69.82 * * *

No. obs. 299 128

Notes: *, * *, * * * Significant to 90, 95 and 99 percent respectively. Omitted variables: male, d_course no. 1to3, D_no intention to start a business, D_Public sector, D_ family enterprise Source: Author’s calculation

Table VII. Determinants of

Entrepreneurship intention efficiency

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5. Conclusions, limitations and some implications for human resource development (HRD) practice In the context of the theory of planned behavior, this paper proposes a three-stage model for the analysis of Entrepreneurial intention efficiency using students from all courses of Business and Economics degrees in higher education in Spain. Results reveal that the explanatory factors for both types of students are different. This could be explained because the students choose one career or another according to their expectations of employment. In this sense, the Entrepreneurship intention efficiency decreases when the students of Business progress in their studies and they are closer in contact with the business reality. Maybe due to personal and family pressures to seek income with less uncertainty. Moreover, the judgments inherent in the university education system in relation to lack of motivation are conveyed to students in business creation. It seems that the theory of exclusion has given some support to the training and the resulting increase in value for the labor market, thus acting as a disincentive for the option of creating a company.

In line with some authors, we think that the university must have a triple role: incentive; encouraging students to start their own business, developer; informing students when they express a desire to create their own business and, finally, a training role; passing on knowledge and bringing students into business models. Therefore, the role of the university should not be confined to mere academic education, but be able to develop the necessary skills in students. There is a need for creation an atmosphere that encourage students to become entrepreneurs.

Despite a relative increase in the study of entrepreneurship students in recent years, due to the importance of this issue, and given the implications for economic growth and society in general, it seems advisable to investigate it in the future. Following Klapper and Tegtmeier (2010), the universities have to advance in entrepreneurial thinking and behavior because this has a positive effect. Given the results achieved in this work and given the significant potential that students have to create the enterprise, university systems should promote and encourage the employee as an interesting option for the future career of students. The point at which this research takes place in Spain seems relevant given that the university system is undergoing a major change that could bring more support to the initiative of setting up businesses. In this sense, the objectives of enterprise education may span learning “for”, “about”, and “through” enterprise, and are generally aimed at enabling the student to think and act in enterprising ways, with self-employment or entrepreneurship generally being a possible rather than intended outcome (Hartshorne, 2002).

Some limitations of this study are related to the period of time considered. The study refers to an academic year and thus to different students for each of the courses (cross section approach). A longitudinal study could provide a greater richness to the results, capturing the effects that persist over time in relation with the Entrepreneurship intention efficiency. The study population covers two degrees apart from technical careers such as engineering. In this sense, the work focuses on a single university. Therefore, extensions of future research could be aimed at addressing the limitations discussed.

Finally, we need to be cautious with us conclusions because entrepreneurship education is different than “traditional” management studies. In this context, and

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according to Kirby (2002), the traditional management education may impede the development of the necessary entrepreneurial qualities and skills. Entrepreneurship education needs a different teaching instructive, hence, there are studies trying to relate entrepreneurship education to work-related learning (Dwerryhouse, 2001); experiential learning (Kolb, 1984); action-learning (Smith, 2001), entrepreneurial training (Gibb, 1999). In other words, entrepreneurship education is more than business management, it is about “learning”, which means learning to integrate experience, skills and knowledge, to get prepared to start with a new venture. For example, Klapper and Tegtmeier (2010) highlight the importance of interdisciplinary learning by empowering students to be proactive, when they compare and contrast two innovative pedagogy experiments in entrepreneurship in two different countries.

Despite the previous limitations, we believe the empirical evidence found in this work allows us to highlight some implications for HRD practice:

. the possible effectiveness of entrepreneurship education for university students should be measured not just in terms of the acquisition of entrepreneurial skills, but in increased motivation, development of creativity, self-confidence, etc.; and

. stimulating entrepreneurship spirit in tertiary education is not only about business and economics knowledge to increase individual career opportunities; it is also about the possibility to increase the countries well-being in terms of economic growth, poverty reduction, sustainable development, etc.

In others words, entrepreneurship education policies should be to promote a more entrepreneurial society and culture by changing the mindsets of university students about entrepreneurship and encouraging them to consider it as a possible way for themselves in the future.

However, in a good number of countries there is still an important divergence between the content currently taught in tertiary education and the expectations arising from the rapid changes in a global economy. In this context, we consider a require for educating decision makers to renew the learning content of tertiary education so that it can impact, in a integrate way, the relevant knowledge and that will empower university students to engage in entrepreneurial activities, and to develop positive attitudes and values in dealing with the conflict generated by change.

In this line of thinking, several national and international initiatives around the world are supporting the development of education programmes which include components on entrepreneurship and employability (see for example Bahri and Haftendorn, 2006).

Note

1. The theory of planned behavior, grounded in social psychology, is based on the premise that much human behavior is planned and is therefore preceded by intention toward that behavior (Fishbein and Ajzen, 1975).

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