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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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