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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
Original scientific paper
Received: September 30, 2025.
Revised: October 27, 2025.
Accepted: November 06, 2025.
UDC:
37.018.43:004.738.5
10.23947/2334-8496-2025-13-3-649-665
© 2025 by the authors. This article is an open access article distributed under the terms and conditions of the
Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
*
Corresponding author: mladen.subotic@uns.ac.rs
Abstract: This study investigates how various socio-demographic variables influence the entrepreneurial potential
among university students. The research was conducted on a sample of 1,008 students from three countries: Serbia, Bosnia
and Herzegovina and Belgium. The instruments applied were the Questionnaire of Entrepreneurial Traits (QET) and the Scale of
Entrepreneurial Potential (SEP). The primary objective was to examine: (a) the role of gender in shaping entrepreneurial potential,
(b) the influence of national context, (c) differences between urban and rural backgrounds, (d) the impact of students’ material
status, and (e) the relationship between academic performance and the development of entrepreneurial capacity. Canonical
discriminant analysis confirmed significance and the structure of differences among students considering their gender, country
of origin and different material status of students, and their scores on the dimensions of the Entrepreneurial Traits model QET as
well as on the Entrepreneurial Potential model SEP. Canonical discriminant analysis did not confirm significance and the structure
of differences among students considering their place of residence and success during studies in their scores on the dimensions
of Entrepreneurial Traits model QET as well as on the Entrepreneurial Potential model SEP. The findings of this research indicate
that socio-demographic factors have a significant impact on students’ entrepreneurial potential, offering a valuable framework for
future studies and analyses, particularly in the context of the growing importance of entrepreneurship in developing countries.
Keywords: Socio-demographic, entrepreneurship, development, student population.
Mia Marić
1
, Mladen Subotić
1*
, Slavica Mitrović Veljković
2
, Ana Nešić Tomašević
2
,
Branislav Dudić
3
, Vesna Rodić Lukić
1
1
University of Novi Sad, Faculty of Education in Sombor, Serbia,
e-mail: mia.maric@uns.ac.rs, mladen.subotic@uns.ac.rs, vesna.rodiclukic@uns.ac.rs
2
University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia, e-mail: mslavica@uns.ac.rs, ana.nesic@uns.ac.rs
3
Comenius University Bratislava, Faculty of Management, Slovakia. e-mail: branislav.dudic@fm.uniba.sk
Socio-demographic Factors and Their Influence on the Development of
Entrepreneurial Potential of Students
Introduction
There is a growing interest in fostering entrepreneurship, particularly in developing countries where
entrepreneurs are increasingly viewed as pivotal agents in addressing persistent economic challenges,
such as high unemployment rates. Number of authors in their recent researches considers the phenom-
enon of entrepreneurship to be crucial implement of faster economic development (Apurba, 2023; Borah
and Bhowal, 2023; Van Praag, Versloot, 2007; Parker, 2009; Audretsch and Peña 2012; Brixiova, 2013;
Toma, Grigore, and Marinescu, 2014). In order to define factors that contribute the most to the develop-
ment of entrepreneurship, recent literature review shows that different authors studied economic factors
and their impact on entrepreneurship (Muithui et al., 2023; Parker, 2004; Sun, 2024; Wennekers et al.,
2005) and on the other hand others examined influence of personality factors and education on entrepre-
neurship (Isma et al., 2023; Thomas and Muller, 2005; Yan, 2010; Martin, McNally and Kay, 2013; Pfeifer,
Sarlija and Zekic Susac, 2016; Soomro et al., 2025; Suryadi and Anggraeni, 2023).
In this study we turn to the impact of sociodemographic factors and the importance of their influence
on the development of entrepreneurship of student population. According to Thornton, Ribeiro-Soriano
and Urbano, (2011) “international organizations such as the Organisation for Economic Co-operation and
Development (OECD) and European Union (EU) are focusing on the environmental drivers of entrepre-
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
neurship, especially the social and cultural factors that influence the individual career choice to be an entre-
preneur and to create a new business (European Commission, 2004, 2006; OECD, 1998, 2000)” (p.106).
Furthermore they conclude that social cultural factors and their influence on entrepreneurship remains
under researched. Turker and Selcuk in their study of factors that affect student entrepreneurial potential
conclude that society that is supportive towards entrepreneurship and fosters entrepreneurial activity of its
younger population will as a result have a higher level of confidence among young entrepreneurs which
leads to development of entrepreneurial activity. Gurol and Atsan, (2006) conclude that in order to define
entrepreneurial characteristics of a society we need to closely examine different factors. Urbano and Alva-
rez (2013) researched the influence of institutions on entrepreneurial activity and their sample consisted
of 36,525 individuals from 30 countries according to (GEM and IMD data for 2008). In their overall assess-
ment they stated that: “while the regulative and normative environments encourage people to become
entrepreneurs, a strong cultural-cognitive environment is needed to create a new firm” (p. 713). Global
Entrepreneurship Monitor studies contextual factors like socio-cultural and demographical influence the
process of forming our personality and influence our perception and the way we act (GEM, 2010).
In our study we will investigate different sociodemographic factors focusing on gender, country of
origin, influence of rural and urban area of residence, material status of students, and influence of success
during studies and try to assess how they influence entrepreneurial potential of students.
Hofsted et, al. (2004) in their research concludes that factors influencing the development of entrepre-
neurship in a society are multidimensional and complex. Nicolae, M., Ion, I. and Nicolae, E. (2016), in their
study state: “that entrepreneurship phenomenon is currently understood as a reflection of the local competi-
tive advantages and disadvantages of the external environment” (p 394). In our research we will focus on
student population and examine sociodemographic factors and their influence on this part of population. Ac-
cording to Shinnar, Giacomin and Janssen, (2012) who used Krueger, Reilly, and Carsrud (2000) statement:
“Students fac[e] an immediate career choice [and]...starting a business may be a realistic option” (p. 425).
This study employed two conceptual frameworks: the Entrepreneurial Traits Model (QET) and the En-
trepreneurial Potential Model (SEP). The QET model encompasses six dimensions—unconventionality and
creativity, achievement orientation and challenge acceptance, entrepreneurial self-efficacy, assertiveness
and communication skills, positive attitudes toward entrepreneurship, as well as interest and knowledge
related to entrepreneurial activity. The SEP model evaluates entrepreneurial potential through dimensions
such as intellectual capacity, self-confidence, motivation, social interaction, physical constitution, emotional
stability, extroversion, and organizational competence. The SEP instrument quantifies respondents’ scores
across these dimensions, with higher scores indicating a greater degree of entrepreneurial potential.
Liberty, Tunde and Tinuola (2016) conclude in their study that sociodemographic factors influence
development of entrepreneurial activity. In this research we will assess the influence of following sociode-
mographic factors: (a) the role of gender in shaping entrepreneurial potential, (b) the influence of national
context, (c) differences between urban and rural backgrounds, (d) the impact of students’ material status,
and (e) the relationship between academic performance and the development of entrepreneurial capacity.
Influence of gender on the development of entrepreneurial potential
Research conducted on the student population revealed that male students exhibit a higher readi-
ness to initiate their own businesses and pursue entrepreneurial careers. This research also shows that
even though women enjoy family support, they feel less self-confident to start their own business (Bela
et al., 2021; Dabic et al., 2012; Martín-Gutiérrez et al., 2025). Despite encountering socio-economic
challenges—such as limited resource access, market inequality, and persistent gender-based stereo-
types—women exhibit resilience through strategies like professional networking, skill development, and
continuous learning (Đurđević, 2025). Gupta and Bhawe (2007) researched proactive personality as a
characteristic that is significantly associated to entrepreneurship. They assessed that this is especially
evident in an environment that is not supportive towards potential entrepreneurs, this lack of support is
characteristic for the environment of developing countries such as Serbia and Bosnia we are researching.
They concluded in their research that more proactive woman had significantly more developed entrepre-
neurial potential, and that this fact held them back from becoming entrepreneurs because of the common
stereotype that entrepreneurship is connected to male population and that proactivity is commonly associ-
ated as a masculine trait. Envick and Lim (2011) according to Bartos et al. (2015) examine in their study
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
of gender and entrepreneurial orientation in the sample of 4 countries: US, Korea, Malaysia and Fiji that
male entrepreneurs are more prone to risk propensity behaviour, they display more aggressive behaviour
when competing on the market than females do, they also discovered that males lead in regard to female
population of US and Korea in regard to independent decision making, and males are also found to be
more confident in decision making process across the sample. Differences in level of entrepreneurial de-
velopment between genders can be explained by gender discrimination women face (Fischer et al., 1993).
Since 1999, Global Entrepreneurship Monitor (GEM) provides data on the fact that women develop less
entrepreneurial potential and stay behind men in entrepreneurship activity. Research results from Bul-
garia show that women have less expressed entrepreneurial potential than men (Yordanova and Tarrazon,
2010), this survey is very interesting to our own study because of the similarity in the mentality in the region
of Balkans. Bartos et al. (2015) conclude in their study that male entrepreneurs in Czech Republic are
more aggressive than female entrepreneurs and more innovative. Shinnar, Giacomin and Janssen, (2012)
in their research which is similar to our own used a sample of 761 university students from three different
nations: Belgium, China and United States, their study pointed to the existence of significant influence of
gender and culture for development of entrepreneurship in a society. Also, this research found that gender
negatively influences the development of entrepreneurship through the society’s lack of support for female
entrepreneurship. Research conducted on student population in India shows that student gender is a fac-
tor that strongly influences the development of entrepreneurship (Sonia Katherin Mathew and Dr. Johney
Johnson, 2014). Demographic factor like gender among others is strongly connected to self-employment
and influences entrepreneurial potential of individuals (Wilson, Kickul and Marlinon, 2007).
Influence of rural and urban area of residence on entrepreneurial potential
Hyunjeong, (2011) in his research found that most of the literature collects data in urban settings
and gives exzamples of Panel Study of Entrepreneurial Dynamics (PSED) and the Global Entrepreneur-
ship Monitor (GEM). He concludes in his study that main difference between rural and urban entrepreneur-
ship is in resources, rural areas lack in education and financial resources but show rich entrepreneurial
potential. Different research point to the fact that the rate of entrepreneurial development is significantly
lower in rural than in urban areas (Eurobarometer, 2007).
According to the research of Capelleras, Contín-Pilart, Martin-Sanchez and Larraza-Kintana, (2013)
that used data from the Spanish GEM project, they found: “that individuals in rural areas who perceive
new opportunities are more likely to become nascent entrepreneurs rather than those who live in urban
ones” (p. 97). Urban environments are assumed to foster greater entrepreneurial intentions in students
due to increased exposure to economic activities compared to rural environments (Al Harrasi and Ali,
2025). Rural and urban areas of residence significantly influence entrepreneurial potential among women
entrepreneurs in Pakistan, with differences in home ownership, household size, and financial position
(Muhammad and Ximei, 2022). Faggio and Silva (2014) in their research of self-employment and entre-
preneurship in rural and urban markets argue that self-employment in rural and urban areas is not the
part of the same phenomenon of entrepreneurship. They find that urban areas provide self-employment of
working people based on innovative behaviour, risk taking propensity which form entrepreneurship, while
rural workers more often engage in self-employment because they lack other job opportunities. Accord-
ing to Duricova (2014) Baumgartner et al., (2013) state that: “entrepreneurship has become a key topic
in rural development” (p. 197). Duricova (2014), in her study on entrepreneurship across rural and urban
regions within the EU, argues that individuals residing in underdeveloped rural areas are more inclined to
engage in entrepreneurial activities compared to those living in more developed urban settings.
However, empirical findings on the influence of residential context remain inconsistent. While some
studies suggest that urban environments exert a stronger impact on the development of entrepreneurial
potential, others indicate that rural areas contribute equally to fostering entrepreneurial capabilities.
Influence of material status of students
Material status has a complex but generally positive influence on students’ entrepreneurial poten-
tial, with financial resources serving as a key enabler of entrepreneurial intentions. The evidence suggests
multiple dimensions of material status impact entrepreneurship. Li (Li et al., 2022) found materialism
positively predicts entrepreneurial intention through a serial mediation involving achievement motivation,
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
while another author (Rajković et al., 2021) specifically noted that financial opportunities to start a new
business was the most influential variable on entrepreneurial intentions. According to Lee and Persson,
(2012) there are number of research that provide evidence of significant connection among personal
wealth and propensity to start entrepreneurial activity (Alger and Weibull, 2010). Friedline and West,
(2015) in their research examined the impact of wealth on young adults and their entrepreneurial activity.
They concluded that young adults with lower material status encounter difficulties in acquiring financial
resources needed to start their own business.
Hosseini (2016) states in his research that: “financial resources within the family stimulates entry into
entrepreneurship” (p. 31). He even found that wealthier is the family background larger is the entrepreneuri-
al venture individuals form. Research in the field of entrepreneurship show that entrepreneurial background
in the family poses a source of different assets for the new entrepreneurs in the family, such as financial
resources, suppliers, connections in the market, connection with the suppliers and knowledge of needed
technologies (Dunn and Holtz-Eakin, 2000). According to Mustapha and Selvaraju, (2015) family also stimu-
lates students by creating a supportive environment which provides them with resources and knowledge
that help them start their entrepreneurial activity after they finish their studies (Bagheri and Pihie, 2010).
OECD and European Commision (2014) consider that young people are more prone to entrepre-
neurial activity, but statistics shows that their rate of becoming entrepreneurs is lower than one of the
adults. They state that: “this is the result of barriers related to lack of awareness, orientation of education
and training, lack of experience, fewer financial resources, limited networks, and market barriers”. OECD
and European Commision (2014) also imply that EU entrepreneurship programs can overcome these
obstacles. One of the programs is The Youth Employment Initiative (YEI) Activities supported include:
“encourage schools and employment services to promote and provide continued guidance on entrepre-
neurship and self-employment for young people”. This can be very important and helpful for the young
people coming from families with lower material status. Motivation and support they lack at home they can
overcome by formal programs and entrepreneurship education. According to Jiménez, Palmero-Cámara,
González-Santos, González-Bernal, Jiménez-Eguizábal, (2015) in their research they concluded that
education influences the increases of entrepreneurial activity, and it is connected to the level of the higher
self-confidence, lower perceived risk and enhanced human capital.
Influence of success during studies on the development of entrepreneurial potential of students
The influence of academic success factors such as education, motivation, practical experience,
and social support positively impacts students’ readiness to become entrepreneurs, as they have great
potential to start businesses with innovative ideas, relevant skills, and necessary resources (Marpaung
et al., 2023). Anderson, Samimi, and Boh (2010) in their book asses that academic success and formal
education can be a “security ceiling” that is hard to escape and embrace other possibilities outside the
given framework of a false feeling of security. Ward (2004) in his research states: “More than ever we
need to prepare young people to build a life of purpose and opportunity in which they are aware of and can
draw on their various talents and abilities. Enterprise Education offers a framework for this kind of learn-
ing” (p. 105). Sharma and Madan, (2014) found in their research that students with high scores on intel-
ligence tests had low propensity towards entrepreneurship but attendance of entrepreneurship courses
resulted in higher propensity towards entrepreneurship. Chad Moutray (2009) examined the Department
of Education data in the USA and found that students with better academic achievement had slightly less
chances of being self-employed and becoming entrepreneurs. Research conducted on student popula-
tion in India shows that student age is a factor that strongly influences the development of entrepreneur-
ship (Sonia Katherin Mathew and Dr. Johney Johnson, 2014). Peterman and Kennedy (2003) conclude
that different educational programs can significantly influence development of entrepreneurship. Several
studies (Gyang et al., 2023; Machado et al., 2022; Mumtaz et al., 2024) provide comprehensive evidence
that entrepreneurial education significantly enhances students’ entrepreneurial potential across different
educational contexts and geographic regions. Gyang et al. (2023) specifically identified self-efficacy as
a critical mediating factor, showing that education builds students’ confidence in their entrepreneurial
abilities, while Machado et al. (2022) added academic engagement as another important mechanism,
demonstrating that entrepreneurial education creates more engaged learners with higher entrepreneurial
potential. Mumtaz et al. (2024) confirmed that students develop positive attitudes, subjective norms, and
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
behavioral control - all key components of entrepreneurial intention. The same author identified a critical
gap between students’ entrepreneurial potential and current curriculum offerings, suggesting that while
the impact is positive, educational systems need improvement to fully capitalize on students’ entrepre-
neurial capacity. Levesque and Minniti (2006) in their research revealed that age is significantly connected
to entrepreneurial potential and activity. Students that are older have more experience and attend more
entrepreneurial courses and consequently have more developed entrepreneurial potential, so attendance
of entrepreneurial programs and courses shows more impact on development of entrepreneurial potential
than student academic success. Above literature survey implies that academic success does not provide
a pattern that detects significant relation between academic success and development of entrepreneur-
ship potential of students.
Materials and Methods
Research methodology
The primary aim of this study is to examine the influence of various socio-demographic factors on
the entrepreneurial potential of university students. The research utilized two key instruments: the Ques-
tionnaire on Entrepreneurial Traits (QET) and the Scale of Entrepreneurial Potential (SEP). Five groups of
socio-demographic factors were analysed: (a) the role of gender in shaping entrepreneurial potential, (b)
the influence of national context, (c) differences between urban and rural backgrounds, (d) the impact of
students’ material status, and (e) the relationship between academic performance and the development
of entrepreneurial capacity.
In this paper we hypothesize that students with different demographic background differ from each
other in terms of expression of certain dimensions of entrepreneurial potential models QET and SEP.
Data collection and descriptive statistics
The research sample comprised university students from three countries—Serbia and Bosnia and
Herzegovina, as EU candidate countries, and Belgium, an EU Member State. Participants were recruited
from three universities and eleven faculties, resulting in a total of 1,008 respondents, including 589 male
and 419 female students. The study adhered to ethical research standards, including institutional approval
from participating universities. Questionnaires were administered during regular class sessions, ensuring
respondent anonymity and the exclusive use of data for scientific purposes. Participants reported clear
understanding of the instructions, and no issues were encountered during the data collection process.
Instruments
This study employed two primary instruments: the Scale of Entrepreneurial Potential (SEP) and the
Questionnaire of Entrepreneurial Traits (QET). The SEP scale assesses entrepreneurial potential across
eight sub-scales: intellectual abilities, self-confidence, motivation, social relations, physical constitution,
emotional stability, extroversion, and organizational skills.
Each SEP sub-scale captures a distinct dimension of entrepreneurial potential. The intellectual
abilities sub-scale evaluates resourcefulness in various situations, the capacity for independent problem-
solving and decision-making, as well as a proactive attitude toward learning and personal development.
The self-confidence sub-scale measures boldness in expressing personal views and assertiveness in
social and professional contexts.
The physical constitution sub-scale reflects aspects of physical fitness, energy, and endurance, which
are considered relevant to sustained entrepreneurial engagement. The organizational skills sub-scale assess-
es individuals’ preference for managerial roles and their ability to effectively plan, structure, and execute tasks.
The extroversion sub-scale—referred to as openness in earlier conceptualizations—includes traits
such as risk-taking propensity, openness to new experiences, and creativity. The motivation sub-scale encom-
passes competitive spirit, grit, initiative, goal orientation, ambition, perseverance, dedication, and work ethic.
The emotional stability sub-scale evaluates an individual’s self-regulation, resilience under stress,
emotional balance, and general optimism. Finally, the social relations sub-scale measures leadership
potential, communicative competence, social influence, teamwork orientation, adaptability, conflict resolu-
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
tion skills, and the ability to make a positive impression in social settings
The SEP inventory consists of 34 items designed to assess respondents’ scores across the eight
sub-scales representing different dimensions of entrepreneurial potential. The total entrepreneurial poten-
tial score is calculated by summing the scores across all sub-scales, with higher total scores indicating
stronger entrepreneurial potential. This instrument was developed specifically for the purposes of this
study, based on theoretical frameworks and prior research on entrepreneurial characteristics.
Responses were recorded using a 5-point Likert-type scale, ranging from “strongly agree” to
“strongly disagree.” Confirmatory factor analysis supported the factorial validity of the inventory, and the
instrument demonstrated acceptable reliability, with Cronbach’s alpha coefficients ranging from 0.751 to
0.756 across individual sub-scales.
The Questionnaire of Entrepreneurial Traits (QET), developed by Gracanin and Coso (2013), is
designed to assess entrepreneurial self-efficacy and attitudes toward entrepreneurship. The inventory
comprises 58 items and evaluates six sub-scales: entrepreneurial unconventionality and creativity, focus
on achievement and acceptance of challenges, entrepreneurial self-efficacy, assertiveness and com-
munication, positive attitudes toward entrepreneurship, and interest in entrepreneurship and knowledge.
The total QET score is obtained by summing scores across all sub-scales, with higher values indicating a
greater level of entrepreneurial potential.
The QET inventory evaluates six interrelated sub-scales that collectively capture key dimensions
of entrepreneurial traits. The first sub-scale, unconventionality and creativity, reflects an individual’s ten-
dency to approach problem-solving in original and non-traditional ways, often involving a willingness to
take risks. It also measures self-perceived creativity and confidence in utilizing these traits. The second
sub-scale, focus on achievement and acceptance of challenges, pertains to one’s motivation to tackle
complex tasks and engage in activities with uncertain outcomes, demonstrating a readiness to embrace
challenges as part of the entrepreneurial process. The third sub-scale, entrepreneurial self-efficacy, is
the most extensive and central within the inventory. It assesses confidence in personal entrepreneurial
capabilities, persistence in goal pursuit, general entrepreneurial orientation, and leadership potential. The
fourth sub-scale, assertiveness and communication, captures interpersonal skills vital to entrepreneur-
ship, particularly the ability to express ideas clearly and interact effectively with others. The fifth sub-scale,
positive attitudes toward entrepreneurship, evaluates favorable perceptions of entrepreneurs and entre-
preneurship, along with an individual’s openness to becoming an entrepreneur. Lastly, the sixth sub-scale,
interest in entrepreneurship and knowledge, focuses on self-assessed understanding of entrepreneurial
concepts and the extent of recent learning in this domain.
All responses were collected using a 5-point Likert-type scale, ranging from “strongly agree” to
“strongly disagree.” Confirmatory factor analysis supported the factorial validity of the instrument, con-
firming its underlying structure. In the present study, the QET demonstrated satisfactory reliability, with
Cronbach’s alpha coefficients ranging from 0.732 to 0.805 across the sub-scales.
Data analysis
The data were processed using the statistical software packages Statistica and SPSS. Descriptive
statistics were employed to examine the basic characteristics of the sample and the distribution of vari-
ables. To assess the existence and strength of relationships between the observed variables, canonical
discriminant analysis was conducted. This method enabled the identification of socio-demographic factors
that most significantly differentiate levels of entrepreneurial potential among student respondents.
Results
The significance and structure of gender differences in scores on the dimensions of the QET ques-
tionnaire were determined using canonical discriminant analysis.
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
Table 1. Indicators of the significance of discriminant functions in separating groups
Function Λ % of
variance
explained
Rc
(canonical
correlation)
Λ
W
partial Wilks’
Lambda
χ
2
(chi-square
statistic)
df
(chi-square
statistic)
P
(p-value)
1 .038 100.0 .190 .964 37.058 6 .000
Male students have higher scores on the dimensions Positive Attitudes toward Entrepreneurs and
Interest in Entrepreneurship, Entrepreneurial Self-Efficacy and Assertiveness and Communication, and
lower scores on Knowledge (ΛW=.964, χ2 (df=6)= 37.058, p<0.01). The ability of these two functions to
classify respondents was 57.6 %.
Table 2. Structural matrix and discriminant function values at group centroids
Function – Indicator Coefficient
Entrepreneurial self-efficacy .642*
Assertiveness and communication .576*
Knowledge -.488*
Positive attitudes toward entrepreneurs and interest in entrepreneurship .331*
Unconventionality and creativity .251
Achievement orientation and acceptance of challenges .183
Function at group centroids
Male .163
Female -.230
Legend:* indicates a statistically signicant structural coefcient
Canonical discriminant analysis was used to determine the significance and structure of gender
differences between male and female students in scores on the dimensions of the SEP questionnaire.
Table 3. Indicators of the significance of discriminant functions in separating groups
Function Λ
% of
variance
explained
Rc ΛW χ² df p
1 0.032 100.0 0.177 0.969 31.927 8 0.000
Male students have higher scores on Motivation (ΛW=.969, χ2 (df=8)= 31.927, p<0.01). The clas-
sification accuracy of this function was 56.7%.
Table 4. Structural matrix and discriminant function values at group centroids
Function – Indicator Coefficient
Motivation –0.513*
Openness –0.215
Self-confidence 0.161
Constitution 0.149
Intellectual abilities –0.097
Social relationships –0.073
Emotionality 0.042
Organizational abilities 0.011
Function at group centroids
Male -.152
Female .213
Legend:* indicates a statistically signicant structural coefcient
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
Canonical discriminant analysis was used to determine the differences and the structure of differ-
ences between students from different countries in scores on the dimensions of the QET questionnaire.
Table 5. Indicators of the significance of discriminant functions in separating groups
Function Λ
% of variance
explained
Rc ΛW χ² df p
1 0.066 65.8 0.249 0.907 97.756 12 0.000
2 0.034 34.2 0.182 0.967 33.747 5 0.000
The results indicate that students from Belgium, when compared to their peers from Bosnia and
Herzegovina, scored significantly higher on the QET sub-scales Positive Attitudes toward Entrepreneurs
and Interest in Entrepreneurship, Unconventionality and Creativity, Entrepreneurial Self-Efficacy, and As-
sertiveness and Communication, while exhibiting lower scores on the Knowledge. These differences were
statistically significant (ΛW = 0.907, χ²(df = 12) = 97.756, p < 0.01).
Furthermore, in comparison to students from Serbia, Belgian students demonstrated signifi-
cantly higher scores on the sub-scales Entrepreneurial Self-Efficacy, Assertiveness and Communica-
tion, Achievement Orientation and Acceptance of Challenges, and Knowledge (ΛW = 0.967, χ²(df = 5) =
33.747, p < 0.01).
The overall classification accuracy of the two discriminant functions was 45.5%, with the lowest
classification precision observed among students from Serbia, indicating greater overlap in their entrepre-
neurial trait profiles relative to the other groups.
Table 6. Structural matrix and discriminant function values at group centroids
Dimension Function 1 Function 2
Positive Attitudes toward Entrepreneurs and Interest 0.620* 0.244
Unconventionality and Creativity 0.505* –0.106
Entrepreneurial Self-Efficacy 0.503* 0.709*
Assertiveness and Communication 0.416* 0.701*
Achievement Orientation and Acceptance of Challenges 0.242 0.603*
Knowledge –0.469* 0.565*
Function at group centroids
Serbia 0.077 0.053
Bosnia and Herzegovina –0.767 –0.069
Belgium 0.227 –0.819
Legend: *statistically signicant structural coefcient
Canonical discriminant analysis was used to determine the differences and the structure of differ-
ences between students from different countries in scores on the dimensions of the SEP questionnaire.
Table 7. Indicators of the significance of discriminant functions in separating groups
Function Λ % of variance explained Rc ΛW χ² df p
1 0.043 77.9 0.204 0.947 54.617 16 0.000
2 0.012 22.1 0.110 0.988 12.198 7 0.094
Students from Bosnia and Herzegovina, in comparison to their peers from Belgium, demonstrated
significantly higher scores across all dimensions of the SEP model (ΛW = 0.947, χ²(df = 16) = 54.617, p
< 0.01). The most discriminating dimensions contributing to this difference were Organizational Abilities,
Social Relationships, Self-Confidence, Constitution, and Motivation.
The second discriminant function did not significantly distinguish the groups of students from differ-
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
ent countries. The classification accuracy of these two functions was 36.5%, with the poorest classifica-
tion results observed among students from Serbia.
Table 8. Structural matrix and discriminant function values at group centroids
Dimension Function 1
Organizational Abilities 0.818*
Social Relationships 0.793*
Self-Confidence 0.694*
Constitution 0.664*
Motivation 0.584*
Openness 0.524*
Emotionality 0.362*
Intellectual Abilities 0.392*
Function at group centroids
Serbia 0.005
Bosnia and Herzegovina 0.342
Belgium –0.822
Legend: *statistically signicant structural coefcient
Canonical discriminant analysis did not find a statistically significant difference between students
from different places of residence in scores on the dimensions of the QET questionnaire (ΛW = 0.996,
χ²(df = 6) = 3.556, p > 0.05).
Table 9. Indicators of the significance of discriminant functions in separating groups
Function Λ
% of variance
explained
Rc ΛW χ² df p
1 0.004 100.0 0.059 0.996 3.556 6 0.736
Canonical discriminant analysis did not find a statistically significant difference between students
from different places of residence in scores on the dimensions of the SEP questionnaire (ΛW = 0.997,
χ²(df = 8) = 3.068, p > 0.05).
Table 10. Indicators of the significance of discriminant functions in separating groups
Function Λ % of variance explained Rc ΛW χ² df p
1 0.003 100.0 0.055 0.997 3.068 8 0.930
Canonical discriminant analysis was used to determine the differences and the structure of differ-
ences between students with different material status on the dimensions of the QET questionnaire.
Table 11. Indicators of the significance of discriminant functions in separating groups
Function Λ % of variance explained Rc ΛW χ² df p
1 0.075 88.5 0.265 0.921 82.581 12 0.000
2 0.010 11.5 0.099 0.990 9.792 5 0.081
Students with below-average material status scored significantly higher on the Knowledge (ΛW =
0.921, χ²(df = 12) = 82.581, p < 0.01) compared to those with average material status. The second discri-
minant function did not significantly distinguish the groups of students with different material status. The
classification accuracy of these two functions was 45.9%, and students from all categories were classified
with roughly equal success.
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
Table 12. Structural matrix and discriminant function values at group centroids
Dimension Function 1
Knowledge 0.898*
Unconventionality and Creativity –0.128
Assertiveness and Communication –0.143
Achievement Orientation and Acceptance of Challenges –0.127
Positive Attitudes toward Entrepreneurs and Interest –0.056
Entrepreneurial Self-Efficacy –0.229
Function at group centroids
Below-average .440
Average –0.182
Above-average 0.191
Legend: *statistically signicant structural coefcient
Canonical discriminant analysis was used to determine the differences and the structure of differ-
ences between students with different material status on the dimensions of the SEP questionnaire.
Table 13. Indicators of the significance of discriminant functions in separating groups
Function Λ % of variance explained Rc ΛW χ² df p
1 0.033 79.0 0.179 0.959 41.553 16 0.000
2 0.009 21.0 0.094 0.991 8.828 7 0.265
Students with above-average material status, compared to those with average status, have higher
scores on Social Relationships, Organizational Abilities, Self-Confidence, and Openness (ΛW = 0.959,
χ²(df = 16) = 41.553, p < 0.01). The second discriminant function did not significantly distinguish the
groups of students with different material status. The classification accuracy of these two functions was
42.5%, with the poorest classification observed among students with below-average material status.
Table 14. Structural matrix and discriminant function values at group centroids
Dimension Function 1
Social Relationships 0.684*
Organizational Abilities 0.587*
Self-Confidence 0.356*
Openness 0.298M
Motivation 0.288
Intellectual Abilities 0.253
Constitution 0.126
Emotionality –0.262
Function at group centroids
Below-average 0.220
Average –0.119
Above-average 0.439
Legend: *statistically signicant structural coefcient
M - marginally signicant coefcient
A multiple regression analysis was conducted to determine whether the dimensions of the applied models
predict student success. This analysis was conducted only on the 208 students who responded to this question.
It was not established that the dimensions of the QET model predict academic success (adjusted
R² = –0.01, F(6, 201) = 0.674, p > 0.05).
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
It was not established that the dimensions of the SEP model predict academic success (adjusted
R² = 0.03, F(8, 199) = 1.769, p > 0.05).
Table 15. Significance of the multiple regression model
Model R Adjusted R² df reg df res F p
QET 0.140 0.020 –0.010 6 201 0.674 0.670
SEP
0.258 0.066 0.029 8 199 1.769 0.085
Discussion
The entrepreneurial potential of young people represents a category of dynamic and complex na-
ture, and as such is subject to the action of various internal and external factors, some of which are heredi-
tary, static and unchanging in nature, while others are subject to minor or major variations and changes
(GEM, 2010; Liberty, Tunde and Tinuola, 2016; Martin, McNally and Kay, 2013; Parker, 2004; Pfeifer,
Sarlija and Zekic Susac, 2016; Thomas and Muller, 2013; Yan, 2010). The main goal of this paper was
to examine the effect of five groups of socio-demographic factors on the development of dimensions of
entrepreneurial potential among the student population: gender, country and place of residence, material
status and success in studies. Entrepreneurial characteristics are theoretically defined and operationally
measured with the help of two models of entrepreneurial potential - QET and SEP. The central research
assumption posited that students would differ in the expression of specific entrepreneurial characteristics,
as measured by the QET and SEP models, depending on the influence of various socio-demographic
factors. The study showed that the expressiveness of the students’ entrepreneurial potential is related to
three categories of socio-demographic factors - gender, country, and financial status of the respondents.
Regarding the relationship between gender and the expression of entrepreneurial potential, the
findings confirmed the existence of gender-based differences across several dimensions of the QET and
SEP models. Specifically, within the QET model, male students exhibited significantly higher scores on
the sub-scales positive attitudes toward entrepreneurs and interest in entrepreneurship, entrepreneurial
self-efficacy, and assertiveness and communication, while scoring lower on the interest in entrepreneur-
ship and knowledge sub-scale compared to female students. Also, the results showed that male students
have a more pronounced dimension of Motivation, within the SEP model. This finding is expected and
speaks of a more pronounced entrepreneurial potential in the male population, in the domain of most
entrepreneurial traits (Bartos et al., 2015; Bela et al., 2021; Dabic et al., 2012; Fischer et al., 1993; Gupta
and Bhawe, 2007; Martín-Gutiérrez et al., 2025; Mathew and Johnson, 2014; Shinnar, Giacomin and
Janssen, 2012; Wilson, Kickul and Marlinon, 2007; Yordanova and Tarrazon, 2010).
When considering the characteristics of the development of certain traits through evolution, the
characteristics of the current socio-cultural environment and the specifics of occupations that have tradi-
tionally been considered predominantly male, and this certainly includes entrepreneurship, the obtained
findings have their deep evolutionary and social roots (Dabic et al., 2012; Gupta and Bhawe, 2007;
Mathew and Johnson, 2014). Namely, throughout the evolutionary period, the qualities of proactivity, in-
dependence, fighting spirit, and willingness to openly and directly advocate for one’s own goals, and even
to take certain risks and deviate from the expected norms and rules, when the situation so dictates, were
encouraged in men (Bartos et al., 2015; Wilson, Kickul and Marlinon, 2007).Traditionally, the socialization
and education of women have emphasized traits such as modesty, adherence to social norms, and be-
havioral conformity, often reinforcing passivity and a dependence on expected roles—primarily within the
family sphere—while placing less emphasis on career independence or entrepreneurial aspirations. This
orientation has frequently directed women toward traditionally female-dominated occupations (Fischer et
al., 1993; Shinnar, Giacomin, and Janssen, 2012; Yordanova and Tarrazon, 2010). In light of these histori-
cal and cultural patterns, it is not surprising that male students tend to show greater interest in entrepre-
neurship, express more positive attitudes toward entrepreneurial careers, demonstrate higher confidence
in goal achievement, display stronger assertiveness and communication skills, and exhibit greater overall
motivation for entrepreneurial engagement.
The finding that female students exhibit higher levels on the interest in entrepreneurship and knowl-
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660
Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
edge sub-scale is encouraging, as it indicates the presence of a critical cognitive predisposition for engag-
ing in entrepreneurial activity. However, the results also suggest that they may lack, to some extent, the
necessary motivation, self-confidence, and active interest to translate this knowledge into entrepreneurial
behavior. These insights should be carefully considered when designing and implementing programs
aimed at fostering female entrepreneurship. Such initiatives should begin by cultivating motivation and
entrepreneurial interest among young women, with the goal of empowering them to independently pursue
and succeed in entrepreneurial careers (Karnavat et al., 2024; Wilson, Kickul and Marlinon, 2007; Yor-
danova and Tarrazon, 2010).
The results also confirmed significant cross-national differences in the expression of entrepre-
neurial potential dimensions, as measured by both the QET and SEP models, among students from the
countries included in the study.Thus, compared to students from BiH, students from Belgium have more
developed dimensions Positive attitudes about entrepreneurs and interest in entrepreneurship, Uncon-
ventionality and creativity, Entrepreneurial self-efficacy and Assertiveness and communicativeness, and
less expressed Knowledge, within the QET model. At the same time, compared to students from Serbia,
students from Belgium have more pronounced dimensions Entrepreneurial self-efficacy, Assertiveness
and communicativeness, Orientation to achievement and acceptance of challenges and Knowledge. This
finding is expected and speaks in favor of the fact that young people from the EU have a more developed
majority of characteristics that make them predisposed to engage in entrepreneurship. On one hand,
these differences may reflect specific socio-cultural contexts in which young people are socialized, par-
ticularly in Western European countries. In these settings, educational systems and societal norms tend
to emphasize achievement orientation, independence, self-reliance, a proactive approach to problem-
solving, as well as the cultivation of uniqueness and creativity from an early age (Bartos et al., 2015;
Gupta and Bhawe, 2007; Pfeifer, Sarlija and Zekic Susac, 2016; Urban and Alvarez, 2013; Yordanova
and Tarrazon, 2010), while on the other hand, different more specific educational contents and meth-
ods, starting from preschool institutions up to higher education institutions, as well as direct programs
intended to encourage and develop entrepreneurship (GEM, 2010; European Commission, 2004, 2006,
2014; Martin, McNally and Kay, 2013; OECD, 1998, 2000, 2014; Thomas and Muller, 2005; Yan, 2010),
in children and young people during their entire growing up, develop entrepreneurial qualities and foster
an entrepreneurial spirit.
The findings show that compared to students from Belgium, students from Bosnia and Herzegovina
have more developed all dimensions of the SEP model, where they are best distinguished by the devel-
opment of the dimensions of Organizational Ability, Social Relations, Self-Confidence, Constitution and
Motivation. Although somewhat unexpected, this finding is nonetheless encouraging, as it demonstrates
that young people from developing, non-EU countries possess several core attributes of entrepreneurial
potential—such as organizational skills, social relations, self-confidence, and motivation—despite facing
different socio-economic conditions. These results underscore the importance of further strengthening
and guiding these existing capacities through targeted educational initiatives and concrete entrepreneur-
ship support programs. Given that the entrepreneurial potential of youth is a key driver of social trans-
formation and broader socio-economic development, especially in transitional contexts, investing in the
entrepreneurial empowerment of young individuals from outside the EU is both a strategic and necessary
endeavor (Audretsch and Peña 2012; Baporikar, 2020; Brixiova, 2013; Čeko and Rađenović-Kozić, 2023;
Kudysheva, 2020; Parker, 2009; Sarlija and Susac, 2010; Sulejman, 2020; Toma, and Marinescu, 2013;
Yordanova and Tarrazon, 2010).
The results did not show the existence of significant differences between students from urban
and rural areas in the expressiveness of the entrepreneurial potential dimensions of the QET and SEP
models. The results of previous studies in this domain are not completely unambiguous (Capelleras et
al., 2013; Duricova 2014; Faggio and Silva, 2014; Al Harrasi and Ali, 2025; Hyunjeong, 2011; Muham-
mad and Ximei, 2022) and this finding points to the fact that young people in urban and rural areas have
equally developed entrepreneurial abilities, skills, knowledge, motivation, and interests needed to engage
in entrepreneurship. To a certain extent, this finding gives a positive picture, when it comes to the urban
and rural population and its readiness to engage in entrepreneurial occupations, which speaks of positive
tendencies and opportunities for growth and development, both in urban and rural areas (Capelleras et
al., 2013; Duricova 2014). On the other hand, if certain incentive programs are planned for the develop-
ment of entrepreneurship and the entrepreneurial potential of the population, it is necessary to organize
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
and implement them, with equal intensity, both in urban and rural areas, whereby the specificities and
needs characteristic of the given environment can be included in concrete incentives and activities (Fag-
gio and Silva, 2014; Hyunjeong, 2011).
When it comes to the effect of financial status on the development of entrepreneurial potential
among young people, differences between students of different financial status were confirmed in terms
of the expressiveness of the dimensions of the QET and SEP models. The analysis revealed that students
with below-average financial status scored higher on the interest in entrepreneurship and knowledge sub-
scale of the QET model compared to those with average financial status. In contrast, students with above-
average financial status demonstrated significantly higher scores on the SEP sub-scales social relations,
organizational skills, self-confidence, and extroversion, relative to students with average financial status.
These findings suggest that different dimensions of entrepreneurial potential may be deferentially influ-
enced by students’ material conditions.This result indicates that young people who are in a better financial
condition have more developed key qualities for engaging in entrepreneurship, such as organizational
skills, self-confidence, and openness to change, skills in social contacts. It is possible that the material
condition alone directly provides them with certain security, self-confidence and openness to various op-
portunities (Alger and Weibull, 2010; Friedline and West, 2015; Hosseini, 2016; Lee and Persson, 2012),
while there is also the possibility that the good material condition of such young people is a consequence
of growing up in a stimulating environment, where the entrepreneurial spirit and entrepreneurship are
nurtured, which further represents an additional factor that contributes to their development of entrepre-
neurial potential (Bagheri and Pihie, 2010; Dunn and Holtz-Eakin, 2000; Li et al., 2022; Mustapha and
Selvaraju, 2015; Rajković et al., 2021). Young people who are of lower material status only have a more
developed dimension of knowledge, which is very encouraging and can have positive effects, if in the
educational sense they are directed in a timely manner towards the development of other entrepreneurial
capacities and skills, and especially motivated through various stimulating programs for engaging in en-
trepreneurship (Jiménez et al., 2015; OECD and European Commission, 2014).
An interesting finding of the study is that students’ academic success does not exhibit a direct cor-
relation with the dimensions of entrepreneurial potential as measured by the QET and SEP models. This
suggests that the core characteristics underlying entrepreneurial potential may operate independently
of traditional academic performance, reflecting distinct cognitive, motivational, and behavioral traits not
necessarily captured by academic achievement alone. and speaks of the fact that they are more related
to practical abilities, skills and action, and less to the general success in the academic community, theo-
retical knowledge and skills needed to achieve success in learning, in a narrower sense, but without the
application of knowledge (Anderson, Samimi and 2010; Machado et al., 2022; Moutray, 2009; Mumtaz et
al., 2024; Sharma and Madan, 2014). The absence of a direct link between academic success and en-
trepreneurial potential—along with the recognition that academic achievement alone does not guarantee
success in entrepreneurship—highlights the need to broaden educational content and methodologies.
Specifically, curricula should be expanded to actively foster the development of entrepreneurial potential
among young people. This includes promoting students’ readiness to engage in entrepreneurship through
practical, experience-based learning formats such as hands-on teaching practice, independent project
work, and guided mentorship. Crucially, these activities should take place in environments that closely
simulate real-world conditions and future workplace settings, thereby enhancing the relevance and appli-
cability of entrepreneurial education (Levesque and Minniti, 2006; Mathew and Johnson, 2014; Peterman
and Kennedy, 2003; Sharma and Madan, 2014; Ward, 2004).
Conclusions
The results of this research confirmed that various socio-demographic factors influence the expres-
sion of the entrepreneurial potential of young people. Thus, it was confirmed that young male respond-
ents, students from the EU, as well as respondents with a better financial status have better developed
most entrepreneurial traits, while young people from urban and rural areas, as well as students of different
academic success, do not differ from each other in terms of the development of dimensions of entrepre-
neurial potential.
Analyzing the social and economic background of the countries from which the respondents in-
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
volved in this research come from, we can already detect major differences in the social structure and
class system that could provide interesting insight for future research. Respondents from Bosnia and
Herzegovina and Serbia come from, a decades long socialist system that now days evolved in market
economy having a very harsh trasitional period. While respondents from Belgium as an EU country come
from a decedes long capitalist system, that nurtured entrepreneurship as its core value. This alone points
to major differences of the respondents perspective of researched phenomenon. Future research com-
paring post socialist societies and the differences in the development of entrepreneurship in regard to
developed countries could be potentially very interesting.
The results obtained in this study hold considerable significance for both theoretical and practical
domains. Theoretically, they enhance the conceptual understanding of entrepreneurial potential, offering
insights into its multidimensional structure and the socio-demographic factors that shape the develop-
ment of specific dimensions. Practically, the findings open important avenues for the more effective plan-
ning and implementation of educational interventions and entrepreneurship support programs. These
programs should be strategically designed to promote female entrepreneurship, support entrepreneurial
initiatives in transitional economies at various stages of EU accession, and empower socially vulnerable
populations—particularly individuals from lower socio-economic backgrounds. Furthermore, the results
highlight the need for a thorough revision and innovation of school and university curricula, with the aim
of systematically fostering entrepreneurial potential among children and youth through the development
of relevant cognitive, emotional, social, and behavioral traits. Possible limitations of the study simultane-
ously open questions for future research, in which it would be expedient to include primary and secondary
school students, to expand the number of countries included in the sample, especially those from the
EU, as well as to examine potential interactions between various socio-demographic factors, with the aim
of creating a more comprehensive model of the action of various factors of entrepreneurial potential in
children and young people.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial,
or not-for-profit sectors.
Conflict of interests
The authors declare no conflict of interest.
Data availbility statement
The original contributions presented in the study are included in the article/supplementary material,
further inquiries can be directed to the corresponding author/s.
Institutional Review Board Statement
Not applicable.
Author Contributions
Conceptualization, M.S. and M.M.; Methodology, M.M., M.S., V. R.L. and S.M.; Formal analysis, V.
R.L. and S.M..; Visualization, V. R.L.; Validation, S.M. and M.S.; Resources, M.S.; Supervision, M.S. and
B.D.; Writing—original draft, M.M., S.M. and M.S.; Writing—review & editing, M.M., V.R.L., S.M., M.S.,
A.N.T. and B.D.; Investigation, A.N.T. and B.D.; Data curation, A.N.T.; Project administration, B.D.
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Marić, M. et al. (2025). Socio-demographic factors and their influence on the development of entrepreneurial potential of
students, International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), 13(3), 649-665.
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