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administrative
sciences
Article
The Impact of Entrepreneurial Education on Technology-Based
Enterprises Development: The Mediating Role of Motivation
Leo-Paul Dana 1, * , Mehdi Tajpour 2, Aidin Salamzadeh 3, * , Elahe Hosseini 4and Mahnaz Zolfaghari 5
Citation: Dana, Leo-Paul, Mehdi
Tajpour, Aidin Salamzadeh, Elahe
Hosseini, and Mahnaz Zolfaghari.
2021. The Impact of Entrepreneurial
Education on Technology-Based
Enterprises Development: The
Mediating Role of Motivation.
Administrative Sciences 11: 105.
https://doi.org/10.3390/admsci11040105
Received: 1 August 2021
Accepted: 10 September 2021
Published: 22 September 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
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Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
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Attribution (CC BY) license (https://
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4.0/).
1Rowe School of Business, Dalhousie University, Halifax, NS B3H 4R2, Canada
2Department of Corporate Entrepreneurship, Faculty of Entrepreneurship, University of Tehran,
Tehran 1439813141, Iran; Tajpour@ut.ac.ir
3
Department of Business Management, Faculty of Management, University of Tehran, Tehran 141556311, Iran
4
Department of Business Administration, Faculty of Economics, Management & Accounting, Yazd University,
Yazd 8915818411, Iran; elahe.hosseini@stu.yazd.ac.ir
5Department of Educational Administration and Planning, Faculty of Psychology and Education, University
of Tehran, Tehran 141556311, Iran; mahnaz.zolfaghari@ut.ac.ir
*Correspondence: lp762359@dal.ca (L.-P.D.); Salamzadeh@ut.ac.ir (A.S.)
Abstract:
Technology-based enterprises play a paramount role in blooming a country economically.
Nevertheless, according to a society’s capacity to launch such enterprises in various eras, their volume
is less than expected in many economies. Therefore, establishing such enterprises is necessary for
developing any country, although its innovation system contributes to establishing them. This paper
considers the impact of entrepreneurial education on technology-based enterprise development,
including motivation as a mediator variable, in Esfahan Scientific and Industrial Town. Despite
much research investigating the correlation between entrepreneurial education and technology-based
enterprises’ progress, it seems that no study has already considered this correlation with remarking
the motivation as a mediator variable. This applied research follows a quantitative research design.
The statistical population includes 500 enterprises in the Esfahan Scientific and Industrial Town,
and for sampling, Cochran’s formula was applied (n = 217). Additionally, the researcher-made
questionnaire and PLS3 software were used for data gathering and analysis. The results demon-
strated that entrepreneurial education elements (including entrepreneurial skill, entrepreneurial
learning, and entrepreneurial intention) positively affect technology-based enterprises’ development,
considering motivation as a mediator variable. However, the impact of entrepreneurial intention
on technology-based enterprises was not supported. It reveals that the entrepreneurial intention
of motivated individuals could have a meaningful effect on the development of technology-based
enterprises. Therefore, motivation is a critical issue to be considered by managers and policymakers
while considering entrepreneurial education-related policies and initiatives.
Keywords:
entrepreneurial education; entrepreneurial intention; motivation; development of
technology-based enterprises
1. Introduction
In today’s hectic life, changes in enterprises’ environment cause a change in their
attitudes (Tajpour et al. 2021a). Furthermore, entrepreneurship is one of the essential
elements in economic development, and it has a significant effect on raising job oppor-
tunities, efficiency improvement, and enhancing the welfare in the scale of the econ-
omy and society (Hosseini et al. 2020a). Besides, the government should dedicate its
resources to growing entrepreneurial education and consequently develop its potential to
improve entrepreneurial activities (Karimi et al. 2010). Based on the entrepreneurship liter-
ature review, entrepreneurial education can improve entrepreneurs’ ability (
Fayolle 2018
;
Tajpour et al. 2020a
). Educational activities positively affect individuals and teams, mainly
through providing incentives and attitudes (Aguinis and Kraiger 2009). Additionally,
Adm. Sci. 2021,11, 105. https://doi.org/10.3390/admsci11040105 https://www.mdpi.com/journal/admsci
Adm. Sci. 2021,11, 105 2 of 17
entrepreneurial education is crucial for solving the unemployment problems among youth
and adults (Sondari 2014). Students might tend to initiate new business models, based
on this approach (Jaafar and Abdul Aziz 2008). Hence, one of the most vital aims in
entrepreneurial education is to facilitate the path and motivate the target population to
make them confident to start a business (Karhunen et al. 2008). One of the critical points is
that the universities have a paramount role in improving entrepreneurship since they can
boost incentives and competition among their graduate students and turn them into solid
assets to increase entrepreneurial activities (Askun and Yıldırım 2011). Entrepreneurial
motivation results from the consensus of positive intuition in entrepreneurs, making them
accomplish the entrepreneurial process and create worth by establishing a new product or
service (Murnieks et al. 2020). Recently, developing technology-based enterprises has led
to a variety of innovative products. In that case, by eliminating the barriers and extending
corporations, enterprises’ activities could be developed.
Increased foreign investments, active supporting associations, and preparing the con-
text for pioneer businesses led to the launching of technology-based enterprises in Iran
(Salamzadeh and Kesim 2017)
. In light of the importance of entrepreneurship, different coun-
tries, including Iran, aim to constitute and expand entrepreneurial institutions, which helps
them identify and train entrepreneurial persons in various fields (Rezaei et al. 2017). Thus, this
research investigates the impact of entrepreneurial education on technology-based enterprises
considering motivation as a mediator variable in Esfahan Scientific and Industrial Town. The
central premise of this topic is that entrepreneurial education affects technology-based enter-
prise development and, consequently, our propensity to start a business. The article fills the
research gap in the broadly defined entrepreneurial education, derived from technology-based
enterprises development, which is currently one of the most dynamically developing research
areas. Unfortunately, relatively few researchers have investigated the relationship between
entrepreneurial education on technology-based enterprises development. The article enhances
our understanding of entrepreneurial education on technology-based enterprises develop-
ment. Thus, we expect to provide a new perspective on entrepreneurial education. Therefore,
we set the article’s aim to empirically examine the impact of entrepreneurial education on
technology-based enterprises development.
The manuscript is structured as follows. First, in the literature review, the related hy-
potheses are defined, and based on them, the conceptual framework is extracted. Secondly,
by the exploitation of an applied research method, data analysis is done. Finally, the paper
concludes with some remarks and directions for future research.
2. Literature Review
By creating new opportunities, entrepreneurship has a fundamental role in societies’
economic and livelihood development (Chitsaz et al. 2019). Above all, most countries
attempt to improve the entrepreneurial education rate accordingly
(Raposo and Paço 2011)
.
Entrepreneurial education is short-term training that includes required skills for initi-
ating and establishing an enterprise so that its value will be created after a short time
(
Järvi 2012
;Shinato et al. 2013;Tajpour et al. 2020b). Additionally, entrepreneurial ed-
ucation aims to provide (potential) entrepreneurs with the required knowledge, skills,
and motivations and, consequently, enhance entrepreneurs’ possibility of success. Re-
searchers present entrepreneurial education through an active approach, and within this,
they focus on different criteria like educational standards, teaching methods, educator’s
capability, courses and labs, and in the end, the educational resources (Valerio et al. 2014).
Based on the previous research, entrepreneurial education positively affects individuals’
intention to be entrepreneurs in the future, and as soon as there would be possibilities
for self-employment, they select their career path as entrepreneurs (Axelsson et al. 2015).
Traditional entrepreneurship approaches neglect the uncertainty and ambiguity processes;
therefore, there is a necessity to propound the entrepreneurial activities (Higgins et al. 2013).
Additionally, using novel educational attitudes can transfer entrepreneurial content to
individuals’ mindsets in different environments (Tajpour et al. 2018a).
Fayolle et al. (2021)
Adm. Sci. 2021,11, 105 3 of 17
emphasized the role of entrepreneurship education as a focal point in promoting en-
trepreneurship awareness and entrepreneurial behavior, which he asserts plays an essential
role in shaping entrepreneurial intentions and increases the potential to undertake startups
to plan their growth strategies. Therefore, entrepreneurship education is not simply a
means to empower individuals to engage in risk-taking, but is also a way to foster a culture
of risk-taking and even policy environments that reward or support risk-taking. By pouring
over the previous researches, many experts and practitioners have reached consensus on
the methods of entrepreneurial teaching, including group discussions, lecturing, preparing
an action plan for the enterprising, case studies, mentoring by a genuine entrepreneur,
scientific visit methods, educational workshops, storytelling for entrepreneurial experi-
ences, and role-playing method (Lonappan and Devaraj 2011). Despite remarking massive
research in entrepreneurship, there is not a vast compromise related to the essential enter-
prise’s elements already; thus, many experts assume this field as an overlooked domain
(Lee 2010)
. Indeed, entrepreneurial education does not mean creating new tools or starting
new businesses, but it includes each attempt to eliminate the barriers that might affect the
entrepreneur’s motivation (Otuya et al. 2013).
Therefore, one of the most significant aims for entrepreneurial education is develop-
ing the motivational stimulus to make individuals start enterprises (
Karhunen et al. 2008
;
Tajpour et al. 2021b
). Many researchers believe that self-motivation is an essential (if not the
most important) factor resulting in higher entrepreneurial intentions
(Bigos and Michalik 2020)
.
Intrinsic and extrinsic motivations are also affected by the context in which the individuals
are entered. Although poorly explaining entrepreneurial intention, social norms are found to
either hinder or enhance an individual’s intrinsic or extrinsic motivations in undertaking a
task, and this reasoning also applies to entrepreneurial motivations (Antonioli et al. 2016). En-
trepreneurial motivation is associated with innovation, a passion for establishing, and a desire
to develop (Cardon et al. 2009). From the vantage point of some researchers, the most critical
factors in raising motivation are a desire for success, a passion for being autonomous, and an
intention to achieve high socio-economic levels (Acs and Terjesen 2013;
Hosseini et al. 2020b
).
In particular, motivations may play a role in explaining how entrepreneurial intentions are
formed. Thus, it has been suggested that different motivations may lead to varying lev-
els of personal attitude, subjective norm and perceived behavioral control and, through
them, to distinct entrepreneurial intentions (Fayolle et al. 2014). Some experts have investi-
gated the essential practical agents for developing an innovative technology-based enterprise
(Tajpour and Hosseini 2020)
. They claim these enterprises’ success factors are their awareness
of employing innovation, their unique organizational atmosphere, and the entrepreneur’s role
as a leader (Groenewegen and Langen 2012). A successful technology-based enterprise has the
potential for growing itself; that is to say, it can develop itself even with few human resources
or even in an inappropriate context and have more opportunities compared to traditional
companies (Blank 2012;Tajpour et al. 2019). Hence, more practical experiences for many years,
scanning the business strategy analytics of serious competitors, following an active marketing
approach, having a business model, using innovation as an idea for developing the enterprise,
and risk-taking are essential elements for the prosperity of an enterprise (Brem 2011).
Moreover, human resources are becoming more significant in an enterprise’s success, and
motivation became the essential element for entrepreneurs (Menkveld 2012). Therefore, the
initial idea, strategy, motivation, team members’ commitment, specialty, and marketing are
the vital agents for expanding the technology-based enterprises
(Chorev and Anderson 2006)
.
According to this, the primary hypothesis of this study is:
Hypothesis 1 (H1).
Entrepreneurial education has a meaningful effect on technology-based
enterprises’ development, considering motivation as a mediator variable.
One of the key elements for an entrepreneur’s failure is lacking the basic skills
for accomplishing their tasks and following their path (Sabokro et al. 2018). Thus, en-
trepreneurial skills training is essential for beginning and continuing entrepreneurial
activities
(Turker and Sonmez Selcuk 2009)
. If the entrepreneurial substances are taught
Adm. Sci. 2021,11, 105 4 of 17
truly, it could make a country bloom in the international arena (Daniel and Almeida 2020).
In other words, they can face new problems, make new strategies, and be up to date with
this kind of education (Hosseini et al. 2020a). Additionally, individuals’ capabilities are the
best predictors for progressing enterprises (Al Mamun et al. 2019). Therefore, entrepreneurs’
initial power for beginning enterprises correlates with education related to launching a
business (Wajdi et al. 2019). Fundamental knowledge and entrepreneurship capabilities
directly affect starting a new business, economic improvement, and the development of
qualified enterprises (Vuˇcekovi´c et al. 2020;Bordbar et al. 2021). Regarding these issues,
the first sub-hypothesis of this research is:
Hypothesis 2a (H2a).
Entrepreneurial skill has a meaningful effect on technology-based enter-
prises’ development.
Hypothesis 2b (H2b).
Entrepreneurial skill has a meaningful effect on technology-based enter-
prises’ development, considering motivation as a mediator variable.
Based on social learning theory principles for entrepreneurial behavior patterns, those
who associate with real entrepreneurs tend to be entrepreneurs in the future (Guerrero and
Espinoza-Benavides 2020). Thus, learning ability is necessary for improving entrepreneurial
capacity (Tajpour et al. 2018b). Learning the entrepreneurship concept allows identifying new
opportunities and overcoming traditional barriers
(Ceptureanu et al. 2020)
. Entrepreneurial
learning is an empirical process, in which during this process, the entrepreneur’s experi-
ences convert to knowledge; but, these experiences do not transform to knowledge directly
(
Salamzadeh et al. 2021
;Trabskaia and Mets 2021). In other words, learning new experiences
is described as a concept that can be explored empirically
(Pittaway et al. 2015)
. Therefore, on
the one hand, entrepreneurship begins with an opportunity, and, on the other hand, detecting
this opportunity depends on enterprises’ capability and capacity to learn from their envi-
ronment (
Lattacher and Wdowiak 2020
;
Saeeda et al. 2020
). While entrepreneurial learning
positively affects finding new opportunities, these opportunities are a major advantage for
enterprises’ achievement (Tajpour et al. 2018b). Above all, the second sub-hypotheses are:
Hypothesis 3a (H3a).
Entrepreneurial learning has a meaningful effect on technology-based
enterprises’ development.
Hypothesis 3b (H3b).
Entrepreneurial learning has a meaningful effect on technology-based
enterprises’ development, considering motivation as a mediator variable.
Entrepreneurial education has a significant role in improving entrepreneurial in-
tention and leads to the success of a business (Vega-Gómez et al. 2020). From the van-
tage point of some researchers, entrepreneurship is a plan to achieve a specific purpose
(
Autio and Acs 2010
). Base on the Theory of Planned Behavior (TPB), each behavior needs
to be planned, which can be predicted deliberately (Engle et al. 2010). Mental maps and
cognitive features can pave the path of entrepreneurial intention and turn it into a process
based on how the roles, models, and patterns are evaluated. Additionally, it clarifies
how decision-making turns into an automated process (Salamzadeh et al. 2014). Psy-
chological studies often refer to intention as the best behavioral predictor (Ajzen 1991).
Intention illustrates an individual’s motivation for putting through a specific plan or pur-
pose (
Conner and Armitage 1998
). Entrepreneurial intention is a mental status, which
drives launching an enterprise (Bird 1988).
Furthermore, the entrepreneurial intention is shaped to prepare a fundamental mind-
set for entrepreneurship (Krueger 2007). In other words, an individual’s consciousness for
establishing a novel business and the desire for planning to get the result is entrepreneurial
intention (Nabi et al. 2010). Another definition of entrepreneurial intention is investing
in an enterprise for progressing in the future (Yu and Wang 2019). Therefore, enterprises
with an entrepreneurial approach are always ready for facing environmental changes
Adm. Sci. 2021,11, 105 5 of 17
and can adjust to new challenges (Tajpour et al. 2015;Tanha et al. 2011). In this case, the
entrepreneurial intention has a significant contribution to comprehend entrepreneurial
behavior. Overall, the third sub-hypotheses are:
Hypothesis 4a (H4a).
Entrepreneurial intention has a meaningful effect on technology-based
enterprises’ development.
Hypothesis 4b(H4b).
Entrepreneurial intention has a meaningful effect on technology-based
enterprises’ development, considering motivation as a mediator variable.
Motivations for technology-based enterprises’ development are important for en-
trepreneurial activities in a country (Ismail et al. 2018). People need the motivation to
continue an action, which is true for everybody, even entrepreneurs. Therefore, some
researchers are trying to analyzing and perceive the relationship between motivations and
entrepreneurs (Ward et al. 2019). Entrepreneurship motivation encourages entrepreneurial
skills. We can analyze them in three aspects: first, invention motivation, second motivation
for opening, third motivation for development. The motivations point to start a process,
orienting, energize others (Munro et al. 2014). Motivation has a close relationship to re-
wards and encouragement of employees. Additionally, these sorts of motivations have
relations with opportunity discoveries (Dimitratos et al. 2012). It reveals the feedback that
individuals might receive regarding the organization’s support from motivational and
creative behaviors. These include organizational support mechanisms that motivate cre-
ative employees to use their capabilities and talents creatively to act entrepreneurially and
stimulate employees’ motivation to use their best capabilities and become more productive
in terms of entrepreneurial education. Chandra (2017) believes that the decision-making
roles that are used by entrepreneurs are very important, and they experience global markets
based on this role (Chandra 2017).
Hypothesis 5 (H5).
Motivation has a meaningful effect on technology-based enterprises’ development.
Additionally, according to the literature review, the conceptual framework (Figure 1)
of this research is:
Adm. Sci. 2021, 11, x FOR PEER REVIEW 6 of 17
Figure 1. Conceptual framework (source: self-elaborated by the authors).
3. Materials and Methods
The purpose of this research is practical, and its method is quantitative. This study’s
statistical population included 500 enterprises in the Esfahan Scientific and Industrial
Town in 2020. The Esfahan scientific and industrial town publishes a list of active compa-
nies on its website annually. Then, we have obtained the number of active companies ac-
cordingly, and sampling was performed based on that number. The reason for selecting
these companies in Esfahan Scientific and Industrial Town was that it was the first organ-
ization to establish incubators and science and technology parks in Iran in 2001. This cen-
ter was established to support knowledge-based companies’ creation and development
and create wealth from science. It has also played a role as an intermediary between gov-
ernment, industry and academia in developing a knowledge-based economy and ulti-
mately turning science into wealth in Iran. Additionally, the criteria for selecting the final
companies to settle in the Esfahan Scientific and Industrial Town is decided and in these
companies, workshops related to entrepreneurship are permanently held, all of which had
participated in some courses. Cochran’s formula was applied, and 217 individuals were
determined as our sample (n = 217). According to Structural Equation Modeling, which
was applied in this research, the sample size should be 5 to 10 times the number of the
questionnaire’s questions (Ishtiaq 2019). For data gathering, a researcher-made question-
naire included 29 questions, which the Likert scale was applied to for conceptual model
variables measurement (1—absolutely disagree, 2—disagree, 3—no idea, 4—agree, 5—
absolutely agree). Likert scale is a tool for measuring people’s attitudes and is used to
prepare attitude questionnaires in management and humanities. In general, three stand-
ard scales have been introduced by Rennes Likert, known as the five-degree, seven-de-
gree, and nine-degree scales. These scales can be used to express agreement or determine
the importance of items. The most common form of the Likert spectrum is 5 degrees. This
scale can also be used to express agreement or assess importance or status. In this study,
a 5-point Likert scale has been used. This scale measures only the subject and issue under
study and not another irrelevant issue. It also expresses a more or less positive or negative
tendency and not an indifferent tendency. The researcher-made questionnaire includes
six entrepreneurial skill scales (Smith et al. 2007), six scales for entrepreneurial learning
(Jerez-Gomez et al. 2005), six scales for entrepreneurial intention (Liñán et al. 2011), six
scales for motivation (Hermans 1987), and five scales for enterprise development (Sohn et
al. 2007). The final questionnaires were distributed virtually and by interview method
Figure 1. Conceptual framework (source: self-elaborated by the authors).
Adm. Sci. 2021,11, 105 6 of 17
3. Materials and Methods
The purpose of this research is practical, and its method is quantitative. This study’s
statistical population included 500 enterprises in the Esfahan Scientific and Industrial Town
in 2020. The Esfahan scientific and industrial town publishes a list of active companies on its
website annually. Then, we have obtained the number of active companies accordingly, and
sampling was performed based on that number. The reason for selecting these companies
in Esfahan Scientific and Industrial Town was that it was the first organization to establish
incubators and science and technology parks in Iran in 2001. This center was established to
support knowledge-based companies’ creation and development and create wealth from
science. It has also played a role as an intermediary between government, industry and
academia in developing a knowledge-based economy and ultimately turning science into
wealth in Iran. Additionally, the criteria for selecting the final companies to settle in the
Esfahan Scientific and Industrial Town is decided and in these companies, workshops related
to entrepreneurship are permanently held, all of which had participated in some courses.
Cochran’s formula was applied, and 217 individuals were determined as our sample (
n = 217
).
According to Structural Equation Modeling, which was applied in this research, the sample
size should be 5 to 10 times the number of the questionnaire’s questions
(Ishtiaq 2019)
.
For data gathering, a researcher-made questionnaire included 29 questions, which the
Likert scale was applied to for conceptual model variables measurement (1—absolutely
disagree, 2—disagree, 3—no idea, 4—agree, 5—absolutely agree). Likert scale is a tool for
measuring people’s attitudes and is used to prepare attitude questionnaires in management
and humanities. In general, three standard scales have been introduced by Rennes Likert,
known as the five-degree, seven-degree, and nine-degree scales. These scales can be used
to express agreement or determine the importance of items. The most common form of the
Likert spectrum is 5 degrees. This scale can also be used to express agreement or assess
importance or status. In this study, a 5-point Likert scale has been used. This scale measures
only the subject and issue under study and not another irrelevant issue. It also expresses a
more or less positive or negative tendency and not an indifferent tendency. The researcher-
made questionnaire includes six entrepreneurial skill scales (Smith et al. 2007), six scales for
entrepreneurial learning (
Jerez-Gomez et al. 2005
), six scales for entrepreneurial intention
(
Liñán et al. 2011
), six scales for motivation (Hermans 1987), and five scales for enterprise
development (
Sohn et al. 2007
). The final questionnaires were distributed virtually and by
interview method with Persian language, and eventually, 213 fully answered questionnaires
were gathered and analyzed (See Appendix A). Entrepreneurship education is considered
as a creative and innovative concept for companies. When employees have entrepreneurial
training in the company, this activity leads to technology-based enterprises’ development.
In this research, entrepreneurial education is considered an independent variable,
technology-based enterprise development as a dependent variable, and motivation as a
mediator variable. The model designed in this article can be the basis of research for other
countries, with the difference that it has different results depending on the conditions and
situation of countries. Smart PLS3 software was used for data analysis. The reason for using
this application was related to the normal distribution of the responses (Kline 2015). Various
criteria were used to evaluate the validity and reliability. Like the research conducted by
Kozlinska et al. (2020)
, structural equation modelling was applied for construct validity,
convergent validity, and divergent validity measurements. Additionally, the reliability of
this questionnaire was estimated by Cronbach’s Alpha coefficient and composite reliability
(Dana and Dana 2005). Regarding Table 1, based on the results, the research has appropriate
validity and reliability. The convergent validity was determined by Average Variance
Extracted (AVE). The AVE for the variables of this research was calculated higher than 0.5
and demonstrates high validity. Besides, the results show that Cronbach’s Alpha coefficient
and composite reliability for each construct are more than the accepted minimum, which
means more than 0.7. Thus, the construct’s reliability is acceptable. Regarding the results of
Table 1, each criterion has acceptable validity and reliability.
Adm. Sci. 2021,11, 105 7 of 17
Table 1. AEV, Cronbach’s alpha, and composite reliability.
Constructs Variables Statements Cronbach’s
Alpha
Combined
Reliability
(CR)
Communality AVE R2Q2
Entrepreneurial
education
Entrepreneurial
skill 1–6 0.965 0.972 0.967 0.852 — —
Entrepreneurial
learning 7–12 0.938 0.951 0.939 0.763 — —
Entrepreneurial
intention 13–18 0.923 0.940 0.928 0.723 — —
Motivation — 19–24 0.918 0.937 0.923 0.714
0.812 0.749
Technology-based enterprises’
development — 25–29 0.916 0.942 0.921 0.802
0.821 0.756
The average variance was applied to achieve the convergent validity, and for estimating
the divergent validity, the square root of variance was extracted (Sabokro et al. 2018). It is re-
ferred to in Table 2that the square root of the variance is more than the acceptable minimum,
which means more than 0.5; thus, divergent validity is ensured. Furthermore, regarding this
point that the estimated square root of the variance is more than the correlation between
variables, the divergent validity is acceptable in a condition that the values of fundamental
diameter are more than the numbers below each item
(Fornell and Larcker 1981)
. Therefore,
the variables have validity, and their divergent validity was approved.
Table 2. Divergent validity.
Variables Entrepreneurial
Skill
Entrepreneurial
Intention
Entrepreneurial
Learning Motivation Technology-Based
Enterprise Development
Entrepreneurial skill 0.923
Entrepreneurial intention 0.837 0.850
Entrepreneurial learning 0.885 0.845 0.901
Motivation 0.819 0.830 0.899 0.932
Technology-based
enterprise development 0.773 0.825 0.884 0.876 0.896
According to the above and the output of the Smart PLS3 application, which is displayed
in Tables 1and 2, the evaluated validity models (convergent and divergent) and the assessed
reliability (Cronbach’s and composite reliability coefficient) are suited to the model.
4. Results
Based on the analysis of the quantitative data, 81% of the respondents were male, and
19% were female; additionally, 57% held a PhD degree, and 43% held a Master’s degree.
Moreover, 37% of the participants were single, and 63% were married. Finally, 23% of the
respondents had five years of experience, 63% had between five and ten years of experience,
and 14% had over ten years of experience.
The model’s goodness of fit was examined in three levels: measurement model
(reliability and validity), structural model (t-test, R
2
and Q
2
), and general model (GOF, NFI
and SRMR). For structural goodness of fit, the ordinary least squares (OLS) are considered,
which is related to t-distribution (Tajpour et al. 2020a). In this method, the amount of t
should be more than 1.96; in this case, it is meaningful and reliable (Thomas 2003). The
results demonstrate that the outputs are more than the critical amount, which means more
than 1.96, and are approved. Values greater than 0.4 for factor load coefficients, greater
than 0.5 for average subscription, greater than 0.7 for combined reliability, and Cronbach’s
alpha indicate a good fit of the measurement models in terms of convergent reliability and
Adm. Sci. 2021,11, 105 8 of 17
validity. As shown in Figure 2, all coefficients of factor loading of the questions except
question 26 are greater than the criterion of 0.4, so by deleting question 26, re-analysis was
performed.
Adm. Sci. 2021, 11, x FOR PEER REVIEW 8 of 17
Technology-based enter-
prise development 0.773 0.825 0.884 0.876 0.896
According to the above and the output of the Smart PLS3 application, which is dis-
played in Tables 1 and 2, the evaluated validity models (convergent and divergent) and
the assessed reliability (Cronbach’s and composite reliability coefficient) are suited to the
model.
4. Results
Based on the analysis of the quantitative data, 81% of the respondents were male,
and 19% were female; additionally, 57% held a PhD degree, and 43% held a Master’s de-
gree. Moreover, 37% of the participants were single, and 63% were married. Finally, 23%
of the respondents had five years of experience, 63% had between five and ten years of
experience, and 14% had over ten years of experience.
The model’s goodness of fit was examined in three levels: measurement model (reli-
ability and validity), structural model (T-test, R2 and Q2), and general model (GOF, NFI
and SRMR). For structural goodness of fit, the ordinary least squares (OLS) are consid-
ered, which is related to t-distribution (Tajpour et al. 2020a). In this method, the amount
of t should be more than 1.96; in this case, it is meaningful and reliable (Thomas 2003).
The results demonstrate that the outputs are more than the critical amount, which means
more than 1.96, and are approved. Values greater than 0.4 for factor load coefficients,
greater than 0.5 for average subscription, greater than 0.7 for combined reliability, and
Cronbach’s alpha indicate a good fit of the measurement models in terms of convergent
reliability and validity. As shown in Figure 2, all coefficients of factor loading of the ques-
tions except question 26 are greater than the criterion of 0.4, so by deleting question 26,
re-analysis was performed.
Figure 2. T-test results.
The results of this criterion showed that the values obtained for the path of the entre-
preneurial skill have a meaningful effect on tech-based enterprises development equal to
(2.698), the path of the entrepreneurial skill has a meaningful effect on tech-based enter-
prises development considering motivation as a mediator variable equal to (2.618), respec-
tively. The path of Entrepreneurial learning has a meaningful effect on technology-based
enterprise development equal to (2.238), the path of entrepreneurial learning has a mean-
ingful effect on technology-based enterprise development equal to (3.891), the path of En-
Figure 2. t-test results.
The results of this criterion showed that the values obtained for the path of the
entrepreneurial skill have a meaningful effect on tech-based enterprises development
equal to (2.698), the path of the entrepreneurial skill has a meaningful effect on tech-based
enterprises development considering motivation as a mediator variable equal to (2.618),
respectively. The path of Entrepreneurial learning has a meaningful effect on technology-
based enterprise development equal to (2.238), the path of entrepreneurial learning has
a meaningful effect on technology-based enterprise development equal to (3.891), the
path of Entrepreneurial intention has a meaningful effect on technology-based enterprise
development equal to (0.656) and the path of entrepreneurial intention has a meaningful
effect on technology-based enterprise development equal to (2.696) where the critical value
of five paths out of six paths is more than the critical value (1.96) at 95% confidence level,
which indicates the significance of paths, the appropriateness of the structural model and
the confirmation of the five research hypotheses. See (Figure 2).
4.1. Coefficient of Determination (R2)
The second criterion for the goodness of fit is the coefficient of determination (R
2
),
which can expose the research’s internal variables. R
2
was applied for determining the
correlation intensity between constructs, which is related to just dependent variables.
In fact, R
2
refers to the impact of exogenous variables on endogenous ones, which has
three amounts of 0.19, 0.33, and 0.67 for three levels as low, intermediate, and high
(Hosseini et al. 2020b)
. This criterion was calculated for technology-based enterprises’
development, and its amount is 0.821, and for motivation, it is 0.812; thus, the structural
model implies solid goodness of fit. See (Figure 3).
Adm. Sci. 2021,11, 105 9 of 17
Adm. Sci. 2021, 11, x FOR PEER REVIEW 9 of 17
trepreneurial intention has a meaningful effect on technology-based enterprise develop-
ment equal to (0.656) and the path of entrepreneurial intention has a meaningful effect on
technology-based enterprise development equal to (2.696) where the critical value of five
paths out of six paths is more than the critical value (1.96) at 95% confidence level, which
indicates the significance of paths, the appropriateness of the structural model and the
confirmation of the five research hypotheses. See (Figure 2).
4.1. Coefficient of Determination (R2)
The second criterion for the goodness of fit is the coefficient of determination (R2),
which can expose the research’s internal variables. R2 was applied for determining the
correlation intensity between constructs, which is related to just dependent variables. In
fact, R2 refers to the impact of exogenous variables on endogenous ones, which has three
amounts of 0.19, 0.33, and 0.67 for three levels as low, intermediate, and high (Hosseini et
al. 2020b). This criterion was calculated for technology-based enterprises’ development,
and its amount is 0.821, and for motivation, it is 0.812; thus, the structural model implies
solid goodness of fit. See (Figure 3).
Figure 3. Standard factor loadings and R2.
4.2. Q2 Criterion
The Q2 criterion is calculated for each dependent variable, and it multiplies the com-
pound amount of constructs with their coefficient of determination. This criterion was
defined by Stone (1977), which indicates the model’s strength of forecasting for the de-
pendent variable. They believe that models with approved goodness of fit should predict
the endogenous constructs indexes. In other words, if relations between constructs were
depicted in a model correctly, in this way, the constructs can affect each other, and the
hypotheses would be approved. The acceptable amounts of Q2 for each endogenous con-
struct are 0.2, 0.15, and 0.35 as low, intermediate, and high forecasting ability (Kline 2015).
The evaluated amount of Q2 for technology-based enterprises’ development is estimated
at 0.756 and for motivation is 0.749, which implies a high acceptance rate.
4.3. The Goodness of Fit (GOF)
In the final model, both the structural and measurement model are estimated, and
then the general goodness of fit index (GOF) is considered. The accepted rate for GOF is
Figure 3. Standard factor loadings and R2.
4.2. Q2Criterion
The Q
2
criterion is calculated for each dependent variable, and it multiplies the com-
pound amount of constructs with their coefficient of determination. This criterion was
defined by Stone (1977), which indicates the model’s strength of forecasting for the de-
pendent variable. They believe that models with approved goodness of fit should predict
the endogenous constructs indexes. In other words, if relations between constructs were
depicted in a model correctly, in this way, the constructs can affect each other, and the hy-
potheses would be approved. The acceptable amounts of Q
2
for each endogenous construct
are 0.2, 0.15, and 0.35 as low, intermediate, and high forecasting ability (
Kline 2015
). The
evaluated amount of Q
2
for technology-based enterprises’ development is estimated at
0.756 and for motivation is 0.749, which implies a high acceptance rate.
4.3. The Goodness of Fit (GOF)
In the final model, both the structural and measurement model are estimated, and
then the general goodness of fit index (GOF) is considered. The accepted rate for GOF is
0.01, 0.25, and 0.36, which refer to low, intermediate, and high amounts. The total GOF is
equal to 0.879, which can confirm the model.
GOF = √average (Commonality) ×average (R2) (1)
Another significant criterion is Standardized Root Mean Residual (SRMR). The acceptance
amount of the final model’s GOF, according to Bayern (2005), is 0.05,
Hu and Bentler (1999)
is
0.08, and based on Ringle and Sarstedt (2016), it is less than 0.10. Based on the results that are
reported in Table 3, this model has a high GOF. Another applied criterion for GOF calculating is
Normed Fit Index (NFI). This index’s rate should be between 0 to 1, and the accepted NFI must
be more than 0.9 (Kline 2015). In this research, NFI is equal to 0.963 that it is approved.
Table 3. Fitness indexes.
SRMR NFI
Accepted amounts ≤0.10 ≥0.9
Calculated amounts 0.07 0.963
Adm. Sci. 2021,11, 105 10 of 17
For ascertaining the role of motivation in technology-based enterprises’ development,
the variance accounted for (VAF) test is extracted. The amount of VAF is equal to 0.341,
demonstrating the minor role of the motivation construct in this research.
VAF = (a ×b)/(a ×b) + c (2)
Eventually, for considering the relations between variables, the statistical t-test was
applied. For approving the primary hypothesis, seven sub-hypotheses were used based
on the table. Six calculated t related to factor loadings of 7 sub-hypotheses are approved
(See Table 4). How each independent variable affects the dependent variable is determined
by considering each path related to the sub-hypotheses. These coefficients manifest how
much the dependent variables can predict by independent variables.
Table 4. t-test and influence coefficients.
Path Influence
Coefficient t-Test Result
Entrepreneurial skill has a meaningful effect on
tech-based enterprises development 0.119 2.698 Supported
Entrepreneurial skill has a meaningful effect on
tech-based enterprises development considering
motivation as a mediator variable
0.089 2.618 Supported
Entrepreneurial learning has a meaningful effect
on technology-based enterprise development 0.485 2.238 Supported
Entrepreneurial learning has a meaningful effect
on technology-based enterprise development,
considering motivation as a mediator variable
0.723 3.891 Supported
Entrepreneurial intention has a meaningful effect
on technology-based enterprise development 0.142 0.656 Not
supported
Entrepreneurial intention has a meaningful effect
on technology-based enterprise development,
considering motivation as a mediator variable
0.109 2.696 Supported
Motivation has a meaningful effect on
technology-based enterprises’ development. 0.419 2.607 Supported
5. Discussion
Regarding that hypothesis for entrepreneurial skill and learning are confirmed, that
is to say, companies’ managers should have a long-term perspective and take risks for
creating new business models (Varblane and Mets 2010). In similar research, the impact
of passion for innovation on entrepreneurial processes and performance has been investi-
gated. The results indicate that some entrepreneurial agents like entrepreneurial education
and entrepreneurial skills significantly affect business performance (Altaf et al. 2019). For
marketing and cultivating the business owners’ strategy, they should have the capability to
communicate and cooperate with customers, suppliers, and other agents. The managers
should have the ability to negotiate and be good listeners. Results are compatible with
Hosseini et al. (2020a) and Wajdi et al. (2019) results. According to Tajpour and Hosseini
(2021a), when people spread their knowledge, skills and expertise among members of
their organization, performance improves, and companies would become more innovative.
Consequently, effective and efficient knowledge management seems essential for success
in this regard. In other words, not only are training and learning of new skills realized,
but also attitudes are changed and, thereafter, it can expand individual self-efficacy so that
individuals’ behavioral, emotional, social, and cognitive skills will be coordinated and
individual efficiency activate cognitive and emotional and affective currents. Additionally,
Elia et al. (2011) emphasized that the development of technology entrepreneurship compe-
tencies should be based on hands-on and experiential methods, making entrepreneurship
Adm. Sci. 2021,11, 105 11 of 17
education more like a process in which the entrepreneurial attitude is instilled in people
based on critical processes capturing the essence of entrepreneurship. Mets et al. (2017)
have also emphasized entrepreneurial competencies “as the perceived learning outcomes of
entrepreneurship education”.
Considering that the second hypotheses, namely, entrepreneurial learning on technology-
based enterprise development and the other, entrepreneurial learning on technology-based
enterprise development, were both mediated through motivation, it can be said that learning
is closely related to the presence and active participation of the individual. Additionally,
by considering this point, entrepreneurial skill education positively affects reducing the
unemployment rate; thus, entrepreneurial skills should be taught before and after establish-
ing a business. According to both approved sub-hypothesis about entrepreneurial learning,
entrepreneurial learning is closely related to the individuals’ tendency and participation.
Employees should be aware of the organization’s strategy and mission for consistent and
sustainable learning and remember that learning and education are the only way to progress
and promote. This cooperation for determining the organizational aims motivates employees
(Tajpour et al. 2018a;Ceptureanu et al. 2020;
Vuˇcekovi´c et al. 2020
). According to Tajpour and
Hosseini (2021b), employees of such companies are their main capital and can be valuable
when the individuals’ knowledge are shared with the members inside and outside the com-
pany. Such knowledge sharing leads to the interaction of experiences and perspectives, and,
consequently, it triggers learning at the company and member level. Besides, the formation of
new relationships becomes a resource for empowering the company and, ultimately, gaining
a competitive advantage by creating knowledge and synergies in dynamic environments.
Considering that the third hypothesis, i.e., entrepreneurial intention on technology-
based enterprise development, was rejected from the perspective of managers, but the
third sub hypothesis, i.e., entrepreneurial intention on technology-based enterprise de-
velopment, was approved through motivation, it can be said that education is first on
people’s attitudes and then on entrepreneurial intention. It is effective, and the intention
is to strengthen entrepreneurial behavior. Learning associations should be supported to
boost the entrepreneurial environment since employees can identify the opportunities and
take them to make innovation and promulgate an enterprise. Therefore, by developing the
entrepreneurial education and learning skills, individuals are encouraged to pursue suc-
cess, innovation, and creativity. Cultivating this atmosphere makes a company analyze the
market correctly, and through this facilitation, employees collect conducive information (Yu
and Wang 2019;Tanha et al. 2011;Tajpour et al. 2015). According to research by Tajpour et al.
(2021c), actually, the greater the diversity of people in terms of culture, education, skills and
age in social relationships, the better the results of starting an entrepreneurial business can
be achieved since experiences of different people in different fields and domains are not the
same. It is suggested that companies invite real entrepreneurs to reinforce entrepreneurial
intention because the entrepreneur’s constructive attitude can affect employees’ intuition
and boost it up.
Considering that the fourth hypothesis, i.e., motivation, has a meaningful effect on
technology-based enterprises’ development, according to Gegenhuber (2021), it can be said
companies’ support for people’s innovation motivates them and ultimately improves and
develops performance technology-based enterprises.
6. Conclusions
According to the research’s purpose, entrepreneurial skills are primary economic
development factors since they can do new business and raise their occupation rate. En-
trepreneurial skills fortify an individual’s efficiency in doing tasks. Through entrepreneurial
education, employees attempt to be eligible for their related domains and conveniently en-
counter new challenges and competitions. Technology-based enterprises have paramount
importance for country growth; thus, managers have an immense responsibility in this field.
Therefore, those countries, which figure out the importance of entrepreneurial education
and its role in formative country development, conceive it as a worthwhile element in their
Adm. Sci. 2021,11, 105 12 of 17
strategic perspective. However, entrepreneurial learning is more than the consciousness of
opportunities; it is a tendency to collect new experiences, skills, and knowledge. Therefore,
entrepreneurship is about behavior, not personality traits, and its foundation relies on
entrepreneurial training. In this case, it can be said that entrepreneurship should be entered
into the educational system of countries, and features that are related to entrepreneurs will
be strengthened. Currently, the country needs a dynamic economy, which is innovative and
necessary for those who have the necessary motives for entrepreneurship. Entrepreneurial
training professionals should increase the impact of these tutorials by allocating funds and
more time to research and developing comparative studies with other countries using the
theory of gap analysis. In addition, the implementation of research studies in examining
the impact of other propulsion variables on the development of technology businesses.
The speed of action in entering the market is one of the leading causes of technology-based
businesses’ development; therefore, it is suggested that businesses enter the market in the
shortest time and with its minimum product or service, and then develop it over time based
on customer views. The choice of a working team is essential, but more important than the
durability and durability of team members. Therefore, it is suggested that one needs to
consider the existing weaknesses among the people in teamwork and technology-based
businesses. Besides, in addition to working on ideas, one needs to educate individuals to
improve their abilities and skills to motivate them to become entrepreneurs.
Considering the importance of government support policies, politicians and decision-
makers in developing the country in developing supportive projects of the establishment
and development of technology-based businesses, supportive policies about incentives,
regulations and creating business space view, the government adopts a good strategy for
supporting technological businesses, which at each stage of the development of business
gives resources in time.
Limitations and Future Research
Although the present study had significant contributions, there were some short-
comings as well. Regarding the study population, a few technology-based enterprises
development managers were reluctant to participate in this survey because of their partial
responses or conservative nature. Furthermore, it was impossible to include all the affective
factors and different characteristics of entrepreneurial education due to various cultures.
These limitations may affect the generalizability of the study outcomes. Consequently, the
authors would recommend that other academicians implement the same model to perform
parallel studies in different cultures or companies. They can also compare the conclusions
of their researches and the results of the present study that leads to the advancement of the
generalizability of the outcomes.
Author Contributions:
Conceptualization, L.-P.D., M.T., A.S., E.H., and M.Z.; methodology, M.T.,
A.S., and E.H.; software, M.T., and E.H.; validation, L.-P.D., A.S., and M.Z.; formal analysis, M.T., and
E.H.; investigation, L.-P.D., M.T., A.S., E.H. and M.Z.; resources, M.T., and E.H.; data curation, A.S.;
writing—original draft preparation, M.T., and E.H.; writing—review and editing, L.-P.D., M.T., A.S.,
E.H. and M.Z.; visualization, M.T., and E.H.; supervision, L.-P.D., and, A.S.; project administration,
A.S. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
Adm. Sci. 2021,11, 105 13 of 17
Appendix A. Questionnaire
1 = Strongly disagree 2 = Disagree 3 = Neither agree nor disagree 4 = Agree
5 = Strongly agree
Entrepreneurial education
Entrepreneurial skill (Based on Smith et al. 2007)
1. Entrepreneurial education courses in an organization help identify the weaknesses
and strengths.
2. Entrepreneurial education courses help create opportunities in dynamic circum-
stances.
3. Taking part in an entrepreneurial education course helps promote your career
credibility.
4. After taking an entrepreneurial education course, I will be determined to continue
working in the firm.
5. Entrepreneurial education courses lead to the development of problem-solving
skills.
6. I will be able to help solve the firm’s problems efficiently after participating in an
entrepreneurial education course.
Entrepreneurial learning (Based on Jerez-Gomez et al. 2005)
7. All parts that constitute this firm (departments, sections, work teams, and individu-
als) are well aware of how they contribute to achieving the overall objectives.
8. All parts that constitute this firm are interconnected, i.e., working together in a
coordinated fashion.
9. This firm promotes experimentation and innovation as a way of improving the
work processes.
10. Experiences and ideas provided by external sources (advisors, customers, training
firms, etc.) are considered as a useful instrument for improving learning skills in this firm.
11. Based on this firm’s culture, employees can express their opinions and make
suggestions regarding the procedures and methods for carrying out tasks.
12. Errors and failures are always discussed and analyzed in this firm at all levels.
Entrepreneurial intention (Based on Liñán et al. 2011)
13. I am ready to provide everything to be an entrepreneur.
14. My ultimate goal is to become an entrepreneur.
15. I will endeavor to establish and run my own firm.
16. I am determined to establish a firm in the future.
17. I have very seriously thought about starting a firm.
18. I had solid intention to establish a firm.
Motivation (Based on Hermans 1987)
19. When I work hard, the demands I make upon myself are very high.
20. Working is something that I like very much.
21. People think that I work very hard.
22. The extent of preparation for accomplishing a specific task indicates the interest to
the task.
23. I usually dedicate more time to do my assignments in the firm than expected.
24. If I cannot gain my goal and cannot accomplish a task well, I will still continue to
do my best to attain that goal.
Technology-based enterprises (Based on Sohn et al. 2007)
25. I usually concentrate on the customers and the related market in the firm.
26. We are going to be successful in the development of new technologies through
entrepreneurial education.
27. We are going to be successful in the development of new process through en-
trepreneurial education.
28. Managing a research and development team leads to success.
29. The quality of relationship with the board members affects the firm’s success.
Adm. Sci. 2021,11, 105 14 of 17
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