entrepreneurial propensity among portuguese high school students

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In comparison with regular high school students, professional/technical ... areas on Entrepreneurial Intention (E.I.) literature, which can be summarized in: the ...


ESTGA - University of Aveiro (PORTUGAL) IT – Instituto Telecomunicações (PORTUGAL) 3 ESAN – University of Aveiro (PORTUGAL)

Abstract Nowadays, with unemployment reaching unprecedented high rates in Portugal, it is important to understand the level of entrepreneurial intention among Portuguese students. Given the present difficulty for youngsters to obtain a first job, it is vital for education programs to encourage and contribute to entrepreneurship development. The main goal is that, in the future, undertakings can begin and successfully materialize, allowing job creation not only for the promoter but also in the community. The objective of this paper is to analyse entrepreneurial propensity of secondary high school students, in particular, to compare entrepreneurial intentions between regular and professional/technical education students. In this work, we examine a case study of a Portuguese secondary high school with both kinds of curricula, using a questionnaire distributed and filled by a representative sample. Aspects like previous job experience, business owned by close relatives, personal mentality and attitudes, were studied in order to understand the individual sensitivity of these students to become entrepreneurs and how their education affects or influences their entrepreneurial intentions. The results show that there is a low level of entrepreneurial propensity across all students and that there is no statistical difference in the results obtained between regular curricula students when compared with the professional/technical students. Keywords: Entrepreneurial propensity, secondary school students, binary choice models



In the last years, Portugal like other countries, has been implementing a significant curricular reform in order to improve academic performance and classroom behaviour so that students can be more prepared and have a more suitable curriculum for their expectations and interests. In comparison with regular high school students, professional/technical students have in their education programs a professional training/internship with a final report, in order to promote exchange of ideas and to ensure work experience. This is a completely different approach when compared with traditional education curricula. The former type of program can possess more value especially in students with risky behaviours and low motivation at school, since it gives them the opportunity to develop the skills for academic success with more specialized practical oriented courses. In this paper, we will study and compare the entrepreneurial intentions among Portuguese high school students using data collected from a secondary high school with both kinds of curricula. It is known that there are many factors contributing to entrepreneurial propensity besides the education program chosen at school. The influence of students' affective factors, their families' professional background and maybe even their gender are also very important and can have a direct influence on their future occupational choices. In particular, since children often learn by example through observations made at home or of close relatives, it is natural that students with family exposure to business tend to be more aware of entrepreneurship and possessing a higher probability of becoming entrepreneurs in the future. This may be due to their engagement in a number of direct-learning experiences, which can influence their entrepreneurial intentions and make them more likely to succeed. With the slowdown in global economic growth, focusing on self-employment is increasingly becoming the gateway into the labour market and a good way to give life to personal ideas. Starting a business requires exploiting market opportunities, dealing with uncertainty and taking risks in order to maximize financial return. In Portugal however, a culture on the valorisation of personal initiative still does not

exist. . Since global crisis erupted in 2008, unemployment rate in Portugal has significantly increased and in the first trimester of 2015 was around 13.7% according to the evaluation released by the National Statistics Institute of Portugal (INE). In particular, Portuguese youth have been significantly affected by unemployment and job precariousness, which are a dramatic social problem and a growing concern. Consequently, the emigration rate of Portuguese youth has also increased in the last few years. Therefore, today more than ever, Portugal needs to promote awareness campaigns in secondary schools in order to stimulate job creation so our students can contribute to the recovery of our country in the future. This paper is structured as follows: In Section 2, we present some recent studies focused on entrepreneurial propensity. The data and the methodology used are presented in Section 3. In Section 4 we present the results of the statistical analysis and finally, in Section 5 the main conclusions are drawn.



There is a growing body of literature arguing that intentions play a very significant part in the decision to start a new firm [1]. Following Liñán and Fayolle [2] classification, there are five main research areas on Entrepreneurial Intention (E.I.) literature, which can be summarized in: the core entrepreneurial intention model; the influence of personal-level variables; the entrepreneurship education and intentions; the role of context and institutions; and the entrepreneurial process. In this chapter, we will point out relevant studies made in these five areas. In studies regarding the core entrepreneurial intention model, there are two major contributions in E.I. models. In [3], Shapero develops an entrepreneurial event model in which business creation is considered as an event that can be explained with the interaction between initiatives, abilities, management, relative autonomy and risk. Ajzen [4] follows the theory of planned behaviour, which considers that any behaviour requires a certain amount of planning and can be predicted by the intention to adopt that behaviour. Recent research on this area has been testing general specifications, new formulations of those models [5], or the inclusion of additional variables [6] and the investigation on alternative configurations of motivational antecedents [7]. In order to identify some factors that may explain differences among secondary students in start-up intention, in [5] a model of E.I. is tested using structural equations , which lead to concluding that the theory of planned behavior is an appropriate tool to model the development of E.I. through pedagogical processes and learning contexts. Education and training should center more in changing individual attitudes than in traditional knowledge and entrepreneurship educational curricula. It should contribute to the development of competences related to entrepreneurship, social and civic skills and cultural awareness. Using a sample of 430 college students, the Hmieleski and Corbett study examines the relationship between improvisation and entrepreneurial intentions concluding that entrepreneurial intentions are found to be significantly associated with measures of personality, motivation, cognitive style, social models, and improvisation. The strongest relationship is found between entrepreneurial intentions and improvisation. [6] Zhao et al. analyse the role of self-efficacy in the development of students’ intentions to become entrepreneurs concluding that the effects of perceived learning from entrepreneurship-related courses, previous entrepreneurial experience and risk propensity on entrepreneurial intentions were fully mediated by entrepreneurial self-efficacy. [7] The area focused on the influence of personal-level variables includes studies on the effect of personal traits and psychological variables (such as emotional stability, extraversion, openness to experience, agreeableness, conscientiousness, risk propensity, locus of control, innovativeness, creativity, etc.), background factors (such as family background, education and experience), gender differences, studies about particular subgroups of the population, and barriers to E.I. [2]. Included in this area is the research made by Marques et al. [8] based on TPB and using a sample of secondary school students taking general academic programs and vocational course programs (data were collected through questionnaires). In order to approach E.I. and the factors preceding the founding of E.I., causal relationships between psychological, demographic and behavioural factors were established. The results show that the E.I. of secondary school students is influenced by such factors. However, the hypothesis of becoming entrepreneurs in the future remains independent of the fact of whether or not students had already experienced some engagement with entrepreneurship.

Related with the influence of family background on E.I., Carr and Sequeira research results suggest significant direct and indirect effects of prior family business exposure on entrepreneurial intent, through the mediation variables of attitudes towards business ownership, perceived family support, and entrepreneurial self-efficacy. [9] The third area of research incorporates studies about the characteristics of the participants, results and evaluation of entrepreneurial education programs (EEP), comparisons and program proposals. According to Liñán and Fayolle [2], the contributions in this category suggest that entrepreneurship education needs to apply differentiated teaching techniques and contents to achieve its full potential. In regards to this, Marques et al. [10] developed a study about the contribution of yoga to the entrepreneurial potential of university students. The results of this study suggest that if entrepreneurial behavior is going to become a priority then yoga should be integrated as a compulsory subject into general education from primary school onwards. The fourth area considers the influence of regional, cultural and institutional environments on the configuration of E.I. About this matter, Engle developed a study with the purpose of testing the ability of the Theory of Planned Behavior to predict entrepreneurial intent in 12 countries. His conclusions suggest that the model of planned behavior, as operationalized in this study, does successfully predict entrepreneurial intent in each of the countries analysed [11]. The fifth main area refers to the actual entrepreneurial process. One of the topics studied in this area is related to the transition from student to business start-up [12]. This study points out the lack of indepth research on the stories, circumstances, contexts and complexities of graduates on their journey from student to business start-up. The link between training, support, intention and actual career choice to start-up a business remains under-investigated.

3 3.1


To measure the entrepreneurial profile we adapted to the Portuguese language the scale used in “Aij’un profil d’entrepreneur?” developed by Gasse [13]. In its final version, this scale is composed of 50 items that measure, in four point Likert scales (from 1 = totally disagree to 4 = totally agree) the intention of creating an enterprise through three principal dimensions: motivations, abilities and attitudes. Motivations are the facts that determine behavior and are the reasons that drive people to do the action. What motivates people to create their own company in the majority of cases is the need for achievement, self-realization and autonomy. Four sub dimensions composed this dimension: realization/success which measures the desire to grow, to perform and to be excellent, power/control assesses the desire to lead and to influence other people, challenge/ambition measures the desire to embark on difficult projects, the need to learn and to achieve personal dreams and autonomy/freedom which assesses the desire to be one’s own boss and the need to make personal decisions. Abilities are a combination of characteristics that enable people to give organized answers in relation to situations, their natural dispositions and the skills that one possesses. There are skills that predispose people to entrepreneurship, like self-confidence and determination. This dimension is constituted by 4 sub dimensions: self-confidence/enthusiasm which measures the confidence that people have in their own abilities and resources, perseverance/determination assesse the ability to persist when facing obstacles, tolerance to ambiguity/stress management measures the ability to manage stress when facing uncertainty and creativity/imagination measures the ability to find multiple solutions to problems. Attitudes are composed of dispositions that people possess in relation to something. This dimension is constituted by two sub-dimensions: destiny/chance which measures the tendency to believe one’s own ability to influence course of action and action/time which measures the orientation to action. The scale was submitted to different studies to assess its psychometric qualities (e.g., reliability, correlations and discriminant validity), which conducted to the elimination of 40 items from the initial 90. In its final version, the Cronbach’s alphas of the three dimensions presented acceptable values (.82 for motivation, .87 for abilities and .70 for attitudes). The instrument was adapted by following the steps shown in the scientific literature for adapting assessment instruments [14]. First, research and language experts translated the items from French into Portuguese. Secondly, a focus group was held to discuss the translated items such as the

equivalence of meaning, for example. Then the language experts back-translated the items into French, and finally the equivalence of meaning of the original and adapted versions was checked. The psychometric qualities of the adapted version of the scale were assessed by the alpha of Cronbach. After analyzing the results of the Cronbach’s alphas for each dimension (as well as the correlations between the items and their dimensions), four items from the Motivation dimension, one item from the Abilities dimension and three items from the Attitudes dimension were dropped. After this initial procedure, the Cronbach’s alphas were .65 for motivation, .76 for abilities and .66 for attitudes. Then, for further analysis, the mean of the items of each dimension was computed. Besides the Gausses’ scale, the questionnaire was also composed of socio-demographical questions (gender, age, scholar year). To assess the entrepreneur intention we also made the following questions: “Do you consider yourself able to create a company in the future?” (Answer: No/Yes), “When you finish high school specify your interest in creating your own company” (Answer: from 1 = reduced to 4 = high), and “When you finish high school specify your interest in working on your own” (Answer: from 1 = reduced to 4 = high); to assess the existence of early business contact through family environment we posed the question “Does anyone in your family own a firm?” (Answer: No/Yes).



After the questionnaires have been prepared, these were tested with young adults with similar ages to the ones in the population we wanted to analyse in order to validate the data collection instrument. The sample size required was calculated so that the margin of error was 5%, the confidence intervals of 90% and assuming an answers distribution of 50%. This resulted in the need to apply a total of 188 questionnaires. The selection process of the individuals who would answer the questionnaire was carried out using a stratified probability sampling, taking into account relevant subpopulation features for our study, as is the case of students in regular education vs. vocational students, and other classic stratification characteristics like gender. The questionnaires were administered among professional curricula students using an online survey application (in one of the informatics classes), while students of regular curricula also received, a paper printed version of the questionnaire in the classroom environment. In both situations, the research team had an amazing help and contribution by the teachers of the school in the analysis.


Sample Characteristics

Analyzing some basic sample characteristics we could point out some of the main descriptive statistics. In table 1 the values for the age of the students and the school year they attend are summarized. Table 1. Descriptive statistics of sample characteristics Min









School Year





In our sample the youngest students were 15 years old and the oldest one was 21 years old. The average of this variable is of 17 years (SD = 1.21). Concerning the distribution of the variable of gender, 54.7% were female (more females than men complete secondary school). In regards to the type of curricula attended by the students who replied to the questionnaire, 58.4% attended a regular curricula course.

4 4.1

RESULTS Correlation Analysis

Table 2 presents the correlations between the variables under study: motivations, abilities and attitudes dimensions, type of class (1 = regular, 2 = professional), gender (1 = female and 2 = male), family antecedents (“Does anyone in your family own a firm?”) (1 = No and 2 = Yes), ability to create a company (“Do you consider yourself able to create a company in the future?”) (1 = No and 2 = Yes), interest in creating a company (“When you finish high school specify your interest in creating your own company”), and interest in working on their own (When you finish high school specify your interest in working on your own). The existence of firms owned by members of the family is significant and positively correlated with motivations (r = .22, p < .05), aptitudes (r = .24, p < .01) and attitudes (r = .21, p < .01). The perception of the ability to create a company is positively correlated with both motivation (r = .27, p < .01) and aptitude (r = .24, p < .01), as well as the interest in creating a company (r = .32, p < .01 and r = .21, p < .01, for motivations and aptitudes, respectively) and the interest in working on their own (r = .34, p < .01 and r = .21, p < .01, for motivations and aptitudes, respectively). A significant positive correlation was also found between gender and abilities (r = .17, p < .05). No significant correlations were found between the type of class and the variables of interest. Table 2. Descriptive statistics and intercorrelations between variables under study M










1. Motivations




2. Abilities





3. Attitudes






4. Type of class (professional)







5. Gender (male)








6. Family antecedents (yes)









7. Ability to create a company (yes)










8. Interest in creating a company











9. Interest in work on their own













Note. *p< .05; **p< .01


Regression analysis

In this subsection we present the model developed to analyse which of our variables could explained the students’ intensions to become entrepreneurs. In table 3 we run a Logit (logistic distribution) and a Probit (standard normal distribution) model to explain the belief students have in their ability to create a firm in the future. In both models only one of the explanatory variables used in the regressions were statistically significant. The indicator of students’ abilities have a positive effect in the probability of firm creation capability. In the Logit model, the conditional marginal effects at the mean (dy/dx) is .27, which states that an increase of one value in the ability indicator of the “average” student will represent a 27% increase in the probability of firm creation. The average marginal effects lead to a value .22 (the average of every individual in the study marginal effect), meaning that a one more value in the ability will lead to an improvement of the probability of 22%. Has expected, in the Probit model the values estimated were very similar to the previous ones’, respectively of 28% and 23%.

Table 3. Results Logit and Probit regressions Ability to create a company (yes)












Abilities -0.412





















Type of class (professional)

Gender (male)

Family antecedents (yes)


Note. *p< .05; **p< .1. Robust SE in parenthesis.

In table 4 we run Ordered Logit and Orderer Probit models to predict the students’ interests in creating a company and their interests in working on their own. In all the models only two explanatory variables were statistically significant, the Motivations (p