The banking industry is a strategic sector for maintaining national economic stability. Through financial intermediation, banks channel public funds to meet various financing requirements. In Indonesia, the banking sector's contribution is reflected in fund mobilization, credit distribution, and transaction services that support business activities. Increasingly dynamic industry development has driven the growing demand for professional workers, requiring banking institutions to optimally manage human resources to meet operational targets and deliver quality services.
Along with these increasing demands, the psychological aspects of employees have become crucial concerns. According to Wahdiniawati et al. (2024), employees are the company's main assets and play an important role in operational processes. Effective and dedicated employees drive smooth operations; however, high-pressure working conditions can generate psychological disorders that hamper performance. Among these are burnout and Work-Family Conflict (WFC), two interrelated phenomena that can reduce productivity and employee well-being.
Burnout is a psychological condition marked by physical, mental, and emotional exhaustion due to prolonged stress (Chandra, 2024). Maslach and Leiter (2016) defined burnout through three main dimensions: emotional exhaustion, cynicism, and reduced self-efficacy. Meanwhile, Rotinsulu et al. (2024) note that 36.33% of banking employees experience work stress as the initial stage of burnout.
Workload is the primary determinant of burnout and WFC. Based on the Job Demands-Resources (JD-R) theory of Demerouti et al. (2001), when job demands exceed available employee resources, this directly triggers stress and indirectly produces burnout through role conflict mediation.
Increasing job demands in the banking sector require employees to meet high-performance targets under strict time pressure and extended working hours. These conditions can lead to excessive workloads, which not only affect employees’ physical and psychological well-being but also disrupt the balance between work and family roles. As a result, employees may experience WFC that potentially contributes to burnout. This condition is important to consider because it may reduce employee productivity, affect service quality, and ultimately influence organizational performance.
Although the relationships among workload, WFC, and burnout have been extensively explored in prior research, studies examining the mediating role of WFC within the specific context of Indonesian banking branch offices remain limited. Employees at Bank Rakyat Indonesia (BRI) Bank Branch Office Samarinda 1 face unique work demands characterized by high-performance targets, direct customer service interactions, and substantial work pressure, which may contribute to both WFC and burnout. Therefore, this study aims to analyze the effect of workload on burnout through the partial mediating role of WFC among employees of the BRI Bank Branch Office Samarinda 1.

2.1. Burnout
Burnout is a psychological syndrome resulting from prolonged exposure to chronic work-related stress. According to Maslach and Leiter (2016), burnout consists of three dimensions: emotional exhaustion, cynicism, and reduced professional effectiveness. Syamsu et al. (2019) described burnout as a condition caused by excessive work pressure that leaves individuals feeling physically and emotionally exhausted. Similarly, Kastaman and Coralia (2022) emphasized that burnout is characterized by decreased productivity and work effectiveness due to accumulated stress. 
From the perspective of the JD-R theory (Demerouti et al., 2001), burnout emerges when job demands continuously exceed the resources available to employees, leading to the depletion of physical and psychological energy.

2.2. WFC
WFC is a cross-role conflict that emerges when demands from the work and family domains collide, and involvement in one role interferes with participation in another role (Campos-Garcia et al., 2021). Greenhaus and Beutell (1985) identified three types of WFC: (1) time-based conflict, (2) strain-based conflict, and (3) behavior-based conflict. These dimensions were used as measurement indicators, in accordance with Sandini et al. (2021).

2.3. Workload
Mangkunegara (2017) defines workload as all activities assigned by the company to employees according to their competence and responsibilities. Robbins and Judge (2017) assert that excessive workload can create stress when employees feel unable to complete tasks within the available time or resources. Makatita et al. (2023) distinguished between quantitative and qualitative workloads. The measurement indicators are based on Koesomowidjojo (2017) and include: (1) working conditions, (2) allocation of working time, (3) achievement targets, (4) work standards, and (5) the work environment.

2.4. Research Hypotheses

2.4.1. Effect of Workload on Burnout
Excessive workload is considered a primary antecedent of burnout. According to the JD-R theory, burnout occurs when job demands exceed the resources available to employees, resulting in prolonged stress and exhaustion (Demerouti et al., 2001). Employees facing high workloads are more likely to experience emotional fatigue and reduced work effectiveness. Previous studies have consistently found that workload has a positive and significant effect on burnout (Chandra, 2024; Dudija & Putri, 2025; Pradana et al., 2017; Romadhoni et al., 2015; Wijaya & Wibawa, 2020). Therefore, the following hypothesis is proposed:
H1: Workload has a positive and significant effect on burnout.

2.4.2. Effect of Workload on WFC
Workload often requires employees to allocate more time, energy, and attention to work responsibilities, making it difficult for them to fulfill family related obligations. This imbalance may increase the likelihood of WFC. Empirical evidence from Baskoro and Handoyo (2020) and Ozgül and Koşarsoy (2024) indicates that higher workload is associated with greater WFC. Therefore, the following hypothesis is proposed:
H2: Workload has a positive and significant effect on WFC

2.4.3. Effect of WFC on Burnout
WFC arises when demands from work and family roles become incompatible, making participation in one role more difficult because of participation in the other role (Campos-Garcia et al., 2021). Employees who experience difficulties in balancing work and family responsibilities are more likely to encounter emotional strain and exhaustion, which may eventually lead to burnout. Hardiani (2021) demonstrated that WFC significantly increased burnout among employees. This finding is consistent with that of Rotinsulu et al. (2024), who found that employees experiencing higher levels of WFC tended to exhibit greater burnout symptoms. Based on these arguments and empirical findings, the following hypothesis is proposed:
H3: WFC has a positive and significant effect on burnout

2.4.4. The Mediating Role of WFC
Excessive workload may contribute to burnout, not only directly but also indirectly through WFC. Employees facing high workloads often devote more time and energy to work-related responsibilities, leaving fewer resources available for their family roles. This imbalance can intensify WFC, which subsequently increases the likelihood of burnout. Wijaya and Wibawa (2020) confirmed that WFC plays a mediating role in the relationship between workload and burnout. Similarly, Ozgül and Koşarsoy (2024) demonstrated that high workload contributes to burnout through increased WFC.  Therefore, the following hypothesis is proposed:
H4: WFC mediates the effect of workload on burnout

Based on theoretical and empirical studies, this research formulates four hypotheses: (H1) workload positively affects burnout; (H2) workload positively affects WFC; (H3) WFC positively affects burnout; and (H4) WFC mediates the relationship between workload and burnout. To facilitate understanding of this research, a conceptual framework was developed, as presented in Figure 1.
 
Figure 1. Conceptual Framework

Source: Primary data processed, 2025

3.1. Research Design
This study used a quantitative approach to examine the influence of workload on burnout through the mediating role of WFC. The study was conducted at the BRI Bank Branch Office Samarinda 1 in Samarinda, East Kalimantan.

3.2. Population and Sample
The population comprised all 84 employees of BRI KC Samarinda 1, including permanent and contract employees from various divisions. A saturated sampling technique was employed, with all members of the population serving as respondents.

3.3. Variables and Measurement
This study examines three variables: workload as the independent variable, burnout as the dependent variable, and WFC as the mediating variable. The indicators used in this study were adapted from previously validated instruments to ensure their construct validity. Burnout was measured using indicators proposed by Maslach and Leiter (2016), including physical exhaustion, emotional exhaustion, cynicism, decreased motivation, and reduced personal accomplishment. WFC was measured based on the dimensions developed by Greenhaus and Beutell (1985), consisting of difficulties in fulfilling family responsibilities due to work time demands, work pressure affecting family life, incompatibility between workplace and family role behaviors, work demands interfering with participation in family activities, and work-related stress influencing attitudes and emotions within the family. Workload was measured using indicators adapted from Koesomowidjojo (2017), including working conditions, allocation of working time, achievement targets, work standards, and the work environment. All questionnaire items were assessed using a five-point Likert scale ranging from strongly disagree to strongly agree. These indicators were selected because of their relevance to the research context and their extensive use in prior studies.

3.4. Data Collection
Primary data were collected through direct observation, interviews, and questionnaire distribution to all the respondents. Secondary data were obtained from reference books, scientific journals, and relevant internal documents.

3.5. Data Analysis Technique
The data were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach with SmartPLS 4.1. A hypothesis is considered supported when the t-statistic is ≥ 1.96 or the p-value is below 0.05.

4.1. Respondent Characteristics
For more details, see Table 1, Table 2, Table 3, and Table 4.

Table 1. Respondent Characteristics by Age

Source: Primary data processed, 2025

Table 2. Respondent Characteristics by Gender

Source: Primary data processed, 2025

Table 3. Respondent Characteristics by Marital Status

Source: Primary data processed, 2025

Table 4. Respondent Characteristics by Years of Service

Source: Primary data processed, 2025

4.2. Outer Model Evaluation

4.2.1. Convergent Validity
Convergent validity was determined by reviewing the factor loading values, which describe the extent to which each questionnaire item represents the latent construct being measured. The results show that all indicators possess outer loading values exceeding 0.70, suggesting that the indicators are capable of adequately measuring their respective latent constructs (see Table 5).

Table 5. Outer Loading Results

Source: Data processed using SmartPLS 4.1, 2025

Furthermore, apart from factor loading, convergent validity can also be evaluated through the Average Variance Extracted (AVE) value, where a construct is said to be valid if the AVE value is > 0.50 (see Table 6).

Table 6. AVE Results

Source: Data processed using SmartPLS 4.1, 2025

The results above show a value (Average Variance Extracted) > 0.50, meaning it is valid and meets the requirements.

4.2.2. Discriminant Validity
Discriminant validity shows that each indicator measures the construct it is supposed to measure and not other constructs. This test is carried out by examining the cross-loading values, which compare the relationship between an indicator and its own construct with other constructs. As shown in Table 7, each indicator has the highest loading value on its respective construct, indicating that the discriminant validity requirement has been met.

Table 7. Cross Loading Results

Source: Data processed using SmartPLS 4.1, 2025

Each indicator exhibited the highest loading on its intended construct. Two borderline indicators merit discussion: WFC5 shows a cross-loading of 0.600 on Burnout (versus 0.715 on its own construct), and B5 shows a cross-loading of 0.643 on WFC (versus 0.717 on its own construct). These patterns are consistent with the theoretical proximity of these constructs—both WFC and burnout involve psychological resource depletion—and with prior literature noting that WFC and burnout share overlapping variances. However, to verify that these borderline cases do not compromise discriminant validity, the Heterotrait–Monotrait (HTMT) ratio was calculated (see Table 8).

Table 8. HTMT Ratio Results

Source: Data processed using SmartPLS 4.1, 2025

All HTMT values were below the conservative threshold of 0.85 (Henseler et al., 2015), confirming discriminant validity, even given the borderline cross-loadings noted above. The HTMT criterion provides stronger evidence of discriminant validity than cross-loadings alone, particularly when constructs are theoretically related, as in this study.

4.2.3. Reliability Test
Construct reliability was evaluated using Cronbach’s alpha and composite reliability. Values above 0.70 indicate that the construct is reliable and suitable for structural-model testing. As presented in Table 9, the Cronbach’s alpha and composite reliability values for all variables were higher than 0.70, indicating that the indicators provided consistent measurement results.
 
Table 9. Composite Reliability and Cronbach's Alpha Results

Source: Data processed using SmartPLS 4.1, 2025

4.3. Inner Model Evaluation

4.3.1. R-Square
In the structural model evaluation, the R-squared (R²) value of each endogenous variable was used to assess the model's predictive ability. A higher R² value indicates that a larger proportion of the construct’s variance is explained, reflecting the model’s better predictive ability. According to Ghozali (2021), the R² predicts a model at 0.75 (high), 0.50 (moderate), and 0.25 (weak) levels. The burnout variable had an R² value of 0.509 (50.9% of the variance explained by the model), while the WFC variable had an R² value of 0.442 (44.2%) (see Table 10).

Table 10. R-Square Results

Source: Data processed using SmartPLS 4.1, 2025

4.3.2. Effect Sizes (f²) and Structural Multicollinearity Assessment based on Variance Inflation Factor (VIF)

Table 11. Effect Sizes (f²) and VIF Results

Source: Data processed using SmartPLS 4.1, 2025

Based on Table 11, the largest effect size was for the workload–WFC path (f² = 0.793), indicating that workload is a powerful predictor of WFC. The direct workload–burnout path showed a medium-to-large effect (f² = 0.231), whereas the WFC–burnout path was smaller (f² = 0.071) but still meaningful. The VIF values for all predictor constructs in the structural model were below 5, confirming the absence of multicollinearity concerns.

4.3.2. Hypothesis Testing
For more details, see Table 12 and Table 13.

Table 12. Path Coefficient Results (Direct Effects)

Source: Data processed using SmartPLS 4.1, 2025

Table 13. Indirect Effects Results (Mediation)

Source: Data processed using SmartPLS 4.1, 2025

The results show that all hypotheses are supported, as indicated by p-values below 0.05 and t-statistics above 1.96. Positive coefficients indicate that the relationships between the variables move in the same direction. Workload had the strongest effect on WFC (β = 0.665), followed by its effect on burnout (β = 0.498). Additionally, WFC significantly affected burnout (β = 0.278). The indirect effect (β = 0.185) confirmed that workload also influenced burnout through WFC.

4.4. Discussion

4.4.1. Effect of Workload on Burnout
Workload had a positive and significant direct effect on burnout (β = 0.498, p < 0.001, f² = 0.231). This is the second-strongest path in the model and represents the health impairment process of the JD-R framework: when job demands persistently exceed available resources, employees' energy is depleted, producing the exhaustion, cynicism, and reduced efficacy that characterize burnout (Demerouti et al., 2001; Maslach & Leiter, 2016). At BRI KC Samarinda 1, tellers, customer service officers, and account officers face simultaneous pressures: high transaction volumes, strict accuracy requirements, customer interaction demands, and performance targets that collectively sustain an above-threshold workload environment. This finding is consistent with those of Chandra (2024), Dudija and Putri (2025), and Pradana et al. (2017).

4.4.2. Effect of Workload on WFC
Workload exerted the strongest effect on work–family conflict in the model (β = 0.665, p < 0.001, f² = 0.793). This large effect reflects the Conservation of Resources (COR) theory prediction that high job demands are the primary precipitant of resource depletion, which manifests as an inability to fulfill one’s family roles. At BRI KC Samarinda 1, account officers frequently conduct after-hours client visits, tellers cannot leave until the reconciliation is complete, and operational staff face unpredictable workload surges. The high proportion of married employees (57.1%) means that most employees simultaneously have substantial family obligations. The disparity between the workload and WFC coefficient (0.665) and the WFC–burnout coefficient (0.278) is theoretically informative; it suggests that while workload is a highly efficient driver of role conflict, not all WFC translates proportionally into burnout—individuals may deploy coping strategies, family support, or job crafting to partially buffer the WFC–burnout conversion. This finding is consistent with Baskoro and Handoyo (2020) and Ozgül and Koşarsoy (2024).

4.4.3. Effect of WFC on Burnout
WFC had a positive and significant effect on burnout (β = 0.278, p = 0.024, f² = 0.071). Although smaller in magnitude than the direct workload–burnout path, this effect is substantively meaningful because it confirms that WFC operates as an independent source of psychological strain that augments burnout beyond the effect of workload alone. Employees who experience role conflict face a 'double bind': they cannot fully satisfy work requirements without sacrificing family obligations, and this persistent tension depletes emotional resources through guilt, frustration, and cognitive rumination. This finding is consistent with those of Hardiani (2021), Wulansari and Yuniawan (2017), Elahi et al. (2022), and Rotinsulu et al. (2024). The relatively smaller coefficient (0.278 vs. 0.498 for workload) indicates that WFC is a secondary—though real and non-trivial—contributor to burnout in this context, which has implications for Human Resources (HR) intervention prioritization (see Section 5).

4.4.4. Mediating Role of WFC
WFC partially mediated the workload–burnout relationship (indirect effect β = 0.185, p = 0.024, 95% CI [0.029, 0.357]). The partial mediation pattern, in which the direct effect remains significant after adding the mediator, indicates that workload affects burnout through two distinct pathways. The dominant pathway is direct (β = 0.498): workload directly depletes employees’ psychological resources without necessarily requiring the intermediate step of role conflict. The secondary pathway is through WFC (β = 0.185): workload first disrupts the work-family balance, and the resulting conflict adds an additional layer of emotional strain that further fuels burnout. In proportional terms, the indirect path accounted for approximately 27% of the total workload–burnout effect (0.185 / [0.498 + 0.185] ≈ 0.27), meaning that nearly three-quarters of the workload effect on burnout operated through the direct channel, with approximately one-quarter transmitted via WFC.
This partial mediation has important implications for HR. This means that interventions targeting only work-family balance (e.g., flexible scheduling) will only partially reduce burnout because the majority of the workload–burnout effect bypasses the WFC pathway. Therefore, effective burnout prevention at BRI KC Samarinda 1 requires direct addressing of workload volume and intensity —not merely managing its spillover into family life. These findings align with Wijaya and Wibawa (2020), Lineuwih et al. (2022), and Ozgül and Koşarsoy (2024), and extend their findings by quantifying the relative contribution of direct versus indirect paths in an Indonesian branch banking context.

This study examined the effect of workload on burnout, mediated by WFC, among all 84 employees of BRI KC Samarinda 1. Using PLS-SEM with 5,000 bootstrap resamples and a comprehensive set of model evaluation tests (outer loadings, AVE, HTMT, composite reliability, R², Q², f², VIF, Standardized Root Mean Square Residual (SRMR)), all four hypotheses were supported: (1) workload positively and significantly affects burnout (β = 0.498); (2) workload positively and significantly affects WFC (β = 0.665); (3) WFC positively and significantly affects burnout (β = 0.278); and (4) WFC partially mediates the workload–burnout relationship (indirect effect β = 0.185). The direct path from workload to burnout was dominant, accounting for approximately 73% of the total effect, whereas the WFC-mediated path accounted for approximately 27%.
For the management of BRI KC Samarinda 1, these findings suggest a two-pronged intervention strategy. First, and most urgently, workload intensity itself must be addressed: realistic daily transaction targets, sufficient staffing during peak periods, and clear overtime policies are needed to prevent chronic resource depletion. Second, work-life balance support, such as flexible shift arrangements, family friendly leave policies, and access to employee assistance programs, can reduce WFC and thereby cut off the secondary burnout pathway, which is particularly important given that 57.1% of employees are married with family obligations. Psychological support programs (e.g., peer support and counseling access) should also be implemented to build recovery resources.