Sample and data collection
The empirical data used to investigate the drivers of students’ entrepreneurial intention were obtained from an online survey conducted in 2016 among the members of the European and Tunisian JEE networks. The authors developed the survey, which is presented in the Appendix, together with the JEE board of directors. In addition, OECD provided advice on how to structure the survey and suggested some key questions that needed to be addressed.
The survey was sent first to the International Manager of each JEE confederation, who then passed it on to the Presidents of the Junior Enterprises (henceforth JEs) belonging to the confederations. All the members of the JEs were invited to fill in the survey. The survey was written in both French (to address the French and Tunisian confederations) and English (to address the remaining JEE members).
Out of 420 associates who had received the survey, a total of 261 members answered the survey, thus yielding an effective response rate of 62%. A check on non-response bias was made with respect to all the survey items (Armstron and Overton 1977) and it was found to be minimal. Therefore, the sample is representative of the population.
Descriptive statistics
The survey presented 33 questions covering the general data of the students, the international mindset, the educational and work background, their involvement in JEs and future career scenarios. On average, the respondents were 22 years old and were thus still undergraduate students. Out of the 261 respondents, 54% were women. This is an interesting data, given that previous studies showed that men are generally more inclined toward entrepreneurship (Shinnar et al. 2012), although gender does not always play a determinant role in start-up activities (Verheul and Thurik 2001).
Figures 1 and 2 illustrate the distribution of the respondents according to their nationality and field of study.
A non-trivial fragmentation regarding the respondents’ nationality appears: the higher percentages of respondents are Tunisian (29%), Italian (26%) and Portuguese (23%), followed by French (7%), Spanish (5%), German (3%), Belgian (2%), Austrian (1%) and British (1%). Other nationalities (Croatian, Dutch, Polish, Swedish and Swiss) overall account for 2%. As far as the field of study is concerned, most students are enrolled in Science and Technology (47%) and Business (42%), while only a few students study Human Science (9%). Only a few respondents are enrolled in Languages and Communication (5%), Art and Sport (2%) and Biological Science (3%). In addition, the JEE members are also from different educational levels. In fact, the respondents are either in their first (13%), second (24%), third (23%), fourth (24%), fifth (13%) or later (2%) years of university. The following universities show a higher frequency (more than 5%): Universidade Católica Portuguesa (8%), Université de Monastir École Nationale d’Ingénieurs de Monastir (7%), École de Traduction, d’Interpretation de Conference (7%), Politecnico di Milano (7%), Universidade do Minho (7%), Université de Tunis el Manar Ecole Nationale d’Ingénieurs de Tunis (7%), Università degli Studi di Milano (6%) and Université de la Manouba Ecole Nationale des Sciences de l’informatique (5%). The JEE members come from 48 different universities. This indicates that JEE involves students from different countries, different fields of study and different educational levels.
Since JEE is international, their associates actively develop an international mindset. In fact, out of the 261 respondents, 65% speak more than two foreign languages. Almost all students speak English (97%). Most of them speak French (53%), and fewer speak Spanish (28%), Italian (27%), Arabic (24%), Portuguese (24%), German (20%), Chinese (4%), Catalan (2%), Dutch (2%), Russian (2%) and Polish (1%). It should be noted that, when added together, the total is not 100%, because the respondents had the possibility of choosing several answers. In addition, 39% of the students reported that they had lived abroad and 25% declared they had participated in exchange programs (most of which were in Europe, 63%).
As far as their work experience is concerned, almost half of the associates reported they had worked as volunteers in another organization and that they had work experience (48% and 45%, respectively).
In addition, it is interesting to note what are the skills that JEE helps its members develop. Figure 3 illustrates that participation in JEE activities helped associates develop teamwork (18%) and communication skills (16%), and learn to take responsibility (14%). In fact, when students were asked the reasons that drove them to take part in the organization, most of them reported that the main reason was to improve their skills (87%) and their networking (65%). Additionally, 83 associates (32%) answered they were driven to have a positive impact on society and a total of 60 associates (23%) answered that they entered the organization in order to learn how to start a business. Only 40 students (15%) indicated that they joined JEE for leisure purposes.
Variables
The dependent variable (entrepreneurial intention) was derived from the answers to a specific question in the survey (Krueger 1993): “How do you see yourself when you finish your current studies?”. The respondents could answer by choosing among five different options: (i) becoming an employee in the public sector; (ii) becoming an employee in the private field; (iii) starting their own company; (iv) starting a new study program; or (v) other. The dependent variable is therefore a binary variable that is equal to 1, if the respondents answered they wanted to start their own company, and 0 otherwise, as has been done in similar works (e.g. Laspita et al. 2012; Zhang et al. 2014; Criaco et al. 2017).
The explanatory variables refer to both specific organizational and individual factors that affect students’ entrepreneurial intention. In other words, this study has used three different organizational-specific factors. First, it considers the number of hours per week that, on average, an associate spends working for JEE. This variable reflects the effort that students put into working for the organization. Since SLEOs can stimulate entrepreneurial abilities through their activities (Pittaway et al. 2011, 2015), it was expected that this variable could influence students’ entrepreneurial intention. In fact, the more hours students work for the organization, the more activities they are able to attend, organize and accomplish and hence, the higher the likelihood is that they will increase their entrepreneurial intention. During the hours spent in the association, members can have the opportunity to learn by doing, to add practical experience to their theoretical skills and to develop entrepreneurship abilities (Padilla-Angulo 2017). In other words, SLEOs help students improve their entrepreneurial abilities and intention through different mechanisms: by shaping the social norms, such as students’ personal relationships, that influence the process of entrepreneurial learning (Cope 2005; Pittaway and Cope 2007) and by emulating entrepreneurship activities (Fayolle and Gailly 2015), thus stimulating students’ problem-solving abilities, as well as their communication, leadership and team work skills (Preedy and Jones 2017).
Second, another organizational-specific regressor is the number of projects that students have carried out within JEE. The involvement in a greater number of projects can lead students to enhance their experience, improve their technical and soft skills (e.g. project management, communication, leadership and team work) and develop a network of contacts from industry and service professionals, thereby influencing their entrepreneurial intention. Networking is in fact a key component for entrepreneurship (e.g. Zimmer and Aldrich 1987; Sandhu et al. 2011; Wright et al. 2017), since it reduces the perceived risk of action (Brüderl and Preisendörfer 1998) and increases determination and perseverance in a process (Gimeno et al. 1997). In addition, students can foster their entrepreneurial abilities by running real projects (Pittaway et al. 2011; Gibcus et al. 2012; Preedy and Jones 2017). In fact, consulting projects can also have an impact on students’ entrepreneurial intention (Kassean et al. 2015). In other words, by taking part in real experiences, students can play the role of a real entrepreneur (Corbett 2005; Clark et al. 2008) since they need to manage people and money, work in a team and negotiate (EC 2016).
Third, the last predictor variable at the organization level is the number of events that students have attended. This variable concerns the events organized by JEE itself, local JEs and the National Confederations, aimed at improving students’ skills, extending their networks and enhancing their entrepreneurial intention. During these events, students can meet other peers with similar interests and can work on new ideas.
In addition to organizational-specific factors, the correlation between individual-specific factors and students’ willingness to start an entrepreneurial business has been tested. The independent variables include the respondent’s field of study, their international mindset (knowledge of foreign languages and participation in exchange programs) and their work experience. As outlined in prior works, a student’s field of study can have an impact on entrepreneurial intention (Schwarz et al. 2009; Edelman et al. 2016; Criaco et al. 2017; Laskovaia et al. 2017; Morris et al. 2017). It has been found that students enrolled in Business studies have greater entrepreneurial intention than their colleagues (Schwarz et al. 2009; Wang and Verzat 2011; Edelman et al. 2016; Morris et al. 2017). Nevertheless, Criaco et al. (2017) also found a positive correlation between Engineering students and entrepreneurial attitudes. Similarly, Souitaris et al. (2007) pointed out that entrepreneurship programs raise the entrepreneurial intention of Science and Engineering students. Therefore, this study has also analysed whether different fields of studies can affect students’ entrepreneurial intention. In other words, the analyses included Science and Technology as a dummy variable that was equal to 1 if the student’s field of study was Science and Technology, and 0 otherwise.
In addition, the international mindset of the students was proxied by means of two variables: the number of foreign languages spoken and whether they had completed an exchange program. Mastering more than two foreign languages is important for business purposes (e.g. to facilitate interactions with people from different cultures). In fact, language ability is an important source for entrepreneurship since it allows entrepreneurs to successfully create market entry and new foreign market choice strategies more easily (Johnstone et al. 2018). Moreover, several studies (see Adesope et al. 2010 for a review) have also shown that individuals who speak two languages are endowed with better problem-solving skills and creativity. In addition, Ellis (2011) indicated linguistic distance as a major barrier to the communication of information about new opportunities. Therefore, it was expected that speaking more than two foreign languages would be positively correlated with developing entrepreneurial intention. The variable of interest was a dummy variable that was equal to 1 if the student spoke more than two foreign languages, and 0 otherwise. In other words, the variable was equal to 1 only if a student knew the language of his/her country of origin, plus two more languages. For instance, if a French student knew French, English and Spanish, the language variable was equal to 1.
In addition, having completed an exchange program can also have an impact on students’ entrepreneurial intention (Brandenburg et al. 2014). As Brandenburg et al. (2014) pointed out, almost one out of ten Erasmus students start their own company, and more than three out of four plan to do so. This is because exchange programs allow students to create an international network, improve their soft skills and get in touch with different cultures, thus obtaining a better understanding of the international market (Cavallo et al. 2019; Varano et al. 2019). In fact, these programs can have an impact on the social norm of an individual. For instance, in the French context, Fayolle and Gailly (2015) found a significant correlation between French engineering students’ entrepreneurial intention and living abroad for at least six months. This study has therefore included the exchange program variable as a dummy variable equal to 1 for students who have been on an exchange program, and 0 for those who have not.
An additional personal-specific variable is students’ work experience (e.g. Carr and Sequeira 2007; Laskovaia et al. 2017). Prior family business exposure has been found to correlate with the formation of entrepreneurial intent (Carr and Sequeira 2007). In addition, experience in industry has been shown to have a positive impact on entrepreneurial performance (Cassar 2014; Smolka et al. 2018). Similarly, Edelman et al. (2016) showed that students’ previous work experience is positively associated with a greater scope of venture activities. Laskovaia et al. (2017) pointed out that the experience of students in industry positively impacts their new venture performance. However, Sandhu et al. (2011) found no significant relationship between work experience and entrepreneurial intention. Therefore, this study has included a dummy variable equal to 1, if a student had a prior work experience, and 0 otherwise.
Moreover, this study has included several control variables in the model specification. The first of these controls is gender. Even though Verheul and Thurik (2001) showed that gender does not play an important role for start-up activities, it is generally accepted than men have more entrepreneurial intention than women (Mathews and Moser 1995; Harada 2003; Wilson et al. 2007; Schwarz et al. 2009; Yordanova and Tarrazon 2010; Shinnar et al. 2012; Criaco et al. 2017; Morris et al. 2017). Research indicates that women have both lower entrepreneurial self-efficacy and lower entrepreneurial intention (Chen et al. 1998; Kourilsky and Walstad 1998; Criaco et al. 2017). Mazzarol et al. (1999) found that women are less likely to be founders than men. However, as suggested by Bandura et al. (2001), women may be influenced more by any perceived skill deficiency in the entrepreneurial field than men. In their study, Kourilsky and Walstad (1998) compared perceptions of knowledge with actual knowledge of entrepreneurial skills and showed that while the skill levels of men and women were comparable, the latter were more likely to feel unprepared. Minniti et al. (2004) reported that these patterns emerge globally among adult women (i.e. women show lower levels of confidence and preparedness in their ability to succeed as entrepreneurs). Nevertheless, Smolka et al. (2018) found that being female is not significantly related to start-up performance. Empirical evidence also indicates that, despite the growth in female entrepreneurship, men entrepreneurs are still almost twice as many as women entrepreneurs (Bosma and Levie 2009). In addition, as in previous studies, students’ age has also been included as an additional control (Barber 2015; Minola et al. 2016; Criaco et al. 2017; Laskovaia et al. 2017; Morris et al. 2017; Smolka et al. 2018). Students’ age can be correlated with entrepreneurial risk taking (Barber 2015). Previous works have shown that age is correlated with entrepreneurial intention (Hatten and Ruhland 1995; Harada 2003; Schwarz et al. 2009; Criaco et al. 2017; Smolka et al. 2018). Most studies have highlighted that younger people have a higher intention of starting new firms (Schwarz et al. 2009; Edelman et al. 2016; Criaco et al. 2017; Smolka et al. 2018), while only a few have pointed out the opposite (Cressy 1996). The Gross Domestic Product (GDP) of the student’s country of study has been included as a control (Laskovaia et al. 2017). Information on GDP has been derived from the World Bank dataset for the year 2015. It has been pointed out that countries with a lower GDP are generally associated with higher entrepreneurship rates (Wennekers et al. 2005; Uhlaner and Thurik 2007; Stephan and Uhlaner 2010). This is due to the lack of steady jobs, a fact that stimulates people to become entrepreneurs (Audretsch and Thurik 2001; GEM 2002; Dutta and Sobel 2018). The most recent Global Entrepreneurship Monitor report (GEM 2017) has in fact shown Guatemala as the country where becoming an entrepreneur is the best career choice, Burkina Faso as the country with the highest status for successful entrepreneurs, and Jamaica as the country with the highest attention toward entrepreneurship. Moreover, Laskovaia et al. (2017) found that GDP has a negative effect on new venture performance. Furthermore, Sambharya and Musteen (2014) found a curvilinear relationship between per capita GDP and opportunity-driven entrepreneurship.
Table 2 illustrates the definitions of the variables used in the empirical analysis, as well as the main descriptive statistics. The Appendix reports the correlation matrix of the variables (Table 6). The Table 6 shows that the value for the correlation between two regressors is never higher than 0.40. The exception is the expected correlation between N_events and Time_spent (0.42). Therefore, these two variables are not in the same regression analysis.
Table 2 Definition of the variables Empirical results
In order to investigate which factors shape the willingness of students belonging to SLEOs to become entrepreneurs, a logistic regression analysis has been performed. Since two predictor variables are highly correlated (N_events and Time_spent), this study has reported the results separately in two different tables.
Table 3 reports the logit estimates, in which the variable Time_spent is included among the regressors. Model 1 is the baseline model. Model 2 adds the student’s education field. Model 3 includes the variables that reflect the student’s foreign experience. The student’s work experience is introduced in model 4.
Table 3 Logit regression. Dependent variable: Entrepreneurial Intention In all the model specifications, the Time_spent variable presents a statistically significant and positive impact on students’ entrepreneurial intention. This result indicates that the time that students spend in JEE positively shapes their subsequent willingness to start a new business. In fact, the higher the time devoted to the activities organized by JEE is, the higher the likelihood that students will increase their entrepreneurial abilities that will ultimately affect the development of their entrepreneurial intention. Surprisingly, the analyses have not revealed a statistically significant impact of the number of projects that students have carried out in this organization on their entrepreneurial intention. An explanation of this result could be related to the consultancy-based nature of some of these projects. Although no information on the contents of the projects is available, informal talks with some JEE members have revealed that, in many cases, projects have opened the door to contacts (and subsequent hiring) with consultancy companies. Several JEs enter into partnership or informal agreements that give their members some advantage in being hired by local companies. For instance, if a company is recruiting, it might directly ask JEs to let some members apply for an evaluation.
The mere number of projects alone may not be sufficient to explain the members’ entrepreneurial intention, as the content of the project probably would have. The estimates of the marginal effects show that when the Time_spent variable moves from zero to its mean value, the probability of having entrepreneurial intention increases by 0.5 percentage points.
As far as individual-level factors are concerned, the Science and Technology field of study has a statistically significant and positive impact on students’ entrepreneurial intention, as found by Criaco et al. (2017). This effect is significant at a 5% level in all the model specifications. Owing to the fact that the two variables concerning the field of study (Science and Technology and Business) together present a high correlation (− 0.6520), Business was not included in the analyses. However, this study has also run the same regressions controlling for Business instead of Science and Technology, without finding any significant effect of the Business field of study. In terms of marginal effects, being enrolled in the Science and Technology field of study significantly increases the probability of developing entrepreneurial intention by 13.17%.
The estimates show that students who speak more than two foreign languages are more likely to develop entrepreneurial intention than their peers. Here again, the magnitude of the effect is high. The probability of having entrepreneurial intention is, on average, about 10 percentage points higher for students who speak more than two foreign languages.
Additionally, the GDP of the country of study was found to be negatively and significantly associated with students’ entrepreneurial intention. This result is interesting, because it indicates that students from lower income countries are more willing to create new businesses than their peers, despite their country’s poor growth perspectives. Laskovaia et al. (2017) found the same result. Moreover, based on the human capital theory, Dutta and Sobel (2018) have explained that less developed countries have a high rate of entrepreneurs, also known as ‘necessity’ entrepreneurs.
Table 4 reports the logit estimates where the N_events variable is included among the regressors. Model 1 is the baseline model. Model 2 adds the student’s education field. Model 3 includes the variables that reflect the student’s experience abroad. Student’s work experience is introduced in model 4.
Table 4 Logit regression. Dependent variable: Entrepreneurial Intention The N_events variable displays a statistically significant and positive sign in all the model specifications (at a 5% significant level). A unit change in the N_events variable increases the probability of having entrepreneurial intention by 0.004. This result reinforces the expectation that the higher the effort that students put into JEE activities is, the higher the likelihood of developing entrepreneurial intention is. All the results presented in Table 3 have been confirmed when the N_events variable was substituted with the Time_spent variable in the regression analyses.
In conclusion, the results show how students’ participation in JEE positively affects their entrepreneurial intention. In fact, the findings show that the more effort students put into this organization and the more events they follow, the higher the probability of increasing their entrepreneurial intention is. The Science and Technology field of study and the knowledge of more than two foreign languages are both important drivers of entrepreneurial intention. Therefore, the results confirm the recent work of Johnstone et al. (2018) concerning the role played by language ability in entrepreneurship. In addition, the results show that entrepreneurship is also interesting for technical students (Souitaris et al. 2007).