Behaviours and entrepreneurial intention: Empirical findings about secondary students

  • Arminda M. Finisterra do Paço
  • João Matos Ferreira
  • Mário Raposo
  • Ricardo Gouveia Rodrigues
  • Anabela Dinis
Article

Abstract

This paper aims to identify some factors that may be explaining differences among secondary students in start-up intentions. For that, the study develops an entrepreneurial intention model sustained by the use of Azjen’s Theory of Planned Behaviour (TBP). Using a sample of students aged between 14 and 15 years old, a questionnaire based on the Liñán and Chen’s Entrepreneurial Intention Questionnaire was administrated. The purpose is to test a model of entrepreneurial intention using structural equations. The findings point that TPB is an appropriate tool to model the development of entrepreneurial intention through pedagogical processes and learning contexts. The education and training should centre itself much more in changing personal attitudes than in knowledge. Moreover, it is desirable that an entrepreneurship educational programme could contribute to the development of competences related to entrepreneurship, social and civic skills, and cultural awareness.

Keywords

Entrepreneurial intention Entrepreneurship education Secondary students 

Introduction

The number of schools offering entrepreneurship courses in last years has risen in many Western countries (Vesper and Gartner 1999). This trend was particularly notorious in the nineties in some universities in the USA, Canada and France (Kyrö 2006). In North America, it seems that the traditional pedagogical methods, such as the writing up a business plan, case studies, lessons or guest entrepreneurs, are still predominant (Solomon et al. 2002). In turn, Europe has been developing several innovative pedagogical initiatives in the last years (Gasse and Tremblay 2006).

In 2002, a European Commission’s report indicated significant differences between countries, related to the situation of entrepreneurship education in national educational systems. For instance, “only Finland has extensively included it in the curriculum of primary and secondary school, as well as in initial vocational training” (Kyrö 2006:95). In Great Britain, Spain and Netherlands there is a relatively broad range of activities related with the entrepreneurship education. Other countries such as Germany, Austria and Switzerland have begun significant efforts in order to establish entrepreneurship education.

Rushing (1990) defends that entrepreneurship education can enhance and develop traits that are associated with entrepreneurial success and provide skills that entrepreneurs will need latter. He also states that entrepreneurship education should be integrated and continued throughout all formal education.

Some investigations have come to support the idea that the psychological attributes, related to entrepreneurship can be culturally acquired (Gibb and Ritchie 1982). To this extent, it seems pertinent to conduct an analysis concerning the contribution of education to foment entrepreneurship. Entrepreneurship education based on a theory of solid learning can contribute to increase the knowledge management and to promote the psychological attributes associated with entrepreneurs. In this sense, Lee et al. (2006) conclude that the school and the education system play a pivotal role in predicting and developing entrepreneurial traits.

As the Green Paper on Entrepreneurship in Europe states, education plays a critical role on the development of enterprising citizens. It is believed that since the very early years of school, education and entrepreneurship should not be dissociated in order to develop entrepreneurial characteristics on a broad part of population.

The identification and study of students’ entrepreneurial characteristics assumes special relevance for the development of adequate educational programmes related with entrepreneurship and business creation. Therefore, given the high regard in which entrepreneurship is held by society (Miller et al. 2009) investigating what factors determine the entrepreneurial intention (EI) is a crucial issue in the entrepreneurship research

EI has been described as a conscious state of mind that directs attention (and therefore experience and action) toward a specific object (goal) or pathway to achieve it (means) (Bird 1989). Researchers typically draw EI to three general factors (Krueger et al. 2000): (1) person’s attitude towards the behaviour, (2) perceived social norms, and (3) person’s self-efficacy will influence intentions. Additionally, Crant (1996) defines EI as one’s judgments about the likelihood of owning one’s own business.

In previous research, personal and environment-based determinants of EI, such as personality traits, attitudes toward entrepreneurship, or social environment have been extensively discussed (Schwarz, et al. 2006; Liñán and Chen 2009; Raposo et al. 2008a; Guerrero et al. 2008). For instance, Raposo et al. (2008b) found that individuals who evidence more propensity for start-ups creation seem to possess more self-confidence and leadership capacity.

EI has proven to be a primary predictor of future entrepreneurial behaviour (Krueger et al. 2000; Schwarz et al. 2006). Nevertheless, there are just a limited number of studies addressing influence factors for EI at pre-university levels of education (Wang and Wong 2004). From this, we establish as a central question - what factors determine EI among secondary students? Accordingly, the aim of this paper is to understand what factors influence entrepreneurial intention of secondary students.

Traditional educational methodologies are likely to privilege predictability, well-defined rules, planning and stability in the classroom. These characteristics may lessen creative learning and behaviour. Understand if traditional educational methodologies of study promote EI is important in order to propose alternative methodologies which raise the students’ entrepreneurial propensity (Oosterbeek et al. 2007). Also, understand what factors influence and shape students’ intention towards starting a business is vital for developing the programmes and policies to promote entrepreneurial behaviour (Barkovic and Kruzic 2010). The present study is a cross-sectional study that focus on the intensity and the propensity for entrepreneurship in secondary students not exposed to an entrepreneurial curricula.

However, we assume that it is difficult to predict if the entrepreneurship intention detected in a certain moment of the individual´s life will accomplish him during the next years. This only could be accessed through a longitudinal study.

This study follows a cognitive approach which explores the conditions that lead to entrepreneurial behaviour. Its application is made through the application of an EI model: the Theory of Planned Behaviour (TPB) by Ajzen (1991). According to this, individuals will stimulate their entrepreneurial potential if they accept as true they have the ability, there are environmental possibilities and there is social support (Kirby 2006).

The paper is structured as follows. First, we present some theoretical background and state our hypotheses. This is followed by a description of our research conceptual model, including the sample, the measures and the analysis. Next, our findings are stated and discussed. The paper ends with final remarks referring important implications for researcher, practitioners and educators.

Literature review

The importance of entrepreneurship education

Entrepreneurship is studied and taught by a very heterogeneous group of academics. Scholars still do not share a single common paradigm and integrative framework as the basis of their work (Fayolle et al. 2006; Raposo et al. 2008a; Verduyn et al. 2007).

Miller et al. (2009) refer that entrepreneurship is an important part of the economic scenery, providing opportunities and jobs for substantial numbers of people. Policy makers believe that increased levels of entrepreneurship can be attained through education (European Commission 2006) and particularly entrepreneurship education. However, there are some differences in the terms used to in the entrepreneurship’s field of knowledge. The term “entrepreneurship education” is familiar in USA and Canada, but the term “enterprise education” is more used in United Kingdom (Kyrö 2006). In this latter case, the focus is more on enterprise creation (and then in education to be a “business man”), whereas the first is more centred in the development of an entrepreneurial spirit.

Entrepreneurship education has been described as one of the most significant achievements of the modern postsecondary educational system and a key factor in economic progress and the creation of jobs (Miller et al. 2009). Katz (2007) argues that entrepreneurship education cannot avoid failure but can diminish the risk of failure. Basically, entrepreneurship education is about creating entrepreneurship competencies, which include knowledge, skills, and abilities (Markman 2007; Miller et al. 2009).

A review of recent literature measuring the impact of general education on entrepreneurship and entrepreneurial activity suggests some possible generalisations. Evidence suggesting a positive link between education and entrepreneurship is robust. For example, Raposo et al. (2008a, 2008b) found that the most important effect on the propensity to start-up a firm among students was education. Results point out the importance of entrepreneurship education in the promotion of the EI. These conclusions have support in others studies (Brice 2004; Hmieleski and Corbett 2006). Florin et al. (2007) stated that the students need to perceive that the application of the skill is feasible and that an entrepreneurial approach is desirable and a focus on developing a positive attitude toward entrepreneurial behaviour appears to be central to entrepreneurship education.

Thus, there has been recently an increased interest from researchers about entrepreneurship education programmes (Veciana et al. 2005; Fayolle et al. 2006; Lee et al. 2006; Tang et al. 2007; Verduyn et al. 2007). The thematic is been studied in several countries and contexts.

In his research, Johansen (2007) performed a quantitative study of former participants in Junior Achievement-Young Enterprise (JA-YE) Europe programmes. Former studies of Company Programme participants from Norway and Sweden have indicated the possible relationship of participation in entrepreneurship education and later entrepreneurial activity. In Sweden, approximately 9% of former students in entrepreneurship education programmes established their own businesses. In Norway, 10% of former participants in JA-YE programmes have subsequently set up a company.

Johansen (2007) found that the start-up rate was significantly higher among participants with an “Enterprise-based” motivation (control group), so usually participants in entrepreneurship education programmes are more likely to become entrepreneurs. Former evaluations of entrepreneurship education programmes have clearly shown these programmes’ usefulness in developing young peoples’ entrepreneurial competences.

Furthermore, some works advance the idea that early formal entrepreneurship education affects the attitudes of students, influencing them in the direction of their future career, and affect their propensity for entrepreneurship when they become adults. For instance, Kourilsky and Walstad (1998) indicate that the very early stimulus of entrepreneurial attitudes, even before high school, can encourage entrepreneurship as a career option, although they have not tested this assertion empirically. Lee et al. (2006) refer that pedagogical approach should encourage children to make decisions and accept mistakes as part of the learning process. In this sense, on the education level, active experimentation should be balanced with abstract conceptualisation, contributing to infuse in the students a larger propensity to entrepreneurship.

For example, in Latin America, Postigo et al. (2006) concluded that there is a need for relevant changes in the education system in order to produce a change in the culture and values necessary to promote entrepreneurship. The Argentinean educational system usually does not promote or motivate the skills necessary for developing entrepreneurs. Students are not shaped with an entrepreneurial attitude because education and social aspiration are mostly oriented to working in big enterprises. In the last decade, this trend has started to reverse, presenting changes principally in the university education system.

Italy faces similar problems concerning entrepreneurship development and education (Postigo et al. 2006). Nevertheless, according to several surveys, Italy has one of the highest firm birth rates in European countries (Reynolds et al. 2000). In fact, entrepreneurial rates are particularly high in the North-Eastern and Central regions. In the field of entrepreneurial education, the situation in Italy is rather atypical when compared with that of North American countries and even with that of other European countries (Postigo et al. 2006).

In Portugal, the panorama is quite similar to the Spanish situation. The last national Global Entrepreneurship Monitor project report about Portugal shows Total Entrepreneurial Activity rates are especially low (round about 4%). This proportion is significantly lower than the 7.1% documented in 2001, and ranks Portugal in the last places of the EU countries in terms of entrepreneurship’s levels. But in comparison to the Spanish, the option of undertaking a business is less rejected by the Portuguese young people (Sanchez and Yurrebaso 2008).

The limited entrepreneurial spirit observed in Spain and Portugal significantly contrasts with the outlook of other regions, such as Latin America. For example, despite the legal barriers to new venture creation, Mexico is one of the more entrepreneurial countries of the world. The results of Sanchez and Yurrebaso (2008) suggest that the differences in entrepreneurial activity observed between countries such as Mexico, Spain and Portugal tend to consolidate themselves from generation-to-generation through mechanisms of social learning.

Since schools are one of the most important instruments for social learning, and entrepreneurship is one main aspect in modern societies and economies, it is important to understand how school’s curricula are adapted to develop enterprising citizens.

Model of entrepreneurial intention

Guerrero et al. (2008) identified the six main models about EI developed in this field, and they are:
  1. 1.

    Entrepreneurial event model (Shapero 1982), that considers the business creation as an event that can be explained with the interaction between initiatives, abilities, management, relative autonomy and risk;

     
  2. 2.

    Theory of planned behaviour (Ajzen 1991) with the premise that any behaviour requires a certain amount of planning and can be predicted by the intention to adopt that behaviour;

     
  3. 3.

    Entrepreneurial attitude orientation (Robinson et al. 1991) that explains the attitude prediction through four different sub-scales (achievement, self-esteem, personal control, and innovation) and three types of reactions (affective, cognitive or conative);

     
  4. 4.

    Intentional basic model (Krueger and Carsrud 1993) that examines the relationship between attitudes and entrepreneurial intentions using a scale which permits greater flexibility in the analysis of exogenous influences, attitudes and intentions;

     
  5. 5.

    Entrepreneurial potential model (Krueger and Brazeal 1994), based on the previous models of Shapero and Ajzen, supporting their evidence from the corporate venture and enterprise development perspectives;

     
  6. 6.

    Davidsson model (Davidsson 1995) that states that intention can be influenced by the conviction defined by general attitudes, domain attitudes and the current situation.

     

This research does not explore all this EI models but only issues of entrepreneurship intention within the context of the TPB (Ajzen and Fishbein 1980; Ajzen 1985; Ajzen 1991). The TBP has been used by several researchers as a framework to explore attitudes towards EI (Liñán and Chen 2009; North 1990; Kirby 2006; Miller et al. 2009; Schwarz et al. 2009; Turker and Selcuk 2008).

There is a relation between the TPB and the Theory of Reasoned Action. The latter is a theory of attitude–behaviour relationships which links attitudes, subjective norms, behavioural intentions and behaviours in a causal sequence (Ajzen and Fishbein 1980). Behaviour is a direct function of intention, which in turn is a function of attitude and subjective norm. Attitude is further deemed to be the product of the individuals’ beliefs and their evaluation of those beliefs. The subjective perception of normative influences is considered to be a “product of individuals’ beliefs that important others think they should or should not perform the behaviour in question, and their motivation to comply with these others” (Shaw and Shiu 2003:1487). Later, Ajzen (1985) extended the model to add a measure of “perceived behavioural control” forming the TPB. This concept is a direct measure that results from antecedents in the form of control beliefs.

The Ajzen (1991) TPB is considered as a relevant tool to model the development of EI through pedagogical processes and learning contexts (Fayolle et al. 2006). Ajzen (1991) considers that intentions toward target behaviour depend on a set of underlying attitudes. Particularly, intentions to take a certain course of action depend on the perceptions of participants regarding personal and social desirability of the behaviour and the perceptions of participants of whether they can successfully perform such action. TPB belongs to a larger family of international models that have been used to explain the manifestation of entrepreneurial behaviour and assumes that human social behaviour is reasoned, controlled or planned since it takes into account the likely consequences of the considered behaviour (Ajzen 1991).

According to the TPB, behaviour that entails planning can be predicted by the intention to adopt that behaviour. The TPB includes three components that predict behavioural intentions (Miller et al. 2009): (1) attitude or desire toward the proposed behaviour, as well as global positive or negative evaluations of performing a particular behaviour; (2) social and subjective norms which take into account other people’s opinions of the proposed behaviour; and (3) perceived control or feasibility of the proposed behaviour. Schwarz et al. (2009) add that according to TPB, individual’s attitudes have an impact on behaviour via intention. These authors define, in particular, three fundamental attitudinal antecedents of intent: (1) personal attitude toward outcomes of the behaviour; (2) perceived social norm; and (3) perceived behavioural control (self-efficacy).

According to Segal et al. (2005), this theory has extensive approval in many behavioural science disciplines and has been used empirically in a diversity of sceneries to predict and understand behavioural intentions. It offers a significant opportunity to amplify our capacity to understand and predict entrepreneurial activity. Furthermore, understanding intentions also helps researchers and policy makers to understand entrepreneurship-related phenomena (Barkovic and Kruzic 2010).

For Liñán and Chen (2009), it could be argued that perceptions regarding general society and external values have an influence on motivational factors determining the EI. Accordingly, Fig. 1 presents the model that will be explored in this research and that describes the attitudinal dimensions as latent variables of EI. Our contribution is the inclusion of new paths in the original model in order to improve it and to adapt it to the current problem. Circles represent the constructs in the model, and arrows represent the hypothesised relationships between two constructs.
Fig. 1

Entrepreneurial intention model

Founded in the literature, and in the results of other studies referred in the theoretical review, the model above was created, together with a set of research hypotheses, as we can see below:
  1. H1:

    Personal attitude positively influences entrepreneurial intention [PA →+ EI]

     
  2. H2:

    Perceived behavioural control positively influences entrepreneurial intention [PBC →+ EI]

     
  3. H3:

    Subjective norm positively influences entrepreneurial intention [SN →+ EI]

     
  4. H4:

    subjective norm positively influences personal attitude [SN →+ PA]

     
  5. H5:

    Subjective norm positively influences perceived behavioural control [SN →+ PBC]

     
  6. H6:

    Personal attitude positively influences perceived behavioural control [PA →+ PBC]

     

The evidences show that the first three hypotheses correspond to the traditional intention model usually used. In what concerns to H4, H5 and H6, these could contribute to the explanation of the internal antecedents.

The model presented considers a group of variables likely to influence the entrepreneurial intention and it is composed of various constructs, each one being measured by several indicators. At it can see the constructs personal attitude (PA), subjective norm (SN) and perceived behavioural control (PBC) are included in the model and, all together, will contribute to the EI. There is also a connexion between the constructs PA and PBC.

In appendix A, we present the indicators for each construct. EI indicates the effort that the person will make to carry out that entrepreneurial behaviour and includes six indicators. PA refers to the degree to which the individual holds a positive or negative personal valuation about being an entrepreneur and includes five indicators. SN refers to the perceived social pressure to carry out (or not) entrepreneurial behaviours (Ajzen 2001) and includes three indicators. PBC refers to the perception of the ease or difficulty of becoming an entrepreneur. It should also include the feeling of being able and the perception about controllability of the behaviour (Liñán and Chen 2009). This construct includes six indicators.

Methodology

For this study, the model of data collection was a survey by self-administered questionnaire with several groups of questions related to the demographic characteristics, the personal attitudes, the subjective norms, the perceived behavioural control and the entrepreneurial intention. The use of self-assessment to determine students’ entrepreneurship attitudes represents well accepted practice in field of entrepreneurship research.

Questionnaires were administered in class to two secondary student’s classes, with permission of the school director. These groups were chosen by the school to integrate an educational project—an entrepreneurial learning pilot experience1 which would be implemented in the school that year. Once the authors were invited to help in the implementation and coordination of that project, the preliminary collection of data could be a good way of monitoring the results.

After collection, the data was statistically analysed and interpreted using the statistical software Statistical Package for Social Sciences (SPSS 16.0) and the Partial Least Squares (Smart PLS) software.

Most of the studies utilising the TPB framework employed the regression analysis technique. This technique, however, does not allow a full examination of model measures in the explanation of behavioural intention and is constrained to using the only direct measures. In light of the complexity of entrepreneurial intention, it may be deemed more appropriate to use structural equation modelling.

Structural equation modelling techniques allow the evaluation of how effectively a conceptual model, which includes observed variables and hypothetical constructs, fits the obtained data (Hoyler and Smith 1994). The structural equation modelling procedure seeks to explain the structure or pattern among a set of latent constructs, which are measured by one or more indicators.

Table 1 shows the main methodological aspects related to the investigation.
Table 1

Synthesis of methodological aspects

Time Basis

Cross-section

Sampling unit

Secondary students

Sample

74 individuals

Response rate

100%

Research method

Self-administered questionnaire

Statistical analysis

Bivariate, multivariate—PLS

Results

Questionnaires were administered to two secondary student’s classes, aged between 14 and 15 years old. 47.3% were female, and the average age was 14.3 years. None of the questionnaires presented missing values.

We divided our analysis in three parts: the descriptive analysis, the reliability and validity analysis and the structural analysis (PLS modelling).

Descriptive analysis

The descriptive statistics of the summated scales, as well as the results of one-sample t test, are presented in Table 2.
Table 2

Descriptives of summated scales and t-tests

 

Minimum

Maximum

Mean

SD

t

Sig.

Entrepreneurial intention (EI)

1.167

4.500

2.824

0.614

−2.462

0.016

Personal attitude (PA)

2.000

4.600

3.278

0.577

4.150

0.000

Subjective norms (SN)

1.667

5.000

3.761

0.630

10.389

0.000

Perceived control behaviour (PBC)

1.833

4.667

3.131

0.505

2.225

0.029

The scales used to measure the phenomena were Likert scales (min 1, max 5), where 3 is the indifference value. Values below 3 (the median point of the scale) represent somewhat negative values in the scale, and above 3 are the positive values.

It should be noticed that EI has the lower mean of the four scales, but also the one of the larger standard deviations, meaning that the group is heterogeneous in what respects to EI. This scale has the largest range (3.33) along with SN. Subjective norms have the largest mean value; nevertheless, as will be shown later, this construct is not directly related to EI in this specific sample.

The scales PA, SN and PBC have scores significantly bigger than 3, although not very far from that value, being all of them lesser than 4.

Reliability and validity analysis

According to Nunnally (1978), reliability and validity are essential psychometrics to be reported. The first step to evaluate those aspects was to use the Cronbach’s alpha and the composite reliability to test reliability of the proposed scales. The usual threshold level is 0.7 for newly developed measures (Nunnally 1978). Values range from 0.69 to 0.79 in the case of Cronbach’s alpha, and from 0.66 to 0.78 in the case of composite reliability (Table 3). Therefore, these scales may be considered as reliable.
Table 3

Reliability measures

Construct

Composite reliability

Cronbachs alpha

EI

0.78

0.79

PA

0.71

0.70

PBC

0.66

0.69

SN

0.66

0.79

To access discriminant validity, we used correlations among indicators and constructs. Items should have higher correlation with their own construct than with any one other, signifying that they are perceived by respondents as fitting in that theoretical construct (Messick 1988). According to the results presented in Table 4, all indicators correlate higher with their own construct than with any other.
Table 4

Cross-loadings

 

EI

PA

PBC

SN

EI1

0.551

0.351

0.250

0.029

EI2

0.547

0.414

0.204

0.085

EI3

0.521

0.408

0.379

0.258

EI4

0.629

0.550

0.358

0.177

EI5

0.636

0.421

0.305

0.078

EI6

0.763

0.522

0.394

0.340

PA1

0.326

0.394

0.338

0.261

PA2

0.252

0.438

0.251

0.144

PA3

0.539

0.774

0.301

0.299

PA4

0.557

0.716

0.389

0.235

PA5

0.400

0.517

0.206

0.052

PBC1

0.304

0.226

0.473

0.026

PBC2

0.184

0.242

0.491

0.150

PBC3

0.336

0.266

0.579

0.186

PBC4

0.130

0.071

0.432

−0.012

PBC5

0.308

0.308

0.639

0.198

PBC6

0.217

0.327

0.352

0.204

SN1

0.177

0.150

0.142

0.407

SN2

0.192

0.246

0.185

0.765

SN3

0.181

0.270

0.211

0.693

EI

1.000

0.737

0.524

0.281

PA

0.737

1.000

0.517

0.358

PBC

0.524

0.517

1.000

0.284

SN

0.281

0.358

0.284

1.000

Structural analysis

The division of a model implies a measurement model and a structural model. The measurement model refers to the indicators and/or sub-constructs that reflect the relevant constructs, while the structural model addresses the relationships between constructs.

Due to the fact that entrepreneurial intention is not a directly observable variable, an analysis based on structural equations is considered adequate. This modelling technique allows incorporating not directly observable variables (latent variables or constructs) to the models. The constructs may be measured by indicators or even by sub-constructs.

Firstly, the estimation of the model is performed by computing the latent variables through an iterative procedure that requires the regression of the variables of the outer and inner models, with the parameters of one part of the model being fixed while estimating those of the other part. After this initial step, the relationships of the outer and inner models are estimated through OLS non-iterative regression. The quality of the model is determined by the observation of the R2, or by the Stone–Geisser test, and by the significance of the structural relationships using the Jackknife and Bootstrap techniques (Chin 1998).

The measurement model is composed by twenty indicators which measure four constructs. Constructs may be measured by reflective indicators and/or formative indicators. In our model, all the indicators are of reflective nature, which mean that they measure the same construct and represent the construct’s visible part.

To test the weights’ significance we used the bootstrapping technique, which consists in generating a large number of sub-samples from the original sample through the systematic deletion of observations. The model is recomputed for each sub-sample, and the resulting weights are averaged. The resulting mean of weights is compared with the original weight. In this case 1,000 valid sub-samples were extracted. Results of the final model are shown in Table 5.
Table 5

Bootstrapping results

Path

Original sample

Sample mean

Standard deviation

Standard error

t Statistics

Sig.

PAEI

0.636

0.632

0.065

0.065

9.859

0.000

PAPBC

0.517

0.533

0.079

0.079

6.513

0.000

PBCEI

0.195

0.204

0.087

0.087

2.243

0.028

SNPA

0.358

0.361

0.112

0.112

3.186

0.002

1,000 bootstrap samples

The paths SN → PBC and SN → EI were considered non significant and successively excluded from the original model (see Appendix B).

According to Chin (1998), relationships between constructs with structural coefficients bigger than 0.2 it should be considered as being robust. It should be noted that the total effect of an independent variable over a dependent variable is bigger than the direct effect, because of the indirect effects. The direct, indirect and total effects on the EI are shown in Table 6.
Table 6

Effects

Path

Direct Effect

Indirect effect

Total effect

SN→EI

n.s

0.264

0.264

PA→EI

0.636

0.101

0.737

PBC→EI

0.195

0.195

SNPA

0.358

0.358

SNPBC

n.s

0.185

0.185

PAPBC

0.517

0.517

n.s. Non-significant with α = 0.05

There are three structural coefficients (direct effects) with absolute value bigger than 0.2—the effect of “Personal Attitude” on “Entrepreneurial Intention”, the effect of “Subjective Norms” on “Personal Attitude” and the effect of “Personal Attitude” on “Perceived Behavioural Control”.

The analysis of the total effects shows that “Subjective Norms” and “Personal Attitude” have a total effect over “Entrepreneurial Intention” bigger than 0.2. “Perceived Behavioural Control” has a total effect on “Entrepreneurial Intention” very close to the threshold value of 0.2, and should not be neglected due to the exploratory nature of the study.

Personal Attitude has the most important effect on EI (0.737), with a very large positive value. Subjective norms, despite not having a direct effect on EI, have an indirect effect over 0.2. As for perceived behaviour control, there is no significant direct effect either, but total effect is very close to the threshold value of 0.2.

In order to complete the model evaluation it is necessary to assess its explanatory capacity, given by the proportion of the total variance of each endogenous variable explained by the model, the R2 statistic (Table 7).
Table 7

Explained variance

Endogenous constructs

R2

EI

0.571

PA

0.128

PBC

0.267

This model explains 57.1% of the variance in entrepreneurial intention based on PA and PBC. According to Liñán and Chen (2009), this result is highly satisfactory, since most previous research using linear models typically explain less than 40%. The model also explains 12.8% of the variance in PA and 26.7% of PBC. These results concur with the ones obtained by Liñán and Chen (2009) using a similar model.

The significance of structural coefficients and the magnitude of direct effects allow testing the research hypotheses. Results are as follow.
  1. H1:

    PA →+ EI—supported

     
  2. H2:

    PBC →+ EI—supported

     
  3. H3:

    SN →+ EI—partially supported2

     
  4. H4:

    SN →+ PA—supported

     
  5. H5:

    SN →+ PBC—partially supported3

     
  6. H6:

    PA →+ PBC—supported

     
Figure 2 presents the final model. The unsupported relationships are not shown on this final model. Next to the arrows (supported relationships) are direct effects (Table 6) and explained variances of endogenous (dependent) constructs are shown inside the circles.
Fig. 2

Final structural model

Conclusions

In this study, we seek the answer to the research question related to what factors determine entrepreneurial intention among secondary students. In order to obtain some explanations for that, an entrepreneurial intention model based on the Azjen’s theory of planned behaviour was applied. This theory was considered an appropriate tool to model the development of EI through pedagogical processes and learning contexts.

Intention is considered the single best predictor of behaviour (Ajzen 1991). In turn, the intention of carrying out entrepreneurial behaviours may be affected by several factors, such as needs, values, wants and beliefs (Bird 1989; Liñán and Chen 2009), as well as the motivational “antecedents” (Ajzen 1991).

Although moving away from the traditional TPB structure as supported by the literature, the adoption of a conceptually acceptable structure for this context has resulted in a model which is better able to explain EI; although it must be noted that one path—SN to EI—remains non-significant. Nevertheless, the total effect is 0.264. Also, the introduction of the path SN to PBC in the original model presents a non significant structural coefficient, but its total effect is 0.185.

Regarding the pattern of relationships showed in the model, one important concern is the traditionally weak role of subjective norm in the TPB. However, in the area of entrepreneurship, this weakness is not so clear. Some authors choose to simply omitted subjective norm (e.g. Veciana et al. 2005), while others found it to be non-significant (e.g. Krueger et al. 2000). However, some studies found SN to significantly explain EI (e.g. Kolvereid and Isaksen 2006). Although there is support for the idea that a direct SN–EI relationship might be established, some controversy remains.

The results also confirmed that personal attitudes are very important to explain the entrepreneurial intention. So the education and training should centre itself much more in changing/stimulate personal attitudes than in provide technical knowledge about businesses, because the effects could be more significant to the process of business creation and to overcome the perceived barriers to entrepreneurship.

However, it is desirable that an entrepreneurship educational programme could also contribute to the development of competences related to entrepreneurship, social and civic skills, communication in a foreign language, mathematical and accounting capacities, digital competences, creative and artistic skills, and cultural awareness.

As it was possible to observe, the extracted variance is less than 0.5 in the two exogenous constructs. This can be considered a limitation of the study, probably associated to some problem of the measure model. In this sense, it is necessary to apply this methodology to different samples. So, we recommend the test of the model here presented in other populations, as well as the development of new indicators in order to fully understand how entrepreneurial intention help determine start-up decisions.

Having in mind the invitation of Ajzen (1991)to consider additional model variables to the traditional TPB structure, in future we could consider the addition of other measures to this model, as the socio demographic and some psychological variables.

For example, Frese (2000), after conducting a series of studies in Tanzania, Uganda, Zambia, Zimbabwe and South Africa, concluded that some psychological variables as innovativeness, autonomy and entrepreneurial orientation were found to be relevant for successful entrepreneurship in Africa. Additionally, Hancock and Fitzsimons (2004), in their study, founded that in South Africa the formal education system contributes a lot to the development of entrepreneurial traits. The authors recommended the reorientation of the formal entrepreneurship education system in order to encourage an enterprise culture.

The expansion of the present study to other countries could be also interesting, as well as the creation of multicultural groups. For example, the study of Dominguinhos et al. (2008) analysed the promotion of an education experience through the creation of multicultural groups, including students from several nationalities (Portugal, Spain, Belgium, Netherlands, Poland and Latvia). They presented an experience developed and implemented in three different business schools in Portugal, Belgium and Latvia. The results allow authors to say that participants, from different countries, enhanced entrepreneurial competencies due to their participation in active methodologies, where their potential was explored and encouraged. These results are aligned with other studies that demand for more experimental, problem solving and active learning activities in entrepreneurship education. The results are consistent across nationalities. Moreover, students are open to these methodologies and recognise that their potential is well explored.

Being this a cross-sectional study, and assuming the limitations of such results concerning entrepreneurial action overtime, we also propose a longitudinal study for futures research, concerning both the results after implementing an entrepreneurial curriculum (1 year later) and after a long term period (for instance in the adult phase, 10 or 15 years later).

Footnotes

  1. 1.

    This educational experience will be based on an extensive network of “mini-companies” exchanging information, catalogues and products. It will include all stages to the creation, development and dissemination of a cooperative inside the school, where the students will have the opportunity to interact with another national or foreign school. In this particular case, the Portuguese students had to interchange ideas and commercialise their products with a Spanish school. So, this methodology will be based on a practical experience where students will have the opportunity to display a wide array of social, personal and business skills

  2. 2.

    Structural coefficient non-significant, but total effect of 0.264

  3. 3.

    Structural coefficient non-significant, but total effect of 0.185

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Arminda M. Finisterra do Paço
    • 1
  • João Matos Ferreira
    • 1
  • Mário Raposo
    • 1
  • Ricardo Gouveia Rodrigues
    • 1
  • Anabela Dinis
    • 1
  1. 1.Department of Business and Economics, Research Unit NECEUniversity of Beira InteriorCovilhãPortugal

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