Abstract
Background: Generation Z (Gen Z) is subject to more frequent and quick changes in the workplace compared to previous generations (such as the Fourth Industrial Revolution [4IR] and the coronavirus disease 2019 [COVID-19] pandemic). Considering the increasing unemployment rate among recent graduates, Gen Z must adopt a proactive and inventive strategy to enhance their desirability as potential employees for organisations.
Aim: The main objective of this research is to determine the predictors of career success for Gen Z from a socioeconomic perspective.
Setting: The target population for the study involved bursary beneficiaries from Sector Education Training Authorities (SETA) of South Africa, Wholesale & Retail SETA (W&RSETA) and Chemical SETA (CHIETA).
Method: A quantitative research approach was followed with data collected from a stratified sample of GenZ individuals who are SETA bursary holders (N = 320). The data were analysed using Statistical Package for the Social Sciences (SPSS).
Results: The findings show that most participants were at a socioeconomic disadvantage during their formation years. No significant relationships were found between proactive career behaviours (i.e., career and mentor engagement) and career success (i.e., career adaptability and career employability) based on the socioeconomic status of the participants.
Conclusion: Facilitating the professional development of Gen Z persons from historically marginalised backgrounds in the workplace requires a comprehensive strategy that tackles educational, social and institutional obstacles.
Contribution: This article provides new knowledge on how research on Gen Z should include co-variates to navigate career outcomes more successfully.
Keywords: career success; employability; Generation Z; Gen Z; proactive behaviours; socioeconomic status.
Introduction
The millennial generation, the subject of extensive analysis and discourse, has reached adulthood and scholarly attention towards it is gradually diminishing (Johnson & Sveen 2020). The focus on the millennial generation has now switched to a new group of workers who are starting to have a significant influence in the workplace – Generation Z (Gen Z) (Hampton & Welsh 2019). They are the most apprehensive generation to date when entering the workforce (Shellenbarger 2019). Gen Z cohorts are entering the workforce amid the challenges posed by the Fourth Industrial Revolution (4IR) and global health pandemics. These circumstances significantly affect economic, technological, social and political conditions, which in turn directly influence labour markets and work environments (Parola 2020).
What sets Gen Z apart is their lack of experience living without the fundamental force of the 4IR, namely the Internet. This has made them adept at navigating the digital world, reliant on technology and quickly embracing artificial intelligence (AI). The Internet was established in 1995 and is considered the earliest member of Gen Z (Goh & Lee 2018; Grow & Yang 2018; Seemiller & Grace 2017). Given the swift advancements in technology and the employment market, it is anticipated that career transfers would occur often (Moon & Hong 2023). Ivaldi, Scaratti and Fregnan (2021) proposed a set of high-level abilities that individuals will require to sustain their careers in a 4IR context. These abilities include technical skills (such as coding and information technology [IT] security), methodological skills (such as decision-making and creativity), social skills (such as networking and knowledge transfer) and personal skills (such as working under pressure and flexibility). In addition, early career employability necessitates acquiring supplementary transferable soft skills and behaviours, rather than relying solely on subject-specific technical knowledge (Papadopoulou 2020).
Gen Z’s arrival in the workforce coincided with the adoption of the 4IR, making them a generation worth studying. Customised career development strategies may be needed to attract, involve and retain them. Nevertheless, the workplaces that Gen Z employees are joining need to adapt more quickly to align with their expectations (Grow & Yang 2018). Traditional hierarchical and sequential career paths, where employees rely passively on the organisation to guide their careers, are becoming obsolete because of globalised economies, rapid societal changes and technological advancements. Changes have made the transition from organisation-led to employee-led career management easier (Peng, Song & Yu 2021; Strauss, Griffen & Parker 2012) and the alteration of work values and behaviours (Rahim & Sati-Raida 2016). Parker and Collins (2010) argue that being proactive in the workplace has become increasingly important in non-linear, decentralised and boundaryless work environments. Amid unpredictability and careers without limitations, individuals must embrace specific proactive professional practices that will result in favourable career outcomes and achievements (Taber & Blankemeyer 2015). Protean and boundaryless careers are the two career orientations that have been popular in career development literature (Gubler, Arnold & Coombs 2014).
The main objective of this research was to determine the predictors of the career success of Gen Z employees from a socioeconomic perspective. Gen Z was considered an appropriate topic for this study, as they are the cohort transitioning from universities into early career development programmes in the workplace. Furthermore, this study is driven by the observation that the unemployment rate among those with advanced degrees has increased twice in the last 20 years (MacGinty 2024). Therefore, graduates need to develop employability skills and personal traits and should have knowledge of labour market conditions to obtain their first job, retain it and successfully secure another employment (Heyler & Lee 2014; Suleman 2018). According to Chan (2017), careers have evolved to be self-directed and adaptable. To succeed in one’s job, it is necessary to go beyond simply setting goals.
This research explores the interrelationships between three variables: Gen Z (based on socioeconomic status), career success and proactive career behaviours. Concerning career success, Vos, Clippeleer and Dewilde (2009) divide career success into subjective and objective elements. The latter entails tangible outcomes, that is, promotion. The former is characterised by intangible outcomes, that is, perceptions of employability. The reported study focussed on subjective career success during the early stages of career development. Hence, early career success was intentionally coined and used for this study as a descriptive term instead of career success, which is a general term. The third and mediatory construct of the study was proactive career behaviour. Proactive career behaviour involves individuals ‘proactively taking charge to anticipate opportunities and overcome risks along their careers’ (Groenendaal et al. 2021:313). Proactive career behaviours are self-initiated, change-inducing and future-focussed (Smale et al. 2019). For the reported research, proactive career behaviours were operationalised through career and mentorship engagement. Early career self-awareness, knowledge of the future of work and engagement in certain proactive career behaviours are necessary for career readiness and success (Chan 2017). This further exacerbates the widespread concern of undergraduate students and graduates not being introduced early enough to career concepts such as employability (Clements & Kamau 2018) and proactive career behaviours (Chan 2017).
This research aims to address the following main research question: What are the predictors of the early career success of Gen Z from a socioeconomic perspective?
More specifically, this research explored the following research questions:
- Is there a significant relationship between Gen Z socioeconomic status during formative years and career success (i.e., career adaptability; career employability) during early career stages?
- Is there a significant relationship between Gen Z socioeconomic status and proactive behaviour (i.e., career engagement; career mentor engagement) during early career stages?
- Does proactive behaviour mediate the relationship between Gen Z and their career success during early career stages based on socioeconomic status?
Literature review
Generation theory
The generation theory posits that individuals who come of age simultaneously encounter comparable socioeconomic circumstances and historical events, leading to shared attitudes and behaviours that manifest in the workplace (Andrade & Westover 2018). According to the authors, the oldest individuals belonging to Gen Z were born in 1995, while the youngest were born in 2009. This implies that by 2024, the oldest members of this generation will be 29 years old and likely in the initial phases of their professional journeys. Knapp, Weber and Moellenkamp (2017) argue that Gen Z might be considered the initial authentic digital natives. This generation will present novel difficulties, expectations, unique abilities and opportunities that companies must adapt to. The entrance of Gen Z into the workforce occurs during intricate changes in workplace culture, partially triggered by the departure of retired Baby Boomers (Goh & Lee 2018). The arrival of Gen Z in the workforce signifies a significant change in how work is done, which may create difficulties for managers and supervisors (Benítez-Márquez et al. 2022; Igel & Urquhart 2012). Gen Z individuals prefer short-term contracts and self-employment in a gig economy, which enables them to work simultaneously for or with several organisations (Seemiller & Grace 2017).
Categorisation of a generation based on different stages of life rather than birth dates was introduced to understand the behaviour patterns and expectations of people with similar socioeconomic background (Karashchuk et al. 2020). Hence, this study integrates the factors of Gen Z and socioeconomic background to ascertain the level of achievement in one’s profession.
Generation Z in the context of socioeconomic status
The influence of socioeconomic factors on generations
The behaviours and similarities of each generation vary across different regions, influenced by cultural and national contexts (Knapp et al. 2017), as well as socio-cultural environmental factors that shape a generation’s expectations, personalities and values during their formative years and continue into adulthood (Macky, Gardner & Forsyth 2008). Therefore, several individuals belonging to the above generations may demonstrate different values and behaviours (Crumpacker & Crumpacker 2007).
Inglehart (1971) indicates that the physical and economic security individuals experience throughout their formative years is directly linked to their socioeconomic status and value preferences later in life. Dalton (1977) argues that generational cohorts are primarily moulded by economic circumstances and prosperity from ages 10 to 20. Among these factors, financial conditions and prosperity at age 10 significantly impact shaping value priorities. The education level of the generational cohort was the second most influential factor in determining value prioritising. The education levels obtained throughout the influential years of a generational cohort directly determine the value priorities of that cohort. Hsieh and Huang (2014) state a correlation between family’s socioeconomic position and the educational and professional prospects available to individuals. Individuals from high socioeconomic statuses are typically related to having access to occupational role models, quality educational resources and active family support. Conversely, those from poor family socioeconomic positions are more likely to experience limited parental involvement in their child’s career development activities. There are just a small number of role models available and the quality of school systems could be a lot higher (Hsieh & Huang 2014).
This study specifically examined three socioeconomic statuses: impoverished (low class), average (middle class) and prosperous (high class). Prior research has defined socioeconomic status as parents’ occupational status and educational levels, as Hsieh and Huang (2014) demonstrated. Nevertheless, the investigation carried out by Hsieh and Huang (2014) revealed that the socioeconomic status of the family was influenced by the occupational and educational status of the male parent, whereas the status of the female parent had no such impact. This suggests that the father’s occupation and educational background significantly shaped the family’s socioeconomic status.
Career success
Wilhelm, Hirschi and Schlapfer (2023) argue that to achieve both subjective and objective career success in today’s work environment, individuals must actively take control of their careers through career self-management. This can be accomplished by consistently engaging in the following career behaviours: (1) establishing their social networks, (2) utilising existing social networks, (3) managing how others perceive them, (4) taking advantage of opportunities for personal development, (5) setting goals and planning their implementation, (6) actively seeking out and exploring career-related experiences and (7) demonstrating a willingness to relocate for career advancement. These approaches highlight the fundamental principles of the boundaryless and protean career theories. A boundaryless career attitude removes the thrill of having a stable, long-term, predictable, physical and psychological work agreement with a single business. The subscribers of this service actively anticipate and embrace change. They proactively create and maintain strong, sustainable relationships with internal and external organisational networks (Gubler et al. 2014; Lochab & Nath 2019). This strategy aligns effectively with Gen Z’s inclination towards short-term work-related desires. Members of Gen Z tend to switch employment more frequently than previous generations and are projected to have more than four employers throughout their careers (Knapp et al. 2017). The protean career orientation is a concept that builds upon the idea of a boundaryless career, as proposed by Zhu and Wang in 2022. Sullivan and Baruch (2009) define protean career-oriented individuals as those who exhibit adaptability, place a high value on personal freedom, possess a strong desire for ongoing learning and prioritise intrinsic rewards. Wells et al. (2018) found that, like their Gen X parents, individuals from Gen Z exhibit strong work ethic. However, they do not support the idea that professional advancement should be based on age or the duration of employment with a particular organisation. They prioritise immediate promotion. As previously stated in this article, career success is defined as the capacity to adapt to one’s career and maintain employment.
Career adaptability
Savickas (1997) defines professional adaptability as:
[T]he willingness to handle expected responsibilities related to preparing for and engaging in a job and unforeseen modifications resulting from changes in employment and work situations. (p. 254)
Zacher, Ambiel and Noronha (2015) and Fiori, Bollmann and Rossier (2015) offer a concise and direct explanation of career adaptability. The first perspective defines career adaptability as a valuable resource that aids employees in effectively navigating career changes and challenges. Conversely, the second position characterises career adaptability as the capacity to successfully handle one’s career development and challenges. Creed, Fallon and Hood (2009) define career adaptability as a self-regulatory process where individuals strategically solve job issues by engaging with their surroundings. The term ‘hierarchical’ refers to a design that allows individuals to adapt to career-related person-environment situations through an agentic process. Individuals who possess a high level of professional flexibility demonstrate the ability to anticipate and prepare for future events (worry) effectively, exhibit a strong inclination towards exploring many alternatives (curiosity), possess the capacity to make informed choices and judgements (control), and show a determined effort with a positive mindset (confidence) (Cai, Tian & Wang 2023). Consequently, individuals with high career adaptability are likelier to excel in these behaviours.
Employability
Perceived employability pertains to an individual’s confidence in their capacity to obtain and maintain a job in the long term, both within and outside of an organisation. This confidence is based on their conviction that they have learned adequate skills, made sufficient connections and developed a feasible career plan. Anderson and Tomlinson (2020) argue that while the literature has clearly defined the tangible and intangible skills and competencies needed for early career-level employability and transitioning into the workplace from a student’s point of view, the same cannot be said from an employer’s perspective. Employability is considered a crucial aspect of effective early or adolescent career planning, and a fundamental skill during career transitions caused by changes in the workplace. It is considered essential to successful career preparation, a basic competency and valuable in work environment changes. According to the authors, the employability of a person currently working differs from that of someone presently unemployed. The former emphasises employment retention, while the latter emphasises job acquisition or entry into the job market (Bernston, Sverke & Marklund 2006). In this study, the term ‘employability’ specifically pertains to career employability, a more detailed concept closely associated with professional advancement. Van der Heijden et al. (2022) highlighted the importance of proactive investments in employability to attain career success. Nevertheless, they also stress that the efficacy of such investment can be optimised with the participation of various support networks, such as family, friends, employers and supervisors. Sou et al. (2022) arrived at a similar finding, stating that individuals with established social capital are more likely to engage in proactive career practices that advance their careers. Therefore, it is essential to educate university students on prioritising and enhancing their social capital.
Proactive career behaviours
Proactive behaviour can be defined as taking initiative to improve existing situations or create new ones, according to Crant (2000). Proactive career habits refer to persons actively assuming responsibility for anticipating opportunities and mitigating risks throughout their careers (Groenendaal et al. 2020). The effectiveness of behaviours is enhanced when they are initiated and controlled by oneself, have the potential to induce change and are focussed on future outcomes (Smale et al. 2019; Jiang et al. 2022; Akkermans & Hirschi 2022; Hirschi & Freund 2014). These behaviours should be intentional, forward-thinking and intended to establish a relationship with future outcomes that will be advantageous to the individual and their surroundings rather than being solely focussed on immediate gains (Rahim & Sati-Raida 2016; Strauss et al. 2012; Vos et al. 2009). This study defined and measured proactive professional practices by assessing career and mentorship engagement.
Career engagement
Career involvement refers to how an individual actively and purposefully develops their career through various work-related actions and behaviours (Hirschi, Freund & Herrmann 2014). Job engagement pertains to an individual’s mental state, sense of self, preparedness and attitudes, with a specific emphasis on job-related behaviours that have a favourable impact on career growth (Hirschi et al. 2014; Nilforooshan & Salimi 2016). Career engagement serves as the connection between school and the workplace, as well as other phases of career development. Nevertheless, the attention given to career involvement in studies involving students currently needs to be more developed (Aryani et al. 2021). Amid the transition from school to work, active involvement in one’s profession can significantly impact success level, particularly in periods of economic instability (Sou et al. 2022).
Mentor engagement
Mentor engagement, as defined by Brodeur et al. (2015), pertains to the level of emotional commitment a mentor exhibits in a mentoring relationship. Engaged mentors enhance the effectiveness of a mentoring relationship by providing support, actively listening and demonstrating empathy towards the growth and progress of their mentees. Singh, Bains and Vinnicombe (2002) argue that mentors should actively work towards offering their mentees assistance in advancing their careers. Similarly, Smith, Howard and Harrington (2005) emphasise that mentors play the role of career sponsors for their mentees. According to Forbrig and Kuper (2021), seeking a mentor is identified as a form of proactive career behaviour. A mentoring relationship should be founded upon trust, exchanging information, providing resources, establishing expectations, professional assistance and resolving problems through collaborative efforts between a seasoned mentor and an aspiring mentee (Hudson 2016). Tsai and Helsel (2016) argue that a mentee should take a proactive approach in actively pursuing, developing, sustaining and taking ownership of a mentor-mentee relationship, as they are the ones who benefit the most from it. To fully capitalise on the advantages of a mentoring relationship, mentees must acquire the skill of effectively overseeing their mentors (Hudson 2016; Maynard 2000). Over time, a mentee who comprehends the responsibilities of both the mentee and the mentor in the mentor-mentee interaction will develop into a proficient mentor in the future (Tsai & Helsel 2016). However, there is a lack of structured mentoring initiatives in businesses, particularly for newly arrived individuals in the organisation (Wang et al. 2022). In this study, the phrase ‘mentor engagement’ is expanded to ‘career mentor engagement’ to provide a more detailed description and highlight the requirement for the mentor to provide mentorship linked explicitly to careers.
A hypothesised model for the study
Based on the preceding the following hypothesised model is proposed for the study (see Figure 1). The socioeconomic background of Gen Z plays a pivotal role in achieving their career success. Therefore, we hypothesise that socioeconomic status is significantly related to career engagement (H1) and mentorship engagement (H2), which are the dimensions of proactive behaviour. We further hypothesise that a significant relationship will exist between career success dimensions, career adaptability (H3) and career employability (H4). We predict that career engagement (H5) and career mentorship (H6) will mediate the relationship between socioeconomic status, career adaptability and career employability. Lastly, we predict that career engagement (H7) and career mentorship (H8) will mediate the relationship between socioeconomic status, career adaptability and career employability.
Research design
Research approach
A quantitative research approach was followed using surveys to collect the data. Quantitative research was deemed most suitable as the objective of the research was to test the relationships between Gen Z (controlling for socioeconomic status), career success and proactive behaviours. The study was cross-sectional in that the data were collected at one point (see Field 2019). In alignment with the quantitative research approach, this study espouses the positivist philosophical worldview. This philosophical belief emanates from the natural sciences and is characterised by the making and testing of theoretical claims (Leavy 2017).
Research method
Sampling
The target population for the study involved bursary beneficiaries from Sector Education Training Authorities (SETA) of South Africa, Wholesale & Retail SETA (W&RSETA) and Chemical SETA (CHIETA). In alignment with the study objectives, probability sampling techniques were suitable for this study. Two probability sampling techniques were combined: cluster and stratified sampling, implying multistage sampling to randomly select participants from the population of interest (Edmonds & Kennedy 2017). For the reported study, the first cluster was made up of 2078 bursary programme beneficiaries that were provided by the two SETAs. The second cluster consisted of 1511 active bursary programme beneficiaries who were contactable. The third cluster was characterised by active bursary programme beneficiaries, classified under Gen Z as defined by age (born between 1995 and 2013), and those between the ages of 18 and 27 in 2022. After the sampling unit was established, a stratified sampling method, in which the population was divided into homogeneous (Edmonds & Kennedy 2017) and mutually exclusive (Rea & Parker 2014) subgroups or strata with shared characteristics (Leavy 2017) was incorporated to divide the cluster into strata primarily based on residential location during formative years and secondarily, on economic status during formative years (N = 320).
The participants in this study consisted of 113 (35.3%) males and 207 (64.7%) females. A total of 97 (30.3%) participants indicated that they used to live in a rural location during their formative years (age range between 10 and 20 years). A total of 129 (40.3%) participants resided in townships, and 26.9% were in urban locations. A total of 27 participants (8.4%) classified their socioeconomic status as poor during their formative years, while 21.9% classified themselves as below average, 60.6 indicated that they were average, 7.2% considered themselves above average, and 1.9% stated that they were affluent during their formative years.
Research procedure
Permission to execute the research was obtained from the SETAs. The surveys were distributed electronically to the participants. The purpose of the study was explained to the participants, and informed consent was obtained. The participants could withdraw at any time without any adverse consequences. The surveys were always dealt with anonymously and were confidential.
Measuring instruments
The data collection instruments are discussed next.
Socioeconomic status
The socioeconomic status of Gen Z cohorts was classified by the socioeconomic status of the participants during their formative years. The participants had three socioeconomic statuses: poor, average and affluent.
Proactive career behaviour
Proactive career behaviour was operationalised by career engagement and career mentor engagement. Hence, the measurement scales used were aligned with the two operational variables.
Career engagement was measured using the Career Engagement Scale developed by Hirschi et al. (2014). The scale consists of nine items, rated using a 5-point Likert scale (1 = Strongly disagree; 5 = Strongly agree). An example of an item of the scale is: ‘In the past six months, I have voluntarily participated in further education, training, or other events to support my career’. In previous studies, the scale yielded Cronbach’s alpha coefficients of 0.94 among a sample of German university students (Hirschi & Freund 2014).
The factor analyses for Career engagement (Measure of sampling adequacy–Kaiser-Meyer-Olkin [MSA–KMO]) (MSA–KMO = 0.88; p ≤ 0.001; variance explained = 49.86%) in this study resulted in two factors, labelled Internal Career Engagement (mean = 3.745; α = 0.82) and External Career Engagement (α = 0.77). Both scales showed acceptable reliability of α ≥ 0.70 (see Field 2019).
The College Student Mentoring Scale (CSMS), conceptualised and initially validated by Crisp (2009), was used to measure career mentor engagement. The original scale consisted of 25 items that were split into the following four subscales: psychological and emotional support (8 items and a Cronbach alpha of 0.91); degree and career support (6 items and a Cronbach’s alpha of 0.90); academic subject knowledge support (5 items and a Cronbach’s alpha of 0.88) and the existence of a role model (6 items and a Cronbach’s alpha of 0.85). Participants were requested to specify the degree to which, while in tertiary, they had a person in their life who offered each of them mentoring experience regardless of who provided the mentorship, that is, parent; faculty; counsellor; friend among others, using a 5-point Likert scale with the following calibration: 1 (Strongly disagree) to 5 (Strongly agree). Sample items of the instrument were, ‘While in tertiary, I have had someone in my life who discusses the implications of my degree of choice’ and ‘While in tertiary, I have had someone who gives me emotional support’. Chong and Thi (2021) found acceptable reliabilities of 0.98 for the scale.
The factor analyses for Career mentor engagement (MSA–KMO = 0.97; p ≤ 0.00; variance explained = 67.23%) in this study resulted in three factors, labelled Psychological and Emotional Support (α = 0.95), Role Model and Advisor (α = 0.95) and Degree and Career Support (α = 0.91). All scales showed acceptable reliability of α ≥ 0.70 (see Field 2019).
Early career success
Early career success was operationalised by career adaptability and career employability. Hence, the measurement scales used were aligned with the two operational variables. The Career Adapt-Abilities (CAAS) International Form 2.0, developed and validated by Savickas and Porfeli (2011), was used to measure career adaptability. The instrument consisted of 24 items split into four subscales of concern (6 items), control (6 items), curiosity (6 items) and confidence (6 items). Participants had to rate how strongly they have developed certain abilities using a 5-point Likert scale with the following calibration: 1 (Not strong) to 5 (Strongest). Sample items of the instrument were ‘Performing tasks efficiently’ and ‘Counting on myself’. The instrument obtained a total reliability score of 0.94 in a South African study (Maree 2012).
The factor analyses for Career Adaptability (MSA–KMO = 0.92; p ≤ 0.00; variance explained = 54.35%) in this study resulted in four factors. Factor 1 represented Self-control (α = 0.88) and factor 2 represented Confidence (α = 0.90), the same factor named in the theoretical scale. Factor 3 represented Mindfulness (α = 0.84), while factor 4 represented Curiosity (α = 0.85). All scales showed acceptable reliability of α ≥ 0.70 (see Field 2019). A subsequent second-order factor analysis (MSA–KMO = 0.83; p ≤ 0.00; variance explained = 62.74%) resulted in one factor, namely career adaptability.
Employability was measured using the Self-perceived Employability Scale developed by Rothwell, Herbert and Rothwell (2008) and further validated by Rothwell, Jewell and Hardie (2009). The 5-point Likert scale (1 = Strongly disagree; 5 = Strongly agree) yielded a Cronbach’s alpha coefficient of 0.84 (Rothwell et al. 2009). A sample of an item of the scale is: ‘I achieve high grades to my studies’.
The factor analyses for Employability (MSA–KMO = 0.85; p ≤ 0.00; variance explained = 52.01%) in this study resulted in four factors. Factor 1 represented the State of the External Labour Market (α = 0.85), factor 2 represented Learning Institution Brand Reputation (α = 0.81), factor 3 represented Self-confidence and Awareness (α = 0.75), while factor 4 represented Academic Performance (α = 0.65). Both scales showed acceptable reliability of α ≥ 0.70 (see Field 2019). A subsequent second-order factor analysis (MSA–KMO = 0.70; p ≤ 0.00; variance explained = 52.04%) resulted in one factor, namely Employability.
Data analyses
The data were analysed using Statistical Package for the Social Sciences (SPSS) (SPSS Inc. 2023). Descriptive statistics (i.e., frequencies, means, skewness, kurtosis, standard deviations) were applied. Exploratory factor analyses were used to determine the underlying factor structure of the measurements. Cronbach’s alpha coefficients were α ≥ 0.70 (see Field 2019). Pearson correlation analyses and multiple regression analyses were applied to test for the magnitude of the relationships between the variables.
Ethical considerations
Ethical approval was obtained from the University of Johannesburg (Ethics number IPPM-2021-583).
Results
The results of the Pearson correlation analyses are reported in Table 1.
The results in Table 1 show no significant relationship between socioeconomic dimensions and career engagement, career mentorship, career adaptation and employability. Career engagement was significantly related to career mentorship (medium effect), career adaptation (medium effect) and employability. Career mentorship was significantly associated with career adaption (medium effect) and employability. Career adaptation was significantly related to employability. These results reject Hypotheses 1 to 4 that the socioeconomic status of Gen Z is related substantially to Proactive behaviours (i.e., career engagement; career mentoring) and career success (i.e., career adaptability and career employability).
The results of the mediation analyses are reported next.
Career engagement mediating the relationship between socioeconomic status and career adaptability
The results of the mediation analyses between career engagement and Gen Z socioeconomic status and career adaptability are reported in Table 2.
| TABLE 2: Mediation analyses – Socio-economic status, career engagement and career adaptability. |
Path c was examined first to determine whether there was a link between the socioeconomic status and career adaptability variables by regressing career adaptability on socioeconomic status. The unstandardised regression coefficient (β = –0.002) associated with the effect of socioeconomic status on career adaptability was insignificant (p < 0.05) with p = 0.09738. Therefore, Path c was insignificant and thus failed Step 1 of mediation testing. The second step entailed examining whether socioeconomic status was related to career engagement (the hypothesised mediator) by regressing the latter on socioeconomic status. The unstandardised regression coefficient (β = 0.04) associated with this relationship was insignificant (p < 0.05) with p = 0.4258. Therefore, the requirements for Step 2 were not met because Path a was insignificant. To establish whether career engagement was related to adaptability, the latter was regressed simultaneously on both career engagement and socioeconomic status (Step 3). The regression coefficient associated with the relationship between career engagement and career adaptability (controlling for socioeconomic status) was significant (β = 0.41, p < 0.05) with p = 0.0000. Therefore, the requirements for Step 3 were fulfilled, and Path b was deemed significant. The fourth and last step of mediation testing included the examination of the relationship between socioeconomic status and career adaptability while controlling for career engagement. The unstandardised regression coefficient (β = –0.02) associated with socioeconomic status and career adaptability while controlling for career engagement was insignificant (p < 0.05) with p = 0.6673. Therefore, Path c’ was negligible and thus failed Step 4 of mediation testing. Based on the results, career engagement did not mediate the relationship between socioeconomic status and career adaptability. Based on the aforementioned results, Hypothesis 5 is rejected that career engagement mediates the relationship between GenZ socioeconomic status and career adaptability.
The results of the mediation analyses between career engagement between Gen Z socioeconomic status and career employability are reported next.
Career engagement mediating the relationship between socioeconomic status and career employability
The results of the mediation of career engagement between socioeconomic status and career employability are reported in Table 3.
| TABLE 3: Mediation analyses – Socio-economic status, career engagement, and career employability. |
Path c was examined first to find out whether there was a link between socioeconomic status and career employability variables by regressing career employability on socioeconomic status. The unstandardised regression coefficient (β = 0.07) associated with the effect of socioeconomic status on career employability was insignificant (p < 0.05) with p = 0.1108. Therefore, Path c was insignificant and thus failed Step 1 of mediation testing. The second step entailed the examination of whether socioeconomic status was related to career engagement (the hypothesised mediator) by regression of the latter on socioeconomic status. The unstandardised regression coefficient (β = 0.034) associated with this relationship was insignificant (p < 0.05) with p = 0.4258. Therefore, the requirements for Step 2 were not met because Path a was insignificant. To establish whether career engagement was related to career employability, the latter was regressed simultaneously on both career engagement and socioeconomic status (Step 3). The regression coefficient associated with the association between career engagement and career employability (controlling for socioeconomic status) was significant (β = 0.19, p < 0.05) with p = 0.0001. Therefore, the requirements for Step 3 were fulfilled and Path b was deemed significant. The fourth and last step of mediation testing included examining the link between socioeconomic status and career employability while controlling for career engagement. The unstandardised regression coefficient (β = –0.06) associated with socioeconomic status and career employability while controlling for career engagement was insignificant (p < 0.05) with p = 0.1470. Therefore, Path c’ was insignificant and thus failed Step 4 of mediation testing. Based on the abovementioned results, career engagement failed to mediate the relationship between socioeconomic status and career employability. Based on the these results, Hypothesis 6 is rejected that mentor engagement mediates the relationship between Gen Z socioeconomic status and career employability.
The results of the mediation of mentor engagement between socioeconomic status and career employability are reported next.
Results: Mediation analyses between socioeconomic status, mentor engagement and career adaptability
The results of the mediation of mentor engagement between socioeconomic status and career adaptability are reported in Table 4.
| TABLE 4: Socio-economic status, mentor engagement, and career adaptability. |
Path c was examined first to find out whether there was a link between the socioeconomic status and career adaptability variables by regressing career adaptability on socioeconomic status. The unstandardised regression coefficient (β = –0.002) associated with the effect of socioeconomic status on career adaptability was insignificant (p < 0.05) with p = 0.09738. Therefore, Path c was insignificant and thus failed Step 1 of mediation testing. The second step entailed the examination of whether socioeconomic status was related to career mentor engagement (the hypothesised mediator) by regressing the latter on socioeconomic status. The unstandardised regression coefficient (β = 0.0636) associated with this relationship was insignificant (p < 0.05) with p = 0.2844. Therefore, the requirements for Step 2 still needed to be met because Path a was insignificant. To establish whether career mentor engagement was related to adaptability, the latter was regressed simultaneously on both career mentor engagement and socioeconomic status (Step 3). The regression coefficient associated with the connection between career mentor engagement and career adaptability (controlling for socioeconomic status) was significant (β = 0.24, p < 0.05) with p = 0.0000. Therefore, the requirements for Step 3 were fulfilled and Path b was deemed significant. The fourth and last step of mediation testing included the examination of the relationship socioeconomic status and career adaptability while controlling for career mentor engagement. The unstandardised regression coefficient (β = –0.02) associated with socioeconomic status and career adaptability while controlling for career mentor engagement was insignificant (p < 0.05) with p = 0.6881. Therefore, Path c’ was insignificant and thus failed Step 4 of mediation testing. Hence, career mentor engagement failed to mediate the relationship between socioeconomic status and career adaptability. Based on the aforementioned results, Hypothesis 7, which is that career engagement mediates the relationship between socioeconomic status and career adaptability, is rejected.
The results of the mediation analyses of mentor engagement between socioeconomic status and career employability are reported next.
Results: Mediation analyses of mentor engagement between socioeconomic status and career employability
The results of mediation analyses of mentor engagement between socioeconomic status and career employability are reported in Table 5.
| TABLE 5: Mediation analyses – Socio-economic status, mentor engagement and career employability. |
Path c was examined first to prove whether there was a connection between socioeconomic status and career employability variables by regressing career employability on socioeconomic status. The unstandardised regression coefficient (β = 0.07) associated with the effect of socioeconomic status on career employability was insignificant (p < 0.05) with p = 0.1108. Therefore, Path c was insignificant and thus failed Step 1 of mediation testing. The second step entailed examining whether socioeconomic status was related to career mentor engagement (the hypothesised mediator) by regressing the latter on socioeconomic status. The unstandardised regression coefficient (β = 0.06) associated with this relationship was insignificant (p < 0.05) with p = 0.2844. Therefore, the requirements for Step 2 were not met because Path a was insignificant. To establish whether career mentor engagement was related to career employability, the latter was regressed simultaneously on both career mentor engagement and socioeconomic status (Step 3). The regression coefficient associated with the connection between career mentor engagement and career employability (controlling for socioeconomic status) was significant (β = 0.12, p < 0.05) with p = 0.0018. Therefore, the requirements for Step 3 were fulfilled and Path b was deemed significant. The fourth and last step of mediation testing included the examination of the connection between socioeconomic status and career employability while controlling for career mentor engagement. The unstandardised regression coefficient (β = –0.06) associated with socioeconomic status and career employability while controlling for career mentor engagement was insignificant (p < 0.05) with p = 0.1538. Therefore, Path c’ was insignificant and thus failed Step 4 of mediation testing. The insignificance of Path c, a, and c’ meant that the minimum requirements for mediation were not met. Hence, career mentor engagement failed to mediate the relationship between socioeconomic status and career employability. Based on the preceding results, Hypothesis 8, that mentor engagement mediates the relationship between socioeconomic status and career employability, is rejected.
Discussion
The primary aim of this study was to identify the factors that influence the career success of Gen Z, focussing on their socioeconomic condition. The motivation for this study stems from the observation that Gen Z is subject to more frequent and quick changes in the workplace compared to previous generations (such as the 4IR and the COVID-19 pandemic). Considering the increasing unemployment rate among recent graduates, Gen Z must adopt a proactive and inventive strategy to enhance their desirability as potential employees for organisations. Considering this viewpoint, examining proactive work behaviours, such as actively engaging in career development and seeking mentorship, is beneficial as a potential indicator of career success. This includes factors such as career flexibility and career employability while considering socioeconomic position. In this study, socioeconomic status refers to the participants’ socioeconomic status during their early developmental years. We adopted the stance proposed by Strauss and Howe (1991), which posits that a succinct categorisation of generations should consider life stages and vital societal functions rather than solely emphasising birth dates.
The study’s findings indicated no statistically significant relationship between socioeconomic characteristics and proactive career practices, such as career and mentoring engagement and career success, including career adaptability and employability. The results contradict the findings of Hsieh and Huang (2014), who suggest that a family’s socioeconomic standing can provide individuals with access to educational options and career advice. These authors also acknowledge the significance of parental support in shaping the career development of young individuals. This variable should have been accounted for in this study. It is essential to mention that a tiny percentage (< 10%) of the participants in this study had a socioeconomic position above the norm during their early years. Most participants in this study likely needed access to professional coaching during their early years, which resulted in a lack of proactive practices that could enhance their job performance.
The study’s findings did not provide evidence for the role of proactive work behaviours in mediating the relationship between socioeconomic level and career success among Gen Z individuals. Once again, these outcomes may be ascribed to the absence of proper mentorship that individuals encountered during their crucial developmental period, which fails to equip them adequately for a professional vocation. Furthermore, according to Smale et al. (2019), proactive behaviour needs to be undertaken by oneself to guarantee favourable future results, such as increased employability. During adolescence, the concept of employability is already considered and seen as a crucial aspect (Douglass and Duffy 2015; Monteiro & Almeida 2015). Therefore, the lack of various support networks, such as family, is crucial in establishing the basis for actively investing in employability and achieving success in one’s job (Van der Heijden et al. 2022).
Practical implications
The results of this study support the importance of prioritising the comprehension and efficient management of Gen Z talent to prosper in the future work environment. Their technological proficiency and emphasis on individual development pose both difficulties and prospects. Conforming to these expectations can result in a more dynamic, innovative and engaged workforce, eventually leading to long-term success for the organisation. Facilitating the professional development of Gen Z persons from historically marginalised backgrounds in the workplace requires a comprehensive strategy that tackles educational, social and institutional obstacles. To promote fair and balanced career advancement, organisations must adopt complete approaches such as inclusive policies within the workplace, strong mentorship initiatives and ongoing chances for professional growth.
Limitations and recommendations
There were certain limitations in this study. Adopting a cross-sectional research methodology prevented the researchers from making causal inferences over an extended period. The research only targeted a specific cohort of Gen Z individuals from SETAs. The sample might be extended to encompass Gen Z individuals from additional SETAs to facilitate comparisons. This study solely employed socioeconomic status as a covariate. Subsequent research endeavours may incorporate additional factors, such as mentorship assistance (e.g. from parents or schools), that can be amalgamated with socioeconomic status. Finally, this study was unbiased, and as a result, it is conducive to further investigation through follow-up interviews to delve deeper into the findings.
Conclusion
The career paths of Gen Z employees are heavily influenced by their socioeconomic status, which determines their access to crucial opportunities, resources and networks necessary for success. Individuals from higher socioeconomic status frequently have advantages such as superior educational resources, expert career advice and financial security. These advantages can result in opportunities for internships, high-quality training and valuable professional networks, all of which contribute to upward social mobility. In contrast, persons from lower socioeconomic backgrounds in Gen Z may encounter obstacles such as restricted educational and professional development access, a smaller network of industry connections and financial limitations that hinder their ability to engage in their careers. These discrepancies can lead to a slower progression in one’s career and restricted employment opportunities, therefore continuing the cycle of inequity. Gaining a comprehensive understanding of these dynamics is essential to develop fair workplace policies and support systems that effectively tackle these disparities, thereby fostering an environment where all Gen Z employees can succeed regardless of their socioeconomic status.
Acknowledgements
This article is partially based on the first author’s thesis of the PhD Degree in Human Resource Development at the University of Johannesburg, South Africa, with supervisors with supervisors Prof. N. Barkhuizen and Dr M. Magau. The thesis still need to be awarded at the time of publication of this article.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
D.M. wrote the initial concept article based on their Masters study. E.N.B. and M.M. were the supervisors of the study and provided editorial inputs.
Funding information
The Wholesale and Retail SETA (W&RSETA) Leadership Chair at University of Johannesburg, funded the study.
Data availability
The data that support the findings of this study are available on request from the corresponding author, D.M.
Disclaimer
The views and opinions expressed in this article are those of the authors and are the product of professional research. The article does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.
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