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ENTREPRENEURIAL INTENTION AMONG SECONDARY STUDENTS: FINDINGS

FROM PORTUGAL

Arminda do Paço (apaco@ubi.pt)

João Ferreira (jjmf@ubi.pt)

Mário Raposo (mraposo@ubi.pt)

Ricardo Gouveia Rodrigues (rgrodrigues@ubi.pt)

Anabela Dinis (adinis@ubi.pt)

University of Beira Interior, Department of Business and Economics, Research Unit NECE

Estrada do Sineiro, 6200-209 COVILHÃ, PORTUGAL

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 (TPB). This theory is considered as

a relevant tool to model the development of entrepreneurial intention through pedagogical

processes and learning contexts. Using a sample of students aged between 14 and 15 years old, it

was administrated a questionnaire based on the Liñán and Chen’s Entrepreneurial Intention

Questionnaire (EIQ). Data was collected before the entrepreneurship education programme. The

purpose is to test a model of entrepreneurial intention using structural equations, before the

educational experience.

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INTRODUCTION

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; Ferreira et al., 2007; Verduyn et al., 2007). Some investigations have come

to support the idea that the psychological attributes, related to entrepreneurship can be culturally

acquired (Gibb and Ritchie, 1982, Vesper, 1990). 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.

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, investigating what factors determine the

Entrepreneurial Intention (EI) is a crucial issue in the entrepreneurship research. For instance

Raposo et al. (2006; 2008b) found that individuals who evidence more propensity for the start-

ups creation seem to possess self-confidence and leadership capacity. Lee et al. (2006) conclude

that the school and the education system play a pivotal role in predicting and developing

entrepreneurial traits.

Entrepreneurial Intention 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.,

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2000): (i) person’s attitude towards the behaviour; (ii) perceived social norms; and (iii) person’s

self-efficacy will influence intentions.

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, 2007; Ferreira et al., 2007; Raposo et al., 2008a,

Guerrero et al., 2008). Entrepreneurial Intention has proven to be a primary predictor of future

entrepreneurial behaviour (Reynolds, 1995; Krueger et al., 2000; Schwarz et al., 2006).

Nevertheless, there have been just a limited number of studies addressing influence factors for EI

of the secondary students.

A central question that arises is what factors determine EI among 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. An

alternative methodology was needed to raise the students’ entrepreneurial propensity

(Oosterbeek et al., 2007; Rodrigues, 2007).

This study follows a cognitive approach through the application of an Entrepreneurial Intention

model. The paper is structured as follows. First, we give some theoretical background and state

our hypothesis. This is followed by a description of our research conceptual model, including the

sample, the measures, and the analysis, and also the presentation of our findings are stated. The

paper ends with final remarks referring important implications for researcher, practitioners and

educators.

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LITERATURE REVIEW

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, Ferreira et al. (2007) and

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 (Kennedy

et al., 2003; Brice, 2004; Bhandari, 2006; Li, 2006; Hmieleski and Corbett, 2006; Florin et al.,

2007). Florin et al. (1993) 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.

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.

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Thus, there has been recently an increased interest from researchers about entrepreneurship

education programmes (Veciana et al., 2005; Chand and Amin-Choudhury, 2006; Fayolle et al.,

2006; Lee et al., 2006; Brodie and Laing, 2007; Frank et al., 2007; Man and Yu, 2007; Pihie,

2007; Tang et al. 2007; Verduyn et al., 2007). Fayolle et al. (2006) refer about the importance to

develop a common framework to evaluate, compare and improve the design of educational

programmes of entrepreneurship.

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

are:

(i) 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;

(ii) Theory of Planned Behaviour (Ajzen, 1991) with the premise that any behaviour requires

a certain amount of planning and it can be predicted by the intention to adopt that

behaviour;

(iii) 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);

(iv) Intentional Basic Model (Krueger and Carsrud, 1993) that examine the relationship

between attitudes and entrepreneurial intentions using a scale to permit greater flexibility

in the analysis of exogenous influences, attitudes and intentions;

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(v) 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;

(vi) Davidsson Model (Davidsson, 1995) intention can be influenced by the conviction

defined by general attitudes, domain attitudes and the current situation.

In the next section the model about EI used in this paper, based in the Theory of Planned

Behaviour, will be explained.

Model of Entrepreneurial Intention

As a result of the literature review, we support our research based on Liñán and Chen’s model

(2007). This model is sustained by Ajzen’s (1991) approach and some propositions from

institutional economy theory (North, 1990). The Azjen’s (1991) Theory of Planned Behaviour

(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. The TPB is part of larger family of international models that have been

used to try to explain the mergence of entrepreneurial behaviour and it assumes that human

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social behaviour is reasoned, controlled or planned in the sense that it takes into account the

likely consequences of the considered behaviour (Ajzen, 1991).

According to Liñán and Chen (2007), it could be argued that perceptions regarding general

society and environment values do have an influence on motivational factors determining the EI.

Figure 1 presents the model that will be explored in this research and it describes the attitudinal

dimensions as latent variables of EI.

Figure 1. Entrepreneurial Intention model

The model above 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 Entrepreneurial

Intention (EI). There is also a connexion between the constructs PA and PBC. The construct PA

H1

H2

H3

H6 H4

H5 PA – Personal Attitude SN – Subjective Norm PBC – Perceived Behavioural ControlEI – Entrepreneurial Intention

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includes five indicators; the construct SN includes three indicators; the construct PBC includes

six indicators; the construct EI includes six indicators (see Annex A).

In order to test the Entrepreneurial Intention Model (Figure 1), a set of research hypothesis were

formulated, as we can see below:

H1: Personal Attitude positively influences Entrepreneurial Intention [PA �+ EI]

H2: Perceived Behavioural Control positively influences Entrepreneurial Intention [PBC �+ EI]

H3: Subjective Norm positively influences Entrepreneurial Intention [SN �+ EI]

H4: Subjective Norm positively influences Personal Attitude [SN �+ PA]

H5: Subjective Norm positively influences Perceived Behavioural Control [SN �+ PBC]

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 and H5, these would explain the internal antecedents.

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

questionnaire is based on the existing theoretical and empirical literature about the application of

the TPB to entrepreneurship.

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Questionnaires were administered in class, with permission from the school director and with the

collaboration of the two secondary student’s classes, aged between 14 and 15 years old, who will

participate in an entrepreneurial learning pilot experience.

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. So, this methodology will be

based on practical experience where students will have the opportunity to display a wide array of

social, personal and business skills.

After collection, the data was statistically analysed and interpreted using the statistical software

SPSS 16.0 (Statistical Package for Social Sciences). The PLS (Partial Least Squares) technique

was also used to test the model recurring to the Smart PLS software. This method consists of a

statistical modelling-based technique through structural equations that allows for the

simultaneous estimation of a group of equations, by measuring the concepts (measurement

model) and the relationships between them (structural model), and it has the capacity to address

concepts not directly observable.

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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

Total sample size was 74 secondary students. None of the questionnaires presented missing

values. 47.3% were female, and the average age was 14.3 years.

According to Nunnally (1978) reliability and validity are essential psychometrics to be reported.

The first step was using Cronbach’s alpha and 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 2). Therefore, these scales may be considered as reliable.

Table 2. 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

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To access discriminant validity we used correlations among indicators and constructs. Items

should have higher correlation with their own construct than with any other, signifying that they

are perceived by respondents as fitting in that theoretical construct (Messick, 1988). According

to the results presented in Table 3, all indicators correlate higher with their own construct than

with any other.

Table 3. Crossloadings

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

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Structural Analysis

The division of a model implies a measurement model and a structural model (Anderson and

Gerbing, 1988). 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 a not directly an 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 (Duarte, 2005;

Raposo et al., 2008a; Rodrigues et al., 2008). In our model all the indicators are of reflective

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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 1000 valid sub-samples were extracted. Results of the final model are shown in Table 4.

Table 4. Bootstrapping results

Path Original

Sample

Sample

Mean

Standard

Deviation

Standard

Error T Statistics Sig.

PA � EI 0,636 0,632 0,065 0,065 9,859 0,000

PA � PBC 0,517 0,533 0,079 0,079 6,513 0,000

PBC � EI 0,195 0,204 0,087 0,087 2,243 0,028

SN � PA 0,358 0,361 0,112 0,112 3,186 0,002

1000 bootstrap samples

The paths SN � PBC and SN � EI were considered non significant and successively excluded

from the original model (see Annex 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

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indirect effects (Raposo et al, 2008; Rodrigues et al., 2008). The direct, indirect and total effects

on the EI are shown in Table 5.

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.

Table 5. 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

SN � PA 0,358 - 0,358

SN � PBC n.s 0,185 0,185

PA � PBC 0,517 - 0,517

n.s. non significant with α=0.05

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

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for Perceived Subjective Norms, 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 6).

Table 6. Explained variance

Endogenous Constructs R Square

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 (2007), 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 (2007) using a similar model.

The significance of structural coefficients and the magnitude of direct effects allow testing the

research hypotheses. Results are as follow.

H1: PA �+ EI – Supported

H2: PBC �+ EI – Supported

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H3: SN �+ EI – Partially Supported1

H4: SN �+ PA – Supported

H5: SN �+ PBC – Partially Supported2

H6: PA �+ PBC – Supported

Figure 2 presents the final model, with the direct effects and explained variances of endogenous

constructs. Two paths were excluded from the initial model (Figure 1).

Figure 2. Final structural model

1 Structural Coefficient non significant, but total effect of 0.264

2 Structural Coefficient non significant, but total effect of 0.185

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CONCLUSIONS

In this study we seek the answer to the research question related to what factors determine EI

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.

Having in mind that Lündstrom and Stevenson (2001), states that the entrepreneurial process

begins before the start-up process, it seems important that educational policies should be directed

to create new attitudes among young students and to the creation of pedagogical materials related

with entrepreneurship education. The results of this research confirmed that supposition, because

personal attitudes are very important to explain the entrepreneurial intention.

So the education and training should centre itself much more in changing personal attitudes than

in knowledge, because the effects could be more significant to the process of business creation

and to overcome the perceived barriers to entrepreneurship.

More, it is desirable that an entrepreneurship educational programme could 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.

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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. This is the subject of ongoing research by the authors.

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ANNEX A - Variables

Personal Attitude (PA)

Indicate your level of agreement with the following sentences from 1 (total disagreement) to 7 (total agreement).

a. Being an entrepreneur implies more advantages than disadvantages to me

b. A career as entrepreneur is attractive for me

c. If I had the opportunity and resources, I’d like to start a firm

d. Being an entrepreneur would entail great satisfactions for me

e. Among various options, I would rather be an entrepreneur

Subjective Norm (SN)

If you decided to create a firm, would people in your close environment approve of that decision? Indicate from 1 (total disapproval) to 7 (total approval).

a. Your close family

b. Your friends

c. Your colleagues

Perceived Behavioral Control (PBC)

To what extent do you agree with the following statements regarding your entrepreneurial capacity? Value them from 1 (total disagreement) to 7 (total agreement).

a. To start a firm and keep it working would be easy for me

b. I am prepared to start a viable firm

c. I can control the creation process of a new firm

d. I know the necessary practical details to start a firm

e. I know how to develop an entrepreneurial project

f. If I tried to start a firm, I would have a high probability of succeeding

Entrepreneurial Intention (EI)

Indicate your level of agreement with the following statements from 1 (total disagreement) to 7 (total agreement)

a. I am ready to do anything to be an entrepreneur

b. My professional goal is to become an entrepreneur

c. I will make every effort to start and run my own firm

d. I am determined to create a firm in the future

e. I have very seriously thought of starting a firm

f. I have the firm intention to start a firm some day

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ANNEX B – Bootstrapping results

Model A

Path Original

Sample

Sample

Mean

Standard

Deviation

Standard

Error

T

Statistics Sig.

PA -> EI 0,636 0,632 0,079 0,079 8,040 0,000

PA -> PBC 0,477 0,494 0,087 0,087 5,460 0,000

PBC -> EI 0,193 0,200 0,087 0,087 2,211 0,030

SN -> EI 0,003 0,010 0,093 0,093 0,031 0,975*

SN -> PA 0,357 0,364 0,117 0,117 3,047 0,003

SN -> PBC 0,119 0,110 0,111 0,111 1,069 0,288

* excluded path

Model B

Path Original

Sample

Sample

Mean

Standard

Deviation

Standard

Error

T

Statistics Sig.

PA -> EI 0,637 0,634 0,065 0,065 9,877 0,000

PA -> PBC 0,477 0,493 0,082 0,082 5,806 0,000

PBC -> EI 0,194 0,203 0,089 0,089 2,165 0,034

SN -> PA 0,358 0,362 0,119 0,119 3,006 0,004

SN -> PBC 0,118 0,111 0,111 0,111 1,061 0,292*

* excluded path

Model C

Path Original

Sample

Sample

Mean

Standard

Deviation

Standard

Error

T

Statistics Sig.

PA -> EI 0,636 0,632 0,065 0,065 9,859 0,000

PA -> PBC 0,517 0,533 0,079 0,079 6,513 0,000

PBC -> EI 0,195 0,204 0,087 0,087 2,243 0,028

SN -> PA 0,358 0,361 0,112 0,112 3,186 0,002

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