What Happens to the Entrepreneurial Intentions of Gen Z in a Crony Capitalist Economy Amidst the COVID-19 Pandemic?

Abstract

Despite years of research, scholars still have a limited understanding of the factors that lead individuals to start their own businesses. Drawing upon the crisis decision theory (CDT), the theory of planned behavior (TPB), the entrepreneurial event model (EEM), and previous research on entrepreneurial intentions (EIs), this study investigates the impact of a set of predictors (i.e., perceived crisis severity, entrepreneurial disposition, support from family/friends, university affiliation, gender, year of study, work experience, presence of a role model, and completion of an entrepreneurship class) on the outcome variable (i.e., EIs) of Generation Z in a highly tourism-dependent transitional economy. Pearson’s correlation and multiple regression were employed to analyze the data collected in May/June 2020 via a self-administered questionnaire from 300 tourism and hospitality students enrolled at five public universities in Croatia. The results indicate that entrepreneurial disposition, work experience, and gender are directly related to EI. The perceived crisis severity does not affect EI. These findings contribute to filling gaps in the existing research on entrepreneurship during major crises, on EIs of Gen Z, on the role of perceived crisis severity in EIs, and on the state of EIs in mono-industrial (i.e., dominated by one industry) crony capitalist ex-communist economies.

1. Introduction

A recent worldwide economic meltdown suddenly caused by the global COVID-19 pandemic has led to a renewed interest in entrepreneurship [1,2,3,4,5,6,7]. There is a wide consensus among scholars, policymakers, and industry professionals that entrepreneurship is an important catalyst in job creation and country development [7,8,9]. However, to encourage entrepreneurship, there is a need to understand why some individuals become entrepreneurs while others do not. Despite decades of research, scholars currently have only a limited understanding of the factors and decision-making processes that lead an individual to set up their own business [10]. What is more, scholarly works investigating entrepreneurship phenomena during major crises, such as a pandemic, are scarce [4,11]. In addition, the influence of perceived crisis severity on the intention to launch a business is an under-researched topic amongst the existing literature on entrepreneurship.

Adding to the challenge, the speed of entrepreneurship development varies across countries due to a divergent mix of political, economic, and socio-cultural factors [12]. Croatia, as compared to the other post-communist Central and Eastern European (CEE) countries, especially those in the Visegrad Group (i.e., V4—Czechia, Hungary, Poland, and Slovakia), has been very slow in the implementation of free-market principles [13,14]. Following Croatia’s Homeland War of 1991–1995 (also known as the Croatian War of Independence), the nation’s communist past has shaped the everlasting transition from a centrally planned economy to a market economy. The fact that Croatia is nowadays one of the most undeveloped EU member countries [15] indicates deeply entrenched crony capitalism and government-sponsored corruption, fostered by the pre-1990s privileged communist elite as a means to retain its privileges in present times [13]. Additionally, between 2011 and 2021, Croatia lost a whopping 10% of its population [16], largely via emigration to other, more developed EU countries. Such a unique legacy naturally raises concerns about the nature of Croatia’s entrepreneurial dynamics and whether some important drivers of entrepreneurial intention (EI) can explain the country’s entrepreneurial reality.

Over the past two decades, tourism has been a driving force of Croatia’s economy, accounting for almost 40% of the country’s export revenues and nearly 20% of GDP in 2019 [17]. This makes Croatia the most economically tourism-dependent country in the EU [18]. Thus, a significant portion of the country’s entrepreneurial potential is likely to reside in the tourism sphere. What is more, decisions about exploiting entrepreneurial opportunities in tourism will be in the hands of the youngest demographic cohort of the workforce—i.e., Generation Z (Gen Z), anyone born between 1995 and 2009 [9]. Importantly, as the long-term values of Gen Z are still being formed, the coronavirus pandemic may have a greater impact on them than on members of previous generations [19]. Specifically, Gen Z is the first generation to have grown up in the digital age [20], and they spend less time in direct face-to-face contact with others [21], which is one of the reasons they experience higher rates of depression and anxiety, as well as a greater need for emotional support [21,22]. The enormous amount of complex information about COVID-19 outstripped Gen Zs’ information-processing capacity, hampered their ability to develop an unbiased assessment of COVID-19, increased their fear of the coronavirus pandemic [23], and deepened their concerns about the future’s uncertainty [19]. The crisis has already had a greater impact on the older cohort of Gen Z (18–23-year-olds) than on previous generations, particularly in terms of employment [21]. Furthermore, health and financial security were the top two COVID-19 concerns for Gen Z [19]. Thus, the importance of understanding the tendencies for the self-employment of Gen Z necessitates research into the unique characteristics of this generation [24], particularly in light of the COVID-19 pandemic.

Despite many studies on (1) the relationship between entrepreneurship and economic development and (2) the factors affecting EI [8,25], little is known about the EIs of Gen Z in a highly tourism-dependent, crony capitalist society, in the face of such an abrupt and rapidly accelerating global crisis as the COVID-19 pandemic. The present study aims at filling this research gap by attempting to answer the following two questions. First, does the perceived severity of the major global crisis affect intentions of Gen Z (specifically, tourism and hospitality students) towards starting a new business? Second, do demographic, psychological, experiential, and contextual predictors affect the EIs of the up-and-coming generation of tourism and hospitality graduates?

The rest of this paper is organized as follows. The next section presents the theoretical context and the discussion in connection with the relationship between the dependent variable (i.e., EI) and a set of predictors (i.e., perceived crisis severity, entrepreneurial disposition, support from family/friends, university affiliation, gender, year of study, length of work experience, presence of a role model, and completion of an entrepreneurship class). Section 3 provides an elaboration of the unique setting for this study—i.e., a highly tourism-dependent transitional economy featuring entrenched communist heritage clad in crony capitalism. Section 4 details the methodology, followed by the results of the empirical research in Section 5. The paper ends with a discussion of the theoretical and practical implications, limitations, and further research.

2. Literature Review

2.1. Entrepreneurial Intention

Entrepreneurial intention (EI), a key predictor of entrepreneurial behavior, is a leading concept in the study of the entrepreneurship phenomena [26,27,28,29]. In this paper, EI is defined as an “individual’s judgments and attitude toward the likelihood of developing one’s own business” [2] (p. 126). As a background theory for understanding EI, this study refers to three complementary models: Sweeny’s [30] crisis decision theory (CDT), Ajzen’s [26] theory of planned behavior (TPB), and Shapero and Sokol’s [28] entrepreneurial event model (EEM).

In CDT, when facing a negative life event, such as a crisis, people go through a three-stage process: assessing the severity of the negative event (i.e., gathering information about causes, comparing the current event with familiar contexts, and/or evaluating the potential consequences of the event); determining response options (i.e., evaluating the controllability of outcomes and the feasibility of responses); and evaluating response options (i.e., determining the resources required to engage in a response and assessing direct and indirect consequences) [30]. In the TPB, entrepreneurial intent is a function of three factors: personal attitude (i.e., the degree to which an individual has a favorable or unfavorable evaluation of starting a business), subjective norms (i.e., one’s perception of about whether family and peers think he or she should start a business), and perceived behavioral control (i.e., a person’s perception of the ease or difficulty of starting a business) [31]. In the EEM model, EI is comprised of three components: perceived desirability (i.e., the attractiveness of starting a business), propensity to act (i.e., one’s desire and willingness to start a business), and perceived feasibility (i.e., the degree to which a person feels capable of starting a business) [32]. In terms of explanatory power, while CDT is a relatively recent theoretical contribution that is empirically in its infancy, both the TPB and the EEM typically explain 30–50 percent of variance in EI [31,32], which leaves about half of the variance in intention unexplained [31].

Researchers have therefore called for the inclusion of additional variables that can influence the decision to start a business [33,34]. These variables can be broadly categorized as demographic, psychological, experiential, contextual support, and crisis-related [2,4,25]. Each category, as it relates both to IE and the objectives of this study, is discussed in the subsequent sections.

2.2. EI and Demographic, Psychological, and Experiential Variables

The demographic variables often explored in relation to starting a new business are gender and age [2,9,35]. In terms of gender, although men and women possess similar intrinsic personality traits that often lead to successful entrepreneurial behavior (e.g., needs for achievement and autonomy) [36], existing research shows EI to be stronger in men than in women [37,38,39,40,41,42]. The observed gender differences in EI may stem, at least in part, from perceptions of which traits and characteristics make a successful entrepreneur [9,36,43]. Namely, traits traditionally viewed as masculine (e.g., aggression, achievement orientation, dominance, independence, challenges, and high risk taking) are deemed more desirable in venture creation [44]. Consequently, women may generally perceive themselves as ill-equipped in areas they perceive to be male ones, which in turn may initially limit their entrepreneurial efforts [9,41,44,45,46]. There are also differences in motives. While women see entrepreneurship more as a means of reconciling their work and child-rearing roles (i.e., a necessity), men tend to see it as a way to make money (i.e., an opportunity) [36]. Regarding age, the jury is still out. While in some studies age is not regarded as a significant determinant of business start-ups [9,35,47,48,49], other studies find age to be an important driver in starting a firm [37,50,51,52,53]. Interestingly, among the latter, it seems that EI is high at an earlier age, and then it tapers off and eventually declines as people settle in their jobs.

Since the potential for failure and loss discourages many from launching their own business, an entrepreneur can be understood as someone with a well-developed sense of confidence [54]. The psychological construct of self-efficacy—i.e., a person’s confidence in themselves to successfully start an entrepreneurial venture [55,56]—has thus played a vital role in predicting EI [32,57,58,59,60]. Naturally, it is the perception of self-efficacy, rather than objective ability, which thrusts individuals into a business endeavor [61]. In addition to self-efficacy, scholars are increasingly exploring a related, focused concept—i.e., entrepreneurial disposition (orientation)—to highlight ingenuity and ambition as equally important aspects of venture creation [54,62,63,64,65,66,67,68]. Therein, entrepreneurial disposition denotes “an individual’s sense of self, his or her judgment of their own personal creativity and personal initiative” [67] (p. 95). In this study, we also explore the especially important notions of creativity and the ability to self-start (i.e., entrepreneurial disposition).

In an attempt to identify who wants to become an entrepreneur, scholars have often investigated the contribution of experience—i.e., “a person’s observation of and/or interaction with objects, entities, and/or events in her/his environment” [69] (pp. 58–59). This general understanding of experience may include factors such as (un)favorable previous work experience and (un)likable role models [12,25,70,71]. That said, much like with age, the link between previous work experience and EI has been found in some studies [5,47,72,73] and not in others [9,35]. With regard to role models, EIs are influenced by exposure to role models; however, this influence depends on from whom (i.e., family, similar models and peers, educators and mentors, successful vs. unsuccessful models, and unrelated models), when (i.e., childhood and adolescence, and comparison of life-cycle stages), and in which context/where (i.e., environment and culture, entrepreneurship programs, and social context and stereotyping) this exposure occurs [10]. Previous research suggests that having entrepreneurial parents [73,74,75,76,77,78,79] and enterprising peers/friends [80] affects the likelihood of venture creation. Accordingly, this study’s focus is on friends and family members as the closest and most important relationships for most people aside from romantic partners [81,82].

2.3. EI and Contextual Support

Prospective entrepreneurs do not make calculated risky decisions in a vacuum. Rather, they seek support from various sources, such as family, friends, and educational institutions [25]. This is not surprising since family and friends are central to human life, and most people maintain relationships with both family and friends [83]. However, the decision to start a new business can elicit different reactions from family and friends [54]. Thus, in addition to being role models, family members and friends can encourage or discourage new venture creation [77,84,85,86]. Altogether, while most research suggests that the expectation of family support invigorates the intention to start a business [25], at least one study finds that the backing provided by family and friends is not sufficient to significantly affect a person’s EI [87]. In addition to family and friends, universities can also foster EI, for instance, by providing opportunities to major in entrepreneurship or to take entrepreneurship classes [57,88,89] that nourish students’ individual creativity, self-reliance, and resilience [25].

2.4. EI and Perceived Crisis Severity

This study endeavors to advance the existing literature by investigating EI during the COVID-19 pandemic. Several studies suggest that the decision to launch a new venture is contingent upon the conditions of the economic environment in which the new business will operate [87,90,91]. According to this viewpoint, it is impossible to evaluate the attitude toward entrepreneurship without considering the perceived crisis severity [30] and the kind and caliber of opportunities offered by the economy [25]. Since the perceived crisis severity, defined as the degree to which people judge a crisis to be severe [92], is driven by the individual’s understanding of the crisis, it may vary over time and differ from the actual risk [93,94].

In assessing crisis severity, prospective entrepreneurs gather and analyze information about the consequences of the COVID-19 disease on the fulfillment of their project [28,30,92,95,96]. This information concerns, for instance, the market volatility, the economic climate, and the likelihood that the crisis will continue to be an issue in the future. Depending on this information, an environment may be viewed as more or less favorable for launching a new business. The characteristics of the economic environment and the caliber of business possibilities invariably deteriorate during a crisis. Thus, one should anticipate a decline in the number of start-ups. For instance, during the 2007–2008 Global Financial Crisis, the entry of new businesses plummeted [97] and the perception of the economic crisis as an obstacle had a negative and highly significant impact on students’ likelihood to start a business [25]. Similarly, a decrease in social entrepreneurial intention was observed among Spanish university students during the COVID-19 crisis [6].

COVID-19 is an ideal example of a crisis with a battery of consequences [94], especially in the travel, tourism, and hospitality industry. The rapid spread of the virus brought about in-restaurant dining restrictions [98], restaurant closures or limited operations [99], intranational and international travel restrictions [99,100,101], flight cancellations [102,103], limited indoor and outdoor activities [99,104], limited general safety (e.g., social, food, cyber, economic, supply-chain, etc.) [105,106], general business disruptions and closures [107], and unemployment [108], to name a few. In addition to the large number of consequences, a striking and consistent observation has been made regarding the difference in severity of COVID-19 at different ages. While severity, the need for hospitalization, and mortality skyrocket with older age, serious or fatal COVID-19 infection is much less common among children, adolescents, and young adults (i.e., 18–24-year-olds) [109,110]. Although, health wise, members of Gen Z (i.e., young adults) are among the least affected by COVID-19, they are harmed by the economic crisis more profoundly than individuals of other generations [19,20,21,22,23,24].

In addition to the adverse impacts, economic downturns can sometimes have positive consequences by igniting entrepreneurial spirit. The decision to start a business depends on the degree to which self-employment is viewed as a feasible second-best option to employment when unemployment rates are high. The concepts of “opportunity-based” and “necessity-based” entrepreneurs are discussed in this area of study, and the research suggests that the latter tends to predominate under situations of higher economic difficulty in comparison to the former [111,112].

In summary, although research on EIs has attracted increasing attention, there are still gaps in the existing research, as evidenced by calls for the inclusion of additional variables that can influence the decision to start a business [33,34]. Some researchers have responded by exploring the role of entrepreneurial disposition in EI, and although the results of the few exploratory studies are promising, further empirical validation is necessary. Moreover, while investigating the impacts of the COVID-19 crisis on EI, scholars have overlooked the potential of perceived crisis severity, an essential concept in CDT, in augmenting EIs [4,11]. Additionally, given the recency of the pandemic, there is a scarcity of research on the relationship between COVID-19 and EI in a variety of political, economic, and socio-cultural contexts [12]. Similarly, the effect of age on EI is inconclusive, with a relatively even split between studies where age is not regarded as a significant determinant of business start-ups, and studies that find age to be an important driver behind starting a firm [9,35,37,47,48,49,50,51,52,53]. The same divergence can be observed in studies exploring the link between previous work experience and EI [5,9,35,47,72,73]. Despite the importance of understanding the tendencies for the self-employment of Gen Z in tourism and hospitality, there is a paucity of research into the unique characteristics of this generation, particularly in view of the COVID-19 pandemic [24]. The present research aims to address these gaps in the literature.

3. Countries in Transition

The term “countries in transition” refers to the formerly communist CEE countries, including the former Soviet Union [113,114,115,116,117], that are going through a difficult process of social, political, and economic change from a centrally planned economy to a market-based one [118]. This transition started following the fall of both the Berlin wall and the communist system in the late 1980’s. In the decades preceding the collapse of communism, private sector enterprise was constrained, constricted, impeded, suppressed, and even made illegal across CEE countries [118]. Now, 30 years after the onset of the transition, the free-market economy has surprisingly remained elusive in many, if not all, facets of CEE society [116].

In Croatia, for instance, between 2007 and 2019, the Travel and Tourism Competitiveness Index (TTCI) exhibited a negative trend in the following four pillars: business environment, human resources and the labor market, ground and port infrastructure, and cultural resources and business travel [119]. The negative tendencies in these four pillars are causes for concern for both Croatia’s economy in general and for tourism in particular. The business environment pillar is indicative of the overall entrepreneurship and investment climate, which then impacts other pillars, such as human resources and the labor market, ground and port infrastructure, and cultural resources and business travel. In that respect, a 2013 report on business, corruption, and crime in Croatia, prepared by the United Nations Office on Drugs and Crime (UNODC) and based on a survey of private businesses in Croatia, unequivocally reveals that corruption and other forms of crime by public officials are a major hindrance to entrepreneurship and investment [120]. Businesses in the building/construction and tourism/accommodation/food sectors were singled out as those most affected by corruption. Since Croatia’s tourism sector, in the pre-pandemic period, contributed almost 40% of the country’s export revenues and nearly 20% of GDP [17], the impact of corruption on the nation’s business environment is staggering.

In addition, based on a 2011 UNODC general population survey, ordinary Croatian citizens have experienced the same levels of corruption as their business counterparts [121]. In the aftermath of the aforementioned 2013 and 2011 UNODC reports, several members of the Croatian Parliament have publicized a number of corruption scandals totaling billions of euros and implicating the highest government officials, the Office of the State Attorney, and the mainstream media outlets [122]. Although corruption is a global phenomenon, Croatia’s ongoing high-level corruption has its roots in Yugoslav-era communism, which provides a unique context for this study. While post-1990 Germany, Poland, and almost all other ex-communist CEE countries enacted “lustration” and/or “de-communization” laws in one form or another, Croatia did not. Lustration and de-communization denote the screening of public officials to ascertain who has participated in human rights abuses perpetrated by the communist regime and/or collaborated with the Communist-era secret police [123,124]. To grasp the roots and the nature of Croatia’s everlasting economic and political climate, within which prospective entrepreneurs must operate, the following three examples illustrate the current state of affairs that can be described as the country’s communist legacy clad in crony capitalism.

In 2013, only three days before Croatia’s EU accession, the Croatian parliament passed a law stating that the European Arrest Warrant should apply only to crimes committed after 2002, an attempt to prevent the extradition of Zdravko Mustač and Josip Perković to Germany, where they were wanted for the 1983 brutal assassination of their compatriot Stjepan Đureković [125]. In communist ex-Yugoslavia, Mustač was the Head of the State Security Service (i.e., the UDBA or secret police, akin to the KGB in the former Soviet Union and the STASI in the former East Germany), while Perković was the Head of the UDBA’s Croatian branch in the then Yugoslav federation. The victim of the assassination was a former CEO of the state-owned INA oil company who had turned dissident and defected to Germany in 1982 with proof of high-level corruption involving funds from the INA and other state-owned companies. Thus, only after pressure from the European Commission, was the duo extradited to Germany in 2013, where, in 2016, both were given a life sentence. In 2019, they were transferred to Croatia, where they are currently serving the rest of their prison terms. However, upon their arrival, their prison sentences were reduced by a Croatian court. According to John R. Schindler, a professor at the U.S. Naval War College, the UDBA assassinated many more people in the West—the vast majority of them Croats—than the KGB, the STASI, and other secret police forces of the Soviet bloc combined [126]. He points to over 60 confirmed UDBA assassinations of Croats abroad.

A second example of joint corruption by the government, the State Attorney’s Office, and the media has come to light thanks to an investigation initiated by the European Public Prosecutor’s Office (EPPO) in Croatia, only a few months after it started operations in June of 2021. Acting on a report submitted by the European Anti-Fraud Office (OLAF), in November of 2021, EPPO’s investigation resulted in the apprehension of both the former Head of the Ministry of Regional Development and EU Funds (MRRFEU) and the Director of Croatia’s Central Finance and Contracting Agency (SAFU) for the crimes of trading in influence and the abuse of office and official authority, which occurred back in 2017 and 2018 [127]. At the time of the arrests, the heads of both the State Attorney’s Office of the Republic of Croatia (DORH) and its special Office for the Suppression of Corruption and Organized Crime (USKOK) admitted that after months of inquiries, collecting documents, and taking statements from some 30 witnesses in relation to the same case, they did not have enough to open an investigation and the USKOK closed the case [128]. Moreover, they denied that their mistakes and oversights were deliberate. Unsurprisingly for many Croatians, the State Attorney General (i.e., the Head of the DORH) remains in her position at the time of writing. Similarly, the State Attorney General reappointed the same person as the Head of the USKOK for a second four-year term [129]. Sadly, the investigative jurisdiction of the EU’s OLAF and EPPO offices is limited to the usage of EU funds in Croatia.

The most recent case of joint corruption occurred in 2022. Only after Croatia’s foreign-owned banks informed it of possible illegal transactions, the USKOK arrested five people suspected of reselling natural gas that belonged to the now partially state-owned INA oil company, causing €113 million in damages [130]. One of the alleged perpetrators, the head of the INA’s natural gas retail department, a mid-level manager, was a member of the ruling political party that remains in power. Despite being the largest formal corruption probe in Croatia to date, news updates about the case in the mainstream media are nonexistent.

As expected, sweeping corruption at both high and low levels of national and local governments has had a disastrous effect on Croatia’s TTCI human resources and the labor market pillar [119]. Specifically, according to the most recent 2021 census, Croatia’s population plummeted from 4.2 million in 2011 to 3.8 million in 2021, representing a loss of 400,000 people (10%) [131]. This decrease is attributed to a combination of low birth rate and emigration toward more prosperous EU countries, both of which were adversely affected by Croatia’s economic, institutional, and judiciary decay [132]. Due to depopulation, Croatia’s elementary and high school enrollment rates have taken a plunge, whereas the highly seasonal tourism industry is suffering from continuously increasing labor shortages, especially in regard to seasonal staff. Importantly, the evident exodus of Croatia’s young adults to other EU countries due to crony capitalism at home [132,133] naturally begs the question of whether those who remain are entrepreneur material.

4. Methodology

The sampling frame for this study comprised all of the tourism and hospitality students at five public universities in Croatia. Because college students were appropriate research subjects in this study [134], and obtaining a random sample of university students either within or across countries would have been very costly and time-consuming, this study used a voluntary response sample within a single country (i.e., Croatia), which is a non-probability sampling technique. Thus, since student e-mail addresses were unavailable, we requested the collaboration from fellow academics at the selected universities, who then posted a survey cover letter, along with a dedicated link to voluntary and anonymously complete the online questionnaire, on their internal student-teacher online class forum. Using a self-administered online questionnaire written in Croatian, 300 usable responses were collected through the Qualtrics software between 18 May and 26 June 2020.

The questionnaire comprised four sections (i.e., A, B, C, and D). To prevent respondent bias, the questions concerning EI were asked at the beginning of the survey, followed by the questions about psychological, experiential, contextual support, and crisis-related variables. Thus, Section A of the questionnaire measured respondents’ university affiliation, gender, and year of study (a proxy for age). Section B included a two-item measure of EI (i.e., I am seriously thinking about starting my own business and I will start my own business in the next 10 years), a one-item measure of the perceived strength of the COVID-19 crisis (i.e., the current economic crisis caused by the COVID-19 pandemic can be an obstacle to starting a new business), and a two-item measure of support from family and friends (e.g., if I decided to start a company, my close family would support that decision) [25]. Section C included a one-item measure of entrepreneurial disposition (i.e., I consider myself to be creative and full of initiative to start a business) [54,67]. Section D measured the participants’ length of work experience, whether they have a close family member or friend who is an entrepreneur (a proxy for role model) [25], and whether they have completed a class that contains the word entrepreneur or entrepreneurship in its official title during their current program of study (a proxy for university support) [35,135,136,137].

Although this parsimonious approach of employing one- and two-item scales in Sections B and C has its limitations, scholars find it a reliable and methodologically acceptable tactic to minimize respondent burden, reduce criterion contamination, and increase face validity [25,54,67,138,139,140,141,142,143,144,145]. All questions in Sections B and C were on a five-point Likert scale ranging from 1 (completely disagree) to 5 (completely agree). Questionnaire design followed the established survey guidelines [146,147] and was evaluated by two social science research experts. Since the instruments employed in this study have already been well validated by prior research in a similar context [25,35,54,67,135,136,137], and this study did not make substantial alterations to the original items, the questionnaire was deemed appropriate for data collection.

Descriptive statistics included a frequency analysis of demographic, experiential, and contextual support variables. The associations between variables (i.e., EI, support from family/friends, crisis severity, entrepreneurial disposition, and demographics) were analyzed using Pearson’s r correlation. Pearson’s r values were interpreted on the basis of the magnitude and direction of the relationship between variables, according to the following widely used criteria: r values <0.3 weak, 0.3–0.7 moderate, >0.7 strong [148]. Multiple regression was used to check for causality between a set of predictors (i.e., support from family/friends, perceived crisis severity, entrepreneurial disposition, and demographics) and the outcome variable (i.e., EI). The reliability of the two scales (i.e., EI and support from family/friends) was tested using the standardized coefficient alpha [149].

5. Results

5.1. Descriptive Statistics

Of the 300 respondents (i.e., tourism and hospitality students), 249 were female and 51 were male, and half of them (50%) were from the University of Split (

Table 1. Respondent profile.

Gender	N	%
Female	249	83.0
Male	51	17.0
Year of study
1st	60	20.0
2nd	48	16.0
3rd	88	29.3
4th	53	17.7
≥5th	51	17.0
University affiliation
University of Split	150	50.0
University of Rijeka	75	25.0
University of Zadar	52	17.3
University of Zagreb	20	6.7
Rijeka College	3	1.0
Work experience
None	20	6.7
<6 months	40	13.3
6–11 months	47	15.7
1–2 years	65	21.7
3 years	37	12.3
4 years	36	12.0
≥5 years	55	18.3
Role model
Yes	193	64.3
No	107	35.7
Entrepreneurship class
Yes	158	52.7
No	142	47.3

). While 29% were at the end of their 3rd year, 20% were freshmen, and just over 17% were in the first year of their graduate (i.e., master’s) degree. The majority (64%) had one or more years of work experience, and only 7% lacked any practical experience. Just over half of them (53%) had completed an entrepreneurship class during their studies thus far, and 64% indicated that they had a close family member or a friend who was an entrepreneur (i.e., a role model).

Table 2. Descriptive analysis.

Constructs/Variables and Associated Items	Mean 1	Standard Deviation	Standardized Cronbach’s α
Entrepreneurial Intentions (EI)			0.81
I am seriously thinking about starting my own business	3.16	1.224
I will start my own business in the next 10 years	3.35	1.125
Support by Family and Friends			0.71
If I decided to start a company, my close family would support that decision	4.39	0.924
If I decided to start a company, my friends would support that decision	4.51	0.756
Crisis Severity
The current economic crisis caused by the COVID-19 pandemic could be an obstacle to starting a new business	3.85	1.141
Entrepreneurial Disposition
I consider myself to be creative and full of initiative to start a business	3.70	0.965

¹ Scale from 1 (completely disagree) to 5 (completely agree).

presents respondents’ ratings of EI, perceived severity of the COVID-19 crisis, support from family and friends, and entrepreneurial disposition. Evidently, the intention to launch a business later (i.e., in the next 10 years) received a somewhat more favorable rating than the intent to start a new venture sooner (e.g., while at a university or soon after graduation). That said, 57% (M = 3.35) and 64% (M = 3.16) of students were unsure or unlikely to start a business in the next 10 years and soon after graduation, respectively. If they were to embark on a business venture, 84% (M = 4.39) and 89% (M = 4.51) of students expected strong support from family and friends, respectively. Additionally, 60% of the students perceived themselves as creative and full of initiative to start a business (M = 3.70). Finally, most respondents (67%, M = 3.85) agreed that the current economic crisis caused by the COVID-19 pandemic could impede a new business venture.

5.2. Inferential Statistics

The standardized Cronbach’s alpha values (0.81 and 0.71) indicate the acceptable reliability and internal consistency of the EI and family/friends support scales, respectively (Table 2) [150]. This study was conducted to explore the impact of a set of predictors (support from family/friends, perceived crisis severity, entrepreneurial disposition, university affiliation, gender, year of study, length of work experience, presence of a role model, and completion of an entrepreneurship class) on the intentions of Gen Z (i.e., tourism and hospitality students) towards starting a new business. In order to determine whether EIs are associated with support from family/friends, crisis severity, entrepreneurial disposition, and demographics, the data were analyzed using Pearson’s r correlation (

Table 3. Pearson’s Correlation.

	Entrepreneurial Intention (EI)
	EI 1 a		EI 2
	r	p	r	p
Gender	0.12 *	0.034	0.17 **	0.004
Year of study	−0.06	0.280	0.05	0.435
University affiliation	−0.10	0.093	−0.08	0.177
Work experience	0.07	0.264	0.18 **	0.002
Role model	−0.10	0.074	−0.18 **	0.002
Entrepreneurship class	−0.09	0.138	−0.08	0.192
Support by family	0.04	0.466	0.17 **	0.004
Support by friends	−0.01	0.869	0.05	0.412
Crisis severity	−0.07	0.205	−0.05	0.347
Entrepreneurial disposition	0.48 **	0.000	0.46 **	0.000
N	300

^a EI 1 = I am seriously thinking about starting my own business; EI 2 = I will start my own business in the next 10 years; * = p < 0.05; ** = p < 0.01.

).

The results reveal that EI1 (i.e., thinking about starting a business) has a weak positive correlation with gender (r = 0.12) and a moderate positive association with entrepreneurial disposition (r = 0.48). Furthermore, the results show that EI2 (i.e., intent to start a business in the next 10 years) has a weak positive correlation with gender (r = 0.17), length of work experience (r = 0.18), and support from family (r = 0.17), a weak negative association with the presence of a role model (r = −0.18), and a moderate positive correlation with entrepreneurial disposition (r = 0.46). Regarding gender, male tourism and hospitality students more often contemplate a business venture and are more likely to start a business in the next 10 years, as compared to their female counterparts. With regard to role models, students with a close family member or friend who is an entrepreneur are less likely to embark on a business venture in the next 10 years. That said, year of study, university affiliation, the completion of an entrepreneurship class, support from friends, and perceived severity of the COVID-19 crisis are not associated with either EI1 or EI2.

To check for multicollinearity,

Table 4. Zero-order correlations among regressors.

	(1) a	(2)	(3)d	(4)d	(5)d	(6)d	(7)d	(8)d	(9)d	(10)d	(11)d	(12)d	(13)d	(14)d	(15)d	(16)d	(17)d	(18)d	(19)d	(20)
(1)	1.000
(2)	−0.105 *	1.000
(3)d	−0.079	0.102 *	1.000
(4)d	−0.045	0.115 *	−0.218 ‡	1.000
(5)d	0.061	−0.197 ‡	−0.322 ‡	−0.281 ‡	1.000
(6)d	0.039	0.007	−0.232 ‡	−0.202 ‡	−0.298 ‡	1.000
(7)d	0.125 *	0.026	−0.058	0.000	−0.051	0.096 *	1.000
(8)d	−0.006	0.052	0.033	−0.018	0.073	−0.149 †	−0.577 ‡	1.000
(9)d	−0.124 *	−0.014	0.123 *	0.112 *	0.014	−0.097 *	−0.264 ‡	−0.458 ‡	1.000
(10)d	0.001	−0.098 *	−0.134 *	−0.117 *	−0.055	0.227 ‡	−0.154 †	−0.267 ‡	−0.122 *	1.000
(11)d	0.040	−0.038	0.004	0.004	0.116 *	−0.093	−0.005	−0.044	0.090	0.014 *	1.000
(12)d	−0.058	−0.098 *	0.134	−0.007	−0.084	−0.019	0.031	−0.027	0.054	−0.071	0.014 *	1.000
(13)d	−0.025	−0.062	−0.025 *	0.123 *	0.006	−0.053	−0.068	−0.039	0.079	0.052	−0.005	−0.105 *	1.000
(14)d	0.042	0.047	0.060	−0.063	0.004	−0.031	0.026	0.009	−0.076	0.069	0.024	−0.115 *	−0.169 †	1.000
(15)d	−0.057	0.011	0.020	0.035	0.034	−0.095	−0.061	0.040	−0.006	0.022	0.044	−0.141 †	−0.206 ‡	−0.227 ‡	1.000
(16)d	0.006	0.073	−0.010	−0.053	−0.041	0.092	0.018	0.010	−0.011	−0.019	−0.181 †	−0.100 *	−0.147 †	−0.162 †	−0.197 ‡	1.000
(17)d	0.023	−0.046	−0.031	−0.049	0.078	0.017	0.000	0.082	−0.088	−0.058	−0.024	−0.099 *	−0.145 †	−0.159 †	−0.194 ‡	−0.139 †	1.000
(18)d	0.046	0.110 *	−0.028	0.021	0.036	−0.002	0.092	0.007	−0.119 *	−0.024	−0.078	−0.052	0.026	−0.024	−0.115 *	0.025	0.018	1.000
(19)d	0.083	0.048	−0.394 ‡	−0.042	0.083	0.264 ‡	0.301 ‡	−0.280 ‡	−0.148 †	0.253 ‡	0.051	−0.041	−0.021	0.023	−0.101 *	0.010	0.001	0.061	1.000
(20)	−0.078	0.146 †	−0.114 *	0.109 *	−0.007	0.090	0.012	0.142	−0.095	−0.191 ‡	0.109 *	−0.019	−0.041	0.010	−0.048	−0.051	0.128 *	0.036	0.019	1.000

^a (1) = crisis severity, (2) = entrepreneurial disposition, (3) = first year of study, (4) = second year of study, (5) = third year of study, (6) = fourth year of study, (7) = Uni of Rijeka, (8) = Uni of Split, (9) = Uni of Zadar, (10) = Uni of Zagreb, (11) = female, (12) = workExp: none, (13) = workExp: <6 months, (14) = workExp: 6–11 months, (15) = workExp: 1–2 years, (16) = workExp: 3 years, (17) = workExp: 4 years, (18) = role model: yes, (19) = entrepreneurship class: yes, (20) = friends/family’s support; d = dummy variable; * = p < 0.05, † = p < 0.01, ‡ = p < 0.001.

reports zero-order correlations among regressors. Since correlation coefficients are smaller than 0.6, multicollinearity does not appear to be a severe issue [151,152]. However, the values of tolerance less than 0.10 and variance inflator factors (VIF) more than 10 suggest multicollinearity among three predictor variables (

Table 5. VIF and tolerance among regressors.

	VIF	Sqrt VIF	Tolerance	R2
(1) Crisis severity	1.07	1.03	0.9353	0.0647
(2) Entrepreneurial disposition	1.17	1.08	0.8547	0.1453
(3) First year of study (d)	2.07	1.44	0.4831	0.5169
(4) Second year of study (d)	1.79	1.34	0.5589	0.4411
(5) Third year of study (d)	2.07	1.44	0.4820	0.5180
(6) Fourth year of study (d)	1.78	1.33	0.5627	0.4373
(7) University of Rijeka (d)	21.09	4.59	0.0474	0.9526
(8) University of Split (d)	27.72	5.26	0.0361	0.9639
(9) University of Zadar (d)	16.89	4.11	0.0592	0.9408
(10) University of Zagreb (d)	7.67	2.77	0.1305	0.8695
(11) Female (d)	1.12	1.06	0.8909	0.1091
(12) Work Experience: none (d)	1.35	1.16	0.7409	0.2591
(13) Work Experience: <6 months (d)	1.58	1.26	0.6328	0.3672
(14) Work Experience: 6–11 months (d)	1.64	1.28	0.6080	0.3920
(15) Work Experience: 1–2 years (d)	1.85	1.36	0.5398	0.4602
(16) Work Experience: 3 years (d)	1.54	1.24	0.6482	0.3518
(17) Work Experience: 4 years (d)	1.54	1.24	0.6511	0.3489
(18) Role model: yes (d)	1.08	1.04	0.9224	0.0776
(19) Entrepreneurship class: yes (d)	1.51	1.23	0.6639	0.3361
(20) Family/friends’ support	1.18	1.09	0.8441	0.1559

d = dummy variable.

). Thus, these three highly correlated variables (i.e., University of Rijeka, University of Split, and University of Zadar) were removed from further analyses.

To check for causality between the set of predictors and the outcome variable, a multiple regression analysis was performed (

Table 6. Multiple regression.

Predictor	Output Variable
Variable	EI
Female (d)	−0.154 β** (0.145)
First year of study (d)	−0.010 (0.185)
Second year of study (d)	0.042 (0.187)
Third year of study (d)	0.059 (0.163)
Fourth year of study (d)	0.181 (0.181)
University of Zagreb (d)	0.019 (0.230)
Work Experience: none (d)	−0.140 * (0.242)
Work Experience: <6 months (d)	−0.157 * (0.192)
Work Experience: 6–11 months (d)	−0.040 (0.183)
Work Experience: 1–2 years (d)	−0.144 * (0.171)
Work Experience: 3 years (d)	−0.084 (0.196)
Work Experience: 4 years (d)	−0.201 ** (0.197)
Role model: yes (d)	0.066 (0.112)
Entrepreneurship class: yes (d)	0.053 (0.121)
Family/friends’ support	0.053 (0.121)
Crisis severity	−0.035 (0.047)
Entrepreneurial disposition	0.472 *** (0.058)
Adjusted R2	0.299
N	300

^β Standardized (Beta) coefficients, with standard errors reported in parentheses; d = dummy variable; * = p < 0.05; ** = p < 0.01; *** = p < 0.001.

). Results show that 29.9% of the variance can be accounted for by three predictors (i.e., entrepreneurship, gender, and length of work experience), collectively (F(17, 282) = 8.499, p = 0.000). Looking at the unique individual contributions of the predictors, the results show that entrepreneurial disposition positively predicts EI (β = 0.472, t = 9.074, p = 0.000). Furthermore, results also reveal that women (β = −0.154, t = −3.045, p = 0.003), those with no work experience (β = −0.140, t = −2.487, p = 0.013), those with less than six months of practical experience (β = −0.157, t = −2.588, p = 0.010), those with 1–2 years of work experience (β = −0.144, t = −2.196, p = 0.029), and those with 4 years of practical experience (β = −0.201, t = −3.385, p = 0.001) are also less likely to report EI. This suggests that tourism and hospitality students who perceive themselves as creative and full of initiative intend to launch a new business venture either soon after graduation or within the next 10 years. It also shows that female students are likely to be more hesitant towards starting a business than their male counterparts. In addition, students with no practical experience and those with one to two years, four years, or less than six months of work experience are likely to be more apprehensive about putting their entrepreneurial skills to the test, as compared to the students with five or more years of practical experience. Ultimately, students’ EIs are not affected by their perceptions of the COVID-19 crisis severity, age (i.e., year of study), university affiliation, family/friends’ support, the presence of role models, or the completion of an entrepreneurship class.

6. Discussion

6.1. Theoretical Implications

Drawing upon CDT, the TPB, the EEM, and previous research on EI, the purpose of the present study was to investigate the impact of a set of predictors (perceived crisis severity, entrepreneurial disposition, support from family/friends, university affiliation, gender, year of study, length of work experience, presence of a role model, and completion of an entrepreneurship class) on the intentions of Gen Z tourism and hospitality students towards starting a new business. Theoretically, this study has contributed to filling gaps in the existing research on entrepreneurship during major crises [4,11], on the EIs of Gen Z [135], on the role of perceived crisis severity in EIs, and on the state of EIs in mono-industrial (i.e., dominated by one industry) crony capitalist ex-communist economies. Based on the regression analysis results, entrepreneurial disposition, the length of work experience, and gender are directly related to EI. Specifically, entrepreneurial disposition is directly and positively related to EI, which is in line with previous research [54,67]. The identified positive influence of entrepreneurial disposition on EI indicates the possibility of generalizing the results as well as the necessity of including entrepreneurial disposition in theoretical frameworks of the drivers behind EI. From the perspective of the TPB and the EEM, this finding is important because it confirms that creativity and the ability to self-start especially foster the development of EI. Similar to [47] and contrary to [9], this study finds that students with longer work experience have a greater propensity to set up their own firm.

In terms of gender, this study finds that women, in comparison with men, have a lower inclination towards entrepreneurship. Although this outcome mirrors past findings [12,41], its interpretation calls for a more cautious approach due to this study’s unique context—i.e., the COVID-19 pandemic. There are two key reasons women exhibit lower EI then men. Traditionally, scholars have attributed women’s lower EI to economic and evolutionary reasons. According to this age-old view, women are less inclined to become entrepreneurs than men because women believe that they are lacking in male stereotypical traits (e.g., aggression, high risk taking, etc.) [45]. In addition to this well-documented view, a more recent school of thought suggests that gender differences in risk taking are amplified even further under stress [153]. While women tend to decrease risk-taking behaviors under stress, men tend to increase them. Because of their over-representation in the hardest-hit, non-teleworkable sectors such as travel, tourism, and hospitality, women bear the brunt of layoffs and income loss to a greater degree than men [154]. Since this study’s sample comprises tourism and hospitality students, the majority of which were female, it seems plausible that women’s lower EIs observed in this study may be, at least in part, a short-term byproduct of their strategies for coping with the pandemic. Thus, the effect of stress on gender differences in EI needs further examination.

Furthermore, the regression output indicates that perceived crisis severity does not hamper Gen Z’s intent to start a business. This result contradicts a previous finding [25] and the basic assumption of CDT. In a study of Italian (Gen Y) students’ EIs, Arrighetti et al. [25] found that the perception of the economic crisis had a negative and highly significant impact on the likelihood of starting a business. Contextually, their study vastly differs from the present study. Whereas their study’s focus was on the economic crisis, this research deals with the global pandemic. Interestingly, in their study they consistently use the phrase “economic crisis”, never actually disclosing its name and duration. For the sake of clarity, their research is set during two back-to-back crises—i.e., the 2007–2008 Global Financial Crisis intertwined with the European debt crisis that lasted from 2009 until the mid to late 2010s. Italy was one of the EU countries hit hardest during the crises, plagued with dramatically high youth (i.e., 15–24-year-olds) unemployment rates that doubled from 20% in 2007 to 40% in 2015 [155]. In addition to the soaring unemployment, Italy fared the worst among the EU countries in terms of the NEET (i.e., not in employment, education, or training) indicator, and among young Italian women, this already unfavorable score was much more significantly pronounced. Unfortunately, Arrighetti et al. did not report the gender distribution of their sample, thus preventing further comparison with the present study. As stated earlier, this study’s finding that perceived crisis severity does not affect EI also contradicts the basic assumption of CDT. According to this assumption, when facing a severe crisis, people evaluate the pros and cons of each coping strategy. In order to avoid stress from potential business failure and loss of resources, individuals are more likely to select a response that conserves their resources (i.e., money, time, energy, strength, emotional suffering, and general wellbeing) [30].

The observed contradiction between the present study on one hand and both the research by Arrighetti et al. and CDT on the other hand could perhaps be explained by the timing of the data collection. In contrast to their research, which took place nine years into the more than a decade-long consecutive crises, this study was conducted in the first six months of the coronavirus pandemic that reached Europe in early 2020. Specifically, the data for this study were collected in Croatia between 18 May and 26 June 2020; the epidemiological situation in Croatia progressively worsened only in October 2020. The timing of this study’s survey coincided with the period marked with low coronavirus infection rates in Croatia, very light COVID-19 countermeasures, and the period when Croatia was opening up for the summer tourism season, which is the nation’s economic lifeline [18]. Therefore, it is possible that, at the time of data collection, the pandemic had not left such a negative imprint on the Croatian students’ psyche, in comparison to their Italian counterparts, who endured serious economic hardships for almost a decade. As a result, the relationship between perceived crisis severity and EI requires further examination. With respect to other predictors included in this study’s analysis, the findings partially contrast the previous literature [5,9,10,25,35,47,57,72,73,74,75,76,77,78,79,80,87,88,89]. Accordingly, support from family/friends, university affiliation, year of study, the presence of a role model, and the completion of an entrepreneurship class do not affect the propensity to set up a firm in this study.

6.2. Practical Implications

From a practical perspective, the fact that 36% of this study’s sample is somewhat or very seriously thinking about launching their own business, with an additional 38% being undecided, suggests that that there is room for more entrepreneurship content in university curricula. Additionally, the fact that, at the time of the survey, almost half of the respondents had not taken an entrepreneurship class suggests that this important subject is not being taught during the freshman year, but rather later in the study program. It also implies that, by the time students actually have the opportunity to take an entrepreneurship class, they have already taken a large number of classes without much, if any, entrepreneurial content. Thus, an entrepreneurship class should be among the first-year foundation/core classes. The goal of such early exposure to an entrepreneurship class would be to provide students with the necessary tools for the subsequent continuous application and development of entrepreneurial skills during much of their remaining journey towards graduation. This study’s findings also suggest that colleges should increase their focus on nurturing entrepreneurial disposition—i.e., fostering students’ confidence in their own creativity and autonomy. Moreover, in an attempt to narrow the observed gap in women’s vs. men’s EIs, class instructors may want to encourage mixed-gender groups in collaborative assignments [156]. If men are overly daring and women too cautious in stressful situations, as suggested in this and prior research, then men and women working together may forge wiser risk-taking decisions then either gender alone.

On a related note, this study also found that over one third of the respondents did not have a close family member or a friend who was an entrepreneur. This discovery indicates that universities should fill this void by creating a shadowing program that matches students with entrepreneurs to gain insight into business careers. In this way, students will have an opportunity to learn first-hand what an entrepreneur does, how they launched their business project, and what they should be doing now to enter the world of entrepreneurship once they graduate. Overall, these findings are important for universities, which should place a greater emphasis on entrepreneurial courses and career counseling. Furthermore, policymakers can use these findings to develop policy guidelines to encourage universities to become more involved in the development of nascent entrepreneurs.

6.3. Limitations and Future Research

Much like other research, this study has certain limitations that open new research avenues. First, the sampling method, which involved using a voluntary response sample within a single country (Croatia), is a limitation as it increases the risk of bias and limits the generalizability of the findings. While future research should try to employ a random sampling method, achieving this goal is often quite difficult due to the obvious financial and practical constraints. Second, this research relied on self-reported data, which are subject to potential bias and can affect the accuracy and validity of the results. One strategy for minimizing the potential bias of self-reported data is to use anonymous surveys, as participants may be more honest and forthcoming in their responses if they are assured that their answers are anonymous. Other methods include using clear and straightforward questions to avoid confusion, as well as employing validated instruments to improve the reliability and validity of the data collected. As explained in the methodology section, in this study we collected data anonymously using instruments that have already been well validated by prior research in a similar context.

Third, since the intensity of COVID-19 restrictions and consequences varied among countries and across time, the contexts of both COVID-19 and EIs are constantly evolving. As mentioned earlier, the data for this study were collected during a period of both low incidence and prevalence of the coronavirus in Croatia [18]. Hence, the students’ feelings of stress and perceptions of severity of the COVID-19 crisis and its impact on EI may have been different in late 2020, when the government enacted tight lockdown measures due to record-high levels of new infections. Consequently, future research could focus on measuring the perceptions of crisis severity during full lockdowns and evaluating their impact on intent to engage in inherently stressful entrepreneurial behaviors.

Fourth, this research employed a cross-sectional design, which limited the study’s conclusions to a specific period during the pandemic. For the same reason, it is not possible to develop causal inferences [136,157]. Thus, future studies may also include the post-pandemic perspective, which could offer additional insights on the entrepreneurship domain and bring us closer to establishing true cause and effect relationships. Fifth, this study collected data on respondents’ entrepreneurial intentions via a self-completed questionnaire, which is a data collection method known to be a source of social desirability bias [158]. Since research shows that there may be a gap between entrepreneurial intentions and entrepreneurial behavior [159], one way of overcoming this challenge would be to conduct a follow-up study with the same group of respondents in order to observe their actual entrepreneurial behavior.

Sixth, the sample comprised undergraduate and graduate students from five public universities in a single field of study (i.e., tourism and hospitality) and in one country. In order to compare this study’s sample with Croatia’s overall student population, ideally one would need data on the general distribution of university students in Croatia. Unfortunately, such data are unavailable. However, if many years of teaching tourism and hospitality students at a university level have taught me anything, it is that female students significantly outnumber male students, which is generally in line with the sample composition observed in this study. Therefore, while this study’s findings apply to some Gen Zs, the findings herein cannot be generalized to the entire population of Gen Z students in Croatia or elsewhere. Additionally, because peoples’ values, opinions, and attitudes can change as they progress through different life stages [160], a longitudinal study of Gen Z is necessary. Seventh, our study was conducted on a single generational cohort. It would also be beneficial to investigate these variables in additional generational cohorts, particularly those who grew up during the COVID-19 pandemic, Generation Alpha (i.e., Gen Alpha), to see how this major crisis affected their resilience, as well as their values and attitudes. Similarly, future research should compare the variables used in this study between Gen Z and Gen Alpha (i.e., anyone born between 2010 2024), to observe which changes remain, and which changes tend to fade out across time.

Eighth, although this study’s setting (i.e., a country with an entrenched communist heritage clad in crony capitalism) represents a specific situational factor that can influence EI, this research did not measure this potentially influential variable. Consequently, the impact of inheriting the previous political and socio-economic plexus on EI, especially in countries that are still undergoing a system change, is unknown. As a result, future research in transition economies could consider specific situational factors influencing EI, such as culture and institutional frameworks, which differ from developed countries. Ninth, in addition to the variables used in this and previous studies on EI, other factors, such as the “grease the wheels” vs. “sand the wheels” views of corruption [161], could be linked to the Gen Z’s intent to launch a business in a crony capitalist economy. Will young, would-be entrepreneurs operating within socio-economic contexts characterized by a high level of corruption end up interpreting corruption as a viable and acceptable practice through which they can overcome the difficulties induced by institutional dimensions of corruption [162]? Additionally, are Gen Z’s EIs in a crony capitalist environment driven more by necessity or opportunity [111,112]? Therefore, other differences among members of Gen Z may exist, but they were not explored in our study.