Next Article in Journal
Large-Eddy Simulation of Wind Turbine Wakes in Forest Terrain
Next Article in Special Issue
Open Innovation in Agribusiness: Barriers and Challenges in the Transition to Agriculture 4.0
Previous Article in Journal
Family Conflict and Suicidal Behaviour in Adolescence: The Mediating Role of the Assertive Interpersonal Schema
Previous Article in Special Issue
Innovation of Family-Owned Enterprises and Government Subsidies: From A Policy-Oriented Perspective
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 15
Issue 6
10.3390/su15065151
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Role of Demographic Factors and Prior Entrepreneurial Exposure in Shaping the Entrepreneurial Intentions of Young Adults: The Case of Croatia

by
Ljiljana Najev Cacija
,
Marina Lovrincevic
* and
Ivana Bilic
Faculty of Economics, Business, and Tourism, University of Split, 21000 Split, Croatia
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 5151; https://doi.org/10.3390/su15065151
Submission received: 1 February 2023 / Revised: 2 March 2023 / Accepted: 10 March 2023 / Published: 14 March 2023
(This article belongs to the Special Issue Entrepreneur Collaboration, Social Entrepreneurship, and Open Innovation from a Sustainability Perspective)
Browse Figure
Versions Notes

Abstract

:
This research was designed in order to investigate the role of important individual and situational factors in shaping entrepreneurial intentions of young adults in the Republic of Croatia. For that purpose, a survey was conducted on the sample of 257 young adults using a questionnaire. In order to test the proposed hypotheses stating that there are statistically significant differences in young adults’ entrepreneurial intentions regarding demographic factors (gender, age, and level of education), prior entrepreneurial exposure, and the perception of prior entrepreneurial exposure, a statistical analysis was performed using the Mann–Whitney and Kruskal–Wallis tests. Overall, the results give partial support for the hypothesis regarding demographic factors and prior entrepreneurial exposure and full support for the hypothesis regarding the perception of prior entrepreneurial exposure. Additionally, CHAID method classification was applied in order to fully grasp the relationship between entrepreneurial intentions and the analyzed factors, and the results clearly indicate that the perception of prior entrepreneurial exposure can be seen as a single best predictor of entrepreneurial intentions.

1. Introduction

According to psychological theories, an individual represents an actor who possesses certain desires and attitudes that shape the goals that the individual pursues using intentional behavior. Intention is one of the cognitive (i.e., mental) mechanisms that can be used to explain human behavior. Intentional behavior that denotes acting towards intention represents the function of willingness to pursue a goal based on the belief that a certain set of actions will satisfy one’s desires [1].
Most behaviors in everyday life are to a great extent under the individual’s volitional control. When a certain behavior is not fully controllable, either internal or external factors may curb the performance underlying intentional behavior. In most cases, when individuals perceive that they personally have control over their behavior, they will tend to act upon their intentions [2]. Krueger et al. [3] (p. 411) pointed out that “in the psychological literature, intentions have proven the best predictor of planned behavior, particularly when that behavior is rare, hard to observe, or involves unpredictable time lags”, which makes the concept of intentional behavior ideal for studying entrepreneurial processes that capture both opportunity discovery and opportunity exploitation.
Entrepreneurship is planned, intentional behavior [4,5]. Many entrepreneurial ideas result from inspiration, but to turn these ideas into reality, an intention has to be set [6]. A “Brilliant business idea” can sometimes be the spark that encourages an actual decision on starting a new venture, but entrepreneurship literature provides evidence that most entrepreneurs actually decide on starting a new business venture even before opportunity recognition [7]. In the context of entrepreneurial intentions of young adults, the most widely used variables include gender, age, education level, prior exposure to self-employment, and parents’ entrepreneurial experience [8], although the available evidence is still fairly inconclusive.
Given the importance of young adults, being a vital strategic resource in the ever-competitive global economy context, factors that shape entrepreneurial intentions of young adults deserve special attention. Additional research of these factors should be undertaken in order to create new insights and new knowledge that will contribute to fostering entrepreneurship.
Entrepreneurial activity in the Republic of Croatia is still underdeveloped. According to Singer et al. [9], the entrepreneurial climate in Croatia should be seen as an inhibitor rather than a stimulus for entrepreneurial activity. Analyzing the NECI index (national entrepreneurship context index), which reflects the overall strength of the national entrepreneurial framework, the Republic of Croatia is at the bottom of the list of countries that participate in GEM ranking (index value = 3.9). On the other hand, the TEA index (total entrepreneurial activity) shows that entrepreneurial activity in the Republic of Croatia is comparable to the European Union average where, in the case of entrepreneurial intention, Croatia scores above the European Union average. Nevertheless, the problem remains that the actual realization of entrepreneurial intentions is still fairly low due to insufficient institutional support.
Accordingly, the primary purpose of this research was to investigate personal factors and prior entrepreneurial exposure in the process of entrepreneurial intention formation in the specific sociocultural context of young adults’ entrepreneurship perception.

2. Theoretical Background

Entrepreneurial intention is a rapidly growing field of research, and the number of studies using the concept of entrepreneurial intention is increasing tremendously [10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31].
Bird [4] defines entrepreneurial intention as a cognitive representation of the actions that have to be carried out in order to create a new venture or create new value within existing companies, while Kreuger [32] describes entrepreneurial intention simply as a commitment to starting a new business.
Ajzen’s theory of planned behavior [2,33] is widely accepted as one of the most prominent approaches to understanding entrepreneurial intentions and decisions, how they are formed, and what precedes them [34]. The concept of intentionality is fairly simple; the individual’s behavior is best predicted by one’s intentions, and intentions are, in turn, predicted by attitudes about the behavior, the subjective norms (a person’s perception of important others’ beliefs that he or she should or should not perform the behavior) encasing the execution of the behavior, and the individual’s perception of their control over the behavior [35]. The three abovementioned antecedents of intention are shaped by beliefs that, in turn, directly affect the process of intention formation.
Recognizing that starting a business is an intentional act holds substantial implications [3], especially regarding the explanatory power that either attitudes or exogenous factors (situational or individual) alone can provide in an attempt to better understand entrepreneurial behavior. Ultimately, an individual’s behavior is best explained by focusing on key attitudes that affect the formation of the antecedents of one’s intentions. Since beliefs and attitudes basically represent the information (being accurate or otherwise) that individuals hold, it can be stated that behavior is determined by information.
According to Ajzen [2], other factors such as personality traits or demographic factors will be related to behavior only to the extent that they contribute to attitudes about the behavior, to perceived control over the behavior, and to normative considerations. However, situational factors, demographic factors, and personality traits affect the formation of key attitudes in the context of intentionality, thus affecting intentions and behaviors.
Translating the theory of planned behavior propositions into an entrepreneurial setting means that entrepreneurial intention is the function of an individual’s attitudes toward entrepreneurship, the opinions that relevant others have about an individual’s potential entrepreneurial engagement, and the perceived control over an option of starting a new venture, along with the individual’s beliefs and attitudes that are in the foundations of these three elements.
Intention-based models have been criticized for their straightforward and linear nature that limits the investigation of mutual, exponential, and/or moderating relationships between variables in these models, often leading to contrasting and mixed results [36]. Nevertheless, the predictive power of intentions is proven to be fairly strong; thus, a strong intention to start a business should result in an eventual attempt [3].
Analyzing the available literature, it becomes evident that two main categories of factors relevant to entrepreneurial intentions have been established: individual and situational factors. Individual factors capture personal characteristics that typically include demographic factors, prior education and experience, and certain personality traits. Situational factors represent the environmental setting, which is typically described by institutions and resources and their respective characteristics that determine an individual’s inclination (propensity) toward entrepreneurship.
Demographic factors such as income, gender, race, and ethnicity influence entrepreneurial intentions [37]. Individuals coming from higher-income families tend to incline more towards entrepreneurship [38], and male adults in the United States demonstrate twice as high a level of entrepreneurial intentions in contrast to female counterparts [39]. Factors such as education and previous professional experience can also affect individual inclinations towards entrepreneurship [40].
Early researchers in the entrepreneurial intention domain have focused on personality traits such as need for achievement [41], risk-taking propensity [42], internal locus of control [43], self-confidence [44], and innovativeness [45]. Leaning on Holland’s assumption [46] that career choice is an expression of personality, some researchers have focused on the “Big five traits” theory, aiming at determining its explanatory power in the context of entrepreneurial intentionality. The underlying idea is that personality as a whole (and not traits) defines one’s inclination towards entrepreneurship. An entrepreneurial individual, according to this theory, is a person demonstrating higher levels of extraversion, conscientiousness, and openness and lower levels of agreeableness and neuroticism. This particular pattern of traits raises the chances that an individual will pursue a career in entrepreneurship [22,47]. Besides relatively stable personality traits, skills that individuals can adopt and develop, such as creativity and emotional intelligence, can also affect the formation of entrepreneurial intentions [48,49].
Young adults (ages 18–29) tend to demonstrate higher levels of inclination towards entrepreneurship in comparison to other groups, but there is also a significant gap visible between entrepreneurial intentions and the actual realization of new ventures for this particular group (only 7.2% of the world’s population of young adults are actively involved in entrepreneurial activities, in contrast to the 25.3% of the young adult population demonstrating entrepreneurial aspirations) [50]. Young adults are more sensitive to new information and have the ability to adjust their expectations faster than other groups. In addition, they tend to demonstrate higher levels of proactiveness, aggressiveness, creativity, and risk-taking propensity [51], and these attributes can be important determinants of entrepreneurial intentions [42,49].
Situational factors can also affect the decision of starting a new business to a great extent. Stenholm et al. [52] found that social norms, values, and attitudes determine the relative desirability of entrepreneurship as a career choice, whereas the level of society’s admiration of entrepreneurs can be assessed as a predictor of entrepreneurial activity [53]. Positive attitudes towards entrepreneurs significantly shape an individual’s entrepreneurial intentions [54]. The theory of social learning [55] emphasizes the importance of observing, modeling, and imitating the behaviors, attitudes, and emotional reactions of others, so individuals coming from successful entrepreneurial backgrounds demonstrate higher levels of inclination towards entrepreneurship [56]. Individuals whose parents have experience in entrepreneurship demonstrate higher levels of entrepreneurial intentions [57], and when the parents’ entrepreneurial experience is perceived as positive, individuals demonstrate higher levels of desirability for and perceived feasibility of an entrepreneurial career [58]. It should be noted that prior entrepreneurial exposure can impact entrepreneurial intentions not only directly but also indirectly, as suggested by the theory of planned behavior [59]. Still, Zapkau et al. [60], drawing from the systematic review of 69 quantitative empirical journal articles, conclude that the findings are ambiguous and that the current state regarding how and in which context prior entrepreneurial exposure impacts the entrepreneurial process is widely unclear.
The aim of this research was to determine the role of demographic factors and prior entrepreneurial exposure in the process of entrepreneurial intention formation. The research hypotheses are stated as follows:
H1. 
There is a statistically significant difference in the young adults’ entrepreneurial intentions regarding the demographic factors of gender, age, and level of education.
H2. 
There is a statistically significant difference in the young adults’ entrepreneurial intentions regarding prior entrepreneurial exposure.
H3. 
There is a statistically significant difference in the young adults’ entrepreneurial intentions regarding the perception of prior entrepreneurial exposure.
Demographic factors such as gender have been proposed to have an impact on entrepreneurial intention [10]. In general, women are considered to express lower levels of entrepreneurial intentions [61,62,63]. In contrast, some studies report no difference between men and women regarding entrepreneurial intentions [64,65,66]. Daim et al. [67] studied entrepreneurial intentions of students in 10 different countries and found that gender differences are country-dependent.
Age is argued to have a negative association with entrepreneurial intentions, e.g., age is seen as being inversely related to entrepreneurial inclination, as some studies confirm that ages from 25 to 34 are most fruitful in terms of starting one’s own business [68,69]. In contrast, some studies give support to the idea that entrepreneurial inclination is not inversely related to age [66].
The relationship between education level and entrepreneurial intention is also inconclusive. Some studies show that education has a positive influence on entrepreneurial performance/intentions [70,71], whereas the relationship between university education in general and entrepreneurship is not so strong and straightforward [72,73] and can be context-dependent [74].
Prior entrepreneurial exposure, in the form of parental experience and a family business background, has a positive influence on entrepreneurial intentions [57,59,75,76,77,78]. Moreover, the perception of parental experience or prior entrepreneurial exposure seems to play a vital role in determining entrepreneurial intentions; Drennan et al. [58] reported that individuals holding positive perceptions of their family’s business experience perceived starting their own business as being both desirable and feasible.

3. Research Methodology, Sample, and Questionnaire

Variables were operationalized by using the measurement scales applied in Drennan et al. [58] for prior entrepreneurial exposure and the perception of prior entrepreneurial exposure (based on the existence of prior entrepreneurial exposure, perception was rated as negative, neutral, or positive), and by adjusting the entrepreneurial intentions scale used in Adrić et al. [79] (3 items out of 5 from the original scale; calculated Chronbach Alpha score: 0.925).
The research was conducted using an online survey in the Republic of Croatia from April to August 2020 on a sample of 257 respondents.
Due to limited resources, a convenience-sampling method was applied, including only students from the Faculty of Economics, Business and Tourism in Split. In total, 300 online questionnaires were distributed, and 260 participants filled out the questionnaire (out of which 3 were not valid). Finally, the response rate was 85.67%, which was highly acceptable. The questionnaire included eight closed-ended questions. The first part of the questionnaire captured demographic factors, the second part included prior entrepreneurial exposure (dichotomous scale yes/no), while the third part assessed entrepreneurial intentions. For entrepreneurial intentions, a five-point Likert scale was applied, where 1 equaled strongly disagree/very negative and 5 equaled strongly agree/very positive. For prior entrepreneurial exposure (if it existed), a three-point Likert scale was applied, where 1 equaled negative experience, 2 equaled neutral, and 3 equaled positive.
Since the data were non-normally distributed, nonparametric tests were used: the Mann–Whitney and Kruskal–Wallis tests. Additionally, the decision-tree classification technique (CHAID method) was applied in order to graphically describe the relationship between the independent variables (demographic factors and prior entrepreneurial exposure) and the dependent variable (entrepreneurial intentions). Assessment of risk for the proposed classification model was calculated, and an additional argument is provided in order to contribute to future conceptual model developments.

4. Results and Discussion

As can be seen in Table 1, in the young adults’ research sample, the majority were female (63.8%), aged 23–26 years old (61.1%), and held undergraduate or graduate diplomas (63.1%). The majority of respondents did not report previous entrepreneurial exposure (63.8%). It can be concluded that the research sample represents an active population in terms of labor-market involvement, where employment options are seriously taken into consideration. A relatively small proportion of the sample (20.6%) had already undertaken steps directed towards self-employment and new venture creation.
Table 2 shows descriptive statistics about prior entrepreneurial exposure. The majority of young adults in the sample did not report any prior entrepreneurial exposure (63.8%) that could affect their general attitudes about entrepreneurship. Out of the respondents who reported prior entrepreneurial exposure, the majority of the respondents reported positive experiences (18.8%), while 10.6% reported a negative experience. It is interesting to note that the smallest proportion of the respondents accounted for those with neutral perceptions of prior entrepreneurial exposure (parental experience).
Table 3 presents descriptive statistics about entrepreneurial intentions.
From the data presented in Table 3, we can conclude that entrepreneurial intentions are mostly neutral on the sample level (ranging from 3.16 for EI1 to 3.35 for EI3 on the scale from 1 to 5). However, the aim of this research was to clarify the role of demographic factors and the perception of prior entrepreneurial exposure in shaping entrepreneurial intentions, so the results will be presented accordingly.
In order to reach an answer to first question of whether there is a statistically significant difference in young adults’ entrepreneurial intentions regarding the demographic factors of gender, age, and level of education, descriptive statistics were determined and the Mann–Whitney and Kruskal–Wallis tests were performed. Gender differences are presented in Table 4.
From the results presented in Table 4, it becomes clear that the mean values for items representing entrepreneurial intentions are higher for male respondents. The highest mean score is recorded for item EI2 (3.44), and the lowest mean value is recorded for item EI1 for both male and female respondents. Generally, all items’ means tended to slightly, but positively, deviate from the mean value (3), so the conclusion of developed entrepreneurial intentions cannot be reached. However, the results of the Mann–Whitney U test showed that there is a statistically significant difference regarding gender for item EI1 (p = 0.044). This result is not fully in line with previous investigations pointing to gender irrelevance in the context of entrepreneurial intentionality, but in the context of this research, it could be explained by cultural values—in Croatia, entrepreneurship is still predominantly seen through the lens of a masculine gender role (stereotype).
In Table 5, age differences are presented.
The results presented in Table 5 clearly indicate the relative neutrality of entrepreneurial intentions for all of the analyzed items. Still, the mean value for all items is slightly higher for respondents aged 23–26 years old compared to the group aged 27–30 years old. The highest mean value is recorded for EI3 (3.52) in the group aged 23–26 years old, while the lowest mean value can be assigned to EI1 in the group aged 27–30 years old. The observed differences can be explained by the characteristics of the younger generation, the population that is presumably still involved in tertiary education processes and perceive their employment as being in the relatively distant future. Even though the population aged 27–30 years old can still be classified as young, this particular group has reached an age where a clearer professional orientation setting is needed, so entrepreneurial intentions in that context can be seen as an option that induces higher risk (compared to alternative employment options). The results of the Mann–Whitney test show that there are statistically significant differences for items EI2 and EI3 (at the 5% significance level) and for item EI1 (at the 10% significance level) regarding the respondents’ ages.
Table 6 presents the descriptive statistics and the Kruskal–Wallis test results regarding education level.
Analyzing the mean values of the entrepreneurial intentions regarding respondents’ education levels, it becomes evident that the highest mean values are recorded for the tertiary education group (ranging from 3.25 to 3.43), while the lowest mean values can be attributed to the postgraduate education group (ranging from 2.43 to 2.71).
Additionally, it is clear that entrepreneurial intentions for the postgraduate group are adversely represented, given the fact that mean values are less than three on the scale from one to five. Even though this particular group is significantly smaller than other analyzed groups (only seven respondents), and the results should be taken with precaution, it is evident that a higher education level is associated with a lower level of entrepreneurial intentions. It can be argued that respondents are willing to use the knowledge acquired through the education process or they are actually using it by working while still studying. In the context of entrepreneurial intentions, by working for the employer, this particular group eliminates the potential failure risk of starting one’s own business. Alternatively, this could be explained by the fear of assigning potential failure of starting a business to an inadequacy of knowledge acquired through the education process, and therefore questioning the investment rationale of their own education.
However, regardless of the analyzed differences, the Kruskal–Wallis test results show that there are no statistically significant differences in entrepreneurial intentions regarding education level, which is in line with similar research.
According to the above-presented results, hypothesis H1, stating that there is a statistically significant difference in the young adults’ entrepreneurial intentions regarding demographic factors of gender, age, and level of education, can be only partially accepted. The research results clearly indicate that such differences can be found for gender and age and not for education level.
Next, in Table 7, the results of descriptive statistics of entrepreneurial intentions and the Mann–Whitney test results regarding prior entrepreneurial exposure are presented.
From the presented results, it becomes evident that entrepreneurial intentions’ mean values differ regarding prior entrepreneurial exposure, which is in line with similar research. For all items representing entrepreneurial intentions, their mean values are higher for the group that reported prior entrepreneurial exposure (3.34 to 3.55) compared to the group that did not report such experience (3.06 to 3.24). The highest mean value recorded was for EI3 (3.55) in the group that reported prior entrepreneurial exposure, while the lowest was for EI1 (3.06) in the group that did not.
These results provide additional support for the argument that prior entrepreneurial exposure may affect personal attitudes and entrepreneurial intentions indirectly via observing model roles—parents. In addition, it can be argued that risk perception has a significant influence on attitudes. Individuals who have previous entrepreneurial exposure may lack the irrational fear of the unknown, and the perception of risk can be reduced due to the successful previous parental experiences or the ability to assess eventual consequences of failure more objectively and realistically.
The observed differences are statistically significant for EI1 (p = 0.038) and EI3 (p = 0.030). According to the presented results, hypothesis H2, stating that there is a statistically significant difference in the young adults’ entrepreneurial intentions regarding prior entrepreneurial exposure, can be partially accepted.
Finally, presented in Table 8 are the results regarding entrepreneurial intentions and the perception of prior entrepreneurial exposure. Given the fact that respondents were evaluating prior entrepreneurial exposure using a five-point Likert scale, three groups were formed: (1) the group that shares negative and very negative experiences (scoring one and two on the scale), (2) the group that shares neutral experiences (scoring three on the scale), and (3) the group that shares positive and very positive experiences (scoring four and five on the scale). The respondents reporting not to have prior entrepreneurial exposure were excluded from the analysis.
As it can be seen in Table 8, the role of the perception of prior entrepreneurial exposure in shaping entrepreneurial intentions is evident. The group sharing negative experiences scored lowest mean values for all items (from 2.78 to 3.15), whereas the group sharing positive experiences scored the highest mean values for all items (from 3.69 to 3.81). In addition, the mean values for entrepreneurial intentions recorded for the group sharing positive experiences were the highest in the overall sample. This result was expected and gives additional support to the argument that entrepreneurial intentions can be shaped by previous experiences, even when those experiences are not personal and direct; they can be affected indirectly through family business exposure. The results of the Kruskal–Wallis test show that there are statistically significant differences for items EI1 and EI3 (at the 5% significance level) and for item EI2 (at the 10% significance level) regarding the perception of prior entrepreneurial exposure.
According to the presented results, hypothesis H3, stating that there is a statistically significant difference in the young adults’ entrepreneurial intentions regarding the perception of prior entrepreneurial exposure, can be accepted.
Table 9 summarizes all previously discussed findings.
The summarized results give support to the conclusion that both age and the perception of prior entrepreneurial exposure are factors that shape entrepreneurial intentions for the most part, while education level cannot be seen as a relevant factor in assessing young adults’ entrepreneurial intentions.
As to additionally evaluate the importance of the proposed factors, a classification using the decision-tree method was applied. It is a nonparametric technique that successfully solves classification and prediction problems [80]. In this case, the classification of young adults according to relevant factors into homogenous groups regarding entrepreneurial intentions was applied. For that purpose, a new variable, entrepreneurial intention (EI), was created by defining the mean values for items EI1, EI2, and EI3, followed by classification into categories, ranging from one to five, representing the intensity of the entrepreneurial intentions. Table 10 presents the model summary, which entails relevant criteria and the risk of incorrect classification (false-positive classification).
The Chi-square automatic interaction detection (CHAID) method was applied. The dependent variable is represented by the intensity of the entrepreneurial intentions. Independent variables, predictors, were represented by relevant factors: gender, age, education level, prior entrepreneurial exposure, and the perception of prior entrepreneurial exposure. The classification using the CHAID method includes the identification of the independent variable demonstrating the strongest interaction with the dependent variable on each level, and the independent variables are merged when observed differences are not statistically significant. The level on which the minimal number of cases is defined, i.e., the decision node (the limit for the segment size that is branching on the parent node and child node), is 40/15. The analysis is carried out by focusing on the answer to a single question and then selecting the best variable to split the dataset into subsets, where the ideal situation is when sizable differences exist between subsets.
In the model presented in Figure 1, it is evident that the largest group of respondents (31.9%) had neutral entrepreneurial intentions. The second group, comprising 30.0% of the respondents, had developed entrepreneurial intentions, while only 3.9% of the respondents reported not having entrepreneurial intentions. Out of the proposed factors, statistically significant differences (relevant for forming groups within the decision tree) were found for the criterion of the perception of prior entrepreneurial exposure (in the first branch). Three groups were created: not having prior entrepreneurial exposure (0), negative and neutral perceptions of prior entrepreneurial exposure (1; 2), and positive perception of prior entrepreneurial exposure (3). It is interesting that within the group having positive perceptions of prior entrepreneurial exposure, the largest proportion of respondents (41.7%) had fully developed entrepreneurial intentions, while in the group that had no prior entrepreneurial exposure, the largest proportion of the respondents (37.7%) had neutral entrepreneurial intentions. For the group of respondents having neutral perceptions of prior entrepreneurial exposure, the largest proportion of respondents developed entrepreneurial intentions (50.0%).
The second classification criterion in the decision tree is gender, but only for the group that has positive prior entrepreneurial exposure. In the gender classification group, the largest proportion of respondents of both sexes had fully developed entrepreneurial intentions: 46.7% male respondents and 39.4% female respondents.
In the presented model, the CHAID classification did not find the factors of age, level of education, and prior entrepreneurial exposure to be relevant, per se. In total, the model includes four groups, two of which were created using double criteria: perception of prior entrepreneurial exposure (negative, neutral, and positive) and gender (male and female). The other two groups were formed using a single criterion: the perception of prior entrepreneurial exposure.
The risk assessment for the proposed model is 0.595, with a standard error of 0.031 (CHAID method). The risk assessment points to the probability of false classification. Specifically, the results show that the risk of false classification of young adults with respect to entrepreneurial intentions, using the selected factors, is 59.5%. Still, given the complexity and unique characteristics of the research problem and the very purpose of this analysis—creating solid foundations for the development of a conceptual model regarding the role of demographic factors and prior entrepreneurial exposure in shaping entrepreneurial intentions—the authors of the paper consider this risk assessment to be acceptable.

5. Conclusions

The concept of entrepreneurial intentionality has been widely recognized in the entrepreneurship literature as a viable model for understanding entrepreneurial behavior, especially regarding the perspective of the decision to pursue entrepreneurial ideas, e.g., starting a new venture.
The predictive power of intention-based models is proven to be fairly strong, and two main categories of factors affecting entrepreneurial intentions have been recognized in the entrepreneurship literature: individual factors that capture personal characteristics and situational factors that represent environmental settings.
This research was designed in order to investigate the role of important individual and situational factors in shaping entrepreneurial intentions of young adults. This particular population group can be considered as a vitally important strategic asset in terms of encouraging entrepreneurship and advancing its contribution to global economic development. In that sense, young adults can be particularly receptive to incentives that governments worldwide are offering in order to promote entrepreneurial activity.
To evaluate the proposed hypotheses stating that there are statistically significant differences in young adults’ entrepreneurial intentions regarding demographic factors (gender, age, and level of education), prior entrepreneurial exposure, and the perception of prior entrepreneurial exposure, research was conducted on a sample of 257 young adults from the Republic of Croatia.
According to the research results, demographic factors can be considered as relevant factors in the context of young adults’ entrepreneurial intentions in the Republic of Croatia. The results suggest that the younger age category (23–26 years old) tends to demonstrate higher levels of entrepreneurial intentions compared to older counterparts (27–30 years old). The younger category is presumably still attending college or university and has an unclear picture of employment prospects, while the older category is expected to have a clearer professional orientation and career path. Contrary to similar research, gender was found to be a relevant factor in assessing entrepreneurial intentions, where male young adults tend to demonstrate higher levels of entrepreneurial intentions compared to female counterparts. These unexpected results can be explained by cultural values and tradition in the Republic of Croatia, where entrepreneurship is still stereotyped as being a masculine career option. Out of demographic factors analyzed, the level of education was found to be irrelevant with respect to entrepreneurial intentions, which is in line with similar research. Overall, demographic factors play an important role in young adults’ entrepreneurial intentions in the Republic of Croatia.
As for the important situational factors of prior entrepreneurial exposure and the perception of prior entrepreneurial exposure, their role was found to be even greater in shaping young adults’ entrepreneurial intentions, which is line with similar research.
Finally, the results give partial support for the hypothesis regarding demographic factors and prior entrepreneurial exposure and full support for the hypothesis regarding the perception of prior entrepreneurial exposure.
In addition to statistical analysis, a decision-tree method was applied (CHAID method) in order to fully grasp the relationship between entrepreneurial intentions (dependent variable) and predictors, capturing demographic factors, prior entrepreneurial exposure, and the perception of prior entrepreneurial exposure. The results of the CHAID classification suggest that the perception of prior entrepreneurial exposure is the single best predictor of entrepreneurial intentions. Albeit the proposed classification has limitations, the authors of this article strongly believe that it has practical value in contributing to the development of a conceptual model regarding the role of individual and situational factors in shaping entrepreneurial intentions.
Since there is a generally a negative perception of entrepreneurship in Croatia, based primarily on “notorious” negative entrepreneurial examples in the past, this research could be a starting point in reshaping current public opinion and improving the general perception of entrepreneurs. For example, the importance of prior entrepreneurial exposure and the perception of it in shaping young adults’ entrepreneurial intentions is undoubtful. However, influencing possible negative perception as a factor that might impact the decision not to become an entrepreneur might be a good starting point in changing the general perception of entrepreneurship in Croatia. Educating young adults that failure is a part of the entrepreneurial process, and that improving skills through failures is a standard path in entrepreneurship, can remove the stigma of “must succeed at the first attempt”. In addition, prior entrepreneurial exposure can be perceived as a first step in taking own entrepreneurial path, but solely one. If policymakers and educational institutions put more effort into emphasizing the importance of an entrepreneurial mindset, it might encourage youth to take that path. So, more entrepreneurial competencies in educational curricula in higher education can benefit not only students participating in that kind of education but the community as well.
Limitations of this research can also be attributed to the relatively small research sample from one country, a lack of participants representing the youngest segment (18–22 years), and the exclusion of psychological aspects and social status that can determine one’s entrepreneurial intentions. Thus, future research should take into consideration additional variables regarding young adults’ behavior and attitudes and include participants from other countries with different economic situations. However, the conclusions drawn from this research can be beneficial for transitional economies, more specifically, South-East European countries, where the lack of similar investigations is still evident, and the need for activating entrepreneurial potential and resources has never been greater.
Finally, the most “valuable” implication can be seen in accenting prior entrepreneurial exposure as a key predictor of entrepreneurial intentions. All outcomes arising from that exposure can be managed by creating an entrepreneurial mindset, thus contributing to the efficiency and efficacy of exploiting entrepreneurial capacity through existing entrepreneurial intentions. The importance of an educational framework for building entrepreneurial competencies is undoubtful, regardless of research results that point to the irrelevance of educational level. Keeping in mind that this research was carried out in Croatia, one of the youngest members of the European Union, and considering all the research limitations, implications for practitioners can also include better convergence of the existing experience in shaping learning outcomes related to entrepreneurship.

Author Contributions

Conceptualization, L.N.C. and M.L.; Methodology, L.N.C., M.L. and I.B.; Investigation, M.L.; Data curation, L.N.C.; Writing—original draft, L.N.C., M.L. and I.B.; Writing—review & editing, M.L. and I.B. 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

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Research data can be provided by authors upon request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Malle, B.F.; Knobe, J. The folk concept of intentionality. J. Exp. Soc. Psychol. 1997, 33, 101–121. [Google Scholar] [CrossRef] [Green Version]
  2. Ajzen, I. Perceived Behavioral Control, Self-efficacy, Locus of Control and the Theory of Planned Behavior. J. Appl. Soc. Psychol. 2002, 32, 665–683. [Google Scholar] [CrossRef]
  3. Krueger, N.F., Jr.; Reilly, M.D.; Carsrud, A.L. Competing models of entrepreneurial intentions. J. Bus. Ventur. 2000, 15, 411–432. [Google Scholar] [CrossRef]
  4. Bird, B. Implementing entrepreneurial ideas: The case for intention. Acad. Manag. Rev. 1988, 13, 442–453. [Google Scholar] [CrossRef]
  5. Katz, J.; Gartner, W. Properties of emerging organizations. Acad. Manag. Rev. 1988, 13, 429–441. [Google Scholar] [CrossRef]
  6. Delmar, F.; Shane, S. Does business planning facilitate the development of new ventures? Strateg. Manag. J. 2003, 24, 1165–1185. [Google Scholar] [CrossRef]
  7. Prabhu, V.P.; McGuire, S.J.; Drost, E.A.; Kwong, K.K. Proactive personality and entrepreneurial intent. Int. J. Entrep. Behav. Res. 2012, 18, 559–586. [Google Scholar] [CrossRef]
  8. Nguyen, C. Demographic factors, family background, and prior self-employment on entrepreneurial intention—Vietnamese business students are different: Why? J. Glob. Entrep. Res. 2018, 8, 10. [Google Scholar] [CrossRef]
  9. Singer, S.; Šarlija, N.; Pfeifer, S.; Oberman Peterka, S. Što čini Hrvatsku (ne)Poduzetničkom Zemljom? 2022, GEM Hrvatska 2021; CEPOR—Centar za Politiku Razvoja Malih i Srednjih Poduzeća i Poduzetništva: Zagreb, Croatia, 2021. [Google Scholar]
  10. Kristiansen, S.; Indarti, N. Entrepreneurial intention among Indonesian and Norwegian students. J. Enterprising Cult. 2004, 12, 55–78. [Google Scholar] [CrossRef]
  11. Turker, D.; Sonmez Selcuk, S. Which factors affect entrepreneurial intention of university students? J. Eur. Ind. Train. 2009, 33, 142–159. [Google Scholar] [CrossRef]
  12. Moriano, J.A.; Gorgievski, M.; Laguna, M.; Stephan, U.; Zarafshani, K.A. Cross-Cultural Approach to Understanding Entrepreneurial Intention. J. Career Dev. 2011, 39, 162–185. [Google Scholar] [CrossRef] [Green Version]
  13. Solesvik, M.; Westhead, P.; Matlay, H. Cultural factors and entrepreneurial intention: The role of entrepreneurship education. Educ. Train. 2014, 56, 680–696. [Google Scholar] [CrossRef]
  14. Guzmán-Alfonso, C.; Guzmán-Cuevas, J. Entrepreneurial intention models as applied to Latin America. J. Organ. Change Manag. 2012, 25, 721–735. [Google Scholar] [CrossRef]
  15. Zovko, L.; Dulčić, Ž.; Bilić, I. Determinants of students’ entrepreneurial intention: An empirical research. Manag. J. Contemp. Manag. Issues 2020, 25, 25–44. [Google Scholar] [CrossRef]
  16. Tong, X.F.; Tong, D.Y.K.; Loy, L.C. Factors influencing entrepreneurial intetion among university students. Int. J. Soc. Sci. Humanit. Stud. 2011, 3, 487–496. [Google Scholar]
  17. Hatak, I.; Harms, R.; Fink, M. Age, job identification, and entrepreneurial intention. J. Manag. Psychol. 2015, 30, 38–53. [Google Scholar] [CrossRef] [Green Version]
  18. Mueller, S. Increasing entrepreneurial intention: Effective entrepreneurship course characteristics. Int. J. Entrep. Small Bus. 2009, 13, 55–74. [Google Scholar] [CrossRef] [Green Version]
  19. Souitaris, V.; Zerbinati, S.; Al-Laham, A. Do entrepreneurship programmes raise entrepreneurial intention of science and engineering students? The effect of learning, inspiration and resources. J. Bus. Ventur. 2007, 22, 566–591. [Google Scholar] [CrossRef]
  20. Zapkau, F.B.; Schwens, C.; Steinmetz, H.; Kabst, R. Disentangling the effect of prior entrepreneurial exposure on entrepreneurial intention. J. Bus. Res. 2015, 68, 639–653. [Google Scholar] [CrossRef]
  21. Karabulut, A.T. Personality Traits on Entrepreneurial Intention. Procedia-Soc. Behav. Sci. 2016, 229, 12–21. [Google Scholar] [CrossRef] [Green Version]
  22. Obschonka, M.; Silbereisen, R.K.; Schmitt-Rodermund, E. Entrepreneurial intention as developmental outcome. J. Vocat. Behav. 2010, 77, 63–72. [Google Scholar] [CrossRef]
  23. Zollo, L.; Laudano, M.C.; Ciappei, C.; Zampi, V. Factors affecting universities’ ability to foster students’ entrepreneurial behaviour: An empirical investigation. J. Manag. Dev. 2017, 36, 268–285. [Google Scholar] [CrossRef]
  24. Miranda, F.J.; Chamorro-Mera, A.; Rubio, S. Academic entrepreneurship in Spanish universities: An analysis of the determinants of entrepreneurial intention. Eur. Res. Manag. Bus. Econ. 2017, 23, 113–122. [Google Scholar] [CrossRef]
  25. Yukongdi, V.; Lopa, N.Z. Entrepreneurial intention: A study of individual, situational and gender differences. J. Small Bus. Enterp. Dev. 2017, 24, 333–352. [Google Scholar] [CrossRef]
  26. Shah, N.; Soomro, B.A. Investigating entrepreneurial intention among public sector university students of Pakistan. Educ. Train. 2017, 59, 841–855. [Google Scholar] [CrossRef]
  27. De Jorge-Moreno, J.; Laborda Castillo, L.; Sanz Triguero, M. The effect of business and economics education programs on students’ entrepreneurial intention. Eur. J. Train. Dev. 2012, 36, 409–425. [Google Scholar] [CrossRef]
  28. Anjum, T.; Farrukh, M.; Heidler, P.; Díaz Tautiva, J.A. Entrepreneurial Intention: Creativity, Entrepreneurship, and University Support. J. Open Innov. Technol. Mark. Complex. 2021, 7, 11. [Google Scholar] [CrossRef]
  29. Elnadi, M.; Gheith, M.H. Entrepreneurial ecosystem, entrepreneurial self-efficacy, and entrepreneurial intention in higher education: Evidence from Saudi Arabia. Int. J. Manag. Educ. 2021, 19, 100458. [Google Scholar] [CrossRef]
  30. Banu Bilgiseven, E.; Kasımoğlu, M. Analysis of Factors Leading to Entrepreneurial Intention. Procedia Comput. Sci. 2019, 158, 885–890. [Google Scholar] [CrossRef]
  31. Anwar, G.; Abdullah, N.N. Inspiring Future Entrepreneurs: The Effect of Experiential Learning on the Entrepreneurial Intention at Higher Education. Int. J. Engl. Lit. Soc. Sci. 2021, 6, 183–194. [Google Scholar] [CrossRef]
  32. Krueger, N. The impact of prior entrepreneurial exposure on perceptions of new venture feasibility and desirability. Entrep. Theory Pract. 1993, 18, 5–21. [Google Scholar] [CrossRef]
  33. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  34. Feder, E.S.; Niţu-Antonie, R.D. Connecting gender identity, entrepreneurial training, role models and intentions. Int. J. Gend. Entrep. 2017, 9, 87–108. [Google Scholar] [CrossRef]
  35. Cameron, R.; Ginsburg, H.; Westhoff, M.; Mendez, R.V. Ajzen’s Theory of Planned Behavior and Social Media Use by College Students. Am. J. Psychocological Res. 2012, 8, 1–20. [Google Scholar]
  36. Liguori, E.W.; Bendickson, J.S.; McDowell, W.C. Revisiting entrepreneurial intentions: A social cognitive career theory approach. Int. Entrep. Manag. J. 2018, 14, 67–78. [Google Scholar] [CrossRef]
  37. Gibson, L.G.; Gibson, R.A. Entrepreneurial attitudes of arts and business students. In Proceedings of the Entrepreneurship: Bridging Global Boundaries, ICSB 2010, 55th Anniversary, International Council for Small Business (ICSB), Cincinatti, OH, USA, 24–27 June 2010. [Google Scholar]
  38. Evans, D.S.; Jovanovic, B. An estimated model of entrepreneurial choice under liquidity constraints. J. Political Econ. 1989, 97, 808–827. [Google Scholar] [CrossRef]
  39. Reynolds, P.D.; Gartner, W.B.; Greene, P.G.; Cox, L.W.; Carter, N.M. The entrepreneur next door: Characteristics of individuals starting companies in America: An executive summary of the Panel Study of Entrepreneurial Dynamics. Available SSRN 2002, 1262320. [Google Scholar] [CrossRef]
  40. Hollenbeck, G.P.; Hall, D.T. Self-Confidence and Leader Performance. Organ. Dyn. 2004, 33, 254–269. [Google Scholar] [CrossRef]
  41. Ryan, J.C.; Tipu, S.A.; Zeffane, R.M. Need for achievement and entrepreneurial potential: A study of young adults in the UAE. Educ. Bus. Soc. Contemp. Middle East. Issues 2011, 4, 153–166. [Google Scholar] [CrossRef]
  42. Brockhaus, R.H. Risk taking propensity of entrepreneurs. Acad. Manag. J. 1980, 23, 509–520. [Google Scholar] [CrossRef]
  43. Bonnett, C.; Furnham, A. Who wants to be an entrepreneur? A study of adolescents interested in a young enterprise scheme. J. Econ. Psychol. 1991, 12, 465–478. [Google Scholar] [CrossRef]
  44. Robinson, P.B.; Stimpson, D.V.; Huefner, J.C.; Hunt, H.K. An Attitude Approach to the Prediction of Entrepreneurship. Entrep. Theory Pract. 1991, 15, 13–31. [Google Scholar] [CrossRef]
  45. Brockhaus, R.H.; Horwitz, P.S. The psychology of the entrepreneur. In The Art and Science of Entrepreneurship; Sexton, D.L., Smilor, R.W., Eds.; Ballinger: Cambridge, MA, USA, 1986; pp. 25–48. [Google Scholar]
  46. Holland, J. Making Vocational Choices: A Theory of Vocational Personalities and Work Environments, 2nd ed.; Pretnice Hill: Englewood Cliffs, NY, USA, 1985. [Google Scholar]
  47. Schmitt-Rodermund, E. Pathways to successful entrepreneurship: Parenting, personality, early entrepreneurial competence, and interests. J. Vocat. Behav. 2004, 65, 498–518. [Google Scholar] [CrossRef]
  48. Zampetakis, L.A.; Kafetsios, K.; Bouranta, N.; Dewett, T.; Moustakis, V.S. On the relationship between emotional intelligence and entrepreneurial attitudes and intentions. Int. J. Entrep. Behav. Res. 2009, 15, 595–618. [Google Scholar] [CrossRef]
  49. Zampetakis, L.A.; Gotsi, M.; Andriopoulos, C.; Moustakis, V. Creativity and entrepreneurial intention in young people: Empirical insights from business school students. Int. J. Entrep. Innov. 2011, 12, 189–199. [Google Scholar] [CrossRef]
  50. OECD. Supporting Youth in Entrepreneurship—Summary Report of a Policy Development Seminar Organised by the OECD and the European Commission; OECD: Brussels, Belgium, 2014. [Google Scholar]
  51. Minola, T.; Criaco, G.; Cassia, L. Are youth really different? New beliefs for old practices in entrepreneurship. Int. J. Entrep. Innov. Manag. 2014, 18, 233–259. [Google Scholar] [CrossRef]
  52. Stenholm, P.; Acs, Z.J.; Wuebker, R. Exploring country-level institutional arrangements on the rate and type of entrepreneurial activity. J. Bus. Ventur. 2013, 28, 176–193. [Google Scholar] [CrossRef]
  53. Spencer, J.W.; Gómez, C. The relationship among national institutional structures, economic factors, and domestic entrepreneurial activity: A multicountry study. J. Bus. Res. 2002, 57, 1098–1107. [Google Scholar] [CrossRef]
  54. Lüthje, C.; Franke, N. The ‘making’ of an entrepreneur: Testing a model of entrepreneurial intent among engineering students at MIT. RD Manag. 2003, 33, 135–147. [Google Scholar] [CrossRef] [Green Version]
  55. Bandura, A.; Walters, R.H. Social Learning Theory, 1st ed.; Prentice-Hall: Englewood Cliffs, NY, USA, 1977. [Google Scholar]
  56. Schindehutte, M.; Morris, M.; Brennan, C. Entrepreneurs and motherhood: Impacts on their children in South Africa and the United States. J. Small Bus. Manag. 2003, 41, 94–107. [Google Scholar] [CrossRef]
  57. Hadjimanolis, A.; Poutziouris, P. Family business background, perceptions of barriers, and entrepreneurial intentions in Cyprus. Int. J. Entrep. Ventur. 2011, 3, 168–182. [Google Scholar] [CrossRef]
  58. Drennan, J.; Kennedy, J.; Renfrow, P. Impact of childhood experiences on the development of entrepreneurial intentions. Int. J. Entrep. Innov. 2005, 6, 231–238. [Google Scholar] [CrossRef] [Green Version]
  59. Carr, J.C.; Sequeira, J.M. Prior family business exposure as integrational influence and entrepreneurial intent: A Theory of Planned Behavior approach. J. Bus. Res. 2007, 60, 1090–1098. [Google Scholar] [CrossRef]
  60. Zapkau, F.B.; Schwens, C.; Kabst, R. The Role of Prior Entrepreneurial Exposure in the Entrepreneurial Process: A Review and Future Research Implications. J. Small Bus. Manag. 2016, 55, 56–86. [Google Scholar] [CrossRef]
  61. Crant, J.M. The proactive personality scale as a predictor of entrepreneurial intentions. J. Small Bus. Manag. 1996, 34, 42–49. [Google Scholar] [CrossRef]
  62. Zhao, H.; Seibert, S.; Hills, G. The mediating role of self-efficacy in the development of entrepreneurial intentions. J. Appl. Psychol. 2005, 90, 1265–1272. [Google Scholar] [CrossRef] [Green Version]
  63. Phan, P.H.; Wong, P.K.; Wang, C.K. Antecedents to entrepreneurship among university students in Singapore: Beliefs, attitudes and background. J. Enterprising Cult. 2002, 10, 151–174. [Google Scholar] [CrossRef]
  64. Wilson, F.; Kickul, J.; Marlino, D. Gender, entrepreneurial self-efficacy, and entrepreneurial career intentions: Implications for entrepreneurship education. Entrep. Theory Pract. 2007, 31, 387–406. [Google Scholar] [CrossRef]
  65. Smith, R.M.; Sardeshmukh, S.R.; Combs, G.M. Understanding gender, creativity, and entrepreneurial intentions. Educ. Train. 2016, 58, 263–282. [Google Scholar] [CrossRef]
  66. Chaudhary, R. Demographic factors, personality and entrepreneurial inclination: A study among Indian university students. Educ. Train. 2017, 59, 171–187. [Google Scholar] [CrossRef]
  67. Daim, T.; Dabic, M.; Bayraktaroglu, E. Students’ entrepreneurial behavior: International and gender differences. J. Innov. Entrep. 2016, 5, 19. [Google Scholar] [CrossRef] [Green Version]
  68. Choo, S.; Wong, M. Entrepreneurial intention: Triggers and barriers to new venture creations in Singapore. Singap. Manag. Rev. 2006, 28, 47–64. [Google Scholar]
  69. Delmar, F.; Davidsson, P. Where do they come from? Prevalence and characteristics of nascent entrepreneurs. Entrep. Reg. Dev. 2000, 12, 1–23. [Google Scholar] [CrossRef] [Green Version]
  70. Van der Sluis, J.; van Praag, M.; Vijverberg, W.P. Education and Entrepreneurship in Industrialized Countries: A Meta-Analysis; Scholar Working Paper Series, WP 51/04, 2004; Amsterdam School of Economics Research Institute (ASE-RI): Amsterdam, The Netherlands, 2004. [Google Scholar]
  71. Quan, X. Prior experience, social network, and levels of entrepreneurial intentions. Manag. Res. Rev. 2012, 35, 945–957. [Google Scholar] [CrossRef]
  72. Galloway, L.; Brown, W. Entrepreneurship education at university: A driver in the creation of high growth firms? Educ. Train. 2002, 44, 398–405. [Google Scholar] [CrossRef]
  73. Pittaway, L.; Cope, J. Entrepreneurship education: A systematic review of the evidence. Int. Small Bus. J. 2007, 25, 479–510. [Google Scholar] [CrossRef]
  74. Franke, N.; Lüthje, C. Entrepreneurial intentions of business students—A benchmarking study. Int. J. Innov. Technol. Manag. 2004, 1, 269–288. [Google Scholar] [CrossRef] [Green Version]
  75. Cooper, A.C.; Gimeno-Gascon, F.J.; Woo, C.Y. Initial human and financial capital as predictors of new venture performance. J. Bus. Ventur. 1994, 9, 371–395. [Google Scholar] [CrossRef]
  76. Birley, S.; Westhead, P. A taxonomy of business start-up reasons and their impact on firm growth and size. J. Bus. Ventur. 1994, 9, 7–31. [Google Scholar] [CrossRef]
  77. McElwee, G.; Al-Riyami, R. Women entrepreneurs in Oman: Some barriers to success. Career Dev. Int. 2003, 8, 339–346. [Google Scholar] [CrossRef]
  78. Fairlie, R.W.; Robb, A. Families, human capital, and small business: Evidence from the characteristics of business owners survey. ILR Rev. 2007, 60, 225–245. [Google Scholar] [CrossRef] [Green Version]
  79. Adrić, I.; Stanić, M.; Bilandžić. Uloga studijskog smjera u formiranju poduzetničkih namjera i sklonosti primjene efektualne logike. Obraz. Poduzet.-E4E Znan. Stručni Časopis Obraz. Poduzet. 2018, 8, 9–26. [Google Scholar]
  80. Kvesić, L. Primjena stabla odlučivanja u kreditnom skoringu. Ekon. Vjesn. Rev. Contemp. Entrep. Bus. Econ. Issues 2013, 26, 382–390. [Google Scholar]
Sustainability 15 05151 g001 550
Figure 1. Decision tree of young adults’ entrepreneurial intentions regarding demographic factors and prior entrepreneurial exposure. Source: research.
Figure 1. Decision tree of young adults’ entrepreneurial intentions regarding demographic factors and prior entrepreneurial exposure. Source: research.
Sustainability 15 05151 g001
Table
Table 1. General characteristics of young adults.
Table 1. General characteristics of young adults.
Frequency%
Gender
M9336.2
F16463.8
Total257100
Age
18–2200.0
23–2615761.1
27–3010038.9
Total257100
Education
Secondary8834.2
Tertiary16263.1
Postgraduate72.7
Total257100
Prior Entrepreneurial Exposure
No16463.8
Yes9336.2
Total257100
Personal Entrepreneurial Activity
No20479.4
Yes5320.6
Total257100
Source: research.
Table
Table 2. Prior entrepreneurial exposure.
Table 2. Prior entrepreneurial exposure.
Frequency%
Prior Entrepreneurial Exposure
None16463.8
Negative2710.6
Neutral155.9
Positive4818.8
Missing30.9
Total257100
Source: research.
Table
Table 3. Entrepreneurial intentions.
Table 3. Entrepreneurial intentions.
NMeanStd. Dev.
Entrepreneurial Intentions (EIs)
EI1—My professional goal is to become an entrepreneur.2573.161.074
EI2—I will put maximum effort into starting my own business.2573.301.101
EI3—I have serious intentions to become an entrepreneur.2573.351.123
Source: research.
Table
Table 4. Descriptive statistics of young adults’ entrepreneurial intentions and the Mann–Whitney U test results regarding gender.
Table 4. Descriptive statistics of young adults’ entrepreneurial intentions and the Mann–Whitney U test results regarding gender.
GenderMFM-W U Test
NMeanStd. Dev.Mean RankNMeanStd. Dev.Mean Rankp (sig.)
EI1—My professional goal is to become an entrepreneur.
(Mann–Whitney U = 6518; Z = −2.018)		933.321.144140.911643.071.025122.240.044
EI2—I will put maximum effort into starting my own business.933.441.118138.481643.231.087123.630.111
EI3—I have serious intentions to become an entrepreneur.933.431.155135.121643.311.105125.530.304
Source: research.
Table
Table 5. Descriptive statistics of young adults’ entrepreneurial intentions and the Mann–Whitney U test results regarding age.
Table 5. Descriptive statistics of young adults’ entrepreneurial intentions and the Mann–Whitney U test results regarding age.
Age23–2627–30M-W U Test
NMeanStd. Dev.Mean RankNMeanStd. Dev.Mean Rankp (sig.)
EI1—My professional goal is to become an entrepreneur.
(Mann–Whitney U = 6914.5; Z = −1.680)		1573.261.045134.961003.011.105119.650.093
EI2—I will put maximum effort into starting my own business.
(Mann–Whitney U = 6704; Z = −2.042)		1573.431.069136.301003.111.127117.540.041
EI3—I have serious intentions to become an entrepreneur.
(Mann–Whitney U = 6287.5; Z = −2.778)		1573.521.090138.951003.101.133113.380.005
Source: research.
Table
Table 6. Descriptive statistics of young adults’ entrepreneurial intentions and the Kruskal–Wallis test results regarding education level.
Table 6. Descriptive statistics of young adults’ entrepreneurial intentions and the Kruskal–Wallis test results regarding education level.
EducationSecondaryTertiaryPostgraduateK-W Test
NMeanStd. Dev.Mean RankNMeanStd. Dev.Mean RankNMeanStd. Dev.Mean Rankp (sig.)
EI1—My professional goal is to become an entrepreneur.883.051.092121.781623.251.052128.6172.711.254124.440.266
EI2—I will put maximum effort into starting my own business.883.301.116134.041623.351.082131.5672.431.134133.540.121
EI3—I have serious intentions to become an entrepreneur.883.281.093103.001623.431.13074.6472.571.13481.290.130
Source: research.
Table
Table 7. Descriptive statistics of young adults’ entrepreneurial intentions and the Mann–Whitney U test results regarding prior entrepreneurial exposure.
Table 7. Descriptive statistics of young adults’ entrepreneurial intentions and the Mann–Whitney U test results regarding prior entrepreneurial exposure.
Prior Entrepreneurial ExposureNoYesM-W Test
NMeanStd. Dev.Mean RankNMeanStd. Dev.Mean Rankp (sig.)
EI1—My professional goal is to become an entrepreneur.
(Mann–Whitney U = 6484.5; Z = −2.080)		1643.061.043122.04933.341.108141.280.038
EI2—I will put maximum effort into starting my own business.1643.241.103124.92933.411.096136.200.226
EI3—I have serious intentions to become an entrepreneur.
(Mann–Whitney U = 6424.5; Z = −2.168)		1643.241.114121.67933.551.118141.920.030
Source: research.
Table
Table 8. Descriptive statistics of young adults’ entrepreneurial intentions and the Kruskal–Wallis test results regarding the perception of prior entrepreneurial exposure.
Table 8. Descriptive statistics of young adults’ entrepreneurial intentions and the Kruskal–Wallis test results regarding the perception of prior entrepreneurial exposure.
Perception of Prior Entrepreneurial ExposureNegativeNeutralPositiveK-W Test
NMeanStd. Dev.Mean RankNMeanStd. Dev.Mean RankNMeanStd. Dev.Mean Rankp (sig.)
EI1—My professional goal is to become an entrepreneur.
(χ2 = 10.712; df = 2)		272.781.05032.83153.40.82845.40483.691.11436.190.005
EI2—I will put maximum effort into starting my own business.
(χ2 = 4.900; df = 2)		273.111.05038.00153.33.90041.87483.671.13642.600.086
EI3—I have serious intentions to become an entrepreneur.
(χ2 = 6.716; df = 2)		273.151.02736.19153.47.99050.85483.811.17951.650.035
Source: research.
Table
Table 9. Differences in young adults’ entrepreneurial intentions regarding demographic factors and prior entrepreneurial exposure.
Table 9. Differences in young adults’ entrepreneurial intentions regarding demographic factors and prior entrepreneurial exposure.
FactorGenderAgeEducationPrior Entrepreneurial ExposurePerception of Prior Entrepreneurial Exposure
EI1—My professional goal is to become an entrepreneur.p = 0.044p = 0.093 p = 0.038p = 0.005
EI2—I will put maximum effort into starting my own business. p = 0.041 p = 0.086
EI3—I have serious intentions to become an entrepreneur. p = 0.005 p = 0.030p = 0.035
Source: research.
Table
Table 10. Summary of the decision tree of young adults’ entrepreneurial intentions according to demographic factors and prior entrepreneurial exposure.
Table 10. Summary of the decision tree of young adults’ entrepreneurial intentions according to demographic factors and prior entrepreneurial exposure.
SpecificationsGrowing MethodCHAID
Dependent VariableEI
Independent VariablesGender, age, prior entrepreneurial exposure, perception of prior entrepreneurial exposure, and education level
ValidationNone
Maximum Tree Depth3
Minimum Cases in Parent Node40
Minimum Cases in Child Node15
ResultsIndependent Variables IncludedPerception of prior entrepreneurial exposure and gender
Number of Nodes6
Number of Terminal Nodes4
Depth2
Source: research.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cacija, L.N.; Lovrincevic, M.; Bilic, I. The Role of Demographic Factors and Prior Entrepreneurial Exposure in Shaping the Entrepreneurial Intentions of Young Adults: The Case of Croatia. Sustainability 2023, 15, 5151. https://doi.org/10.3390/su15065151

AMA Style

Cacija LN, Lovrincevic M, Bilic I. The Role of Demographic Factors and Prior Entrepreneurial Exposure in Shaping the Entrepreneurial Intentions of Young Adults: The Case of Croatia. Sustainability. 2023; 15(6):5151. https://doi.org/10.3390/su15065151

Chicago/Turabian Style

Cacija, Ljiljana Najev, Marina Lovrincevic, and Ivana Bilic. 2023. "The Role of Demographic Factors and Prior Entrepreneurial Exposure in Shaping the Entrepreneurial Intentions of Young Adults: The Case of Croatia" Sustainability 15, no. 6: 5151. https://doi.org/10.3390/su15065151

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop