Introduction
An emerging young entrepreneur is a young individual who aspires and desires to establish a business, and also believes that this is possible. Emerging young entrepreneurs are the future of the entrepreneurial ecosystem. Young people are reported to initiate new businesses at higher rates than their seniors (GEM, 2023a). Early-stage young entrepreneurs have a greater propensity to introduce new products, a greater likelihood of exporting their products, and a slightly higher probability than their seniors of achieving higher levels of employment growth in their businesses (OECD/European Commission, 2021). Furthermore, despite having less experience, their intention to embark on a new venture increases when exposed to entrepreneurial experiences and business education (Bignotti & le Roux, 2020; Liu et al., 2021). But not everything is positive, since emerging young entrepreneurs also confront obstacles. Although they manage to establish their companies, the stability of their businesses is lower (GEM, 2023c). In European economies, new entrepreneurs tend to have much lower job creation expectations, possibly owing to the high costs of hiring staff (GEM, 2023c). Young people logically tend to have less knowledge, experience, networks and resources than senior adults when starting a business (GEM, 2023a; OECD/European Commission, 2023) and consequently require more assistance. Moreover, some authors suggest that it is possible that young people may wish to rethink the framework of entrepreneurship, and there is a probability that entrepreneurship may have emerged out of necessity (Liñán & Jaén, 2022) as a result of the impact that the COVID-19 pandemic had on young workers (World Economic Forum, 2023). It is, therefore, necessary to study entrepreneurship in emerging young entrepreneurs.
Despite the fact that emerging entrepreneurs have both positive and negative drivers for entrepreneurship, some authors have classified entrepreneurial orientation specifically in young people by means of levels, degrees and profiles based on primary data (Liu et al., 2020, 2021; Ramírez-Montoya et al., 2023; Sabahi & Parast, 2020). Secondary GEM data has, meanwhile, been used to create broad age-related profiles in some studies (Cinar et al., 2019; Erkut, 2016), whereas other scholars have examined personality traits, entrepreneurial competencies and classifications on the basis of entrepreneurial ecosystems or sustainability-focused entrepreneurs (Botha, 2024; Chakuzira et al., 2024; Halberstadt et al., 2024; Tabak et al., 2024). Bearing the above in mind, the first research question was formulated: would examining young people’s profiles be the most appropriate way in which to study entrepreneurship patterns?
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The entrepreneurial mindset has been a significant concern for researchers (Pidduck et al., 2023). Individuals are inherently diverse, and many empirical analyses on entrepreneurship have sought to capture this essence. This, therefore, led to the formulation of the second research question: which approach best fits as regards studying the profiles of young people who aspire to become entrepreneurs? Research on entrepreneurship has predominantly focused on cognitive-behavioural approaches, which are based on the seminal articles of Ajzen (1991), Covin and Slevin (1989), and Krueger and Carsrud (1993). This is also reflected in recent systematic reviews (Maheshwari et al., 2023; Wales et al., 2020; Yangailo & Qutieshat, 2022). However, the latest approach, which also integrates dispositions and beliefs with a robust business vision, is represented by Individual Entrepreneurial Orientation (IndEO) (Clark et al., 2024), a multidimensional foundational theory derived from Entrepreneurial Orientation (EO) (Covin & Slevin, 1989; Lumpkin & Dess, 1996; Miller, 1983). It is consequently important to explain EO, which is the core of IndEO.
EO is a strategic process that is developed by a company in order to achieve new developments, products, services and businesses in which managers go through an entrepreneurial process (Lumpkin & Dess, 1996). Although the EO theory is built upon an organisational perspective, seminal works such as that of Lumpkin and Dess (1996) were pioneers as regards studying EO at the individual level (IndEO). The aforementioned authors therefore proposed a model containing five dimensions: Autonomy, which is described as ‘the independent action of an individual or a team in bringing forth an idea or a vision and carrying it through to completion’ (Lumpkin & Dess, 1996, p. 127), signifying that individuals who exhibit autonomy have the ability and willingness to self-direct in pursuit of a goal; Innovativeness, which ‘reflects a firm’s tendency to engage in and support new ideas, novelty, experimentation, and creative processes that may result in new products, services or technological processes’ (Lumpkin & Dess, 1996, p. 142); Risk Taking, which refers to ‘incurring heavy debt or making large resource commitments, in the interest of obtaining high returns by seizing opportunities in the marketplace’ (Lumpkin & Dess, 1996, p. 144); Proactiveness, which consists of ‘taking initiative by anticipating and pursuing new opportunities and by participating in emerging markets’ (Lumpkin & Dess, 1996, p. 146), and Competitive Aggressiveness, which is ‘a firm’s propensity to directly and intensely challenge its competitors to achieve entry or improve position’ (Lumpkin & Dess, 1996, p. 148). Competitive Aggressiveness, therefore, reflects an attitude in an individual who adopts unconventional tactics in order to compete in an industry. In summary, IndEO is understood as ‘autonomous, proactive, innovative, competitive, and risk-taking dispositions and behaviours that individuals exhibit when pursuing value-creating opportunities’ (Clark et al., 2024, p. 356).
The IndEO comprises the theoretical foundation of this research and is also where some gaps have been identified that are related to not only the theoretical perspective but also its methodological approach.
First, previous research on IndEO has characterised entrepreneur typologies by primarily studying employees within the company (top managers, employees, leaders) (Covin et al., 2020; Mustafa et al., 2018; Rigtering et al., 2024), but the study of individuals from the general population, such as young people, has been less empirical (Clark et al., 2024). Second, although researchers have acknowledged the heterogeneity of entrepreneur (Pidduck et al., 2023; Wales et al., 2020), understanding the exceptions (other profiles beyond the most common ones) is still necessary (Clark et al., 2023). It is relevant to explore certain individual categories of young people that may differ from those with a high level of IndEO who have received a business-oriented education. Thirdly, in terms of the methodologies employed, academic research has employed methods focused on analysing relationships between IndEO dimensions, particularly Innovativeness, Risk Taking, and Proactiveness (Adeniyi et al., 2024; Y. H. Al-Mamary & Alshallaqi, 2022; Hutasuhut et al., 2024; Kumar et al., 2021; Sobaih & Elshaer, 2022). Peer-reviewed scholarly research has consequently established predictions based on these relationships by employing structural equation modelling (Manley et al., 2021) or statistical significance analyses such as regression analysis and the ANOVA test (Frunzaru & Cismaru, 2021; Kumar et al., 2021; Manley et al., 2021). Less attention has been paid to other quantitative methods that enable segmentation, such as the identification of entrepreneur profiles, and our study was consequently carried out using the Chi-square Automatic Interaction Detection (CHAID) algorithm and decision tree modelling. This statistical method is used to model intricate interactions between categorical and continuous variables and evaluate the independence of all the values in a predictor field with regard to a target variable. The main benefits of CHAID are its ease of use and readability, and its effectiveness as regards managing large databases (Botha, 2024). Despite the benefits of CHAID, this technique has rarely been applied in literature in order to classify the IndEO levels of emerging entrepreneurs. However, it is worth highlighting that some studies use these decision trees in conjunction with variables such as previous entrepreneurial experiences (Belas et al., 2019; Liu et al., 2020, 2021, entrepreneurial competencies (Botha, 2024), and student grades (Ramírez-Montoya et al., 2023). Other classification techniques have also been utilised, such as machine learning, random forest, cognitive mapping and the interactive multiple criteria decision-making method (Ferreira et al., 2017; Huang et al., 2023; Sabahi & Parast, 2020; Ye et al., 2024). However, not all researchers have conducted analyses of all the levels of IndEO as occurs in this study through the use of theoretical and methodological innovation. Finally, prominent authors in the IndEO field have encouraged the scientific community to strengthen its knowledge of this approach (Clark et al., 2024; Wales et al., 2020).
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Using the above as a basis, the objective of this research is to study the relationship between the aforementioned dimensions (Autonomy, Innovativeness, Risk Taking and Competitive Aggressiveness) and items that characterise IndEO and different entrepreneurship levels in emerging young entrepreneurs. The research specifically: (i) establishes the dimensions that best explain the level of IndEO (low, medium, high); (ii) identifies the items that best predict the level of IndEO, and (iii) examines whether sociodemographic variables and entrepreneurial experiences predispose the level of IndEO. The research additionally evaluates significant differences among segments of profiles of young entrepreneurs and gender.
The results of this research are an original contribution since they suggest that the existence of levels of IndEO can be influenced by the level of Autonomy, Innovativeness, Risk Taking, Competitive Aggressiveness and prior entrepreneurial experiences, particularly within the context of emerging entrepreneurs. This research also contributes to the field of IndEO by reflecting the idea that entrepreneur profiles can be predicted by means of the levels of the dimensions of the IndEO constructs.
The paper is structured as follows: first, an explanation of the literature review carried out is provided, after which there is a description of the methodology employed. An outline of the main results is then shown, followed by a presentation of the discussion. Finally, the main conclusions, implications and limitations are provided.
Literature review
Individual entrepreneurial orientation in young people
There is evidently an academic research interest in measuring IndEO within companies (Covin et al., 2020; Kraus et al., 2019; Lumpkin & Dess, 1996; Mustafa et al., 2018; Rigtering et al., 2024) and, to a lesser extent, outside organisations by concentrating on the population in general (Boada-Grau et al., 2016; Ferreira et al., 2017; Goktan & Gupta, 2015; Howard & Floyd, 2024; Lee et al., 2011; Santos et al., 2020). Moreover, the interest in researching young people has increased in recent years (Adeniyi et al., 2024; Hutasuhut et al., 2024; Liu et al., 2020, 2021; Ramírez-Montoya et al., 2023).
With regard to studies concerning young entrepreneurs, authors such as Lee et al. (2011) provide a foundational yet enduring contribution with their instrument, which has been applied in diverse cultural contexts. Their work remains highly relevant, since the authors reduced the five dimensions of Entrepreneurial Orientation (EO) conceived by Lumpkin and Dess (1996) to four (Autonomy, Innovativeness, Risk Taking and Competitive Aggressiveness), while excluding Proactiveness, arguing that the Proactiveness dimension overlaps with Innovativeness and Competitive Aggressiveness. Later, Boada-Grau et al. (2016) adapted the instrument conceived by Lee et al. (2011) to the Spanish language while maintaining the four constructs. This research employs the instrument proposed by Boada-Grau et al. (2016), considering the adaptation made for young individuals and to the Spanish language.
Using this approach as a basis, Adeniyi et al. (2024) identified a positive association between the dimensions of innovation and proactivity within IndEO and students’ readiness for entrepreneurship, particularly in terms of their entrepreneurial intentions. Hutasuhut et al. (2024) investigated the impact of entrepreneurship education and patriarchal culture on IndEO and the entrepreneurial intentions of university students. This research highlights that education influences IndEO, and that IndEO (as a mediating variable) further amplifies the effect of entrepreneurship education on business creation intentions. In their work, Y. H. Al-Mamary and Alshallaqi (2022) indicated a strong relationship between IndEO and entrepreneurial intention through the dimensions of Autonomy, Innovativeness, Risk Taking and Proactiveness. However, these authors did not find a relationship between IndEO and entrepreneurial intention through the Competitive Aggressiveness dimension. Liu et al. (2020) found that Need for Achievement, Need for Autonomy, Risk Taking Propensity, Internal Locus of Control and Creative Tendency predict entrepreneurial tendency, both positively and negatively. Moreover, Kumar et al. (2021) highlighted that university students with management and entrepreneurship backgrounds are significantly different as regards the dimensions of IndEO, such as Risk Taking, Innovativeness and Proactiveness, as their scores are higher when compared to those of their counterparts with science and technology backgrounds. Baldo et al. (2024) determined that students’ perceptions of barriers to entrepreneurship influence their entrepreneurial orientations in terms of Innovativeness and Risk Taking.
With regard to entrepreneur profiles, several studies focusing on young entrepreneurs have utilised decision tree methodologies. Botha (2024) reflected profiles of emerging and established entrepreneurs and found that some personality traits, such as Social Intelligence and Value Creation, are the best predictors in young emerging entrepreneurs. In the case of the profile of established entrepreneurs, other behavioural predictors have been obtained, such as Growth Mindset, Opportunity Recognition (Innovation), Flexibility, and Adaptability. Liu et al. (2020) classified students majoring in business into high, medium, and low levels of entrepreneurial inclination using various dimensions and sociodemographic and educational aspects. Liu et al. (2021) found that Perceived Behavioural Control (team cooperation, foundation ability, innovation and social skills) was the most important predictive dimension with which to found sports businesses. Sabahi and Parast (2020), meanwhile, found that Proactiveness, Social Self-Efficacy, Appearance Self-Efficacy and Comparativeness are the most important factors as regards predicting project performance. Along similar lines, some scholars have also classified profiles of entrepreneurs in contexts involving more experienced individuals by evaluating entrepreneurial competencies and entrepreneurial ecosystems, with an emphasis on sustainability (Chakuzira et al., 2024; Halberstadt et al., 2024; Tabak et al., 2024).
IndEO, sociodemographic variables, and entrepreneurial experiences
Other contextual variables that predict IndEO include age, gender, knowledge area and entrepreneurial experiences. Goktan and Gupta (2015) suggested that age influences IndEO, while Aydin et al. (2024) identified that younger individuals have significantly higher entrepreneurial intentions when compared to older individuals. Furthermore, the mediation of IndEO has been partially validated in the relationship between age and entrepreneurial intention. Miralles et al. (2017) found that entrepreneurial experience variably influences entrepreneurial intention according to age groups (young and older adults). However, Liu et al. (2021) and Bignotti and le Roux (2020) did not find that age had a significant relationship with entrepreneurial tendency or intention. With regard to gender, Mueller and Thomas (2001), Liu et al. (2021), and Goktan and Gupta (2015) demonstrated the influence of gender on IndEO. Goktan and Gupta (2015) showed that men achieve higher IndEO than women, and Kumar et al. (2021) similarly found that men have greater Proactiveness (as IndEO) and a higher propensity to become entrepreneurs than women. However, they did not find differences between men and women in the IndEO dimensions associated with Risk Taking and Innovativeness. In Indonesia, Hutasuhut et al. (2024) found that a patriarchal culture did not have a negative influence on IndEO in the case of either men or women, although the authors suggested that this could be attributed to the fact that the students were young and unmarried.
Some studies have found that a young person’s area of knowledge (reflected in the academic studies pursued) has an influence on entrepreneurship. From the perspective of IndEO, Nikitina et al. (2023) evidenced that students on science, technology, engineering and mathematics courses scored lower in the dimensions of Risk Taking and Innovation than did business students. Paray and Kumar (2020) found a positive relationship between students’ academic backgrounds (the degrees studied) and their intention to start a new business, while Sansone et al. (2021) suggested that a student with a scientific background will have greater technological knowledge than other students and that this knowledge may lead to a future business project. However, Hutasuhut et al. (2024) did not identify any significant differences between academic backgrounds and IndEO.
With regard to previous experience and its influence on entrepreneurial intention, Bignotti and le Roux (2020) found that different types of prior experience have a positive influence on young people’s entrepreneurial intention, these types of experience are specifically, the experience of having attempted to start a business, having previously worked in a company, and an education in entrepreneurship. Other authors posit that the timing of the experience matters. Merida and Rocha (2021) demonstrated that the likelihood of a young person who engages in entrepreneurship returning to paid employment decreases throughout their career. They also found that early entrepreneurs (young individuals) earn higher salaries, while late entrepreneurs (seniors) confront a salary penalty for starting a venture later, thus earning less throughout their careers. Other authors have advocated that previous experience can also be acquired through entrepreneurial education (e.g., universities), which moderates the entrepreneurial intention of young individuals (Bignotti & le Roux, 2020; Laguna-Sánchez et al., 2020; Perez et al., 2024) and even predicts a high level of enterprising tendency (Liu et al., 2021). Nevertheless, other researchers have not found that prior experience is a strong predictor for young entrepreneurs (Reissová et al., 2020).
Methodology
Data
The study sample comprised 477 students at a public university in Spain from six different areas of knowledge. The characteristics of the sample are provided in Table 1.
Table 1
Characteristics of the sample
Sociodemographic characteristics | Frequency | % (Participants N = 477) | |
|---|---|---|---|
Gender | Male | 158 | 33.1% |
Female | 319 | 66.9% | |
Age (years) | 17–18 | 23 | 4.8% |
19–20 | 136 | 28.5% | |
21–22 | 235 | 49.3% | |
23–24 | 47 | 9.8% | |
> 24 | 33 | 6.9% | |
No answer | 3 | 0.6% | |
Knowledge area | Experimental Sciences | 41 | 8.6% |
Economic and Business Sciences | 116 | 24.3% | |
Technical Sciences (engineering) | 84 | 17.6% | |
Social Sciences | 162 | 34.0% | |
Legal Sciences | 63 | 13.2% | |
Health Sciences | 11 | 2.3% | |
Have you had any entrepreneurial experience? | Yes | 116 | 24.3% |
No | 361 | 75.7% | |
Instrument
The data were collected using questionnaires developed on the basis of the IndEO scale devised by Langkamp Bolton and Lane (2012) the EO scale devised by Lee et al. (2011). The official language of communication at the university is Spanish, which functions as the principal means of communication among the students. All interactions, including the questionnaire, were consequently conducted in Spanish. The questionnaire was validated in its Spanish version by Boada-Grau et al. (2016). It consists of 12 items divided into 4 dimensions: (1) Autonomy, which ‘is related to the rejection of parental and family support, a positive attitude towards problems, self-sufficiency in facing challenges and the contribution of one’s own resources in order to set up a business venture’ (Boada-Grau et al., 2016, p. 5); (2) Innovativeness, which ‘has to do with aspects such as enjoying working with new things, having innovative ideas and making future predictions’ (Boada-Grau et al., 2016, p. 5); (3) Risk Taking, which ‘has to do with facing difficulties and an interest in creating and founding one’s own company’ (Boada-Grau et al., 2016, p. 5), and (4) Competitive Aggressiveness, which ‘is related to the conviction that one will be successful in setting up a company and persevering despite previous failures’ (Boada-Grau et al., 2016, p. 5). Each item was measured on a 1–7-point Likert scale where (1) represented ‘Strongly disagree’, (4) represented ‘Neutral’, and (7) represented ‘Strongly agree’.
According to Hernàndez and Pascual Barrera (2018), the questionnaire had a high level of overall reliability (Cronbach’s alpha (α Cronbach) = 0.85 (0.85–0.89), ω = 0.85). The four subscales were: (1) Autonomy (α = 0.6, ω = 0.61; for instance, ‘I don’t want any financial support from my parents because I am already an adult’); (2) Innovativeness (α = 0.78, ω = 0.78; for instance, ‘I enjoy working on new things, so I am usually up to date with recent trends and current fashion’); (3) Risk Taking (α = 0.72, ω = 0.75; for instance, ‘I think that founding a new venture is the only way to succeed in life’), and (4) Competitive Aggressiveness (α = 0.75, ω = 0.76; for instance, ‘Even if I launch new ventures and fail many times, I will keep on trying until I succeed’). As recommended by (Boada-Grau et al., 2016), we additionally used questions related to sociodemographic variables such as age, gender, knowledge area, and engagement in entrepreneurial experiences.
Procedure
The sample was obtained through the use of non-probabilistic sampling, also known as convenience sampling (Kerlinger & Lee, 2002), over three academic years. The anonymity of the participants as regards their questionnaire responses was maintained during the longitudinal sample collection. The researchers obtained their informed consent electronically.
In order to explore the profiles of students with a higher or lower propensity towards IndEO, the analysis was conducted using the 12 items and the 4 dimensions corresponding to IndEO. Sociodemographic variables such as age, gender, knowledge area, and past entrepreneurial experiences were also included (Table 2).
Table 2
Definitions of variables
Type | Variables | Operationalisation |
|---|---|---|
Independent | Gender | 0 = Male, 1 = Female |
Age | 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 35, 41, 46 | |
Knowledge area | 0 = Experimental Sciences, 1 = Economic and Business Sciences, 2 = Technical Sciences (engineering), 3 = Social Sciences, 4 = Legal Sciences, 5 = Health Sciences | |
Have you had any entrepreneurial experience? | 0 = No, 1 = Yes | |
Autonomy Dimension | ||
Item 1- I do not want any financial support from my parents because I am already an adult. | Items measured on a Likert scale of 1–7 points, where 1 = Strongly disagree, 4 = Neutral, and 7 = Strongly agree | |
Item 2- I am always positive about problems arising in my life, and resolve them on my own. | ||
Item 3- If I launch a new venture company, I can furnish my own funds and human resources. | ||
Innovativeness Dimension | ||
Item 4- I enjoy working on new things, so I am usually up to date with recent trends and current fashion. | ||
Item 5- I usually have progressive and innovative ideas rather than conservative ideas. | ||
Item 6- I enjoy talking about the future, and when I do so, I can persuade my friends to agree with my predictions. | ||
Risk Taking Dimension | ||
Item 7- I prefer to live a challenging life rather than a comfortable one, even though I know I may face many difficulties along the way. | ||
Item 8- I am more interested in establishing my own venture company than getting a job. | ||
Item 9- I think that founding a new venture is the only way to succeed in life. | ||
Competitive Aggressiveness Dimension | ||
Item 10- If I were to launch a startup company, I am confident that I could make it successful and earn profits. | ||
Item 11- Even if I have people flatly refuse my request, I persist even if they might think of me as a pest. | ||
Item 12- Even if I launch new ventures and fail many times, I will keep on trying until I succeed. | ||
Dependent | Level of individual entrepreneurial orientation (IndEO Level) | Level 1 or tercile 1 = low Level 2 or tercile 2 = medium Level 3 or tercile 3 = high |
Data analysis
The data were analysed using both descriptive statistics (mean, median, minimum, maximum, standard deviation) and inferential statistics (CHAID decision trees).
The CHAID method has been identified as being the most appropriate technique with which to select the most significant segmentation variables, i.e. those with the greatest explanatory power when segmenting large samples (Chung et al., 2004). This technique requires categorical or ordinal dependent variables and a set of independent variables or categorical predictors., which makes it suitable for analysing ordinal and nominal data usually obtained through questionnaires (Blanco-Blanco et al., 2017; López-Martín et al., 2018). By combining these variables, it is possible to identify distinct segments or divisions for profiling (Guevara-Otero et al., 2023; Onoja et al., 2018). Some of the key advantages of CHAID include its ability to identify the most significant predictors of the dependent variable and the intuitive interpretation of results by means of segmentation trees, along with its efficacy as regards classifying new observations (in this case, emerging young entrepreneurs) into the resulting segments (Chung et al., 2004; Legohérel & Wong, 2006). Furthermore, it allows the derivation of multivariate predictive models that outperform other techniques, such as discriminant analysis or logistic regression (Richard’s et al., 2008). Unlike multiple linear regression, CHAID specifically eliminates the requirement to meet assumptions of homoscedasticity, normality, multicollinearity, and independence, making it a valuable exploratory tool that guides the design of more refined models and subsequent parametric analysis. However, despite these benefits, CHAID has seldom been utilised in literature in order to classify the IndEO levels of emerging entrepreneurs.
With regard to data segmentation, the CHAID algorithm was chosen using the IBM© SPSS Statistics v.28 statistical software. This allowed the analysis of dependent variables of a nominal nature and achieved the main objective of the study, which was to identify the items and dimensions of the IndEO scale that contribute the most to explaining the level of IndEO of young people. The independent predictor variables indicated in Table 2 were used for this purpose, and the criterion or dependent variable was the level of IndEO. This was calculated as the sum of the 12 IndEO items, with a maximum score of 84 points. It was then transformed into a dummy variable based on two cut-off scores (three tertiles: 1, 2, and 3). Finally, the analysis included the present analysis element for each individual (minimum = 16, maximum = 83). Table 3 shows the classification of IndEO test scores.
Table 3
Classifications of IndEO level test scores
Dimension | Maximum score | Low score | Medium score | Highs core |
|---|---|---|---|---|
Autonomy | 21 | 3–10 | 11–14 | 15–21 |
Innovativeness | 21 | 3–13 | 14–17 | 18–21 |
Risk Taking | 21 | 3–7 | 8–12 | 13–21 |
Competitive Aggressiveness | 21 | 3–10 | 11–15 | 16–21 |
IndEO Level | 83 | 16–43 | 44–56 | 57–83 |
Results
Individual entrepreneurial orientation of emerging young entrepreneurs
The IndEO scale was used to measure the students’ Individual Entrepreneurial Orientation. Table 4 presents: (a) the number and percentage of respondents in each of the ‘low’, ‘medium’, and ‘high’ categories, as defined in Table 3 (Classifications of IndEO level test scores), along with the dimensions of which it is composed, and (b) the unconditional average score for each dimension and its interpretation related to the ranges in Table 3.
Table 4
Individual Entrepreneurial Orientation level scores (n = 477)
Individual entrepreneurial orientation level score | |||||
|---|---|---|---|---|---|
Entrepreneurial characteristics | Low | Medium | High | Mean | Interpretation of the mean |
Autonomy | 152 | 186 | 139 | 12.36 | Medium |
31.9% | 39.0% | 29.1% | |||
Innovativeness | 156 | 182 | 139 | 14.91 | Medium |
32.7% | 38.2% | 29.1% | |||
Risk Taking | 162 | 203 | 112 | 9.70 | Medium |
34.0% | 42.6% | 23.5% | |||
Competitive Aggressiveness | 167 | 208 | 102 | 12.18 | Medium |
35.0% | 43.6% | 21.4% | |||
IndEO Level | 154 | 188 | 135 | 49.15 | Medium |
32.3% | 39.4% | 28.3% | |||
The students surveyed attained an overall average score of 49.15 for the IndEO Level, signifying that they had a medium level of entrepreneurial orientation (Table 3). This suggests that they had strengths as regards certain entrepreneurial characteristics and might, therefore, be entrepreneurs in certain contexts or environments (Lee et al., 2011; Morales-Alonso et al., 2016).
However, it is also evident that the overall score is based on a wide range of individual scores, which allows an alternative interpretation. In fact, 28.3% of the students had a high entrepreneurial orientation, while 39.4% scored in the medium range and 32.3% scored low. It would, therefore, appear that some of the students were much more inclined towards the entrepreneurial spirit than others.
Dimensions of IndEO that best determine the level of individual entrepreneurial orientation
In order to explore the dimensions of the IndEO scale that contribute the most to explaining the level of Individual Entrepreneurial Orientation of the young people surveyed, the results of the model are shown in Fig. 1.
This model analyses the potential influence of the independent variables, which include age, gender, knowledge area, entrepreneurial experiences and individual levels of Autonomy, Innovativeness, Risk Taking and Competitive Aggressiveness, on the dependent variable (IndEO Level) based on the level of Individual Entrepreneurial Orientation level.
The summary of the results obtained from this model reveals that, of the 8 independent predictor variables considered, only 2 have been included in the model: the level of Competitive Aggressiveness and the level of Autonomy. The variables related to age, gender, knowledge area, entrepreneurial experiences and individual levels of Innovativeness and Risk Taking do not seem to significantly influence the respondents’ individual levels of entrepreneurial orientation.
Fig. 1
Dimensions of IndEO that best determine the level of individual entrepreneurial orientation. Risk estimate: 0.020. Standard error: 0.021. Overall percentage correct: 73.4%. Source: The authors
Figure 1 shows the presence of the two predictor variables included in the model, which are, in order of importance: the Competitive Aggressiveness and Autonomy levels. The best predictor of individual aspiring young entrepreneurs’ level of Entrepreneurial Orientation is associated with their level of Competitive Aggressiveness, which relates to their belief that they will succeed in setting up a business and their perseverance despite previous failures χ²=345.338 (df = 4; padj.<0.001). Furthermore, this variable is divided into three segments (nodes 1, 2, and 3), which allow the classification of three profiles: one composed of nodes 0, 1, 4, 5, and 6, one formed of nodes 0, 2, 7, and 8, and a third composed of nodes 0 and 3.
The first profile comprises the classification of the first bifurcation of the variable ‘level of Competitive Aggressiveness’. It is made up of 43.6% of the sample, who have a medium level of Competitive Aggressiveness which is associated with the belief that the participants will be successful in the creation of their business and will be persistent despite failures. Of these young aspiring entrepreneurs, 63% are more likely to have a medium level of IndEO, while 24.5% have a high level (node 1). This segment is from the second predictor variable ‘level of Autonomy’ χ²=87.582 (df = 4; padj.<0.001), and is divided into three groups according to their level (low, medium or high) of Autonomy (related to the positive attitude towards problems, self-sufficiency to confront challenges and the contribution of their own resources to start a business venture). The first group is made up of those with a medium level of Autonomy (node 4), 78.5% of whom have a medium level of IndEO. The second group corresponds to young people with a low level of Autonomy (node 5). Of these, 61.4% have a medium level of IndEO and 36.8% have a low level. The third and last group corresponds to individuals with a high level of Autonomy (node 6), of whom 58.6% have a high level of IndEO and 39.7% have a medium level. Participants with a medium level of Competitive Aggressiveness will, therefore, maintain a medium level of IndEO unless their level of Autonomy is high, thus increasing the likelihood that their IndEO will reach a high level.
The second profile is related to the second bifurcation of the variable Competitive Aggressiveness level. It consists of 35% of the sample, who have a low level of Competitive Aggressiveness. Of these aspiring young entrepreneurs, 75.4% have a higher predisposition to a low level of IndEO, while 23.4% have a medium level (node 2). A division of the students into two groups on the basis of their level of Autonomy can be observed in this segment. This segmentation is obtained from the analysis of the bifurcation from the second predictor variable, Autonomy level χ²=41.343 (df = 2; padj.<0.001) which forms two groups. The first group corresponds to individuals with a medium or high level of Autonomy (node 7). Of these, 53.7% have a low level of IndEO, while 43.9% have a medium level. The second group consists of participants with a low level of Autonomy (node 8). Of these, 96.5% have a low level of IndEO. Participants with a low level of Competitive Aggressiveness will, therefore, maintain a low level of IndEO unless their level of Autonomy is high, thus increasing the probability of their IndEO reaching a medium level.
Finally, the third profile stems from the third bifurcation of the variable Competitive Aggressiveness level. It consists of 21.4% of the sample and represents the segment of aspiring young entrepreneurs who have a high level of conviction to succeed in creating their own company and persevere despite failures. Of these individuals, 80.4% have a greater predisposition towards a high level of IndEO (node 3). Participants with a high level of Competitive Aggressiveness are, therefore, more likely to have a high level of IndEO.
A further characterisation of each final segment was also undertaken. This was done by testing the significance of the differences among the segments using the dependent and independent variables in the CHAID algorithm (i.e. IndEO and the four dimensions of IndEO). Once the non-normality of the data distribution of the variables had been verified, the median values for each segment were calculated and the H-Kruskal Wallis tests were conducted. The results are shown in Appendix Table 5.
When considering IndEO as the dependent variable, note that, of the six resulting segments, segments 5 (node 7) and 6 (node 8) obtained the lowest scores regarding Individual Entrepreneurial Orientation, while segments 2 (node 4) and 3 (node 5) obtained intermediate evaluations for almost all of the elements, and finally, segments 1 (node 3) and 4 (node 6) obtained the highest scores in the analysis, with significant differences among the six segments and a clear correspondence between IndEO and the four dimensions analysed.
Furthermore, Appendix Table 6 shows the presence of significant differences among the segments for different levels of IndEO for each gender. The results additionally indicate a correspondence among the IndEO levels for all the segments for both men and women. However, there are no significant differences between men and women within each segment.
Items of IndEO that best determine the level of individual entrepreneurial orientation
In order to show the items of the IndEO scale that influence young people’s Individual Entrepreneurial Orientation to a greater or lesser extent according to the presence or absence of these indicators in the decision tree, the most notable findings from the decision tree are presented in Fig. 2. The results of the model show that, of the 16 independent predictor variables considered (the 12 items, plus age, gender, knowledge area and entrepreneurial experiences), only 3 have been included in the model. These correspond to the following questionnaire items: Competitive Aggressiveness- Item12- ‘Even if I launch new ventures and fail many times, I will keep on trying until I succeed’; Innovativeness- Item 6- ‘I enjoy talking about the future, and when I do so, I can persuade my friends to agree with my predictions’, and Innovativeness- Item 4- ‘I enjoy working on new things, so I am usually up to date with recent trends and current fashion’. This indicates that, a priori, the age, gender, knowledge area, entrepreneurial experiences, and the remaining items do not appear to significantly influence the young participants’ levels of IndEO.
Upon observing Fig. 2 it will be noted that the best predictor of the level of the students’ IndEO is associated with the variable Competitive Aggressiveness- Item12- ‘Even if I launch new ventures and fail many times, I will keep on trying until I succeed’ χ²=263.931 (df = 8; padj.<0.001), which branches into five segments (nodes 1, 2, 3, 4, 5). These segments allow us to propose the classification of five profiles composed of the following nodes: The first profile consists of nodes 0, 1, 6, and 7; the second consists of nodes 0, 2, 8, and 9; the third consists of nodes 0 and 3; the fourth consists of nodes 0 and 4, and finally, the fifth consists of nodes 0 and 5.
Fig. 2
IndEO items that best determine the level of individual entrepreneurial orientation. Risk estimate: 0.331. Standard error: 0.022. Overall percentage correct: 66.9%. Source: The authors
The key findings for each of the profiles are shown as follows. The first profile contains the classification results obtained from the initial bifurcation of the Competitive Aggressiveness- Item 12 variable. The bifurcation is formed of 28.5% of the sample and represents the segment of students who are neutral or somewhat disagree with the idea of ‘Even if I launch new ventures and fail many times, I will keep on trying until I succeed’. It reflects that 55.1% of these individuals have a higher predisposition towards a medium level of IndEO (node 1). This medium level is maintained by 68% of them (node 7) if they additionally consider the idea of ‘I enjoy working on new things, so I am usually up to date with recent trends and current fashion’ (Innovativeness- Item 4). In contrast, for the 59% who express neutrality or consider that they do not enjoy working on new things or staying up to date with trends and fashion (Innovativeness- Item 4), their level of IndEO decreases to a low level (node 6). It is, therefore, possible that the medium level of IndEO obtained by participants with a central tendency to keep trying to start businesses (even if they fail until they succeed) will decrease to a low level if they additionally express their inclination not to enjoy working on new things or staying up to date with trends and fashion.
The second profile contains the results of the second bifurcation of the Competitive Aggressiveness- Item 12 variable. The bifurcation is formed of 26% of the sample and represents the segment of students who strongly disagree and disagree with the idea of ‘Even if I launch new ventures and fail many times, I will keep on trying until I succeed’. This indicates that 74.2% of them have a greater predisposition towards a low level of IndEO (node 2). Within this segment, upon analysing the bifurcation by means of the second predictor variable, Innovativeness- Item 6, ‘I enjoy talking about the future, and when I do so, I can persuade my friends to agree with my predictions’ χ²=42.258 (df = 2; padj.<0.001), it will be noted that the 95.8% who remained neutral or admitted to some extent to not enjoying talking about the future, and, if they do, not believing they can persuade their friends to agree with their predictions, are more likely to achieve low levels of IndEO (node 8). Similarly, the 44.2% who admitted to enjoying talking about the future and believing they can persuade their friends to agree with their predictions are more likely to achieve low levels of IndEO (node 9). However, in the same proportion, the 44.2% who acknowledged enjoying talking about the future and believing they can persuade their friends to agree with their predictions have a higher likelihood of achieving medium levels of IndEO (node 9). In this respect, it seems that the question Innovativeness- Item 6, ‘I enjoy talking about the future, and when I do so, I can persuade my friends to agree with my predictions’, does not modify the low level of individual entrepreneurial orientation for those who strongly disagree or disagree with the idea of ‘Even if I launch new ventures and fail many times, I will keep on trying until I succeed’.
Finally, an analysis of the third, fourth, and fifth profiles is provided. These profiles are formed of 20.5%, 13%, and 11.9% of the sample, respectively. They represent those young people who somewhat agree (node 3), agree (node 5), and strongly agree (node 4) with the idea of ‘Even if I launch new ventures and fail many times, I will keep on trying until I succeed’. The findings show that the greater the number of respondents who agree with the idea of persisting until they succeed, even if they start new ventures and fail multiple times, the higher the likelihood that their IndEO level will be high. The 82.5% of the sample who strongly agree with this idea have a higher predisposition to a have a high level of IndEO (node 4). Similarly, the 58.1% of the sample who agree with this idea have a higher predisposition to have a high level of IndEO (node 5). However, the 58.2% of the sample who somewhat agree with this idea have a higher predisposition to have a medium level of IndEO (node 3).
Furthermore, in order to characterise each final segment, we analysed the significance of the differences between the segments regarding the dependent and independent variables of the CHAID algorithm (i.e. IndEO and the 12 items of the four dimensions of IndEO). Once the non-normality of the data distribution of the variables had been confirmed, the median values for each segment were calculated, and the H-Kruskal Wallis tests were performed. The results obtained are shown in Appendix Table 7.
With regard to the dependent variable IndEO, namely individual entrepreneurial orientation, note that, of the seven resulting segments, segments 4 (node 4) and 6 (node 5) attained the lowest scores, while segments 1 (node 3) and 5 (node 7) attained intermediate evaluations for all the items. Segment 7 (node 9) corresponds to low to medium scores, and finally, segments 2 (node 4) and 3 (node 5) attained the highest scores in the analysis. This allows us to state that there are significant differences among the segments, with a general correspondence between the levels of IndEO and the items associated with the dimensions of IndEO.
In order to complete the characterisation of the segments, the gender of the aspiring young entrepreneurs was analysed. We specifically evaluated whether there were significant differences among the seven resulting segments obtained after carrying out the CHAID analysis for IndEO for both males and females. We additionally examined whether there were significant gender differences for each of the seven segments. The results shown in Appendix Table 8 indicate that there are significant differences among the segments, thus making it possible to highlight that there is a correspondence between the levels of IndEO by segments for both males and females. Segments 2 (node 4) and 3 (node 5) therefore reflect the highest levels of IndEO, while segments 4 (node 4) and 6 (node 5) have the lowest levels of IndEO. However, segment 3 (node 5), the second most valued and formed of those competitive young individuals who perceive themselves to be persistent in the face of failure in creating their business, significantly showed that males have higher levels of IndEO than females.
Sociodemographic variables and entrepreneurial experiences that best determine the level of individual entrepreneurial orientation
The last objective of this study was to determine whether sociodemographic variables and entrepreneurial experiences predispose the level of IndEO.
The results of this model show that, of the 4 predictor independent variables (age, gender, knowledge area and entrepreneurial experience), only one variable, which is entrepreneurial experience, has been included in the model. The remaining variables, similar to that which has occurred in previous analyses, do not appear to significantly influence the respondents’ individual level of IndEO.
Figure 3 illustrates the most significant finding of this model. The results show that 27.9% of the respondents engaged in entrepreneurial experiences or activities (node 2). Of these, 53.3% were more inclined towards a high level of IndEO, while 46.7% were inclined towards a medium level. Moreover, 72.1% of the students had no entrepreneurial experiences (node 1). Of these, the majority (62.7%) had a medium level of IndEO, while 37.3% had a high level. Participation in entrepreneurial activities therefore increases the propensity to have a high level of IndEO or maintain a medium level of IndEO.
Fig. 3
Entrepreneurial experiences that best determine the level of individual entrepreneurial orientation. Risk estimate: 0.399. Standard error: 0.027. Overall percentage correct: 60.1%. Source: The authors
The two resulting segments were characterised in more detail by evaluating the significance of the differences among the segments using the dependent and independent variables in the CHAID algorithm (i.e. IndEO and participation in previous entrepreneurial experiences), along with the four dimensions of IndEO. Upon verifying the normality of the data distributions of the variables, the mean values for each segment were calculated, and t-tests were performed for the variables that had a normal distribution. The median values for each segment were also calculated, and the Mann–Whitney U test was applied to those variables with a non-normal distribution. The results are presented in Appendix Table 9.
When considering IndEO as the dependent variable, it will be observed that segment 2 (node 2), which represents individuals with previous entrepreneurial experience, had the highest level of IndEO. Furthermore, this segment attained higher scores in all the dimensions of IndEO analysed. However, these detected differences were statistically significant in the dimensions of Innovativeness and Risk Taking. It is consequently evident that young people of any gender who engage in entrepreneurial experiences take more risks and are more innovative, leading to a higher level of IndEO.
Finally, Appendix Table 9 demonstrates significant differences between the IndEO levels in the segment of young people without entrepreneurial experience (segment 1) and that of young people with entrepreneurial experience (segment 2) for both males and females. The findings suggest that both men and women with entrepreneurial experience have higher levels of IndEO than their equivalents without entrepreneurial experience. In addition, it is evident that men attain higher levels of IndEO than women when both genders have entrepreneurial experience.
Discussion
The findings shown herein provide new insights into Individual Entrepreneurial Orientation (IndEO) and individuals’ attitudes and beliefs as regards entrepreneurship. By analysing IndEO levels, this study has identified the key items and dimensions that best explain variations in IndEO among young aspiring entrepreneurs.
In practice, entrepreneurship varies significantly, and young people’s interest in starting a business does not always come to fruition (OECD/European Commission, 2023). This research, which was carried out by segmenting profiles, contributes to avoiding a uniform approach to young people’s entrepreneurship by providing a classification of entrepreneurial orientation based on factors that predominantly shape this orientation.
The first two models analysed through the use of CHAID resulted in one that predicted the levels of IndEO by means of dimensions and another that predicted the levels of IndEO by means of individual items. The results suggest that both models, which operate at different levels (classification through the use of dimensions versus items), provide greater predictive accuracy for IndEO levels (low, medium, high) in emerging young entrepreneurs. The study additionally highlights the impact of prior entrepreneurial experience, age, gender and academic background on IndEO levels.
A key finding was that item 12 in the Competitive Aggressiveness dimension (Table 2), which concerned persistence despite business failure, emerged as a robust predictor of IndEO. This aligns with that stated in previous studies, which underscore the importance of perseverance as regards fostering entrepreneurial orientation (Kumar et al., 2021; Santos et al., 2020). It is very important to state that, within Competitive Aggressiveness, the aspect that influences IndEO is perseverance, while competitiveness does so to a lesser extent, because in an economic context such as the current one, the labour market is increasingly seeking human capital that knows how to work in a team in a cooperative and non-competitive manner. Perseverance can and should be encouraged from a very early age, as should autonomy. It is, therefore, necessary to insist on the importance of reviewing educational models from the beginning of formal education. Collaboration between the different educational stages is essential, and although this may seem obvious, it is not a reality. When you get to university, you can work, but the impact is much more limited. The relevant literature also highlights the positive relationship between resilience and IndEO (Sulphey & Klepek, 2024), along with the role played by perseverance as a moderator between attitude and intention in techno-entrepreneurship (Maziriri et al., 2024).
Items 4 and 6 (Table 2) in the Innovation dimension, which are associated with the enjoyment of working on new ideas and discussing future situations, were also significant predictors. In this respect, the academic and technological environment in which young university students currently develop facilitates and stimulates innovation, preparing them to confront complex challenges with an innovative perspective. These findings are in turn consistent with research linking innovation with entrepreneurial readiness (Adeniyi et al., 2024) and entrepreneurial intention (Y. H. Al-Mamary & Alshallaqi, 2022).
The relevance of these items may stem from the clarity with which they resonate with the young participants’ current stage of life. For instance, item 12 reflects experiences tied to past entrepreneurial attempts, while items 4 and 6 capture behaviour and attitudes that are easily recognisable for the participants, such as discussing new ideas. This supports the idea that young people with a forward-looking perspective may be more inclined towards entrepreneurship (Vankov et al., 2022).
Of the IndEO dimensions (Autonomy, Innovation, Risk Taking and Competitive Aggressiveness) the strongest predictors in our model were Competitive Aggressiveness and Autonomy. This could be largely owing to the conditions of the academic, social and economic environment in which young emerging entrepreneurs operate, along with the demands of an increasingly competitive and globalised labour market. They in turn echo other research suggesting the direct and positive effect of Competitive Aggressiveness on entrepreneurial intention (Y. H. S. Al-Mamary et al., 2020) and finding that autonomy is a key factor in students’ entrepreneurial orientation, with a strong relationship with entrepreneurial intention (Y. H. Al-Mamary & Alshallaqi, 2022; Y. H. S. Al-Mamary et al., 2020). However, in our study, unlike that which was found by Y. H. Al-Mamary and Alshallaqi (2022) and Y. H. S. Al-Mamary et al. (2020), the Risk Taking dimension did not have strong predictive power, which might reflect young people’s limited experience in navigating personal or entrepreneurial risks. To enhance the measurement of Risk Taking, future research could incorporate qualitative approaches, thus encouraging young people to reflect on past risky situations and how they envision acting in similar circumstances in the future.
Previous research has highlighted the critical role played by Innovativeness, Autonomy and Competitive Aggressiveness in determining Entrepreneurial Orientation (Y. H. Al-Mamary & Alshallaqi, 2022; Liu et al., 2021). One of the major contributions of our study that of exploring the classification by levels of IndEO, which are high, medium, and low, in greater depth. In this respect, our research suggests that the propensity for a high level of IndEO increases with higher levels of Competitive Aggressiveness and also with participation in previous entrepreneurial experiences. Even with medium levels of Competitive Aggressiveness, a high level of IndEO is more likely if the degree of Autonomy is high. Conversely, medium levels of IndEO are associated with the absence of previous entrepreneurial experiences, medium levels of Competitive Aggressiveness, medium-high levels of Innovativeness, and medium-low levels of Autonomy. However, low levels of IndEO correspond to low levels of Competitive Aggressiveness, Autonomy and Innovativeness.
Interestingly, prior entrepreneurial experience, which some studies have not identified as a strong predictor for young entrepreneurs (Reissová et al., 2020), emerged as influential in our findings. This study aligns with institutional findings (GEM, 2023a), demonstrating that entrepreneurial experience fosters sustained entrepreneurship. Similarly, other researchers have found that entrepreneurial education promotes skills, positive attitudes towards entrepreneurship, and competencies for the labour market (Bignotti & le Roux, 2020; Laguna-Sánchez et al., 2020; Liñán & Jaén, 2022).Our results provoke further discussion, not only highlighting the influence of entrepreneurial experience on IndEO levels, but also demonstrating that these levels increase among young people who engage in entrepreneurial activities and simultaneously take more risks and display greater innovation. This highlights the importance of entrepreneurial education and promoting experiences among young individuals within the entrepreneurial ecosystem.
The results indicate that, a priori, age, gender and academic field are not key predictors of IndEO in the young aspiring entrepreneurs sampled. However, gender does impact on the IndEO levels of those emerging entrepreneurs with entrepreneurial experiences and high levels of perseverance in the face of competition. Although there is no clear scientific consensus as to whether these variables reliably predict IndEO or its levels, some researchers have identified the influence of age (Goktan & Gupta, 2015) and academic field (Nikitina et al., 2023) on IndEO. Our findings confirm the influence of gender on IndEO, in line with those of Goktan and Gupta (2015) and Liu et al. (2021). In this respect, our results confirm that men achieve higher levels of IndEO than women when both genders have entrepreneurial experience and are perceived as being competitive and persistent in the face of entrepreneurial failure, which invites further reflection on gender differences. Several studies have focused on gender disparities in IndEO and entrepreneurial intention. For instance, Goktan and Gupta (2015) found that men tend to achieve higher IndEO than women, while Kumar et al. (2021) noted that male students demonstrate greater perseverance towards entrepreneurial intention and a higher propensity to become entrepreneurs.
These findings suggest the need for further investigation into gender differences by categorising them into distinct profiles in order to better understand entrepreneurial behaviour. The importance of segmentation in addressing gender disparities is underscored, particularly as female entrepreneurship remains significantly lower, especially among young women (GEM, 2023b). This research expands on the existing knowledge concerning entrepreneurship and provides valuable insights for future studies.
Conclusions, implications, and limitations
This study provides valuable insights into the theoretical aspects of Individual Entrepreneurial Orientation (IndEO). It has been observed that the disposition and behaviour of entrepreneurs can, as reflected through their IndEO, be categorised into distinct profiles. The findings demonstrate that these profiles can be predicted by the levels of IndEO dimensions, as defined by theoretical constructs. Notably, the study suggests that the levels of IndEO may be influenced by factors such as Competitive Aggressiveness, Autonomy, Innovativeness, and prior entrepreneurial experiences, particularly within the context of emerging young entrepreneurs. This implies that, although individual entrepreneurs exhibit behaviours such as Autonomy, Innovativeness, Competitive Aggressiveness, and Risk Taking, the degree to which these behaviours are manifested is significant.
In particular, the dimensions of Autonomy, Competitive Aggressiveness, and Innovativeness emerge as being particularly pertinent as regards predicting IndEO in young emerging entrepreneurs. The methodology employed facilitated the analysis of IndEO at various levels, simultaneously identifying the specific items and dimensions that best explain the degree of IndEO in young individuals. It was specifically found that Competitive Aggressiveness and Autonomy are significant predictive dimensions, especially when the first is exhibited at a medium level. In this respect, the model that yields the highest overall prediction accuracy is that which analyses IndEO dimensions at different levels: low, medium, and high. Moreover, previous entrepreneurial experience acts as a driver as regards achieving higher levels of IndEO.
However, this research is not without limitations. While the study has examined IndEO in relation to other factors, such as motivations for new ventures and young individuals’ perceptions of their future (Boada-Grau et al., 2016), the authors recommend considering additional variables, particularly with regard to changes in the reasons for starting a business. For example, it may be relevant to explore whether new ventures are initiated primarily out of necessity rather than professional or personal aspirations (Liñán & Jaén, 2022). Recent global crises may also have influenced entrepreneurial intentions (Liñán & Jaén, 2022; World Economic Forum, 2023). Comparing IndEO with other models of entrepreneurial intention and exploring new expectations, motivations and reasons for starting new ventures among young individuals would provide further insights.
Moreover, although a validated Spanish-language survey was employed, the responses may still have been subject to cultural bias. The interpretation of the questions could have varied depending on the context in which the data was collected, potentially limiting the generalisability of the findings. The authors therefore propose to extend the sample to include other cultural contexts and languages. It would also be beneficial to investigate public universities, business schools and institutions with a broader range of profiles, and to incorporate diverse languages and socio-economic statuses in order to enhance the generalisability of the research models. These avenues of research are promising and would contribute to understanding whether the entrepreneurial patterns among young aspiring entrepreneurs remain consistent or are undergoing change.
In conclusion, the findings of this research are critical not only for the business schools and universities that are aiming to enhance IndEO, but also in order to foster an entrepreneurial spirit among young aspiring entrepreneurs. It is essential to promote entrepreneurship and equip young people with specific entrepreneurial knowledge by means of programmes created for this purpose within the education system, extending beyond universities to earlier stages of education. It is also crucial to establish mechanisms with which to compensate for young entrepreneurs’ lack of experience, such as mentoring programmes or dedicated entrepreneurial support departments within organisations so as to assist during the early stages of their ventures.
Furthermore, continuous training mechanisms should be established in order to support entrepreneurs as regards expanding their networks, with civil initiatives such as entrepreneurial or sector-specific associations (Sepúlveda-Molina et al., 2022). An in-depth understanding of different entrepreneurial profiles is essential when designing these initiatives. For instance, if prior entrepreneurial experience is a decisive factor for IndEO, programme designs should address not only business knowledge but also strategies with which to foster innovation, thus overcoming the initial fear of Risk Taking, and developing Competitive Aggressiveness.
Finally, the identification of the dimensions in which to intervene in order to strengthen IndEO could have highly relevant practical implications. In the educational sphere, this identification would make it possible to promote IndEO within the educational system from early stages, thus facilitating the development of entrepreneurial skills in a progressive manner. In the business sphere, this knowledge could guide strategic actions with which to encourage intra-entrepreneurship, thus strengthening the innovative and competitive capacity within organisations.
Declarations
Competing interests
Authors declare not competing interests.
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