Youth’s Entrepreneurial Intention: A Multinomial Logistic Regression Analysis of the Factors Influencing Greek HEI Students in Time of Crisis

Abstract

Governments’ coronavirus disease (COVID-19) measures have forced the community to stay at home. During this period, youths have had time to think about their career paths. For some, a conventional eight-hour job in a private company is undesirable; meanwhile, entrepreneurship can mitigate the adverse effects of the crisis, such as unemployment. Accordingly, this study investigates the intention of Greek youths that study in a higher education institution (HEI) to engage in entrepreneurship in times of crisis, and highlights the factors that drive them to enter the business arena. This study designed and distributed a questionnaire to 369 Greek youths who were studying at the University of Thessaly. The data from the empirical research were used to develop a multinomial logistic regression model to investigate youths’ entrepreneurial intention and reveal the driving factors. The results showed that during times of crisis, youths appeared hesitant to enter the business arena. However, those who were more confident indicated that entrepreneurship could provide them with greater satisfaction. Driving factors for engaging in entrepreneurship were family and friends. Inhibiting factors for establishing a new business were having previous work experience in a family business and lack of educational knowledge. This study contributes to the understanding of youths’ entrepreneurial intention and the driving factors that play a key role in shaping this intention in Greece during a crisis period, since there are few studies on this topic.

1. Introduction

The consequences of the pandemic of coronavirus disease are expected to be long term, despite the fact that two years have passed since its outbreak, especially in the labor market which has suffered a significant blow. Since the spring of 2020 when the coronavirus disease (COVID-19) first appeared in most of the countries worldwide, unemployment rates began to rise rapidly. Along with the lockdown in schools and businesses, a “lockdown” has affected the dreams of millions of young people who realized that searching and finding a job in times of a pandemic crisis is a feat. Years of efforts by states to develop the labor market have been dismantled in just a few months, leading to a tsunami of rejected job applications from new graduates looking for a chance to jump-start their careers. The ongoing lockdowns have disproportionately affected young people both economically and socially, prompting many to make decisions that are likely to be painful later in life.

Based on the above, the motivation of this research is to present entrepreneurship, as a measure to mitigate and overcome the difficulties of a crisis in the labor market for youths [1]. Regarding the target group of youths that focus on entrepreneurship, university students are often those who can be characterized as potential entrepreneurs, but the investigation of their entrepreneurial intention is the main variable that can predict the behavior of university students towards entrepreneurship. Entrepreneurial intention is defined as the conscious state of mind that precedes action and directs attention toward entrepreneurial behaviors such as starting a new business. It is the first step in the business creation process and is the most frequently studied factor of business creation. This kind of approach is based on an established model in the literature that links intention with subsequent actions and has been suggested several times as the best predictor of entrepreneurial behavior. According to the theory of planned behavior, planned behaviors (such as starting a business) are intentional and thus can be predicted by the intention towards that behavior (Ajzen, 1991). Therefore, intentions will determine the motivational factors that influence the behavior; they are indications of how hard people are willing to try and how much effort they will put into performing the behavior in question. Ajzen (1991) suggests that a person’s "attitude towards behavior", "subjective norms", and "perceived behavioral control" are the factors that determine his intentions.

According to the latest related literature, the factors that influenced entrepreneurial intention of university students are separated into two categories: the individual factors (micro level) and environmental factors (macro level). The micro-level factors mainly include individual and psychological characteristics, entrepreneurial knowledge and the abilities of youths, while the macro-level factors mainly include economic level, policy environment and entrepreneurial education. However, scholars focus mostly on the investigation of the internal, rather than the external factors. Thus, this paper chooses to attend to the examination of both internal and external factors that are not often reported from scholars. As some of the internal factors, age and gender will be examined, while from the macro environment, factors such as the personal social network such as friends, family background (previous work experience of parents and family business) and previous work experience of youths will be considered in this analysis. Based on the three theories of planned behavior (TPB), emotional theory and entrepreneurial cognitive theory, as well as the perception of specific situations encountered by university students, this paper attempts to explore entrepreneurial intention from three perspectives, including individual background (age, gender, previous work experience and educational level), family background (parents’ work experience and family business), and social network (friends).

Thus, the scope of this research is twofold: (i) to investigate the intention of Greek youths that study in a higher education institution towards entrepreneurship in times of the pandemic crisis, and (ii) to highlight the external factors, except from unemployment, that drive them to enter the business arena. To approach the research, an empirical study was conducted on undergraduate students at the University of Thessaly in Greece.

The remainder of this paper is organized as follows. Section 2 provides the literature review and background of youth entrepreneurship, how youth entrepreneurship has evolved in Greece, and the factors that promote entrepreneurship for Greek youth. Section 3 discusses the survey data as well as the key variables and multinomial models. Section 4 reveals the main factors that drive youth toward entrepreneurship in a crisis. Section 5 presents the conclusions, proposals for future research, and implications for the promotion of entrepreneurship among Greek youths.

2. Literature Review

2.1. Unemployment: The Most Important Challenge Faced by Youth in the Labor Market in Times of Crisis

The COVID-19 outbreak changed daily life and disrupted existing social constants. Two years on, youths appear to be the most vulnerable group in the global community [2]. Youths are vulnerable not only to the virus itself but also to the socioeconomic dimensions of the pandemic [3]. University closures, the online transfer of traditional educational processes, loss of contact with friends and peers, unemployment and the feeling of insecurity for vocational rehabilitation, prolonged stay at home measures, and the existence of a general state of crisis has resulted in youth anxiety, depression, and loneliness, as well as insecurity about the future [4]. Among these aspects, career anxiety has important implications for youths. More than one in six youths have lost their jobs since the onset of the pandemic, while those who remain employed have seen their working hours decline by more than 20%, which has driven them to think more about their working future [5].

Since the 19th century, young people have been considered pioneers of progress, culture, justice, and democracy [6]. However, youth unemployment is a growing problem that has significant long-term consequences for individuals, communities, economies, and societies [7]. Over the past decade, youth transition from school to work has become longer, more complex, and more turbulent. Youth unemployment has increased in all EU countries since 2008, with the proportion of job seekers aged under 25 ranging from 7% in Austria, 8% in the Netherlands, and almost 50% in Spain [2,8].

In Greece, the prior economic crisis has turned this already difficult situation into a nightmare for young people [9]. The employment rate of people aged under 25 has decreased more than that of any other age group, which has reduced their contribution to total employment to just 4%. Simultaneously, their unemployment rate has increased to unprecedented levels, reaching 60% at the height of the crisis. As a result, many young people have been driven to inaction. It is noteworthy that the percentage of those aged 20–34 who were not engaged in employment, education, or training increased from 20% in 2007 to 27% in 2018 (reaching 37% during the crisis).The COVID-19 pandemic has exacerbated this problem. Youths are now disproportionately affected by the economic impact of COVID-19 due to their increased participation in the sectors that have been most affected by the pandemic, such as the service industry (e.g., retail sales, catering, customer service, etc.) and other informal forms of employment that are often insufficiently covered by the welfare state, while it has become more difficult to integrate various employment protection and subsidy arrangements [10].

To better understand the issue of youth unemployment among the 13 regional units of Greece, it is necessary to calculate the location quotient for youth unemployment per regional unit. This will make it possible to compare each region with the whole of Greece and measure the convergence or deviation of youth unemployment in each region from the national average, as well as the geographical similarity or differentiation between regions [11]. When the index has a value of 1, regional youth unemployment is equal to national youth unemployment. When the index is less than 1, youth unemployment falls short of national youth unemployment. When it is higher than 1, the opposite applies [12,13]. Figure 1, Figure 2, Figure 3, Figure 4 and Figure 5 present the spatial distribution of youth unemployment for each of the 13 regional units of Greece from 2009–2020. The identified geomorphological features were digitally drawn by using geographical information system (GIS) software. The more intense the color in a regional unit, the greater the concentration of the unemployed in it. It is noteworthy that from 2009–2020, most unemployed youths are concentrated in the center of Greece. Central Greece and Thessaly present the highest rates of youth unemployment, despite both having a strong agricultural sector that employs youths. However, youths are not willing to be employed in this sector because they prefer the tertiary sector. Epirus also shows high youth unemployment [9,10]. This is because the unemployed youths either stopped working because their job contacts were of limited duration and had ended, or because they were fired. In addition, most of the youths work seasonal jobs such as for hotels or catering companies, which are temporary [14].

Difficult access to the labor market has deprived Greece of its economy, as youths comprise of one of the most dynamic sections of the population. This, in turn, reduces the productive dynamics of the Greek economy, undermines its ability to produce high-quality products and services, and affects the prospects for the realization of the necessary transformation of its productive model. Therefore, to mitigate the effects of the crisis, youths commonly turn toward entrepreneurship. Entrepreneurship is a rewarding journey that helps youths to gain confidence to tackle real-world problems and follow their dreams.

2.2. Entrepreneurship as a Youth Response to the Effects of a Crisis

During the COVID-19 pandemic, global attention has focused on taking measures for economic recovery [15]. Entrepreneurship, as a driving force for growth, is a multidimensional phenomenon that enhances employment growth, innovation creation, dissemination of new technologies, and competition intensification. Starting a new business helps an individual to acquire new knowledge and skills and reduce unemployment, since its creation is characterized by the establishment of new job positions [15,16].

Youths follow the same approach because they recognize entrepreneurship as a key way to deal with the effects of the crisis. As youths have been recognized as the most vulnerable group in terms of unemployment, they should turn to other employment solutions—the most important being youth entrepreneurship [1]. Doing so will help to reduce youth unemployment and increase economic growth. Youth entrepreneurship refers to the development of business activities among people aged 15–24 [9,17]. This age bracket refers to a human being’s most creative period; therefore, it should be combined with high levels of willingness and the work ethic to achieve goals and ensure a safe work future. There are two types of youth entrepreneurship: (1) opportunity and (2) necessity [18]. The first refers to entrepreneurship that is motivated by the exploitation of a business opportunity that an individual identifies and evaluates in the context of their financial environment, then considers in terms of increasing their income or offering job independence [19,20,21,22]. The second type is when a young person is forced to start a business due to lack of job availability, dissatisfaction with existing employment, and fear of possible dismissal. It has the sole purpose of maintaining income, which is “threatened” by shrinkage. While these two types of youth entrepreneurship are polarizing, an individual’s entrepreneurial motivation can move between these two types [18].

The distribution of necessity and opportunity entrepreneurship is closely linked to a country’s per capita income level. The higher the income, the greater the percentage of young entrepreneurs who will be motivated by the desire to seize an opportunity rather than have a need for a livelihood [21]. However, compared to other countries, the continuing recession in Greece has led many young Greeks to enter the business arena out of necessity rather than to take advantage of real business opportunities. Therefore, it is necessary to investigate the driving and inhibiting factors that lead Greek youths to engage in entrepreneurship to better understand how a crisis can affect necessity entrepreneurship.

Youth entrepreneurship, like all other types of entrepreneurships, is influenced by several factors. The most critical factors include the socioeconomic environment in which young people try to integrate into and its influence on their personality and social background. Other factors include youths’ decision-making processes, special skills and knowledge related to the business arena, capital, disposable income, and innovation [23]. Thus, it can be understood that entrepreneurship is a complicated process, and youths should be prepared to face possible difficulties during this journey. The most common problem is related to sourcing funds. Certainly, it is important for entrepreneurs to be able to cope financially with future problems. A deterrent factor for young people’s business activities is the inefficiency of the state, whose bureaucracy and high tax provide constant obstacles for young people who want to engage in entrepreneurship [17]. Another problem faced by young entrepreneurs is their lack of experience, yet it makes sense that a young person will not have much work experience. Considering the above, it should be clarified that young people who choose to engage in entrepreneurship should be prepared to (1) face the difficulties that will arise, and (2) show the necessary maturity to protect their investment.

2.3. Driving Factors of Youth’s Entrepreneurial Intention

Entrepreneurial intention refers to an individual’s decision-making process before performing an action that drives them to enter the business arena by establishing a new business and becoming an entrepreneur. Entrepreneurial intention is related to several sociodemographic factors such as age, sex, educational background, previous work experience, level of education, and university (Figure 6) [24,25]. Among the demographic factors, age and sex have the greatest influence on shaping entrepreneurial intention. Based on the literature, males appear to be more positive when embarking on an entrepreneurial career than females [26]. Meanwhile, other studies argue that there is no difference between males and females in terms of entrepreneurial intention [27,28]. Accordingly, the impact of sex on entrepreneurial intention remains unclear, and further research is required [24,26,29]; therefore, we posit the first hypothesis as follows:

H1. 

Male youths demonstrate higher entrepreneurial intention than female youths.

Regarding the role of age in entrepreneurial intention, research has shown that the older an individual is, the less willing they will be to develop business activities [30]. Therefore, younger people tend to be more active in establishing new businesses than older people; thus, age is a decisive factor in entrepreneurial intention. However, other studies show that age does not have a significant effect on entrepreneurial involvement [31]. Therefore, further investigations are required, and we propose the second hypothesis accordingly:

H2. 

People aged over 25 are more likely to be involved in entrepreneurship.

Education level contributes to individuals’ motivation to engage in entrepreneurship. Studying at university seems to be more positively related to the choice of becoming an entrepreneur. However, the relationship between university education and entrepreneurship remains contested [29,32]. For instance, some scholars have stated that students, especially those who study at a business school, feel encouraged to enter the business arena [31]. Meanwhile, other studies have stated that the impact of education level remains unclear [9,33]. Therefore, we propose the following hypothesis:

H3. 

Education level contributes to youths’ entrepreneurial intentions.

Youths’ work experience in the business field enables them to recognize the risks and opportunities associated with establishing a new business [27]. Therefore, work experience can positively affect youths’ entrepreneurial intentions. In general, the more knowledge young people gain from their work experience and roles held in a previous company, the more positive they feel about becoming an entrepreneur [28,34]. Therefore, we propose the fourth hypothesis as follows:

H4. 

Students with prior business work experience will display a higher level of entrepreneurial intention than students without prior business work experience.

While entertainment and sports personalities, artists, and national or international leaders are role models for youths [35], family members and friends are also influential [36]. A role model acts as an example and maintains open communication; these factors help to drive youths into making good choices while maintaining open communication. Parents can support their children when dealing with different issues, such as the pressure they may receive from their peers and other negative influences [27,35,36]. Therefore, regarding entrepreneurial intention, if a child has been raised in a family that has an entrepreneurial background, it can affect their intention of also becoming an entrepreneur. In general, since the children of entrepreneurs have knowledge and skills related to business operation, following the same career path is a natural choice [35]. Accordingly, a parental role model is the most important factor for entrepreneurial intention. Moreover, work experience in a family business can play an important role in enhancing youth entry to the business arena, and Chaudhary (2017) states that having a family background in entrepreneurship can act as a positive factor for shaping youths’ entrepreneurial intentions. Accordingly, we propose the following hypotheses:

H5. 

Youths with entrepreneur parents have a higher level of entrepreneurial intention than youths with non-entrepreneur parents.

H6. 

Youths who have work experience in a family business have a higher level of entrepreneurial intention than youths who have no work experience.

H7. 

Friends act as decisive role models and can affect youths’ entrepreneurial intention.

3. Materials and Methods

Data and Method

To investigate the driving factors of Greek youths towards entrepreneurship in the context of the COVID-19, we created and administered a questionnaire to 369 undergraduate and postgraduate students at the Department of Business Administration at the University of Thessaly. Participants aged over 18 years old and were recruited for answering the questionnaires through the mailing list of the University of Thessaly, as the survey was conducted online, via the application of Google Forms, between May–June 2020. Of the 369 participants, who completed the online study, all have replied to the ‘check-in’ email, which has been sent 24 hours following completion and were thus have included in the current research. In addition, for further support the participants, we sent emails, which offered further support if needed, providing the opportunity for a telephone call with the research team, so that they could discuss any aspects of the questionnaire that they found troublesome. The email also included an expression of appreciation for their participation and did not request a response from the recipient if help was not needed. The survey included a three-point Likert scale and demographic questions and could be completed in approximately 10 min. To identify the factors that drive Greek youths to engage in entrepreneurship as a way of dealing with the adverse effects of the COVID-19 pandemic, we performed a multinomial logistic regression analysis using the responses to predict the probabilities of different possible outcomes.

Multinomial logistic regression analysis predicts categorical variables or the probability of participating in a category as a dependent variable based on multiple independent variables [37]. This type of regression analysis is often used as it does not require regularity, linearity, or homoscedasticity [38,39]. In addition, multinomial logistic regression analysis uses a maximum likelihood estimation to assess the probability of categorical participation [40]. The resultant model allows us to characterize the probability that a respondent will decide on a particular multinomial distinct choice via the values of the explanatory variables. The distribution functions that characterize explanatory variables are often nonlinear [33]. Thus, once the multinomial logistic regression model is created, the parameters can be used to predict the probability of an event occurring by comparing it with the reference category [41].

Given the predictors X₁, …, Xp, multinomial logistic regression models the probability of each level j of Y by

$$\begin{gathered} p_j\left(x\right):=P\lfloor Y=J|X_1=x_1,\dots , X_p=x_p\rfloor \\ =\frac{e^{\beta 0_j+{\beta }_{1J}X1+\cdots +\beta pjXp}}{1+{\sum }_{l=1}^{J-1}{e}^{{\beta }_{0l}+{\beta }_{1l}{X}_1+\cdots +{\beta }_{pl}{X}_p}} \end{gathered}$$

(1)

for j = 1, …, J − 1j = 1,…,J − 1 and (for the last level JJ).

$$\begin{gathered} p_j\left(x\right):=P\lfloor Y=J|X_1=x_1,\dots , X_p=x_p\rfloor \\ =\frac{1}{1+{\sum }_{l=1}^{J-1}{e}^{{\beta }_{0l}+{\beta }_{1l}{X}_1+\cdots +{\beta }_{pl}{X}_p}} \end{gathered}$$

(2)

Note that Equations (1) and (2) imply that ∑Jj = 1pj(x) = 1∑j = 1Jpj(x) = 1 and that there are (J − 1) × (p + 1)(J − 1) × (p + 1) coefficients245. Furthermore, Equation (5) reveals that the last level, J,J, is given a different treatment. This is because it is the reference level (it could be a different one, but it is the tradition to choose the last one).

The multinomial logistic model has an interesting interpretation in terms of logistic regressions. Taking the quotient between Equation (1) and Equation (2) gives

$$\log \left(\frac{p_j\left(x\right)}{p_J\left(x\right)}\right)={\beta }_{0j}+{\beta }_{1j}{X}_1+\cdots +{\beta }_{pj}{X}_p$$

(3)

If J = 2, J = 2, it is the same up to a change in the codes for the levels: the logistic regression giving the probability of Y = 1Y = 1 versus Y = 2.Y = 2. On the LHS of Equation (4) we have the logarithm of the ratio of two probabilities and on the RHS a linear combination of the predictors. If the probabilities on the LHS were complementary (if they added up to one), then we would have a log-odds and hence a logistic regression for Y.Y. This is not the situation, but it is close: instead of odds and log-odds, we have ratios and log-ratios of non-complementary probabilities. In addition, it gives a good insight on what the multinomial logistic regression is: a set of J−1J−1 independent logistic regressions for the probability of Y = jY = j versus the probability of the reference Y = J.

Equation (3) gives also interpretation on the coefficients of the model since

$$p_j\left(x\right)=e^{{\beta }_{0j}+{\beta }_{1j}{X}_1+\cdots +{\beta }_{pj}{{\rm X}}_{ppj \left(x\right).pj\left(x\right) }}=e^{{\beta }_{0j}+{\beta }_{1j}{X}_1+\cdots +{\beta }_{pj}{{\rm X}}_{ppJ \left(x\right).}}$$

(4)

Therefore:

e^β0j: is the ratio between p_j(0)/p_J(0), the probabilities of Y = j when X₁ =…= X_p = 0.X₁ =…= X_p =0. If e^β0j > 1 (equivalently, β_0j > 0), then Y = j is more likely than Y = J. If e^β0j < 1 (β_0j < 0), then Y = j is less likely than Y = j.

eβ^ℓj,ℓ ≥ 1: is the multiplicative increment of the ratio between p_j(x)/p_J(x) for an increment of one unit in X_ℓ = x_ℓ, provided that the remaining variables X₁,…,X_ℓ−1,X_ℓ+1,…,X_p do not change.

If e^βℓj > 1 (equivalently, β_ℓj > 0), then Y = j becomes more likely than Y = j for each increment in Xj. If e^βℓj < 1 (β_ℓj < 0), then Y = j becomes less likely than Y = j.

4. Results

4.1. Descriptive Analysis

Table 1. Participants’ demographic characteristics.

Questions	Variables	Alternatives	Ν	%	Mean	Min	Max
What is your sex?	Sex	Male	137	37.1
		Female	232	62.9
How old are you?	Age, mean (std. dev.)		23.5 (7.72)		23.5	18	55
What is your educational level?	Education level	Undergraduate	337	91.3
		Postgraduate	32	8.7
Do you have any work experience?	Work experience	No	119	32.2
		Yes	250	67.8
How many years of work experience do you have?	Years of work experience	None	119	32.2
		Less than 1 year	90	24.4
		1–3 years	62	16.8
		More than 3 years	98	26.6
Do you have work experience in a family business?	Experience in family business	None	158	63.2
		Less than 1 year	32	12.8
		1–3 years	23	9.2
		More than 3 years	37	14.8
Please indicate your father’s work status	Father’s work status	Entrepreneur	64	17.4
		In private sector	134	36.3
		In public sector	109	29.5
		Other	62	16.8
Please indicate your mother’s work status	Mother’s work status	Entrepreneur	24	6.4
		In private sector	123	33.3
		In public sector	96	26
		Other	126	34.1

presents the participants’ demographic characteristics. Of the total sample (N = 369), 62.9% (N = 232) are female and 37.1% (N = 137) are male, with a mean age of 23.5 (7.72) years. The majority are undergraduate students (91.3%, N = 337) followed by postgraduate students (8.7%, N = 32). Most students attend the University of Thessaly, regardless of grade (72.4%, N = 267). Regarding the university department, most participants attend the School of Economics and Administrative Sciences (65.9%, N = 243). Most have previous work experience (67.8%, N = 250): 26.6% (N = 98) have worked for more than 3 years, 24.4% (N = 90) have worked for less than 1 year, and 16.8% (N = 62) have worked for 1–3 years. Of the 250 participants with work experience, 14.8% (N = 37) have worked in a family business for more than 3 years, 12.8% (N = 32) have worked for less than 1 year, and 9.2% (N = 23) have worked for 1–3 years. However, 63.2% (N = 158) of those with work experience have not worked in a family business. Finally, regarding parents’ working status, 36.3% (N = 134) and 29.5% (N = 109) of participants’ fathers work in the private and public sectors, respectively, while the largest percentage of mothers work in an unspecified category or do not work at all (34.1%, N = 126), or work in the private sector (33.3%, N = 123).

Table 2. Descriptive statistics of participant responses.

Questions	Variable	Alternatives	Ν	%	Mean	Std. Dev.	Min	Max
Do you plan to start a business within the next year?	Youth’s willingness	Not at all likely	289	78.3	1.33	0.66	1	3
		Moderate likely	40	10.8
		Very likely	40	10.8
Please indicate the degree to which you believe best represents your level of business knowledge	Knowledge	Not at all knowledge	145	39.3	1.92	0.84	1	3
		Moderate knowledge	109	29.5
		Very high knowledge	115	31.2
How attractive is it for you to combine part-time employment with entrepreneurship?	Mixed work status	Not at all attractive	82	22.2	2.33	0.82	1	3
		Moderate attractive	83	22.5
		Very attractive	204	55.3
How attractive is entrepreneurship to you?	Attractiveness of being entrepreneur	Not at all attractive	99	26.8	2.24	0.85	1	3
		Moderate attractive	82	22.2
		Very attractive	188	50.9
Does being an entrepreneur mean great satisfaction for you?	Satisfaction	Not at all	76	20.6	2.34	0.8	1	3
		Moderate	92	24.9
		Very much	201	54.5
Are you ready to make every effort to become an entrepreneur?	Efforts toward entrepreneurship	Not at all	179	48.5	1.81	0.86	1	3
		Moderate	82	22.2
		Very much	108	29.3
Please indicate the degree to which your friends would support your decision to start a business	Friends’ support	Not at all	29	7.9	2.7	0.61	1	3
		Moderate	51	13.8
		Very much	289	78.3
Do you feel you have the ideas to establish a new business?	Creative ideas	Not at all	153	41.5	2.07	0.95	1	3
		Moderate	37	10.0
		Very much	179	48.5
Do you believe that it is difficult to develop a business plan in Greece during the COVID-19 pandemic?	Difficulties in business plan	Not at all	68	18.4	2.35	0.77	1	3
		Moderate	104	28.2
		Very much	197	53.4

presents the participants’ business intention responses. Overall, 78.3% (N = 289) have no plans to start their own businesses within the next year. Regarding business knowledge, 39.3% (N = 145) have no knowledge of starting a business at all, while 31.2% (N = 115) have much knowledge. Most participants have a combination of part-time employment in a private company as well as business activity (55.3%, N = 204). In addition, they state that being an entrepreneur is appealing (50.9%, N = 188), and being an entrepreneur means great satisfaction (54.5%, N = 201). Conversely, 48.5% (N = 179) do not feel ready to become entrepreneurs, but plan to start their own business in the next year (78.3%, N = 289), and their friends will support them. Finally, inhibiting factors include the lack of ideas (48.5%, N = 179) and developing a business plan during the COVID-19 pandemic in Greece (53.4%, N = 197).

4.2. Multinomial Logistic Regression Analysis

To respond to the study objective, we performed a multinomial logistic regression analysis to highlight the factors that drove youths toward entrepreneurship in times of crisis. Multinomial regression analysis is a statistical modelling method that is applied in cases where the dependent variable y is categorical with more than two categories. The dependent variable was youth intention to follow the path of entrepreneurship immediately after completing their studies [42,43], which was categorized as follows: (1) not at all likely, (2) moderately likely, and (3) very likely. The independent variables were sex, age (as a continuous variable), father’s employment background, mother’s employment background, educational level, university location, university department, years of work experience, years of work experience in a family business, level of business knowledge, preference between having a part-time job and being an employer, opinion on whether being an entrepreneur is appealing, insight on whether being an entrepreneur implies great satisfaction, support from friends, whether lack of ideas would be a deterrent regarding starting a business, and whether the difficulties of developing a business plan would prevent them from starting a new business in Greece during the COVID-19 pandemic.

Table 3. Multinomial logistic regression analysis of youths’ entrepreneurial intention (Model 1).

2 vs. 1	OR	Std. Error	p	95% Δ.Ε.
Sex
Male	0.388	0.457	0.039	0.158–0.952
Female
Father’s work status
Entrepreneur	1.765	0.783	0.468	0.381–8.186
In private sector	3.275	0.640	0.064	0.935–11.474
In public sector	1.047	0.721	0.950	0.255–4.3
Other
Mother’s work status
Entrepreneur	0.139	1.188	0.097	0.014–1.426
In private sector	0.832	0.486	0.704	0.321–2.154
In public sector	0.538	0.588	0.291	0.17–1.702
Other
Education level
Undergraduate	1.292	0.954	0.789	0.199–8.385
Post graduate
Work experience
No	2.775	0.811	0.208	0.566–13.601
Yes
Years of work experience
None	0.329	0.857	0.195	0.061–1.767
Less than 1 year	1.500	0.795	0.610	0.316–7.125
1–3 years
More than 3 years
Experience in family business
None	0.489	0.850	0.400	0.093–2.588
Less than 1 year	0.093	1.204	0.048	0.009–0.98
1–3 years	1.172	0.853	0.853	0.22–6.24
More than 3 years
Age	0.967	0.046	0.468	0.883–1.059
Knowledge	1.096	0.266	0.731	0.651–1.844
Moderate knowledge	1.174	0.249	0.519	0.721–1.913
Mixed work status	2.292	0.325	0.011	1.213–4.33
Attractiveness of being an entrepreneur	2.094	0.341	0.030	1.074–4.082
Satisfaction	0.968	0.311	0.916	0.526–1.778
Efforts toward entrepreneurship	0.614	0.294	0.098	0.345–1.094
Friends’ support	1.594	0.398	0.241	0.731–3.477
Lack of creative ideas	1.633	0.222	0.027	1.056–2.525
Difficulties with business plan	0.603	0.265	0.056	0.359–1.013

and

Table 4. Multinomial logistic regression analysis of youths’ entrepreneurial intention (Model 2).

3 vs 1	OR	Std. Error	p	95% Δ.Ε.
Sex
Male	1.391	0.469	0.482	0.554, 3.491
Female
Father’s work status
Entrepreneur	3.440	0.813	0.129	0.699, 16.932
In private sector	4.657	0.767	0.045	1.036, 20.942
In public sector	2.254	0.712	0.254	0.558, 9.098
Other
Mother’s work status
Entrepreneur	0.715	0.915	0.714	0.119, 4.295
In private sector	0.455	0.617	0.202	0.136, 1.526
In public sector	0.249	0.680	0.041	0.066, 0.945
Other
Education level
Undergraduate	0.182	0.882	0.054	0.032, 1.026
Post graduate
Work experience
No	4.546	0.890	0.089	0.794, 26.021
Yes
Years of work experience
None	0.991	0.862	0.992	0.183, 5.373
Less than 1 year	0.748	0.841	0.730	0.144, 3.888
1–3 years
More than 3 years
Experience in family business
None	0.749	0.922	0.754	0.123, 4.569
Less than 1 year	0.079	1.265	0.045	0.007, 0.943
1–3 years	0.358	0.860	0.232	0.066, 1.932
More than 3 years
Age	1.021	0.040	0.595	0.945, 1.104
Knowledge	1.005	0.319	0.987	0.538, 1.878
Moderate knowledge	1.686	0.289	0.071	0.956, 2.971
Mixed work status	0.625	0.329	0.153	0.328, 1.19
Attractiveness of being entrepreneur	0.445	0.428	0.058	0.193, 1.029
Satisfaction	13.807	0.900	0.004	2.365, 80.597
Efforts toward entrepreneurship	3.955	0.396	0.001	1.82, 8.592
Friends’ support	12.057	1.028	0.015	1.607, 90.464
Lack of creative ideas	0.823	0.260	0.453	0.494, 1.37
Difficulties with business plan	0.809	0.306	0.487	0.444, 1.472

present the multinomial logistic regression analysis results for the two models. We performed an appropriate inverse transformation of the regression coefficients to interpret the model results. The tables include the ratio of complementary probabilities (odds ratio [OR]) below. The overall model is statistically significant (X2 (56) = 165.614, p-value < 0.001) compared to the zero model, and the model explains 36% of the variability of the dependent variable (Cox and Snell R2 = 0.362) (Appendix A 

Table A1. Model fitting information of the model.

Model	Model Fitting Criteria	Likelihood Ratio Tests
	−2 Log Likelihood	Chi-Square	df	Sig.
Intercept only	496,753
Final	331,139	165,614	56	0.000

).

Model 1 shows that males are 61.2% less likely than females to declare a moderate likelihood of starting their own business within the next year than state that they do not intend to proceed, regardless of the influence of other independent variables (OR = 0.388, p = 0.039). Regarding the years of work experience in a family business, participants with 1–3 years’ work experience are 90.7% less likely than those with no experience to declare a moderate likelihood to start their own business within the next year, relative to stating that they do not intend to do so, regardless of the effect of the other independent variables (OR = 0.093, p = 0.048). Regarding the degree of attractiveness, combining part-time employment with starting a new business activity emerges as an additional determinant of starting a business within the next year. Participants are 2.292 times more likely to be moderately willing than unwilling to starting their own business within the next year, regardless of the influence of other independent variables (OR = 2.292, p = 0.011). Moreover, as the degree of attractiveness of being an entrepreneur increases, participants are 2.094 times more likely to have a moderate likelihood of establishing their own business within the next year than not at all, regardless of the influence of other independent variables (OR = 2.094, p = 0.030). Finally, the prominence of having no business ideas leads participants to be 63.3% more likely to have a moderate likelihood of becoming an entrepreneur within the next year than not at all, regardless of the effect of other independent variables (OR = 1.633, p = 0.027) (Table 3).

Model 2 shows that participants with fathers who work in the private sector are 4.657 times more likely to start their own business than those whose fathers do not work in this sector, regardless of the influence of other independent variables (OR = 4.657, p = 0.045). In addition, participants with mothers who work in the public sector are 75.1% less likely to start their own business than those whose mothers do not work in this sector, regardless of the influence of other independent variables (OR = 0.249, p = 0.041). In addition, participants who have 1–3 years of work experience in a family business are 92.1% less likely to start their own business compared to those who do not have similar experience, regardless of the influence of other independent variables (OR = 0.079, p = 0.045). Further, participants who most agree that being an entrepreneur means great satisfaction are 13.807 times more likely to start their own business, regardless of the influence of other independent variables (OR = 13.807, p = 0.004). In addition, participants who agree that they are ready to become an entrepreneur are 3.955 times more likely to start their own business, regardless of the influence of other independent variables (OR = 3.955, p = 0.001). Finally, participants are 12.057 times more likely to start their own business if their friends supported them, regardless of the influence of other independent variables (OR = 12.057, p = 0.015) (Table 4).

5. Discussion

A crisis, such the recent coronavirus disease (COVID-19) can affect youths in different ways and can result in feelings of anger, despair, uncertainty, fear, loneliness, and social exclusion [44]. In Greece, while young people were attempting to recover from the adverse effects of the prior economic crisis, the COVID-19 pandemic overturned them once again in their routine [45,46,47]. Some of the major concerns that have affected Greek youths over the last two years of the pandemic involve job seeking, future career prospects, and unemployment [48,49]. Greece can be highlighted as a champion of youth unemployment among EU countries since its youth unemployment rate exceeds 32%, which is more than double the EU average [9,10]. Accordingly, youths have increasingly engaged in informal forms of employment—a choice that has been facilitated by labor market reform during the crisis. Although engaging in this employment type has gradually reduced unemployment, the current situation cannot be considered satisfactory as salaries are extremely low, the “skills mismatch” problem is exacerbated, and “over-qualification” is rife [10,14].

However, are there any alternative ways to help youths address the effects of a crisis? Can entrepreneurship be proposed as an ideal way for youths to mitigate the harmful effects of the pandemic in the labor market? This study investigated the entrepreneurial intention of youths towards entrepreneurship, as well the highlights the factors, except from unemployment, that push youth access in the business arena. The findings show that participants do not plan to establish a new business next year as they feel insecure and unprepared. Most participants state that becoming an entrepreneur can offer great satisfaction, but they do not have the knowledge to enter the business arena. This indicates a paradoxical situation for the participants: most are students in business schools and are, therefore, over-qualified, yet they state that they lack the sufficient knowledge regarding their engagement with entrepreneurship [50,51]. One explanation for this phenomenon is the lack of connection between the education that youths receive at university and the failure to cultivate meaningful relationships in educational institutions. This weakness results in ineffective professional guidance, which does not help youths understand the appropriate steps they need to follow to engage in entrepreneurship after graduation [52,53,54]. Another reason why youths feel that they lack the necessary knowledge to engage in entrepreneurship is due to the value of their degrees after graduation. During their studies, youths primarily acquire theoretical knowledge, which may be insufficient for engaging in a difficult career path such as entrepreneurship. Therefore, linking university teaching staff with industry professionals can help provide youths with the relevant skills that they may need as entrepreneurs. This will also ensure that the curriculum is fully in line with current market trends; moreover, the use of teaching methods such as experiential learning can better encourage young people [55,56].

The family environment is also a critical driving factor in young people’s career choices. Generally, the influence of the family environment on a young person’s career choice depends on many factors [57] such as parents’ education, mentality and ideals, family size, parenting standards, parents’ work background, parents’ ambitions and desires for the professional rehabilitation of their child, parents’ attitudes toward certain professions, and parent–child relationships [58]. The family, as a social, psychological, and economic entity, plays an important role in shaping an individual’s personal and professional identity. Therefore, the family environment cultivates values, attitudes, and behavioral patterns that influence youths and shape their careers. In the current study, participants stated that their parents’ work background mostly affected their preference for entrepreneurship [59]. Furthermore, participants whose fathers worked in the private sector were 4.657 times more likely to become an entrepreneur. This means that a self-employed father may inspire their child to become an entrepreneur, whereas mothers may have a greater influence on their child’s academic life [60].

However, it is noteworthy that youths who had previous work experience in a family business presented less entrepreneurial intention than those who did not have previous work experience. This finding is inconsistent with the previous studies that have confirmed a positive relationship between previous work experience in a family business and entrepreneurial intention. This is because working in a family business can be an enjoyable experience for family members; however, there are also many pitfalls that can lead youths to leave the business arena [61]. Working for a family business can be problematic because it is not a “normal” business but is one in which a close family member is the boss. This makes the situation much more complex. In addition, the lack of separation between family and work issues often creates tension between family members. Accordingly, these issues can affect the entrepreneurial intention of youths who have previous business experience [61].

Further, young people feel the need to become more independent from their parents during adolescence. This does not only include financial independence, but also involves decision-making about their lives [62]. Young people discuss the various issues that concern them, such as careers, with their friends. Although it is difficult for many parents to accept, their children’s bonds with their peers are important, beneficial, and supportive. In the current study, participants stated that their friends could act as a key support system regarding their decision to enter the business arena. Since the entrepreneurship path is quite difficult for young people, their friends’ support is vital [63].

Considering the findings of this study presents plenty of theoretical and practical implications for the field of entrepreneurial intention. The development of the intention to be an entrepreneur can be characterized as multiplex process, which can be influenced by factors from the micro and macro environment. Regarding the factors from the internal environment this study further enriches the research on the antecedents of university students’ entrepreneurial intention by the construction of a model that is based on the combination of both internal and external factors. Specifically, it can be indicated that the prediction of the entrepreneurial intention of the university students depends on the specific contexts involved. Therefore, in the terms of these specific contexts, this study proposes a business model for the enhancement of the entrepreneurial intention of university students that links the individual, the family, and the social network level of youths. In sum, our findings enrich research on the factors influencing entrepreneurial intention, provide a theoretical basis for formulating policies to encourage entrepreneurial intention among university students, and help explore effective ways to enhance entrepreneurial intention and behavior.

6. Conclusions

Entrepreneurship is a critical factor in a country’s economic development. Policymakers and governments have recognized the contribution of entrepreneurship in a country’s innovation, productivity, and job creation, especially for youths who must mitigate unemployment. Therefore, it is vital to encourage young people to pursue entrepreneurship. Accordingly, this study investigates the readiness of Greek youths to enter the business arena during a crisis.

The results support the idea that youths are not ready to start a business activity next year. Their decisions are based on a wide range of factors such as a lack of knowledge and creative ideas. However, participants who showed highest entrepreneurial intention were females aged 23.5 years. Under Greece’s democratic government, females feel more confident about getting involved in business activities and choosing entrepreneurship over salaried jobs. Female contributions to economic activity are constantly increasing in Greece. In Greece, encouraging women’s entrepreneurship is included in a set of policies aimed at developing their business potential, fighting unemployment, and promoting gender equality. In addition, the outbreak of the COVID-19 pandemic has not created a negative environment for female entrepreneurship but has strengthened it, mainly via the adoption of telecommuting, which may be a consequence of restrictive measures to curb the COVID-19 pandemic. Meanwhile, this trend will seemingly continue as it emerges that employees are more efficient when working from home. After the creation of a legal framework for telecommuting, working women will be able to work without neglecting any family duties.

The results also highlight that educational attainment is a key factor that influences youths’ entrepreneurial intentions. While the participants comprised students at business schools, they stated that they did not have the necessary knowledge regarding business operation. There are two reasons for this. First, because there is no link between universities and businesses. Moreover, entrepreneurship courses have not been integrated into lower levels of education in Greece, such as primary education. Second, the results show a relationship between family background and youths’ entrepreneurship intentions. Youths seem to be more influenced by their fathers’ occupational background, especially when they are self-employed. However, it is noteworthy that youths with previous work experience in a family business appear hesitant about engaging in entrepreneurship.

While this study significantly contributes to the field of youth entrepreneurship and highlights its new dimensions in times of crisis, some limitations remain. Specifically, the sample only covered students studying in the Department of Business Administration at the University of Thessaly. Therefore, future research could add more students from other Greek universities and institutions to improve generalizability. In addition, this study did not consider factors such as culture, readiness, and perceived obstacles. Therefore, to evaluate these factors, a qualitative methodology would be more appropriate for assessing the complexity of the determinants and precedents of youths’ entrepreneurial intentions. Even though quantitative research is preferred in the entrepreneurship field, future studies could use mixed methods (qualitative and quantitative) to provide a more comprehensive perception of the previous factors and determinants that trigger business behavior among youths.