Predictors of employee burnout among frontline bank staff in South Africa: a multi-theoretical approach Open Access

Employee burnout has emerged as a pervasive issue in high-pressure service industries, with the financial sector—and banking in particular—being especially vulnerable due to the relentless pace, stringent regulatory scrutiny, and mounting performance pressures (Bresler and Visser, 2021). Recognised by the World Health Organization (2019) as a work-related phenomenon, burnout negatively impacts both employee well-being and broader organisational performance. In South Africa, this challenge is further compounded by profound structural inequalities. According to the World Bank (2023), South Africa remains one of the most unequal societies globally, and these disparities significantly exacerbate employee burnout through a web of socio-economic and workplace stressors.

For many banking employees, financial stress begins outside the workplace, driven by high household reliance ratios and intergenerational financial responsibilities—commonly referred to as “black tax”—which have been shown to predict emotional exhaustion (Mashego and Barkhuizen, 2021). These macro-level inequalities are reflected within organisations themselves. Race and gender discrepancies continue to characterise the South African banking sector, where women and historically marginalised racial groups encounter limited advancement opportunities and workplace micro-aggressions, contributing to feelings of depersonalisation and professional inefficacy (Motsa and Themane, 2020). Additionally, macroeconomic stressors such as persistent unemployment and post-pandemic volatility have intensified client distress, placing front-line bank employees under even greater pressure as they serve increasingly anxious and financially burdened customers (Motsa and Themane, 2020).

Burnout is a significant issue in the financial sector, particularly among frontline employees, who face high levels of stress due to tight deadlines, demanding customers, and performance targets. This occupational stress often leads to chronic fatigue, emotional exhaustion, and negative attitudes toward work, life, and clients (Valente et al., 2018; Zablah et al., 2012). Service quality, which is critical to banking performance, relies heavily on the motivation and satisfaction of frontline employees (Biswakarma and Gnawali, 2020; Kappagoda, 2012). However, unclear job expectations, dysfunctional workplace dynamics, and inadequate support systems aggravate burnout and lead to higher employee resignation rates (Hills, 2018; Business Tech, 2021).

South Africa's banking sector, as part of an emerging market economy, faces unique challenges, including economic instability, high unemployment, and inequality. Rapid digitalization and restructuring efforts have increased productivity but added pressure on employees, who often struggle to adapt to these changes (Hasan and Kashif, 2020; Kulkarni, 2006). Burnout among frontline employees contributes to declining job satisfaction, poor health, and higher resignation rates, as seen in major banks like Nedbank and Standard Bank, which experienced employment declines between 2017 and 2019 (Business Tech, 2021).

Unlike studies in Western economies where burnout in the banking sector is relatively well documented, there is limited empirical evidence from South Africa. Existing African studies suggest that employees in the region face unique stressors, such as cultural expectations, under resourcing and digital adaptation pressures (Ndlovu and Mofokeng, 2021; Nxumalo and Setati, 2022), Furthermore, restructuring automatation and retrenchments have added layers of uncertainty and workload (Hyz and Kalandatsis, 2021). Thus, a sector-specific investigation into burnout predictors is timely and necessary.

While predictors of burnout such as job demands, workload, and work-life imbalance are widely documented in Western and Asian banking contexts (e.g. Kappagoda, 2012; Kulkarni, 2006; Zhang et al., 2024), limited empirical work has examined these antecedents in South Africa's banking sector. The few available local studies (e.g. Ndlovu and Mofokeng, 2021; Nxumalo and Setati, 2022) identify stressors such as digitalisation and emotional labour but do not focus specifically on frontline staff, who are most exposed to customer pressures and regulatory performance targets. Moreover, South Africa presents a unique socio-cultural context—including structural inequality and obligations such as “black tax”—that may interact with organisational factors in ways not captured in studies from other regions.

This study therefore addresses a key gap by testing whether established predictors of burnout (job demands, work-life imbalance, work environment, and areas of work-life) also explain burnout among frontline banking staff in South Africa. In doing so, it responds to calls for more evidence from emerging markets (Bresler and Visser, 2021) and provides insights into whether contextual factors alter the strength or significance of traditional burnout predictors. Importantly, the unexpected finding that work environment does not predict burnout contributes novel evidence that challenges prior research and calls for further investigation.

Burnout is generally defined through three interconnected dimensions: emotional exhaustion, cynicism (or depersonalisation), and reduced personal accomplishment (Maslach et al., 2001). Emotional exhaustion reflects feelings of being emotionally overstretched and depleted. Cynicism establishes an aloof or negative attitude toward the job or clients, while reduced personal accomplishment involves feelings of incompetence or lack of achievement. These components are highly interrelated, forming a cycle where one dimension reinforces the others (Maslach and Leiter, 2021; Edú-Valsania et al., 2022).

Burnout is a complex phenomenon shaped by a confluence of structural, psychological, and relational dynamics. In high-pressure and inequality-laden environments like South Africa's banking sector, a single theoretical lens is inadequate for capturing its multifaceted causes. Therefore, this study draws upon eight complementary theories, each of which illuminates distinct antecedents and predictors of burnout. These theoretical lenses form the basis for the study's conceptual framework and hypotheses and provide a foundation for examining the extent to which predictors validated in other contexts hold true for South African frontline banking staff.

The JD-R model (Demerouti et al., 2001; Bakker and Demerouti, 2007) posits that burnout arises when job demands—such as long hours, emotional labour, or performance pressure—exceed the personal or organisational resources available to the employee. In the South African banking context, structural stressors such as staff shortages, digitisation, and compliance burdens contribute to this imbalance. Frontline employees bear the brunt of these demands without always receiving adequate administrative or psychosocial support.

COR theory (Hobfoll, 1989; Hobfoll et al., 2018) emphasises that individuals strive to acquire and retain resources (e.g. time, emotional energy, support) and experience stress when these are threatened or lost. In post-pandemic banking environments, retrenchments, digital transformation, and continuous restructuring have triggered resource loss spirals, creating a sense of insecurity and cumulative stress. This theory reinforces the predictive role of workload and insufficient support in employee burnout.

Social Exchange Theory (Blau, 1964; Cropanzano and Mitchell, 2005) frames burnout as a breakdown in reciprocal organisational relationships. In South Africa's historically racialised corporate structures, employees from previously disadvantaged backgrounds may perceive limited access to promotion, recognition, or influence as violations of implicit psychological contracts. Such perceptions of organisational injustice lead to emotional withdrawal, cynicism, and ultimately burnout.

Bandura's (1997) Self-Efficacy Theory underscores the importance of perceived ability to perform one's job. In a rapidly digitising banking sector, employees—particularly older staff—may feel overwhelmed or underprepared. Where digital upskilling is inadequate, this erosion of self-efficacy leads to disengagement, helplessness, and burnout. This is especially salient for frontline staff navigating customer systems without sufficient technological support.

Maslow's (1943) theory suggests burnout may result when basic psychological needs go unmet. In the South African context, the theory must be adapted to reflect collectivist norms. Here, belongingness needs—such as fulfilling family obligations or maintaining community status—may override personal self-actualisation. Employees who fail to meet these socio-cultural expectations may experience guilt, emotional fatigue, and psychological strain, contributing to burnout.

The Work-Home Resources Model (Bakker et al., 2019) expands on JD-R theory by highlighting how work demands deplete home resources, and vice versa. Many respondents in the 31–40 age group—often with caregiving responsibilities—struggled to maintain equilibrium between personal and professional life. Role overload, compounded by “black tax,” accelerates resource depletion and emotional exhaustion, making work-life imbalance a potent driver of burnout.

Work-Family Conflict Theory (Greenhaus and Beutell, 1985) further supports the role of dual-role conflict in predicting burnout. When time and energy are divided between job performance and family caregiving, conflict arises, especially in socio-economically strained households. In the banking sector, employees with children or dependents are especially vulnerable to inter-role strain, confirming the predictive strength of work-life conflict as a burnout antecedent.

Finally, Organisational Culture Theory (Schaufeli and Enzmann, 1998) and the Areas of Worklife Model (Leiter and Maslach, 2004) contextualise burnout as a result of deep-seated organisational dysfunction. Toxic cultures characterised by poor communication, micro-management, or lack of fairness exacerbate burnout risk. The Areas of Worklife Model adds that burnout also stems from misalignment between the employee and the organisation in six domains: workload, control, reward, community, fairness, and values. In this study, mismatches in workload and recognition were particularly salient, especially among enterprise bankers who lacked administrative support.

This theoretical integration provides a comprehensive lens for understanding burnout and offers a robust foundation for the study's hypotheses. It not only synthesises global models with South Africa's unique socio-cultural realities but also guides the empirical analysis of predictors such as job demands, work-life imbalance, work environment, and work-life domains.

Although burnout has been widely studied in Western and Asian contexts, research in African banking remains relatively limited. In Europe and Asia, organisational culture, workload, and work-life conflict have consistently emerged as strong predictors of burnout (Kulkarni, 2006; Kappagoda, 2012; Biswakarma and Gnawali, 2020; Zhang et al., 2024). By contrast, African studies are fewer and often highlight additional context-specific stressors. For example, Ndlovu and Mofokeng (2021) found that digitalisation pressures and limited managerial support drive burnout in South African banks, while Nxumalo and Setati (2022) identified emotional labour and cultural role conflict as significant contributors. Hyz and Kalandatsis (2021) further showed how restructuring and retrenchments intensified uncertainty and workload. However, these studies seldom isolate frontline staff, who are most exposed to client interactions, regulatory monitoring, and sales pressures. This gap motivates the present study.

Beyond the workplace, socio-economic inequality amplifies these stressors. Employees are often expected to financially support extended families—referred to as “black tax”—while managing demanding jobs, contributing to chronic exhaustion (Mashego and Barkhuizen, 2021). South Africa's extreme Gini coefficient also reflects systemic disparities that extend into organisational hierarchies, reinforcing perceptions of injustice and exclusion (Commission for Employment Equity, 2023). These contextual issues are particularly salient in the banking sector, where employees interface with distressed clients and are frequently monitored for performance against strict metrics (Motsa and Themane, 2020).

Burnout among frontline banking employees in South Africa is shaped by a convergence of workplace stressors and broader socio-cultural obligations. This section outlines the four main predictors examined in this study, grounding each in relevant theoretical and empirical literature.

High job demands, including excessive workload, emotional labour, customer aggression, and performance pressures, are among the most established predictors of burnout. Research in Asian banking contexts (Kulkarni, 2006; Kappagoda, 2012) and European service industries (Zablah et al., 2012) consistently demonstrates the strain imposed by prolonged working hours and customer-facing demands. Studies in Nepal also confirm that workload strongly predicts burnout (Biswakarma and Gnawali, 2020). In South Africa, Nxumalo and Setati (2022) note that outdated systems and digitalisation exacerbate workload burdens. Yet, most of these studies aggregate banking employees, without distinguishing frontline workers. It is therefore uncertain whether job demands exert the same intensity of effect on frontline employees in South Africa's banks, who are uniquely positioned at the intersection of client and organisational pressures.

Work-life imbalance, defined as persistent conflict between personal responsibilities and professional obligations, has long been linked to burnout (Greenhaus and Beutell, 1985; Van Dick et al., 2021). In Western settings, studies show that work-family conflict consistently predicts emotional exhaustion (Zhang et al., 2024). African research extends this by noting the compounding role of cultural obligations. For example, Ndlovu and Mofokeng (2021) emphasise how caregiving and long commuting times exacerbate imbalance, while Mashego and Barkhuizen (2021) highlight the financial strain of “black tax.” However, there remains limited evidence on how these socio-cultural obligations interact with professional stressors for frontline employees, who often work long hours under strict monitoring. Testing this relationship in South Africa's banking sector helps to contextualise global theories of work-life conflict within an emerging market setting.

Toxic organisational environments, characterised by micromanagement, poor communication, and perceived unfairness, are often cited as significant drivers of burnout in Western and Asian contexts (Schaufeli and Enzmann, 1998; Kappagoda, 2012; Biswakarma and Gnawali, 2020). Evidence from Sri Lanka and Nepal suggests that organisational environment factors sometimes outweigh individual-level stressors (Kappagoda, 2012). In South Africa, however, findings are mixed. Mkhize and Moletsane (2022) argue that post-apartheid workplace cultures continue to foster burnout, while Ndlovu and Mofokeng (2021) found managerial support moderates these risks. The inconsistent evidence raises the question of whether organisational environment is a significant predictor in South African frontline banking. This study empirically tests that assumption.

Beyond the workplace, broader social, economic, and cultural dynamics also shape burnout. International research often treats these indirectly as part of work-family conflict (Greenhaus and Beutell, 1985), but South African studies emphasise their salience. Mashego and Barkhuizen (2021) show how “black tax” obligations drain employees' resources, while national statistics confirm the broader stress of persistent inequality (World Bank, 2023). These unique socio-economic obligations may interact with professional demands in ways underexplored in international literature. By explicitly testing work-life dynamics as a predictor, this study contributes to contextualising burnout in South Africa's frontline banking sector.

In sum, while predictors such as job demands and work-life imbalance are consistently validated in Western and Asian studies, their relevance in African contexts, particularly among frontline banking staff, remains underexplored. Furthermore, socio-cultural realities such as inequality and black tax are seldom incorporated into burnout models. This study fills these gaps by empirically testing whether established predictors operate similarly in South Africa's frontline banking sector, thereby extending global burnout theory into an emerging market setting. Table 1 links the hypothesis to the theoretical framework.

The study employed a quantitative research design. Quantitative research approaches have an impartial method of directing research in which understanding is demonstrated by scientific methods, rather than by feelings, opinions, values, or personal interpretations. A leading commercial bank was used in the study. Due to the limited resources, the population of this study only covered branches in the Eastern and Western Cape provinces. In general, the population of this study is comprised of frontline employees in the bank's different departments which include administrators, sales support transaction bankers, relationship executives, credit analysts, area and regional managers, and employees in commercial asset finance, investments, and merchant services.

To select a sample, this study employed the convenience sampling method which is classified under the non-probability sampling technique. Convenience sampling technique is often used in qualitative research but is also applicable in quantitative studies, the participants of the study are selected based on the convenience of the researcher (Stratton, 2021). This sampling technique encounters motivation bias as respondents can be motivated to participate in the study depending on their interests in the research topic, a wish to express a certain disgruntled viewpoint, or any desire to support specific opinions (Kumar, 2011). Despite the limitations of this sampling method, convenience sampling is commonly used because it is not costly, not as time-consuming as compared to other sampling strategies, has no need for a sampling frame, is simplistic, and guarantees the inclusion of the type of people required in the sample (Stratton, 2021). Furthermore, the selected sample for this study was considered to be heterogeneous with the advantages of providing a diverse racial group and mixed gender. The sampling technique was adopted primarily because it is easier for the researcher to access the sample population in facilitating the collection of data. In addition to convenience, it is easier to select a sample that exhibits similar characteristics guided by these sampling techniques which in this study are frontline employees in the banking sector.

The sample size of 81 respondents meets the minimum threshold for multiple regression analysis, which typically requires 15–20 observations per predictor variable (Brooks, 2019). With four predictors in the model, a sample of 60–80 is acceptable for maintaining statistical power. Although the study aimed to collect 150 responses, a 54% response rate (n = 81) was achieved. This is considered sufficient for internal validity and is consistent with guidelines by Mugenda and Mugenda (2003), who suggest a 50% response rate is acceptable in organisational research. Nevertheless, this is acknowledged as a limitation with implications for generalisability.

Data were collected through self-administered questionnaire surveys which were sent electronically to the subjects of the study. The respondents were given a maximum period of 5 weeks to return the questionnaires. This provided the respondents adequate time to participate in this study as they could complete the questionnaire at their convenience. The questionnaire was divided into three sections. The first section measured participants' levels of burnout. The second section of the questionnaire measured the various factors that could contribute to employee burnout, while the last section covered biographical and work-related information and demographic variables, such as age, gender, length of tenure, etc.

Employee burnout was measured using the Maslach Burnout Inventory – General Survey which can be used within any occupation (Schaufeli et al., 1996). The inventory consisted of 22 questions and measured the three dimensions of burnout, namely emotional exhaustion, cynicism, and feelings of reduced personal accomplishment/efficacy. The MBI-GS is a self-administered questionnaire that consists of 16 items evaluated using a Likert frequency scale that ranges from 1 to 7, divided into three subscales connected to burnout level; namely emotional exhaustion (5 items), cynicism (5 items), and personal efficacy (6 items) (Gutierrez-Martínez et al., 2021). High scores on the emotional exhaustion and cynicism subscales indicate higher work-related burnout, while low scores on the personal efficacy subscale suggest work-related burnout.

The various factors that could contribute to burnout were measured using the Job-demands Resources (JD-R) model, the Work Environment Scale (WES), and the Areas of work-life scale (AWS). It is suggested by the JD-R model that a combination of high job demands and low job resources can result in a high-stress work environment that may eventually lead to enduring burnout. The model consists of 22 questions and measures the job demands concerning job resources. The Work Environment Scale (WES) measures the work environment and job satisfaction and consists of 25 questions. The Areas of work-life (AWS) identifies six key areas of the work environment as most relevant to the relationships people develop with their work namely, workload, control, reward and recognition, community, fairness, and values. The AWS measures employees' perceptions of their work environments in a sample of frontline business bank employees within a South African bank.

Data were analysed using descriptive statistics, correlation analysis, and multiple linear regression. The regression model was used to assess the strength and significance of the relationship between the dependent variable (employee burnout) and four independent variables (job demands, work-life imbalance, work environment, and areas of work-life). The regression technique was appropriate given the study's aim to identify predictors (antecedents) of burnout among frontline banking employees. The regression equation is expressed below;

Where $yit$ is a dependent variable (⁠$JobBurnout$ $xit=(1,xit,1,xit,2…Ki−1)$ is a $Ki$ vector explanatory variable (⁠$JobDemandsit+Workloadit+WESit+AWSit$⁠), for observational unit $i$ and $uit$ is an observable error term where the dual index $it$ denotes $tth$ observation of the $ith$ equation in the system.

A total of 150 questionnaires were distributed for the purpose of this analysis. Only 81 were completely filled and returned, which resulted in a response rate of 54%. On the other hand, 70 (47%) of the total questionnaires were either not returned or not correctly filled. Mugenda and Mugenda (2003) argue that a response rate of 50% or higher is sufficient to carry out the research analysis in that it will yield robust results. This implies that a response rate of approximately 54% attained in this study is adequate for this data analysis.

Maslach employee burnout, job demands, workload and life balance, work environment, and areas of work-life, the summarized results of the reliability statistics are reported in Table 2. Specifically, these results focus on the Cronbach’s alpha coefficient of all the scales under-review. It is concluded that after the exclusion of items 1 and 12 respectively in scales of areas of work-life and Maslach employee burnout, all the coefficients of Cronbach’s alpha exceed the required 0.70 cut-offs.

In support of the data, normality is the skewness and kurtosis results, the computed z-values of these measures are also between the interval of −1.96 and 1.96. This, therefore, suggests that the data is approximately normally distributed in terms of skewness and kurtosis.

The survey data collected on Maslach burnout, job demands, workload and life balance, work environment and areas of work-life were computed into a single variable per factor using the means of each factor. As a result, Pearson's pair-wise correlation coefficient analysis was conducted at a 5% confidence level to determine the direction and significance of the relationship. According to the reported results as presented in Table 3, there is a weak, negative and significant relationship between burnout and all the determinants of burnout considered in this study. Specifically, only workload and life balance have a stronger correlation of approximately 0.52 with burnout. Areas of work life have the weakest negative correlation with burnout.

The regression analysis approach has been adopted to test the specified prepositions. Since there is one dependent variable and four independent variables, the study applies Multiple Linear Regression (MLR) to the variables under review. First, the model summary results are reported in Table 3. Specifically, the R (Multiple correlation coefficient) predicts the relationship between the dependent variable and the regressors of the model (Chienwattanasook and Jermsittiparsert, 2019). The computed R-value of 61% signifies that there is a strong and significant relationship between the variables. Furthermore, the R-Squared (Coefficient of determination) indicates that taken as a set, the predictors; workload and life balance, work environment job demands, and areas of work-life account for approximately 37% of the variance in employee burnout.

The analysis of variance (ANOVA) is presented in Table 4 below. These results predict the significance of the regression model on the 95% confidence interval reference to the R-squared (Chienwattanasook and Jermsittiparsert, 2019). The ANOVA is used to examine if the computed R-squared in the model summary is statistically greater than 0. Therefore, it is evident from Table 4 that the overall regression model is significant. This implies that overall the regression analysis is statistically significant as the four predictors taken together predict employee burnout.

According to the results in Table 5, the variables of, job demands, workload and life balance, and areas of work-life are statically significant at 5%, 1%, and 5% respectively. This implies that all these significant variables explain a significant amount of burnout among frontline workers within the banking sector. Therefore, it can be concluded that the demands of the job, workload, and personal life balance as well as areas of work-life are key determinants of employee burnout. The working environment was found to not influence the burnout of frontline workers in the banking sector of South Africa. The summary of these results is presented in Table 6 below.

This study examined the predictors of employee burnout among frontline staff in South Africa's banking sector using a multi-theoretical framework, incorporating the Job Demands-Resources (JD-R) model, Conservation of Resources (COR) theory, Work-Family Conflict theory, Work-Home Resources model, Self-Efficacy theory, Maslow's Hierarchy of Needs, Social Exchange theory, and the Areas of Worklife model.

The findings reveal that job demands, work-life imbalance, and areas of work-life significantly predict burnout, while the work environment variable showed no significant effect. These results support and extend theoretical understandings of burnout in several ways.

The statistically significant impact of job demands on burnout reinforces the JD-R model (Demerouti et al., 2001), which posits that excessive demands deplete an employee's energy and coping resources, leading to emotional exhaustion. This is also consistent with the COR theory (Hobfoll, 1989), which suggests that sustained effort without resource replenishment creates a cycle of psychological strain. Employees working over 51 h per week experienced the highest levels of burnout, reflecting these theoretical assertions.

The strong relationship between work-life imbalance and burnout validates both the Work-Family Conflict theory (Greenhaus and Beutell, 1985) and the Work-Home Resources model (Bakker et al., 2019). Many participants, particularly those aged 31–40, reported strain from caregiving responsibilities and extended family obligations (“black tax”). These findings align with the idea that conflict between personal and professional roles depletes emotional and cognitive resources, increasing burnout risk.

Self-efficacy theory (Bandura, 1997) helps explain burnout among employees who reported difficulty adapting to new digital tools and systems. When workers feel ill-equipped to meet technological demands, their sense of competence diminishes, contributing to emotional exhaustion and disengagement.

Findings related to work-life dynamics also reflect Maslow's Hierarchy of Needs (1943). In collectivist cultures like South Africa, unmet social and familial obligations may create emotional dissonance and guilt, leading to burnout. Employees who are unable to meet these responsibilities due to work demands may feel psychologically strained, despite achieving at work.

The Social Exchange theory (Blau, 1964) further contextualises burnout as a response to perceived organisational injustices. Employees who feel under-recognised or unfairly treated—especially within South Africa's historical context of workplace inequality—may disengage emotionally from their work as a form of reciprocal withdrawal.

Interestingly, the study found no significant relationship between the broader work environment and burnout. This challenges findings from Organisational Culture Theory (Schaufeli and Enzmann, 1998), which emphasises toxic culture as a burnout driver. A potential explanation may be the buffering role of unmeasured variables like individual coping styles, job autonomy, or managerial support. Alternatively, it is possible that the frontline employees in this study have adapted to poor environments or have other psychosocial buffers in place.

Finally, results relating to areas of work-life (Leiter and Maslach, 2004)—particularly around fairness, control, and workload—highlight how a mismatch between employee needs and workplace realities intensifies burnout. Enterprise bankers, for example, reported the highest burnout levels, potentially due to limited administrative support and excessive role strain.

In summary, the discussion demonstrates that burnout is not a result of a single factor but a confluence of psychological, organisational, and social stressors. Integrating eight theoretical models allowed for a more holistic understanding of burnout in South Africa's banking sector, reinforcing the study's value and contribution to the literature on occupational health in emerging economies.

High levels of burnout have a negative impact on productivity, performance, and client service levels. As such the South African banking sector should consider implementing strategies to reduce and combat employee burnout. Many frontline employees are burnt out without even realising it because they are often unaware of the signs of burnout and may mistake it for stress. There are several strategies to address this. First, employers should hire employees with high levels of emotional intelligence during the hiring process, as this may reduce organisational work-family conflict, job burnout, and intention to leave (Giao et al., 2020). Once the right candidate has been hired, induction training for new employees should consist of practical hands-on training in the bank's systems and the work the employee will be doing in the new role.

Second, when necessary, ongoing face-to-face training should be provided to existing employees on a regular basis. Virtual training can reach more employees than face-to-face training, but employees may be present in the training but are not focused and listening attentively because they are preoccupied with something else. Face-to-face training requires attention and interaction. Training can be based on daily work activities and sharing best practices among colleagues, or it can be based on mental and physical health workshops. Employers should hold burnout workshops on a regular basis to educate employees on the differences between burnout and stress. Employees should also be made aware of the effects of burnout, particularly on their health, as a wake-up call to start taking their health more seriously. Employee Assistance Programs (EAPs) are another tool that South African banks can use to reduce burnout. Employee assistance programs (EAPs) are employee benefit programs that provide professional guidance and advice to employees dealing with work-related conflict and personal problems.

Third, management should encourage employees to take leave if no leave has been taken in the previous 12 months, and systems should be set up to notify both the employee and the manager that at least 5–10 days of leave should be taken if no leave has been taken in the previous 12 months. This way, the employer ensures that an employee takes annual leave regularly, which also helps to reduce burnout.

Finally, in this study, work overload was discovered to be one of the major contributors to burnout. Employees should be given a reasonable workload, and resources should be made available where they are lacking. It benefits both the employer and the employee when employees believe their workload and resources are being distributed fairly. Well-treated employees are more likely to treat customers well. Employees' workloads should gradually decrease once adequate resources are provided. This means that critical vacancies should be filled as soon as possible to reduce workload and burnout caused by a lack of resources. Employers can reduce burnout by implementing some of the above recommendations.

This study contributes to the growing body of burnout literature by identifying sector-specific predictors within the underexplored context of South Africa's banking industry. Future research could extend the sample to include diverse banking institutions and job levels, apply longitudinal designs, or examine coping mechanisms.

Findings suggest that the Department of Employment and Labour needs to regulate national and institutional policies that can guide workloads, support flexible work arrangements, and strengthen labour protections for customer-facing employees in the banking sector. The regulator could consider employee well-being metrics in its risk assessments.

Banks should invest in proactive burnout mitigation strategies, such as Employee Assistance Programs (EAPs), mental health education, and managerial training in workload distribution. Recruitment processes could include emotional intelligence screening, and retention strategies should incorporate regular burnout monitoring.

This study is subject to several limitations. First, the use of convenience sampling limits the generalisability of the findings. Second, the sample size, while statistically adequate, may not fully reflect the range of burnout experiences across different branches or institutions. Third, the exclusive focus on frontline employees omits the burnout experiences of mid- and senior-level staff. Fourth, the cross-sectional design limits the ability to infer causality. Lastly, the use of self-reported measures may be influenced by social desirability bias.

This study empirically investigated the predictors of employee burnout among frontline staff in South Africa's banking sector. Results show that job demands, work-life imbalance, and areas of work-life significantly predict burnout, while the working environment does not appear to play a meaningful role. These findings confirm three of the four hypotheses. They offer insights into how high-pressure, customer-facing roles—when coupled with personal and cultural expectations—can increase burnout risk. By highlighting these predictors, this study contributes to theory-building in emerging market contexts and proposes actionable interventions for banking institutions. Addressing these burnout drivers can enhance workforce resilience, customer service, and organisational sustainability.