Introduction

The COVID-19 pandemic reshaped how employees relate to their work and accelerated the visibility of a workplace behaviour now widely discussed as quiet quitting. The term describes workers who continue to fulfil their formal job descriptions yet withdraw psychologically [1], limiting their effort to the contractual minimum and disengaging from discretionary contributions such as collaboration, initiative, and voluntary tasks [2]. Rather than a formal resignation, quiet quitting reflects a decline in work engagement that can quietly erode individual and organisational performance. Survey evidence has amplified this concern: a large share of the global workforce reports low emotional involvement with their jobs, signalling that reduced engagement is not marginal but widespread.

Bibliometric evidence indicates that scholarly attention to the phenomenon in human resource management has grown sharply since 2022, clustering around employee engagement, burnout, and work-life balance [3]. Conceptually, quiet quitting has been operationalised through three components—detachment, lack of initiative, and lack of motivation—captured by the Quiet Quitting Scale, which offers a reliable way to measure the phenomenon across job sectors [4]. When engagement falls broadly, organisations face lower productivity and creativity, weaker goal attainment, and a heavier burden on the remaining committed employees. Understanding the antecedents of quiet quitting is therefore of practical and theoretical importance, especially in service settings where employee behaviour directly shapes customer experience.

The local coffee shop sector in Surabaya provides a compelling context. Point-of-interest data place the city first nationally in the number of coffee outlets, and the industry is dominated by young workers who face fast-paced service, continuous customer interaction, and flexible but demanding shift systems. Central Surabaya—comprising the Tegalsari, Simokerto, Genteng, and Bubutan sub-districts—is a hub of commercial and culinary activity where these pressures are pronounced. Sustained emotional labour, fluctuating workloads, and service targets can gradually reduce engagement and heighten the tendency toward quiet quitting.

This study draws on the Job Demands–Resources (JD-R) framework, which holds that withdrawal behaviour emerges when job demands outweigh the job and personal resources available to employees [5], [6]. Within this framework, three variables are examined. Self-efficacy, the belief in one’s capability to complete tasks and overcome obstacles, functions as a personal resource that helps employees interpret pressure as a manageable challenge [7]; higher self-efficacy has also been shown to predict stronger work engagement [8]. Burnout, the syndrome of emotional exhaustion, cynicism, and reduced personal accomplishment [9], represents the depletion of resources under chronic strain and is a recognised concern among the predominantly young workforce [10]. Work-life balance reflects the extent to which employees maintain equilibrium between work and personal life, a resource that supports recovery and continued involvement.

Prior studies establish part of this picture but leave a clear gap. Research on Generation Z workers in Vietnam found work-life balance to be the strongest driver of burnout and quiet quitting intention [11]. A study of Generation Z workers in the Special Region of Yogyakarta reported that burnout and work-life balance, together with job satisfaction, jointly explained a substantial share of quiet quitting [12]. Conceptual reviews similarly frame quiet quitting as a psychological response to an imbalance between demands and resources, with burnout as a central mechanism [13], and job satisfaction and organisational justice have likewise been linked to the behaviour among Generation Z employees [14]. However, most of this evidence centres on burnout and work-life balance among general Generation Z samples, and the role of self-efficacy in relation to quiet quitting remains rarely tested. Studies focusing specifically on local coffee shop employees are also scarce in Indonesia.

Unlike previous studies that have primarily examined quiet quitting through burnout and work-life balance, this study extends the existing literature by explicitly incorporating self-efficacy as a personal resource within the Job Demands–Resources (JD-R) framework. Integrating self-efficacy with burnout as a job demand and work-life balance as a contextual resource provides a more comprehensive explanation of quiet quitting intention by capturing both personal and work-related factors. In addition, this study contributes empirical evidence from employees of local coffee shops in Central Surabaya, a service setting characterised by intensive customer interaction, high work demands, and a predominantly young workforce that has received limited attention in previous quiet quitting research.

Accordingly, this study analyses the partial and simultaneous effects of self-efficacy, burnout, and work-life balance on quiet quitting intention among local coffee shop employees in Central Surabaya. By incorporating self-efficacy alongside the more frequently studied predictors, the study aims to offer a more complete account of the personal and demand-related factors that shape quiet quitting in a high-contact service context, and to contribute empirical evidence to human resource management scholarship.

Method

This study employed a quantitative explanatory approach to test the relationships among self-efficacy (X1), burnout (X2), work-life balance (X3), and quiet quitting intention (Y). The target population consisted of employees of local coffee shops in Central Surabaya. Because no official registry records the exact number of such employees, and staffing fluctuates with operational needs, the population was treated as infinite. The Cochran formula for an unknown population was therefore used to determine the minimum sample size, with a 95% confidence level (Z = 1.96), an assumed proportion of 0.5, and an 8% margin of error, yielding a required minimum of 150 respondents.

Respondents were recruited through non-probability purposive sampling. To be eligible, an individual had to work at a local coffee shop in one of the four Central Surabaya sub-districts (Tegalsari, Simokerto, Genteng, or Bubutan), be involved in operational or customer-service activities (for example as barista, cashier, server, or kitchen crew), have at least three months of tenure, and be actively employed during the study period. Primary data were collected through a structured questionnaire distributed via Google Form, using a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5).

The instrument was developed from the operational definitions of each construct. Self-efficacy items captured employees’ confidence in mastering tasks, meeting standards, persisting under pressure, managing information, and solving work problems, consistent with efficacy theory [7]. Burnout items reflected emotional exhaustion, depersonalisation, and reduced accomplishment, following the classic burnout formulation [9]. Work-life balance items measured the perceived equilibrium between job demands and personal life, and quiet quitting intention items were adapted from the detachment, lack of initiative, and lack of motivation dimensions of the Quiet Quitting Scale [4].

Data were analysed with IBM SPSS Statistics version 31. The analysis began with validity testing using the Pearson product-moment correlation and reliability testing using Cronbach’s alpha. Classical assumption tests—normality (Normal P-Plot and the Kolmogorov–Smirnov test), multicollinearity (tolerance and variance inflation factor), and heteroscedasticity (scatterplot inspection)—were then conducted. Multiple linear regression followed, with the F-test assessing the simultaneous effect, the t-test assessing partial effects, and the coefficient of determination (R²) quantifying explanatory power. The research model is summarised in Fig. 1.

Figure 1. Research conceptual framework

Based on the framework and the reviewed literature, four hypotheses were proposed. H1: self-efficacy, burnout, and work-life balance simultaneously affect quiet quitting intention. H2: self-efficacy has a partial effect on quiet quitting intention. H3: burnout has a partial effect on quiet quitting intention. H4: work-life balance has a partial effect on quiet quitting intention.

Results and Discussion

A. Respondent Characteristics

The 150 respondents were relatively balanced by sex and dominated by young workers with short tenure, which is characteristic of the coffee shop industry and directly relevant to a phenomenon often associated with younger employees. Their profile is presented in Table 1.

Table 1. Respondent Profile (n = 150)

B. Validity and Reliability

All 49 questionnaire items were valid, with corrected item–total correlations exceeding the critical r-table value of 0.159 at the 0.05 level. Each construct also demonstrated good internal consistency, since every Cronbach’s alpha coefficient surpassed the 0.60 threshold. A summary is reported in Table 2.

Table 2. Validity and Reliability Summary

C. Classical Assumption Tests

Normality was examined through the Normal P-Plot and the Kolmogorov–Smirnov test. As shown in Fig. 2, the residual points cluster along the diagonal line, indicating a normal distribution.

Figure 2. Normal P-Plot of regression residuals

The Kolmogorov–Smirnov test confirmed this result, and the multicollinearity test showed acceptable tolerance and VIF values for all predictors, as reported in Table 3. Because every tolerance exceeds 0.10 and every VIF is below 10, the model is free of multicollinearity.

Table 3. Normality and Multicollinearity Tests

The heteroscedasticity test relied on the scatterplot of standardised predicted values against studentised residuals. In Fig. 3, the points scatter randomly above and below zero without a systematic pattern, indicating homoscedasticity. All classical assumptions were therefore satisfied, and the regression model was suitable for hypothesis testing.

Figure 3. Scatterplot for the heteroscedasticity test

D. Regression and Hypothesis Testing

Multiple linear regression produced the equation Y = 26.160 − 0.441X1 + 0.236X2 − 0.187X3 + e. The coefficients, together with the partial t-test results, appear in Table 4. Self-efficacy and work-life balance carry negative coefficients, whereas burnout carries a positive coefficient.

Table 4. Regression Coefficients and Partial t-Test

The simultaneous effect was tested with the F-test, summarised in Table 5. The F-count of 47.054 far exceeds the F-table value of 2.67, with a significance below 0.001, so H1 is accepted: the three predictors jointly influence quiet quitting intention.

Table 5. Simultaneous F-Test (ANOVA)

The coefficient of determination is reported in Table 6. The R² of 0.492 indicates that self-efficacy, burnout, and work-life balance together explain 49.2% of the variation in quiet quitting intention, while the remaining 50.8% is attributable to factors outside the model.

Table 6. Model Summary

E. Discussion

The simultaneous result confirms that quiet quitting intention is not driven by a single cause but by the interplay of employees’ confidence in their abilities, their level of exhaustion, and their capacity to balance work and personal life. This pattern is consistent with the JD-R framework, in which withdrawal behaviour arises from an imbalance between job demands and the job and personal resources available to workers [5], and with evidence that such imbalance lowers well-being and raises turnover intention [15]. The explained variance of 49.2% is close to the joint contribution reported for Generation Z workers in Yogyakarta [12], while conceptual work similarly positions quiet quitting as a resource-imbalance response [13].

The partial results add nuance. Self-efficacy exerts a negative and significant effect, meaning that employees who trust their capacity to handle demanding, high-contact service tasks are less inclined to withdraw. Interpreted through efficacy theory and the JD-R notion of personal resources, confident employees tend to frame pressure as a surmountable challenge and sustain their involvement [7], [8]. Because self-efficacy has rarely been tested directly against quiet quitting, this finding is a novel contribution, showing that self-efficacy can act as a protective personal resource.

Burnout shows a positive and significant effect and emerges as the dominant predictor. As emotional exhaustion, cynicism, and diminished accomplishment accumulate, employees appear to conserve their remaining resources by limiting engagement to the minimum [9]. This aligns with evidence linking burnout to disengagement among Generation Z workers and to quiet quitting more broadly [10], [13], reinforcing burnout as a central antecedent.

Work-life balance likewise has a negative and significant effect, indicating that better balance is associated with lower quiet quitting intention. Within JD-R and conservation-of-resources logic, balance allows employees to preserve and replenish personal resources, so demands are less likely to escalate into withdrawal. This corroborates findings from Vietnam, where work-life balance was the strongest driver of quiet quitting intention [11]. It contrasts, however, with a study whose combined model reported a positive association for work-life balance [12], a divergence plausibly linked to the long hours and shift systems typical of coffee shops, where balance is a resource whose benefits are felt more acutely; related work also shows that satisfaction- and justice-related resources shape quiet quitting in this generation [14].

Conclusion

This study advances the understanding of quiet quitting in high-contact service work by showing that, among 150 local coffee shop employees in Central Surabaya, self-efficacy, burnout, and work-life balance jointly explain 49.2% of the variation in quiet quitting intention (F = 47.054); partially, self-efficacy (t = −3.836) and work-life balance (t = −3.113) reduce quiet quitting intention while burnout (t = 6.730) increases it, with burnout the strongest driver, and these results reinforce the Job Demands–Resources perspective and imply that managers can curb quiet quitting by strengthening employees’ confidence, containing exhaustion through fair workloads and schedules, and protecting work-life balance; future research should extend the model with additional predictors such as job satisfaction, compensation, organisational support, and leadership, broaden the sampling to other regions and sectors, and further probe the still under-examined link between self-efficacy and quiet quitting.

Acknowledgment

The author thanks the local coffee shop employees in Central Surabaya who participated in the survey, as well as the academic supervisors at Universitas Pembangunan Nasional “Veteran” Jawa Timur for their guidance throughout the research.