Work-Life Balance, Quality of Work Life, and Employee Performance among Indonesian Civil Servants: the Mediating Role of Job Satisfaction

Abstract

Employee performance among Indonesian civil servants has become a critical issue under fiscal-efficiency policy, which increases work pressure while limiting operational resources. This study examines the relationships among work-life balance, quality of work life, job satisfaction, and employee performance at the South Kalimantan National Road Implementation Agency. A cross-sectional explanatory survey was conducted with 158 operational civil servants. Data were collected using a five-point Likert-scale questionnaire and analyzed with Partial Least Squares Structural Equation Modeling. The model explained 55.4% of the variance in employee performance and 46.8% of the variance in job satisfaction. All proposed relationships were statistically supported. Work-life balance had the strongest relationship with job satisfaction (β = 0.537), while quality of work life had the strongest direct relationship with employee performance (β = 0.445). Job satisfaction partially mediated the relationship between work-life balance and employee performance (β = 0.196) and between quality of work life and employee performance (β = 0.147). This study contributes by showing that job satisfaction acts as a psychological mechanism linking recovery conditions and workplace resources to civil-servant performance in a fiscally constrained public-sector setting. Practically, agencies should improve workload distribution, schedule predictability, supervisory support, coordination, and non-financial recognition. Because the design was cross-sectional, the findings indicate statistically supported relationships rather than definitive causal effects.

Keywords: work-life balance; quality of work life; job satisfaction; employee performance; civil servant.

Introduction

The performance of civil servants is central to public-service delivery and good governance in Indonesia, particularly in infrastructure agencies whose outputs directly affect connectivity, economic mobility, and public welfare. While formal performance- management instruments exist, they often fail to capture the influence of work-life boundaries, employee well-being, and workplace quality on sustained performance outcomes (Fatimah et al., 2025; Haricharan, 2023; Mohammad et al., 2025). At the South Kalimantan National Road Implementation Agency, the official 2024 quarterly Employee Performance Target (Sasaran Kinerja Pegawai or SKP) recap classified employee performance into five categories: Very Good, Good, Poor, Very Poor, and No Rating. Across the first to fourth quarters, the number of employees rated Very Good was 77, 77, 74, and 48, respectively, while the Good category included 82, 87, 89, and 114 employees.

The Poor category included one employee only in the third quarter, whereas the Very Poor category increased from none in the first quarter to one employee in both the second and third quarters and three employees in the fourth quarter. Six employees received no rating in the first quarter, with none recorded in the subsequent quarters. The reduction in Very Good ratings and the increase in Very Poor ratings Employee performance among Indonesian civil servants has become a critical issue under fiscal-efficiency policy, which increases work pressure while limiting operational resources. This study examines the relationships among work-life balance, quality of work life, job satisfaction, and employee performance at the South Kalimantan National Road Implementation Agency. A cross-sectional explanatory survey was conducted with 158 operational civil servants.

Data were collected using a five-point Likert-scale questionnaire and analyzed with Partial Least Squares Structural Equation Modeling. The model explained 55.4% of the variance in employee performance and 46.8% of the variance in job satisfaction. All proposed relationships were statistically supported. Work-life balance had the strongest relationship with job satisfaction (β = 0.537), while quality of work life had the strongest direct relationship with employee performance (β = 0.445). Job satisfaction partially mediated the relationship between work-life balance and employee performance (β = 0.196) and between quality of work life and employee performance (β = 0.147). This study contributes by showing that job satisfaction acts as a psychological mechanism linking recovery conditions and workplace resources to civil-servant performance in a fiscally constrained public-sector setting.

Practically, agencies should improve workload distribution, schedule predictability, supervisory support, coordination, and non-financial recognition. Because the design was cross-sectional, the findings indicate statistically supported relationships rather than definitive causal effects. indicate an administratively meaningful downward shift in top- tier performance ratings rather than a statistically significant decline because the records were not subjected to inferential statistical testing. These empirical conditions justify using work-life balance and quality of work life as key explanatory variables. Work-life balance is relevant because employees reported work spillover into personal time, while quality of work life is relevant because fiscal-efficiency measures affected workplace support, facilities, compensation perceptions, and administrative conditions.

Examining these two variables provides a contextual explanation of employee performance that goes beyond formal appraisal metrics. Work-life balance has been widely recognized as a critical determinant of employee outcomes. Building on the Effort- Recovery Model (Meijman & Mulder, 1998) and supported by more recent studies on employee well-being (Halbesleben et al., 2014; Sonnentag & Fritz, 2015), sustained work demands without adequate recovery accumulate as fatigue and progressively erode cognitive capacity, motivation, and performance. Complementary theoretical perspectives, such as the Job Demands-Resources (JD-R) Model (Bakker & Demerouti, 2017), highlight that employee performance is influenced not only by demands but also by available resources and recovery opportunities. Recent empirical investigations in the Indonesian public sector consistently confirm that employees who maintain healthy boundaries between professional and personal domains display higher engagement and productivity (Aulia & Yaman, 2024; Satrya et al., 2025).

Quality of work life, in turn, captures the organization's capacity to meet employees' physiological, psychological, and social needs through fair compensation, safe conditions, participation, and growth opportunities (Nanjundeswaraswamy et al., 2024). When these conditions deteriorate, employees tend to withdraw discretionary effort, undermining both individual and organizational performance (Sihombing et al., 2024; Yusnita & Melati F, 2023). Job satisfaction refers to employees' affective evaluation of their job and work environment. In this study, job satisfaction is treated as a mediating mechanism because work-life balance and quality of work life may first shape how satisfied employees feel before influencing their performance. Employees who have better recovery opportunities and more supportive work conditions are more likely to experience satisfaction, which can encourage stronger effort, commitment, and performance.

However, previous findings remain inconsistent. Faustina and Julianti (2024) found that job satisfaction did not mediate the relationship between work-life balance and employee performance, while Putri and Ardiana (2024) reported no significant mediating role of job satisfaction in the quality-of- work-life pathway. These mixed findings indicate the need to re-examine job satisfaction as a mediator in the Indonesian civil-servant context, especially under fiscal-efficiency pressure. The main novelty of this study is the mediation testing of job satisfaction in a fiscally constrained Indonesian public infrastructure agency. This context is important because civil servants at the South Kalimantan National Road Implementation Agency are required to maintain public- service performance while facing budget-efficiency pressure and limited operational resources.

Prior studies have produced inconsistent evidence on whether job satisfaction mediates the effects of work-life balance and quality of work life on employee performance. Therefore, this study addresses this gap by testing both direct and indirect relationships in one integrated model. The fiscal-efficiency setting provides the contextual novelty, while the Effort- Recovery Model and the Job Demands-Resources framework provide the theoretical basis for hypotheses H1 to H7. This study examines the direct relationships of work-life balance and quality of work life with employee performance and job satisfaction, as well as their indirect relationships with employee performance through job satisfaction, among civil servants at the South Kalimantan National Road Implementation Agency. The study contributes theoretically by integrating the Effort-Recovery Model and the Job Demands- Resources framework to explain how personal recovery conditions and organizational work resources influence employee performance through an affective mechanism.

It also extends the application of these frameworks to a fiscally constrained Indonesian public infrastructure agency, a context that remains underrepresented in previous research. Practically, the findings provide an operational basis for agency leaders to control workload, establish predictable work schedules, strengthen workplace facilities and supervisory support, and monitor job satisfaction as part of employee- performance management under budget constraints.

Methods

This study employed a quantitative cross-sectional explanatory design to examine the relationships among work- life balance, quality of work life, job satisfaction, and employee performance. Because the data were collected at one point in time, the term “effect” in this study refers to statistically supported relationships within the PLS-SEM model and should not be interpreted as definitive causal evidence. Stronger causal inference would require longitudinal or experimental data (Creswell & Creswell, 2023; Hair et al., 2022). The study was conducted at the South Kalimantan National Road Implementation Agency, a public infrastructure agency responsible for national road and bridge development, maintenance, and supervision in South Kalimantan Province. The initial population consisted of 166 civil servants working at the agency.

Because this study focused on operational work conditions, eight senior structural positions were excluded, consisting of one agency head, four section heads, and three work-unit heads. Therefore, the eligible sampling frame consisted of 158 operational civil servants. A census was conducted among all eligible respondents, and all 158 questionnaires were usable for analysis. This approach was considered appropriate for a bounded organizational population, although the possibility of self-report and non- response bias cannot be fully eliminated (Saunders et al., 2023; Sekaran & Bougie, 2020). Data were collected using a structured questionnaire consisting of 42 indicators across four constructs: work-life

Result and Discussion

General Overview of the Research Object

The South Kalimantan National Road Implementation Agency is a technical unit under the Ministry of Public Works. The agency is responsible for the construction, preservation, maintenance, and supervision of national roads and bridges in South Kalimantan Province. The characteristics of the 158 respondents are presented in

Descriptive Analysis

. The respondent profile was limited to gender, age, education, tenure, and employment status, which were considered sufficient to describe the operational civil-servant population examined in this study. Descriptive Analysis Table 3 presents the mean, standard deviation, and response distribution of the four research constructs. All constructs recorded observed responses across the full five- point Likert scale, with a minimum response of 1 and a maximum response of 5. These values represent the observed response range of the questionnaire items rather than the standardized latent-variable scores generated by SmartPLS. Using the theoretical midpoint of 3.00 as a benchmark, all four constructs received generally favourable evaluations. Work-life balance recorded the highest mean value of 3.784, followed by quality of work life at 3.723, employee performance at 3.686, and job satisfaction at 3.664.

The standard deviations ranged from 0.878 to 0.985, indicating moderate variation in respondents’ assessments. Most responses were concentrated in categories 4 and 5. However, job satisfaction had the highest combined proportion of responses in categories 1 and 2, indicating that some employees still reported less favourable job experiences. Table 4 shows that employee performance was positively correlated with job satisfaction (r = 0.634), quality of work life (r = 0.606), and work-life balance (r = 0.364). Job satisfaction was also positively correlated with work-life balance (r = 0.553) and quality of work life (r = 0.425). The correlation between work-life balance and quality of work life was very low (r = 0.039), indicating that both variables represent different aspects of employees’ work conditions.

These results provide preliminary support for the proposed model, while

PLS-SEM Analysis Results

Measurement Model Assessment

The measurement model was assessed through indicator reliability, internal consistency reliability, convergent validity, and discriminant validity. Indicator reliability was examined using outer loading values, while internal consistency reliability was evaluated using Cronbach’s alpha and composite reliability. Convergent validity was assessed using average variance extracted. The assessment followed the recommended criteria of outer loadings above 0.70, reliability values above 0.70, and AVE values above 0.50 (Hair et al., 2022). The final measurement model comprised 42 indicators. All outer loading values exceeded the recommended threshold of 0.70, ranging from 0.732 to 0.853. Cronbach’s alpha values ranged from 0.885 to 0.958, composite reliability values ranged from 0.913 to 0.963, and AVE values ranged from 0.617 to 0.640.

These results demonstrate adequate indicator reliability, internal consistency reliability, and convergent validity for all indicators included in the final measurement model. The detailed measurement results are presented in

Structural Model Assessment

The structural model was assessed through explanatory power, effect size, predictive relevance, and hypothesis testing. R-square was used to determine the proportion of variance explained in the endogenous constructs, while f-square was used to assess the relative contribution of each predictor. Predictive relevance was evaluated using Q-square, PLSpredict, and CVPAT (Hair et al., 2022; Shmueli et al., 2019). The R-square value for employee performance was 0.554, with an adjusted R-square of 0.545 (see Table 8). This means that work-life balance, quality of work life, and job satisfaction jointly explained 55.4 per cent of the variance in employee performance. The R-square value for job satisfaction was 0.468, with an adjusted R-square of 0.461. This indicates that work-life balance and quality of work life explained 46.8 per cent of the variance in job satisfaction.

Predictive relevance was first assessed through the blindfolding procedure. Employee performance obtained a Q- square value of 0.343, while job satisfaction obtained a Q- square value of 0.287. Both values were above zero, indicating that the structural model had predictive relevance. The PLSpredict procedure also produced positive Q²predict values of 0.457 for employee performance and 0.439 for job satisfaction. The f-square results show that work-life balance had a large effect size on job satisfaction. Quality of work life had medium effect sizes on both employee performance and job satisfaction. Job satisfaction had a medium effect size on employee performance, while the direct relationship between work-life balance and employee performance had a small effect size (see Table 9). The PLSpredict results showed that all indicator-level Q²predict values were above zero.

The PLS-SEM model also produced lower root mean square error values than the linear model benchmark for all indicators of employee performance and job satisfaction. These results indicate that the model demonstrated adequate out-of-sample predictive performance. The CVPAT results further supported the predictive capability of the model. The overall PLS-SEM prediction loss was significantly lower than the indicator-average benchmark, with an average loss difference of -0.418 and a p-value below 0.001. The PLS-SEM prediction loss was also significantly lower than the linear-model benchmark, with an average loss difference of -0.180 and a p-value below 0.001. Therefore, the proposed model demonstrated acceptable explanatory and predictive performance. The mediation assessment showed that the direct and indirect relationships were significant and operated in the same positive direction.

Work-life balance had a significant direct relationship with employee performance (β = 0.145, p = 0.030) and a significant indirect relationship through job satisfaction (β = 0.196, p < 0.001). Quality of work life also had a significant direct relationship with employee performance (β = 0.445, p < 0.001) and a significant indirect relationship Hypothesis Testing Hypothesis testing used bootstrapping with 5,000 resamples to assess the significance of each proposed relationship. A hypothesis was accepted when the t-statistic exceeded 1.96 and the p-value was below 0.05, indicating statistical significance at the 5 percent level (Hair et al., 2022). To provide a more detailed interpretation of the bootstrapping output presented in Figure 2, Table 10 reports the results of the direct and indirect effect testing for all proposed hypotheses.

All seven hypotheses were statistically supported. Work- life balance showed the strongest relationship with job satisfaction (β = 0.537), while quality of work life had the strongest direct relationship with employee performance (β = 0.445). Job satisfaction partially mediated both relationships, with an indirect effect of 0.196 and a VAF of 57.48% for the work-life-balance pathway, and an indirect effect of 0.147 and a VAF of 24.83% for the quality-of-work-life pathway. Because both the direct and indirect effects were positive and statistically significant, the mediation was classified as complementary partial mediation. These findings indicate that work-life balance is associated with performance mainly through job satisfaction, whereas quality of work life is associated with performance through both direct and indirect pathways.

Since the study used a cross-sectional design, the results should be interpreted as statistically supported relationships rather than definitive causal effects. Effect of Work-Life Balance on Employee Performance Work-life balance was positively associated with employee performance, but the direct relationship was relatively small (β = 0.145; f² = 0.031). This result supports the Effort- Recovery Model because employees who have sufficient recovery time are better able to preserve energy, concentration, and emotional stability. However, the small effect size indicates that balanced work and personal roles alone do not strongly determine performance in this organizational setting. The limited direct contribution can be understood from the operational context of the South Kalimantan National Road Implementation Agency.

Employees must complete administrative and technical duties, coordinate across work units, meet strict deadlines, and manage field-related risks. During the fiscal-efficiency period, restrictions on official travel, meetings, facilities, and other operational resources also affected the way employees completed their duties. Under these conditions, performance depends more immediately on the availability of workplace resources, clear procedures, supervisory support, safety arrangements, and effective coordination than on work-life balance alone. This explains why quality of work life had a stronger direct relationship with performance (β = 0.445; f² = 0.340). The finding is consistent with Andian and Kadarningsih (2025), Prasetyo and Wardoyo (2023), and Haar and Brougham (2022), who reported that healthier work-life arrangements are associated with better work outcomes.

In this study, however, work-life balance appears to support performance mainly by protecting employees' energy and strengthening their job satisfaction. Therefore, feasible managerial actions include limiting unnecessary after-hours assignments, improving schedule predictability, and distributing workloads more evenly. These actions require limited additional spending and are realistic under the agency's fiscal-efficiency constraints. Effect of Quality of Work Life on Employee Performance Quality of work life had a positive and comparatively strong relationship with employee performance (β = 0.445; f² = 0.340). This finding is consistent with the Job Demands- Resources framework, which proposes that adequate job resources help employees meet demanding work requirements and sustain performance.

In the studied agency, those resources include safe working conditions, clear procedures, fair treatment, supportive supervision, functional facilities, teamwork, and opportunities to develop work-related capabilities. The stronger direct effect of quality of work life is understandable because many duties at the agency depend on concrete workplace resources and coordination. In this study, quality of work life can be interpreted through several dimensions. Fairness supports performance when employees perceive task allocation, workload distribution, appraisal, and compensation practices as consistent and transparent. Safety is important because road and bridge activities require employees to perform administrative and field-related duties under secure working conditions. Growth opportunities help employees improve their technical and administrative capabilities.

Social integration strengthens cooperation across administrative and implementation units, while supportive supervision provides direction, feedback, and problem-solving assistance. Facilities also play a direct role because employees need adequate work tools, operational support, and functional infrastructure to complete their duties effectively. When these dimensions are weak, employees may face practical barriers in completing their work. The descriptive results also showed that perceived income fairness and commitment to completing tasks with coworkers were among the lower-rated quality-of- Measurement Model Assessment Variable Item Outer Loading CA CR AVE Decision Work-Life Balance WLB.1 0.798 0.938 0.947 0.617 Valid WLB.2 0.796 0.938 0.947 0.617 Valid WLB.3 0.784 0.938 0.947 0.617 Valid WLB.4 0.778 0.938 0.947 0.617 Valid WLB.5 0.737 0.938 0.947 0.617 Valid WLB.6 0.823 0.938 0.947 0.617 Valid WLB.7 0.781 0.938 0.947 0.617 Valid WLB.8 0.818 0.938 0.947 0.617 Valid WLB.9 0.810 0.938 0.947 0.617 Valid WLB.10 0.732 0.938 0.947 0.617 Valid WLB.11 0.779 0.938 0.947 0.617 Valid Quality of Work Life QWL.1 0.828 0.938 0.947 0.640 Valid QWL.2 0.783 0.938 0.947 0.640 Valid QWL.3 0.802 0.938 0.947 0.640 Valid QWL.4 0.798 0.938 0.947 0.640 Valid QWL.5 0.795 0.938 0.947 0.640 Valid QWL.6 0.789 0.938 0.947 0.640 Valid QWL.7 0.809 0.938 0.947 0.640 Valid QWL.8 0.814 0.938 0.947 0.640 Valid QWL.9 0.782 0.938 0.947 0.640 Valid QWL.10 0.803 0.938 0.947 0.640 Valid Job Satisfaction JS.1 0.747 0.885 0.913 0.636 Valid JS.2 0.782 0.885 0.913 0.636 Valid JS.3 0.853 0.885 0.913 0.636 Valid JS.4 0.809 0.885 0.913 0.636 Valid JS.5 0.792 0.885 0.913 0.636 Valid JS.6 0.797 0.885 0.913 0.636 Valid Employee Performance EP.1 0.811 0.958 0.963 0.633 Valid EP.2 0.801 0.958 0.963 0.633 Valid EP.3 0.800 0.958 0.963 0.633 Valid EP.4 0.785 0.958 0.963 0.633 Valid EP.5 0.783 0.958 0.963 0.633 Valid EP.6 0.786 0.958 0.963 0.633 Valid EP.7 0.827 0.958 0.963 0.633 Valid EP.8 0.836 0.958 0.963 0.633 Valid EP.9 0.799 0.958 0.963 0.633 Valid EP.10 0.759 0.958 0.963 0.633 Valid EP.11 0.813 0.958 0.963 0.633 Valid EP.12 0.742 0.958 0.963 0.633 Valid EP.13 0.737 0.958 0.963 0.633 Valid EP.14 0.832 0.958 0.963 0.633 Valid EP.15 0.811 0.958 0.963 0.633 Valid Source: SmartPLS output, 2026.

HTMT Assessment Construct Pair HTMT Job Satisfaction ↔ Employee Performance 0.684 Quality of Work Life ↔ Employee Performance 0.636 Quality of Work Life ↔ Job Satisfaction 0.459 Work-Life Balance ↔ Employee Performance 0.380 Work-Life Balance ↔ Job Satisfaction 0.602 Work-Life Balance ↔ Quality of Work Life 0.079 Source: SmartPLS output, 2026. work-life indicators. These results suggest that fairness, teamwork, supervision, safety, facilities, and development opportunities deserve managerial attention rather than treating quality of work life as a single general condition. This result supports Aulia and Yaman (2024), Sihombing et al. (2024), and Nanjundeswaraswamy et al. (2024), who found that supportive and fair working conditions are associated with stronger employee performance. The evidence does not imply that every workplace intervention will automatically improve performance.

It indicates that practical improvements should focus on the dimensions most closely related to daily task completion. Under fiscal constraints, feasible actions include clarifying work procedures, improving coordination, strengthening supervisory feedback, maintaining essential safety standards, and communicating compensation and task- allocation decisions more transparently.

Figure 2. Structural Model Output (Bootstrapping)

Hypothesis Testing

was conducted through bootstrapped PLS-SEM.

Effect of Work-Life Balance on Employee Performance

. • H7: Job satisfaction mediates the

Effect of Quality of Work Life on Employee Performance

.

Effect of Work-Life Balance on Job Satisfaction

Work-life balance had the strongest relationship in the model with job satisfaction (β = 0.537; f² = 0.540). This large effect indicates that employees' ability to manage work and personal responsibilities is closely associated with how positively they evaluate their jobs. When work demands repeatedly extend into evenings, weekends, or family time, y VIF Decision Work-Life Balance 1.590 Below 3.30 Quality of Work Life 1.753 Below 3.30 Job Satisfaction 2.178 Below 3.30 Employee Performance 2.243 Below 3.30 Source: Author calculation based on SmartPLS latent variable scores, 2026. employees may still complete their duties but experience lower satisfaction with their overall work situation. This relationship is particularly relevant in the agency because employees face deadline-driven administrative work, coordination demands, and field assignments.

The respondent profile also shows that many employees have long organizational tenure and are in age groups likely to carry substantial family responsibilities. Schedule uncertainty and after-hours work may therefore affect their satisfaction more strongly than their immediate task output. The result is consistent with Irawanto et al. (2021), Haar and Brougham (2022), and Inegbedion (2024), who found that healthier boundaries between work and personal life are associated with more favourable job attitudes. The evidence supports low-cost managerial adjustments rather than broad promises of flexible work for every position. The agency can reduce avoidable after-hours communication, provide earlier notice of field assignments, clarify urgent and non-urgent tasks, and monitor workload concentration across employees.

These measures are feasible under fiscal-efficiency conditions and may improve satisfaction without reducing accountability or service standards.

Effect of Quality of Work Life on Job Satisfaction

Quality of work life was positively associated with job satisfaction (β = 0.404; f² = 0.306). This medium effect indicates that employees are more satisfied when they perceive their workplace as fair, safe, supportive, and meaningful. The finding also shows that quality of work life should be interpreted through its specific dimensions rather than as a general workplace atmosphere. In this study, the lower-rated indicators related to income fairness and commitment to completing tasks with coworkers point to two relevant concerns. First, employees may compare compensation and workload arrangements with those of their colleagues, making transparent and consistent procedures important for maintaining satisfaction. Second, the demands of coordination across administrative and field units may create uneven experiences of teamwork.

These issues become more visible during fiscal-efficiency measures because restricted resources can increase competition for facilities, travel opportunities, and operational support. The result is consistent with Putri and Ardiana (2024), Siagian et al. (2024), Yusnita and Melati (2023), and Nanjundeswaraswamy et al. (2024). Their findings similarly show that fairness, meaningful work, supportive relationships, and development opportunities shape job satisfaction. The evidence supports practical actions such as clearer task Effect Size Assessment Relationship f-square Interpretation Work-Life Balance → Employee Performance 0.031 Small Work-Life Balance → Job Satisfaction 0.540 Large Quality of Work Life → Employee Performance 0.340 Medium Quality of Work Life → Job Satisfaction 0.306 Medium Job Satisfaction → Employee Performance 0.159 Medium Source: SmartPLS output, 2026. allocation, consistent supervisory communication, recognition of employee contributions, and access to low-cost learning opportunities.

These recommendations are more feasible than large financial incentives in the current budget context.

Effect of Job Satisfaction on Employee Performance

Job satisfaction was positively associated with employee performance (β = 0.365; f² = 0.159). The medium effect size indicates that satisfaction has a meaningful, but not exclusive, role in explaining performance. Satisfied employees are more likely to maintain effort, respond constructively to work demands, and remain committed to completing organizational responsibilities. However, performance also depends on operational resources, procedures, skills, and supervisory conditions. In the agency context, job satisfaction is especially relevant because material incentives and operational resources are constrained. Employees who perceive fair appraisal, supportive supervision, recognition, and meaningful public-service contributions may maintain performance even when financial flexibility is limited.

This interpretation is consistent with Gazi et al. (2022), Kui et al. (2022), Mujahidin (2024), and Prasetyo and Wardoyo (2023), who reported positive relationships between job satisfaction and performance. The practical implication is not that satisfaction alone guarantees high performance. Rather, the evidence suggests that non-financial management practices can help sustain effort. Timely feedback, transparent appraisal, visible recognition, and respectful supervisory communication are feasible actions that can strengthen satisfaction without requiring major additional expenditure.

Mediating Function of Job Satisfaction in the Link between Work-Life Balance and Employee Performance

Job satisfaction partially mediated the relationship between work-life balance and employee performance. The direct effect of work-life balance on performance was 0.145, while the indirect effect through job satisfaction was 0.196. The VAF value was 57.48%, indicating complementary partial mediation because both the direct and indirect effects were positive and statistically significant. Thus, job satisfaction transmitted a substantial part of the relationship, and the indirect pathway was stronger than the direct pathway. This result means that work-life balance is associated with performance mainly when employees interpret balanced work arrangements as a positive feature of their job. Predictable schedules, limited intrusion into personal time, and reasonable recovery opportunities can improve employees' satisfaction, which in turn is associated with stronger concentration, commitment, and work continuity.

The finding is consistent with Amelia et al. (2023), Nuurramadhan and Darmastuti (2024), Prasetyo and Wardoyo (2023), and Medina-Garrido et al. (2023). For management, the coefficient pattern suggests that work-life initiatives should not be treated only as scheduling rules. Their effectiveness depends on whether employees experience them as fair, supportive, and responsive to their needs. Feasible actions include clearer expectations regarding working hours, advance notice of assignments, balanced workload distribution, and supportive communication. Because the study is cross-sectional, these results indicate statistically supported relationships rather than definitive causal effects.

Mediating Function of Job Satisfaction in the Relationship between Quality of Work Life and Employee Performance

Job satisfaction also partially mediated the relationship between quality of work life and employee performance. The direct effect of quality of work life on performance was 0.445, whereas the indirect effect through job satisfaction was 0.147. The VAF value was 24.83%, indicating complementary partial mediation. Unlike the work-life balance pathway, most of the relationship operated directly rather than through job satisfaction. This pattern reflects the practical nature of quality of work life in the agency. Fair treatment, safe working conditions, functional facilities, supportive supervision, growth opportunities, and effective social integration can directly help employees complete their duties. At the same time, these conditions may improve employees’ evaluation of their jobs, creating an additional indirect pathway through job satisfaction.

The result aligns with Alridho et al. (2024), Aulia and Yaman (2024), Siagian et al. (2024), and Nanjundeswaraswamy et al. (2024)tion is that the agency should prioritize workplace improvements that remove operational barriers while also strengthening employees' sense of fairness and support. Under fiscal-efficiency constraints, this may include protecting essential facilities, clarifying procedures, improving coordination, maintaining safety practices, and providing constructive supervision. These measures are supported by the findings, while larger recommendations involving compensation reform or extensive new programs should be presented as longer-term managerial options rather than direct

Practical Implications

The practical implications are derived directly from the strongest empirical findings. First, because quality of work life had the strongest direct relationship with employee performance (β = 0.445), agency leaders should prioritize improvements in daily work conditions, including essential facilities, work safety, coordination, clear procedures, and constructive supervision. Second, because work-life balance had the strongest relationship with job satisfaction (β = 0.537), managers should protect employees’ recovery opportunities by clarifying task priorities, distributing workloads fairly, giving earlier notice of field assignments, and reducing unnecessary Bootstrap CI p-Value Decision Direct Effects H1 Work-Life Balance → Employee Performance 0.145 2.167 [0.005, 0.270] 0.030 Accepted H2 Quality of Work Life → Employee Performance 0.445 6.386 [0.310, 0.585] <0.001 Accepted H3 Work-Life Balance → Job Satisfaction 0.537 7.133 [0.385, 0.678] <0.001 Accepted H4 Quality of Work Life → Job Satisfaction 0.404 5.473 [0.252, 0.542] <0.001 Accepted H5 Job Satisfaction → Employee Performance 0.365 4.284 [0.192, 0.526] <0.001 Accepted Mediation Effects H6 Work-Life Balance → Job Satisfaction → Employee Performance 0.196 3.596 [0.097, 0.312] <0.001 Accepted H7 Quality of Work Life → Job Satisfaction → Employee Performance 0.147 3.454 [0.067, 0.234] 0.001 Accepted Note: β represents the standardized path coefficient.

The 95% bootstrap confidence intervals do not include zero, indicating that all direct and indirect effects are statistically significant Source: SmartPLS output, 2026. after-hours communication. Third, because job satisfaction partially mediated both relationships, practical interventions should not only focus on performance outputs but also monitor employees’ satisfaction with supervision, recognition, fairness, and work conditions. These actions are feasible under fiscal-efficiency constraints because they emphasize managerial coordination and non-financial recognition rather than large new spending. Compensation reform, extensive remote-work arrangements, and large development programs may remain relevant long-term options, but they should not be presented as direct consequences of the statistical findings because their feasibility depends on regulation, job type, and available resources.

Within the fiscal-efficiency policy context, the most feasible actions are those that require limited additional expenditure. These include clarifying task priorities, distributing workloads more evenly, providing earlier notice of field assignments, reducing unnecessary after-hours communication, maintaining essential safety and work facilities, improving coordination across units, strengthening supervisory feedback, and recognising employee contributions through non-financial means. Compensation reform, extensive remote-work arrangements, and large development programs may be relevant managerial options, but they should not be presented as direct consequences of the statistical findings because their feasibility depends on regulation, job type, and available resources.

Limitations and Future Research

This study has several limitations. First, the cross- sectional design measured work-life balance, quality of work life, job satisfaction, and employee performance at one point in time. Therefore, the identified relationships should not be interpreted as definitive causal effects or as evidence of changes over time. Second, although procedural and statistical steps were used to reduce common method bias, this issue cannot be fully eliminated. Procedurally, respondents were informed that their participation was voluntary and that their identities and responses would remain confidential. The questionnaire also used neutral wording, grouped items according to their respective constructs, and emphasized that there were no right or wrong answers. Statistically, the full collinearity VIF assessment showed values below the recommended threshold, indicating that common method bias was unlikely to be a serious threat.

However, all variables were still measured using self-reported questionnaires completed by the same respondents at a single point in time. Future studies should collect data from multiple sources, separate the measurement of predictor and outcome variables over time, or include a marker variable to provide stronger evidence against common method bias. Conclusion This study found that work-life balance, quality of work life, and job satisfaction were significantly associated with employee performance among 158 operational civil servants at the South Kalimantan National Road Implementation Agency. Work-life balance had its strongest relationship with job satisfaction (β = 0.537), while quality of work life showed the strongest direct relationship with employee performance (β = 0.445). Job satisfaction was also positively associated with employee performance (β = 0.365).

The model explained 55.4% of the variance in employee performance and 46.8% of the variance in job satisfaction. Job satisfaction provided complementary partial mediation in both relationships. The indirect effect of work-life balance on employee performance was 0.196, with a VAF of 57.48%, while the indirect effect of quality of work life was 0.147, with a VAF of 24.83%. These findings support the Effort-Recovery Model and the Job Demands-Resources framework by showing that employee performance is associated with both recovery opportunities and supportive workplace resources, partly through employees’ job satisfaction. Under fiscal-efficiency constraints, feasible managerial actions include improving workload distribution, increasing schedule predictability, reducing unnecessary after-hours assignments, clarifying work procedures, strengthening supervisory feedback, improving coordination, and providing non-financial recognition.

These recommendations are limited to the empirical relationships identified in this study. The findings should not be generalized beyond operational civil servants in the single agency examined. The cross- sectional design and self-reported measures do not establish definitive causal relationships and may involve common method bias. Future research should prioritize longitudinal studies during fiscal-austerity implementation, comparisons across public agencies, the use of objective performance data, and the inclusion of employee well-being and perceived organizational support.

Conclusion

s from the study.

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