BANGLADESH JOURNAL OF MULTIDISCIPLINARY SCIENTIFIC RESEARCH 10(4) (2025), 30-41 30 MULTIDISCIPLINARY SCIENTIFIC RESEARCH BJMSR VOL 10 NO 4 (2025) P-ISSN 2687-850X E-ISSN 2687-8518 Available online at https://www.cribfb.com Journal homepage: https://www.cribfb.com/journal/index.php/BJMSR Published by CRIBFB, USA PERSON-ORGANIZATION FIT AND JOB BURNOUT AS PREDICTORS OF QUIET QUITTING IN VOCATIONAL EDUCATION Jing Zhou (a)1 Hooi Sin Soo (b) Azelin Binti Aziz (c) (a) PhD Candidate, School of Business Management, Universiti Utara Malaysia, Sintok 06010, Kedah, Malaysia; Guizhou Communications Polytechnic University, Guiyang City 551400, Guizhou Province, China; E-mail: 13994932icepoint@gmail.com (b) Associate Professor, School of Business Management, Universiti Utara Malaysia, Sintok 06010, Kedah, Malaysia; E-mail: jennies@uum.edu.my (c) Lecturer, School of Business Management, Universiti Utara Malaysia, Sintok 06010, Kedah, Malaysia; E-mail: azelin@uum.edu.my A R T I C L E I N F O Article History: Received: 25th February 2025 Reviewed & Revised: 25th February to 16th June 2025 Accepted: 18th June 2025 Published: 20th June 2025 Keywords: Quiet Quitting, Vocational Education, Job Burnout, Work Overload, China JEL Classification Codes: M5, M540, C3, I2 Peer-Review Model: External peer review was done through double-blind method. A B S T R A C T In recent years, the phenomenon of quiet quitting, characterized by employees' psychological disengagement while continuing to meet only the minimum job requirements, has garnered increasing attention in organizational research. Despite its growing relevance, empirical studies examining this behavior within the context of vocational education remain limited, particularly in China. This study examines the relationships between person-organization fit (P-O fit), work overload, job burnout, and quiet quitting among faculty members in Chinese vocational colleges. A cross-sectional survey design was employed, and data were collected from 588 teaching staff members using structured questionnaires. Partial least squares structural equation modeling (PLS-SEM) was applied to analyze the hypothesized relationships among the variables. The results show that P-O fit is significantly and negatively associated with quiet quitting, both directly (β = –0.274, p < 0.001) and indirectly through the reduction of job burnout (β = –0.191, p < 0.001). Although work overload does not have a significant direct effect on quiet quitting (β = 0.105, p = 0.113), it exhibits a significant indirect effect through job burnout (β = 0.202, p < 0.001), which acts as a key mediating variable. Additionally, job burnout demonstrates a strong, positive relationship with quiet quitting behavior (β = 0.462, p < 0.001). These findings suggest that alignment between individuals and organizations, along with effective management of job-related strain, is key to understanding quiet quitting among vocational lecturers. This research contributes to the limited empirical literature on quiet quitting in Chinese vocational education and provides a quantitative assessment of the underlying organizational and psychological mechanisms involved. The study contributes theoretically by extending the Conservation of Resources (COR) theory, validating burnout as a mediating mechanism between organizational stressors and withdrawal behaviors in the underexplored context of Chinese vocational education. Practically, it offers actionable insights for reducing quiet quitting through improved P-O fit, balanced workload management, and early intervention for burnout. © 2025 by the authors. Licensee CRIBFB, USA. This open-access article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0). INTRODUCTION Quiet quitting has evolved into an observable yet subtle dilemma across various professional domains, including education (Serenko, 2024). Within Chinese vocational colleges, quiet quitting is emerging as an increasingly prominent concern among teaching staff, who continue to dissipate their psychological behaviour in the workplace, while only exercising the very basics of their role. Several features energize this event, behavior, and phenomenon (Li et al., 2025). In the context of vocational education in China, vocational educators are often expected to work high workloads, often in a stationary position, with administrative tasks and limited professional development opportunities, which adds layers of occupational stress and dissatisfaction (Zhang et al., 2024). Vocational teachers may also face more professional limitations in terms of institutional validation, professional prestige, and opportunities for career advancement. According to Wang and Huang (2025), the emergence of reflection, emotional drain, and management of administrative chaos, as well as limited workplace identity and forced workload expectations, creates a sense of numbness among teachers. Where educators retain draining expectations to relieve emotional strain and frustration, this can lead to job dissatisfaction and even quitting the profession 1Corresponding author: ORCID ID: 0009-0009-6090-7804 © 2025 by the authors. Hosting by CRIBFB. Peer review is the responsibility of CRIBFB, USA. https://doi.org/10.46281/c9d2ab72 To cite this article: Zhou, J., Soo, H. S., & Aziz, A. B. (2025). PERSON-ORGANIZATION FIT AND JOB BURNOUT AS PREDICTORS OF QUIET QUITTING IN VOCATIONAL EDUCATION. Bangladesh Journal of Multidisciplinary Scientific Research, 10(4), 30-41. https://doi.org/10.46281/c9d2ab72 http://creativecommons.org/licenses/by/4.0/) http://creativecommons.org/licenses/by/4.0/) https://www.openaccess.nl/en https://doi.org/10.46281/c9d2ab72 https://orcid.org/0009-0009-6090-7804 https://orcid.org/0000-0001-5283-593X https://orcid.org/0000-0003-0946-121X Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 31 (Li et al., 2021). While vocational education plays a significant role in fulfilling national economic priorities and human capital imperatives for the future, a disengaged educator workforce poses a serious threat to ensuring the quality of education, developing institutions, and student learning (Bernuzzi et al., 2025). Therefore, it is essential to systematically examine the elements and conditions that contribute to quiet quitting in this sector. Quiet quitting among vocational college teaching personnel presents substantial, multidimensional, and serious challenges (Pan et al., 2025). It creates not only personal dissatisfaction and decreased morale, but it ultimately decreases teaching quality, student engagement, and institutional performance. When teaching staff disengage from their professional obligations, they may refuse to accept responsibilities for curriculum development, student oversight and mentoring, and various academic initiatives that are crucial to establishing and sustaining a vibrant and encouraging learning environment (Lu et al., 2023). According to Lv et al. (2023), quiet quitting can also contribute to a culture of mediocrity that has the potential to undermine team cohesiveness and collective professional expectations across an institution. For institutions focused on providing supplementary learning experiences to develop students' applied skills and knowledge, widespread quiet quitting can ultimately hinder the alignment of learning objectives with labour market needs (Wei et al., 2021). At the institutional level, persistent individual quiet quitting behaviours collectively contribute to higher levels of voluntary turnover intention and absenteeism, as well as reduced retention of experienced teaching staff (J. Lu et al., 2023). These efforts exacerbate the burden on an institution's resources and ability to administrate its workforce, while limiting its ability to sustain educational quality and viability (Xueyun et al., 2023). As vocational colleges in China continue to expand in line with national policy priorities, finding solutions to the evolving quiet quitting problem is critical to protecting future institutional sustainability and educational quality. In response to this issue, this study brings together three variables — P-O Fit, work overload, and job burnout — to examine the relationships these variables have with quiet quitting behavior among vocational college teaching staff. By examining these variables, the present study addresses the critical need for empirical evidence on the organizational and psychological factors contributing to quiet quitting in Chinese vocational education. Meanwhile, investigating how these relationships interrelate is valuable for institutional leadership. In addition, the results of this study and analysis provide leaders with valuable insights into improving institutional alignment, assessing workload expectations, and fostering a working environment that enables staff to thrive. The purpose of this study was to empirically explore the direct and indirect relationships involving P-O Fit, work overload, job burnout, and quiet quitting among teaching staff in vocational colleges in China. By applying a structured empirical framework, the study aims to illustrate how P-O Fit and work overload contribute to burnout and quiet quitting and identify the processes that these two factors follow. The study contributes to an understanding of quiet quitting by exploring it within the unique context of Chinese vocational colleges, which include different institutional and socio-cultural dimensions compared to systemic issues present within corporate sectors or higher education university settings. By considering both organization-level and individual-level psychological variables, the study provides practitioners with a comprehensive perspective on employee disengagement, rather than simply an employee displaying job dissatisfaction. Furthermore, the discussion section presents the findings in the context of previous studies, while the conclusion outlines the study's implications in both theoretical and practical terms. LITERATURE REVIEW P-O Fit plays a critical role in shaping employee attitudes and behaviors in today’s dynamic work environment (Tsemach & Barth, 2023). When employees perceive alignment between their personal values, skills, and the organization’s culture and expectations, they are more likely to remain engaged and committed to their roles. Conversely, a lack of fit can result in decreased motivation, job dissatisfaction, and difficulty performing effectively (Serenko, 2024). In such cases, quiet quitting—characterized by minimal discretionary effort and emotional detachment—often emerges as a passive form of disengagement. This behavior, although subtle, can have significant implications for organizational performance, particularly when no immediate replacements are available (Foltz et al., 2025). Recognizing this, many organizations have begun prioritizing the alignment of individual capabilities with organizational needs to reduce quiet quitting (Xueyun et al., 2023). When employees experience a strong sense of fit, their engagement increases, and the likelihood of quiet quitting diminishes. Work overload is widely recognized as a key factor that negatively affects employee motivation and performance (Wang et al., 2022). When employees face excessive workloads, they often experience stress and disengagement, which may lead to quiet quitting—a behavior where individuals reduce their effort and psychological investment without formally resigning. Although training and support from human resources are essential, it is challenging to address each employee’s needs individually under high-pressure conditions (Kothari et al., 2021). Conversely, when work is distributed fairly and remains within manageable limits, employees tend to show higher engagement and improved performance (Liu, 2020). However, unequal or excessive workloads may push employees toward burnout and withdrawal (Prentice et al., 2025). Therefore, work overload may significantly contribute to the occurrence of quiet quitting. When employees perceive a poor fit between their attributes and the organization's expectations—such as mismatched skills, values, or goals—they are more likely to experience job burnout(Xueyun et al., 2024). A lack of alignment between employee competencies and job demands often leads to frustration, reduced motivation, and emotional exhaustion. In contrast, when employees feel supported and experience a strong sense of person-organization fit, they are more motivated to improve their skills and contribute meaningfully to their roles (Gabelaia & Bagociunaite, 2024). Low motivation and disengagement not only diminish individual performance but also heighten the risk of burnout over time (M. Lu et al., 2023). Therefore, fostering a positive work environment that promotes alignment between employee capabilities and organizational expectations is crucial to preventing burnout and supporting sustainable performance (Perveen et al., Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 32 2025). Work overload is a significant factor contributing to reduced employee productivity and increased job burnout (Fang et al., 2024). When employees are consistently assigned tasks that exceed their capacity or fall outside their job descriptions, their motivation tends to decline, leading to emotional exhaustion and a decrease in performance. In contrast, maintaining reasonable workload expectations enables employees to stay focused and productive. Additionally, motivation plays a crucial role in helping employees cope with demanding work conditions by encouraging skill development and resilience (Thu Trang & Thi Thu Trang, 2024). When employees are empowered and supported through training, guidance, and a balanced workload, they are better equipped to manage stress and avoid burnout (Jeilani & Hussein, 2025). Therefore, excessive work demands without adequate support can significantly increase the likelihood of job burnout. Job burnout, characterized by emotional exhaustion, reduced personal accomplishment, and depersonalization, significantly impairs employees’ effectiveness and engagement at work (Soren & Ryff, 2023). Employees experiencing burnout are more likely to disengage from their roles, which may manifest as quiet quitting—a passive form of withdrawal marked by minimal effort and psychological detachment. This phenomenon presents a growing challenge for organizations, as it often occurs without explicit communication, making it difficult for management to respond in a timely and supportive manner. Enhancing employee performance through skills development and behavioral support is essential to maintaining productivity (Engle et al., 2024). Moreover, fostering positive behavioral change through motivation and organizational support can mitigate the adverse effects of burnout (Farahmandpour & Voelkel, 2025). Thus, job burnout may serve as a key predictor of quiet quitting behavior. When employees perceive a poor fit between their personal values, skills, and the characteristics of their job, it often leads to reduced motivation, lower performance, and diminished productivity (Gone et al., 2025). Such misalignment can foster dissatisfaction and emotional exhaustion, which are core components of job burnout (Gundlach, 2025). In turn, employees experiencing burnout are more likely to psychologically withdraw from their roles, exhibiting quiet quitting behaviors characterized by minimal engagement and effort. While some may eventually leave the organization, others remain physically present but disengaged, posing significant management challenges (Henderson et al., 2024; Khan et al., 2021). This decline in employee commitment and cooperation ultimately affects organizational performance. Given this dynamic, job burnout may serve as a key psychological mechanism linking person-organization misfit to quiet quitting. Work overload poses a significant challenge to employees, often resulting in reduced productivity and impaired job performance. When employees are overwhelmed by excessive demands and lack sufficient motivation or resources, they struggle to meet job expectations effectively. Inadequate organizational support further exacerbates this issue, making it challenging for employees to maintain their performance under pressure. To address these challenges, management must provide targeted support and consider redesigning job roles to align with employee capabilities and reduce unnecessary burden (Gillison et al., 2023). Without such interventions, persistent work overload can lead to emotional exhaustion and job burnout, conditions that may prompt employees to adopt quiet quitting as a coping response. Thus, job burnout may serve as a mediating mechanism through which work overload influences quiet quitting behavior. The review of existing studies highlighted that there are mixed and unclear findings regarding the relationship among P-O fit, work overload, job burnout, and quitting. Hence, the purpose of this study was to investigate the relationships between person-organization fit, work overload, job burnout, and quitting. To achieve this purpose, the following hypotheses are developed. H1: There is a relationship between P-O Fit and quiet quitting. H2: There is a relationship between work overload and quiet quitting. H3: There is a relationship between P-O Fit and job burnout. H4: There is a relationship between work overload and job burnout. H5: There is a relationship between job burnout and quiet quitting. H6: Job burnout mediates between P-O Fit and quiet quitting. H7: Job burnout mediates between work overload and quiet quitting. The relationships based on the hypotheses are drawn in the model of this study, shown in Figure 1. Figure 1. Research Model Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 33 MATERIALS AND METHODS In this study, data from the population (lecturers) were collected from 9 vocational colleges from eastern, central, and western China, all with differing levels of economic development and distribution of teaching resources. In anticipation of the formal survey, a pilot study was conducted further to refine the questionnaire's quality before data collection. The study initially collected data from 61 lecturers and then adjusted the data based on the issues raised during the pilot study. This study employed cluster sampling, where data were collected randomly. Krejcie and Morgan (1970) established the minimum sample size requirement of 384 people in their table for sample size determination when the population exceeds 10,000. The data collection for this study occurred from March to May 2025. The teacher development centers of the nine vocational colleges were approached via phone and email, and they were requested to distribute the questionnaires. Each college contacted by the research team employed a random sampling approach, selecting a list of their own chosen number of lecturers based on the minimum sample size of this study. The colleges distributed the link to the online questionnaire on the Questionnaire Star platform randomly through on-campus distribution channels. During the final data collection, a total of 588 questionnaires were returned in the formal study. The sample size for each college was proportionate to the college's representation in the total sample, ensuring the sample's representativeness and a reasonable allocation of samples from each college. The Teacher Development Center assisted with data collection surveys in each college, and participants (lecturers) were selected randomly from the college's faculty list. Additionally, in some colleges, the questionnaire was distributed through WeChat, while others were approached via email. Each questionnaire was sent anonymously, allowing for sample diversity and reliability. To ensure sample accuracy and relevance, the colleges were the first to identify themselves from the sample, and only individual teachers from the recognized colleges were allowed to proceed with the questionnaire. After the questionnaire data collection was completed, the research team promptly downloaded and backed up the sample data, screened out invalid questionnaires, and maintained the identity and integrity of the sample data. The outlined method of operation provided a means of enhancing study data quality and research reliability, laying a firm foundation of unquestioned confidence and robustness for all subsequent analysis. All measurements were based on a Likert scale. The P-O-Fit scale was adapted from the Person-Organization Fit Scale (POFs) proposed by Cable and DeRue (2002). However, the work overload scale was adapted from the ROS scale by Peterson et al. (1995). Moreover, the job burnout scale used the MBI-General Survey (MBI-GS), which was more relevant to the Chinese cultural context (Wu et al., 2021). Finally, the quiet quitting of lecturers was measured using the QQ scale developed by Anand et al. (2024). This study utilized IBM SPSS 26 and SmartPLS 4 for data analysis. First, the demographic data was analyzed at the first point. Furthermore, measurement model assessment and structural model assessment were conducted to evaluate the reliability of the data and examine the relationship between the research variables. RESULTS This study used IBM SPSS 26 to analyze the demographic data. The demographic profile reported in Table 1 shows that the sample was predominantly female, with women comprising 67% (n = 394) of the respondents, while men accounted for 33% (n = 194). This gender imbalance may reflect broader trends in the vocational education workforce, where female educators are more prevalent. Regarding marital status, a substantial majority of the participants (76%, n = 449) reported being married, followed by 18% (n = 107) who identified as single, and 5% (n = 32) who selected "Other," potentially indicating widowed, divorced, or other non-specified statuses. Educational attainment among respondents was relatively high. The majority held a Master's degree (62%, n = 366), while 28% (n = 162) had obtained a Bachelor's degree. A smaller proportion had completed doctoral studies, with PhD holders representing 8% (n = 48), and an additional 2% (n = 12) reported other qualifications. In terms of professional experience, the most common range was 10 to 15 years of teaching, reported by 36% (n = 211) of participants. Those with less than five years of experience comprised 24% (n = 141), and 22% (n = 129) had between five and ten years of experience. Fewer respondents reported longer tenures, with 14% (n = 80) indicating 15–20 years and only 5% (n = 27) having 20–25 years of teaching experience. Regarding academic rank, "Senior Lecturer" was the most frequently reported title (40%, n = 237), followed by "Associate Professor" (32%, n = 187). Lecturers constituted 15% (n = 85) of the sample, while Professors made up a relatively small proportion (5%, n = 32). An additional 8% (n = 47) fell into the "Other" category, indicating roles that may not align with the conventional academic hierarchy. Finally, the geographical distribution of respondents was skewed towards Eastern China, where 65% (n = 381) of the vocational colleges were located. Western China accounted for 20% (n = 119) of the sample, and Central China represented the remaining 15% (n = 88). This regional imbalance may reflect the institutional focus of the research or the actual distribution of vocational institutions across the nation. Table 1. Demographics Variable Category Frequency Percentage Gender Male 194 33% Female 394 67% Marriage Status Married 449 76% Single 107 18% Other 32 5% Educational Level PhD (Doctorate) 48 8% Master's Degree 366 62% Bachelor's Degree 162 28% Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 34 Other 12 2% Years of teaching experience Less than 5 years 141 24% 5-10 Years 129 22% 10-15 Years 211 36% 15-20 Years 80 14% 20-25 Years 27 5% Academic Titles Lecturer 85 15% Senior Lecturer 237 40% Associate Professor 187 32% Professor 32 5% Other 47 8% The region where your vocational college is located Eastern China 381 65% Central China 88 15% Western China 119 20% The data from this study were analyzed using SmartPLS 4 to assess the measurement model and determine convergent validity. It is based on the four-factor assessment. Initially, the investigation of factor loadings was conducted. In the reflective measurement model, indicators with loadings below 0.70 are considered for deletion. However, this study found that all indicators were above 0.70 (Hair et al., 2011). Hence, the reliability of the individual item was significantly established in this study. Secondly, the study analyzed the Cronbach's alpha findings to test the reliability of the instruments. Thirdly, composite reliability was also assessed to evaluate the reliability of the individual instruments. The findings of both should be above 0.70 (Hair et al., 2011) for significant reliability of the instruments. The study found that the value for all variables was less than the recommended threshold. Hence, the reliability of the individual item was significantly achieved. Moreover, the study investigated the average variance extracted to confirm convergent validity. According to Hair et al. (2011), the value for average variance extracted above 0.50 is considered significant. Hence, the study found that convergent validity was significantly established, as the data reported in the study are reliable and significant (see Table 2 and Figure 2). Figure 2. Measurement Model Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Table 2. Convergent Validity Construct Indicators Factor Loadings Cronbach's alpha Composite reliability Average variance extracted JB JB1 0.851 0.955 0.961 0.735 JB2 0.860 JB3 0.859 JB4 0.840 JB5 0.850 JB6 0.908 Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 35 JB7 0.881 JB8 0.851 JB9 0.812 POF POF1 0.802 0.898 0.921 0.660 POF2 0.796 POF3 0.798 POF4 0.824 POF5 0.809 POF6 0.844 QQ QQ1 0.811 0.936 0.948 0.725 QQ2 0.732 QQ3 0.874 QQ4 0.897 QQ5 0.864 QQ6 0.894 QQ7 0.877 WO WO1 0.870 0.955 0.965 0.847 WO2 0.922 WO3 0.955 WO4 0.922 WO5 0.932 Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Next, the study performed an analysis for discriminant validity. This analysis is used to assess discrimination in the data collected from the research instruments. In this study, two methods are employed to assess discriminant validity. Initially, the study employed the Heterotrait-Monotrait (HTMT) method for assessing discriminant validity. According to Henseler et al. (2015), an HTMT value below 0.85 indicates acceptable discriminant validity. The findings reported in Table 3 confirmed that HTMT was significantly achieved, indicating that the variables of this research have data that establish significant discriminant validity. Table 3. Discriminant Validity – HTMT Construct JB POF QQ WO JB POF 0.575 QQ 0.703 0.599 WO 0.592 0.322 0.470 Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Moreover, the study used the findings of cross-loadings to confirm discriminant validity. For the assessment of discriminant validity with cross-loadings, the study investigated whether the loadings of one variable's indicators are greater than those of other variables correlated with it. The findings shown in Table 4 confirmed that the cross-loadings were significantly established (Hair et al., 2011). Hence, the study found no issues related to discriminant validity in the data. Table 4. Cross-loadings Indicators JB POF QQ WO JB1 0.851 -0.427 0.463 0.692 JB2 0.860 -0.445 0.463 0.643 JB3 0.859 -0.442 0.473 0.562 JB4 0.840 -0.420 0.483 0.516 JB5 0.850 -0.392 0.534 0.481 JB6 0.908 -0.529 0.687 0.457 JB7 0.881 -0.476 0.686 0.385 JB8 0.851 -0.522 0.671 0.359 JB9 0.812 -0.589 0.684 0.348 POF1 -0.373 0.802 -0.446 -0.199 POF2 -0.379 0.796 -0.424 -0.216 POF3 -0.381 0.798 -0.382 -0.190 POF4 -0.404 0.824 -0.409 -0.248 POF5 -0.450 0.809 -0.466 -0.253 POF6 -0.630 0.844 -0.567 -0.396 QQ1 0.527 -0.412 0.811 0.378 QQ2 0.478 -0.420 0.732 0.357 QQ3 0.584 -0.452 0.874 0.376 QQ4 0.622 -0.530 0.897 0.488 QQ5 0.607 -0.535 0.864 0.400 QQ6 0.621 -0.550 0.894 0.365 QQ7 0.553 -0.432 0.877 0.345 WO1 0.382 -0.157 0.273 0.870 WO2 0.557 -0.321 0.479 0.922 WO3 0.553 -0.334 0.448 0.955 Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 36 WO4 0.498 -0.294 0.380 0.922 WO5 0.590 -0.327 0.468 0.932 Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Meanwhile, the study also examined the findings of the variance inflation factor (VIF) to identify multicollinearity issues in the data. These issues are evident in the data when the independent variables are highly correlated with each other. However, if the VIF value for all variables is found to be less than 3.3, it confirms that no multicollinearity issues are present in the data. The findings of Table 5 confirm that all variables received the VIF values less than 3.3 (Hair et al., 2011). Hence, the study found no issues with multicollinearity in the research data. Table 5. Multicollinearity Assessment Construct JB QQ JB 1.920 POF 1.115 1.442 WO 1.115 1.485 Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Furthermore, the findings of the structural equation model were used to test the hypotheses and examine the relationships between the research variables. First, job burnout was found to have a strong and statistically significant positive effect on quiet quitting (β = 0.462, t = 6.156, p < 0.001), indicating that higher levels of burnout are associated with increased tendencies toward quiet quitting behaviors. This suggests that burnout plays a critical role in shaping disengagement and withdrawal intentions in the workplace. Secondly, P-O Fit exhibited a significant negative relationship with both job burnout and quiet quitting. Specifically, P-O Fit negatively predicted job burnout (β = -0.413, t = 10.068, p < 0.001), implying that better alignment between individual and organizational values reduces burnout. Additionally, P-O Fit had a significant adverse direct effect on quiet quitting (β = -0.274, t = 5.552, p < 0.001), suggesting that a strong P-O Fit may directly mitigate tendencies toward disengagement, beyond its indirect effect via burnout. On the other hand, work overload showed a significant positive relationship with job burnout (β = 0.439, t = 11.152, p < 0.001), supporting the idea that excessive workload substantially contributes to employee burnout. However, its direct path to quiet quitting was not statistically significant (β = 0.105, t = 1.583, p = 0.113). This indicates that while work overload may not directly lead to quiet quitting, its influence on such behavior may be mediated through job burnout. The findings of direct paths are reported in Table 6 and Figure 3. Figure 3. Structural Model Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Table 6. Direct Paths Direct Paths Original sample Standard deviation T statistics P values JB -> QQ 0.462 0.075 6.156 0.000 POF -> JB -0.413 0.041 10.068 0.000 Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 37 POF -> QQ -0.274 0.049 5.552 0.000 WO -> JB 0.439 0.039 11.152 0.000 WO -> QQ 0.105 0.066 1.583 0.113 Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Furthermore, the mediating hypotheses were tested with structural equation modeling. The indirect path from P-O Fit to quiet quitting via job burnout was found statistically significant and negative (β = -0.191, t = 5.177, p < 0.001). This result suggests that part of the influence of P-O Fit on quiet quitting is mediated through its effect on job burnout. Specifically, when individuals perceive a more substantial alignment between their values and those of the organization, they experience lower levels of burnout, which in turn reduces their propensity to engage in quiet quitting. This highlights job burnout as a significant mediator, suggesting that improving organizational fit can indirectly mitigate disengagement by alleviating burnout. Similarly, the indirect path from work overload to quiet quitting via job burnout was positive and statistically significant (β = 0.202, t = 4.296, p < 0.001). This finding demonstrates that work overload contributes to quiet quitting behaviors indirectly by increasing job burnout. While the direct effect of work overload on quiet quitting was not significant, this result confirms that its impact is entirely mediated through burnout. In other words, an excessive workload may not directly cause employees to disengage, but it significantly raises burnout levels, which subsequently lead to quiet quitting. The findings of indirect paths are reported in Table 7. Table 7. Indirect Paths Indirect Paths Original sample Standard deviation T statistics P values POF -> JB -> QQ -0.191 0.037 5.177 0.000 WO -> JB -> QQ 0.202 0.047 4.296 0.000 Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting The study ultimately analyzed the data to assess its predictive relevance. The findings in predictive relevance confirm the predictive power of the research model. For this purpose, the study used the PLS blindfolding method to assess Q2. The value of Q2 above 0 is considered significant for appropriate predictive relevance. The findings reported in Table 8 and Figure 4 confirm that the Q2 value for dependent variables was above 0. Hence, it was confirmed that the model of study has a significant predictive power. Figure 4. Predictive Relevance Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 38 Table 8. Predictive Relevance Construct SSO SSE Q² JB 5292 3449.111 0.348 POF 3528 3528 0.000 QQ 4116 2612.643 0.365 WO 2940 2940 0.000 Note. POF = Person Organization Fit, WO = Work Overload, JB = Job Burnout and QQ = Quiet Quitting This study systematically addressed its research objectives through direct path testing and mediation effect analysis. A total of five direct hypotheses and two indirect hypotheses were proposed. Except for H2, all were statistically supported, demonstrating the model’s strong explanatory power and validating the hypothesized relationships among the variables. Table 9 summarizes the results of the hypothesis testing. Table 9. Testing Hypotheses Hypotheses Path Relationships Results H1 P-O Fit → Quiet Quitting Supported H2 Work Overload → Quiet Quitting Not Supported H3 P-O Fit → Job Burnout Supported H4 Work Overload → Job Burnout. Supported H5 Job burnout → Quiet Quitting Supported H6 P-O Fit →Job Burnout→ Quiet Quitting Supported H7 Work Overload→ Job Burnout → Quiet Quitting Supported DISCUSSIONS This study aimed to investigate the relationships among P-O Fit, work overload, job burnout, and quiet quitting among lecturers in Chinese vocational colleges. Drawing on COR theory and employing PLS-SEM, the study tested seven hypotheses, yielding results that offer both theoretical insights and practical implications. The findings provided strong support for most of the hypothesized relationships, with H1, H3, H4, H5, H6, and H7 being statistically confirmed, while H2 was not. H1 posited a negative relationship between P-O Fit and quiet quitting. The results confirmed a significant and negative direct effect (β = -0.274, p < 0.001), indicating that higher alignment between individual and organizational values directly reduces the likelihood of disengagement. This finding aligns with Farahmandpour and Voelkel (2025), who noted that well-matched skills and values enhance employee attitudes and reduce withdrawal behaviors. H2, which hypothesized a positive relationship between work overload and quiet quitting, was not statistically supported (β = 0.105, p = 0.113). This contrasts with Fernández-Arias et al. (2024), who found that increased workload can escalate withdrawal behavior. One possible post hoc explanation is that in the vocational education context, high workloads may be normalized, and faculty may not perceive them as sufficient cause for immediate disengagement unless accompanied by emotional exhaustion. Alternatively, institutional pressure or concerns about job security may suppress overt withdrawal responses. H3 and H4 explored antecedents of job burnout. P-O Fit was negatively related to job burnout (β = -0.413, p < 0.001), supporting H3 and reinforcing findings by Wang et al. (2022) and Gabelaia and Bagociunaite (2024), who suggested that alignment enhances intrinsic motivation and buffers emotional strain. H4 was also supported, as work overload significantly predicted higher burnout levels (β = 0.439, p < 0.001), confirming studies by Fang et al. (2024) and Dong et al. (2025) on the psychological cost of excessive demands. H5 was strongly supported, showing that job burnout positively predicts quiet quitting (β = 0.462, p < 0.001). This highlights burnout as a key proximal antecedent of psychological disengagement. The result confirms prior research by Emir et al. (2023) and Fang et al. (2024), who found that burnout is a precursor to reduced emotional commitment and discretionary effort. The findings also affirmed the mediating role of job burnout in both paths: H6 confirmed that job burnout mediates the relationship between P-O Fit and quiet quitting (β = -0.191, p < 0.001). This suggests that P-O Fit not only directly reduces disengagement but also does so indirectly by lowering emotional exhaustion. This is consistent with Drouin- Rousseau et al. (2024), who emphasized the motivational benefits of value alignment. H7 revealed that work overload indirectly contributes to quiet quitting through job burnout (β = 0.202, p < 0.001). Although the direct path was non- significant, this mediation path suggests a full mediation effect, meaning that the experience of burnout is the channel through which excessive workload leads to disengagement. This supports Drüge et al. (2021) and Dymecka et al. (2024), who observed that the psychological toll of overload often manifests through burnout symptoms before behavioral withdrawal. Overall, these findings suggest that P-O Fit serves as a protective factor, directly and indirectly reducing quiet quitting, while work overload primarily influences job burnout. The central role of burnout as a mediating mechanism aligns with the Conservation of Resources theory, which posits that resource depletion—whether caused by misfit or overexertion—leads individuals to withdraw as a psychological coping mechanism. The mixed support for the direct effect of work overload suggests that workload alone may not be sufficient to trigger quiet quitting unless it threatens psychological resources. Conversely, P-O Fit and organizational support appear critical in preserving employee engagement. These results Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 39 contribute to a growing body of literature on disengagement behaviors in non-Western academic contexts, providing practical insights for human resource policies. Vocational institutions may mitigate quiet quitting by enhancing organizational-personal alignment, promoting realistic workload management, and addressing signs of burnout through proactive interventions. CONCLUSIONS The purpose of this study was to investigate the relationships between person-organization fit, work overload, job burnout, and quitting. Therefore, this research sheds light on the existing empirical literature on the antecedents of quiet quitting by outlining the importance of P-O Fit, work overload, and job burnout as predictor variables of quiet quitting behaviors of teaching staff in the context of vocational colleges in China. The findings illustrate the role of P-O Fit in terms of a significant pessimistic prediction of quiet quitting, both directly and indirectly through job burnout. However, these findings demonstrate that values congruence between an employee and an organization can be a necessary factor in reducing disengagement. On the other hand, this study highlights that the role work overload plays in quiet quitting is also noteworthy. While it was not a statistically significant direct predictor of quiet quitting, it had a significant indirect effect through job burnout, illustrating that burnout serves as a mediator between excessive workload and withdrawal. Moreover, the research also supports existing literature by demonstrating that P-O Fit has a buffering effect on job burnout while work overload has the opposite effect. According to the findings, what is perhaps even more important, however, is that job burnout was also the most significant predictor of quiet quitting, emphasizing its salient role in vocational education contexts as opposed to traditional higher education settings. Therefore, the implications of this research for institutional management and policy are significant, as it illustrates that the quality of organizational aspects, namely P-O Fit, and effective management of workload demands can potentially reduce burnout and, hence, disengagement. From a theoretical perspective, this research makes valuable contributions to the literature on employee disengagement by adding to the discussion on quiet quitting in the limited studied context of vocational education, particularly in China. Before this research, most studies on quiet quitting have focused on company employees and healthcare staff contexts. This study has contributed to the literature by highlighting the lack of research on teaching staff in vocational colleges. Nevertheless, the involvement of teaching staff in vocational college institutions raises the possibility that work stressors and organizational reactivity differ substantially. The findings enhance the literature by identifying P-O Fit and job burnout as predictors of quiet quitting tendencies among Chinese vocational college teaching staff, presenting evidence on how both work organizational fit and employee wellbeing are related to the phenomenon of quiet quitting. Additionally, the study identifies a more straightforward indirect path from work overload to quiet quitting via job burnout. Therefore, this study provides a finding that reinforces job burnout as a critical intermediary psychological response and mediating variable when examining withdrawal behaviors and cognitions. Furthermore, by contextualizing these relationships in Chinese vocational institutions, the research has produced culture-specific values to address the lack of international literature on employee disengagement in non-Western educational contexts. For the practical implications, the negative relationship between P-O Fit and quiet quitting suggests that institutions should focus their recruitment, selection, and retention strategies on personnel who align with the organization. Furthermore, initiatives that include structured onboarding processes, value-based hiring practices, and ongoing organizational socialization would reinforce P-O Fit and decrease disengagement behaviour. Moreover, the study identified job burnout as an important variable that influences quiet quitting. It is essential to note that work overload was an indirect contributor to quiet quitting, with burnout serving as a mediating factor. Consequently, vocational colleges in China should introduce workload management strategies that ensure expectations do not exceed the teaching and administrative load capacity of the staff. Moreover, policies that support the workplace environment, such as flexible scheduling, mental health initiatives, and professional development opportunities, can help better manage burnout issues that may be occurring in the workplace. Moreover, these findings confirm that educational leaders need to be aware of employee wellbeing. Additionally, it is essential to foster an open communication environment in academic settings that enables leaders to engage in candid dialogue with employees when signs of burnout or disengagement emerge. The practical implications of this study suggest that to eliminate quiet quitting in vocational colleges, educational institutions should address both organizational and psychological issues affecting employees simultaneously. This study focused on teaching staff at Chinese vocational colleges. It examined the effects of P-O Fit and work overload on quiet quitting, with job burnout as a mediating variable. Although the research provides both theoretical and practical insights, several limitations should be noted. First, the sample was drawn exclusively from vocational colleges in China, which may limit the generalizability of the findings to other educational settings, such as universities or primary and secondary schools. Second, the study employed a cross-sectional design, which restricts the ability to capture the dynamic and causal relationships among variables over time. Third, although the mediating role of job burnout was confirmed, other potential moderators, such as perceived organizational support, psychological resilience, or professional identity, were not examined. Author Contributions: Conceptualization, J.Z., H.S.S. and A.B.A.; Methodology, H.S.S.; Software, J.Z.; Validation, J.Z., H.S.S. and A.B.A.; Formal Analysis, J.Z.; Investigation, J.Z.; Resources, J.Z.; Data Curation, J.Z.; Writing – Original Draft Preparation, J.Z., H.S.S. and A.B.A.; Writing – Review & Editing, J.Z.; Visualization, J.Z.; Supervision, H.S.S. and A.B.A.; Project Administration, H.S.S. and A.B.A.; Funding Acquisition, J.Z. All authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement: Ethical review and approval were waived for this study, as the research does not involve vulnerable groups or sensitive issues. Funding: Authors received no funding for this research. Zhou el al., Bangladesh Journal of Multidisciplinary Scientific Research 10(4) (2025), 30-41 40 Acknowledgment: We extend our sincere appreciation to all participants who contributed to this study. 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Exploring relationships of job satisfaction and burnout with turnover intention among Chinese English language teachers. The Asia-Pacific Education Researcher, 33(3), 587-601. https://doi.org/10.1007/s40299-023-00755-9 APPENDICES Appendix A: Measurement Questionnaire Person-Organization Fit There is congruence between my own values and the values of the university I work for. In this university, there is congruence between my own values and the values of the other lecturers. In this university, there is congruence between my own values and the values of the head of department. In this university, there is congruence between my own values and the characteristics of the work I perform. In this university, there is congruence between my personal expectations and provided opportunities. In general, I am highly fit with my university. Work Overload I have been given too many responsibilities at work. The amount of work I have to do interferes with the quality of life I want to maintain. I feel overburdened by my work. I feel there is a need to reduce some aspects of my work. In general, my workload is severely overloaded. Job Burnout I feel emotionally drained from my work. I feel used up at the end of the workday. I feel tired when I get up in the morning and have to face another day at work. Working all day is really a strain for me. I feel burned out from my work. I have become more callous toward work since I took this job. I have become less enthusiastic about my work. I doubt the significance of my work. I have become more and more indifferent to the contribution of my work. In general, I am feeling increasingly burned out in my work. Quiet Quitting I am doing the bare minimum work to avoid being fired. I feel that I lack interest in attending meetings. I often avoid working more hours unless there is additional pay. I feel there is a lack of passion and enthusiasm in me to work above and beyond. I feel there is a lack of opportunities to learn and grow at my university. I feel there is a lack of meaningfulness at work. Generally, I prefer quiet quitting at work. Publisher’s Note: CRIBFB stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. © 2025 by the authors. Licensee CRIBFB, USA. This open-access article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0). Bangladesh Journal of Multidisciplinary Scientific Research (P-ISSN 2687-850X E-ISSN 2687-8518) by CRIBFB is licensed under a Creative Commons Attribution 4.0 International License. https://doi.org/10.1080/19368623.2024.2389074 https://doi.org/10.1108/JKM-10-2022-0792 https://doi.org/10.3390/ijerph20166570 https://doi.org/10.1080/23311975.2024.2371549 https://doi.org/10.1177/17411432231212288 https://doi.org/10.1016/j.cedpsych.2021.102030 https://doi.org/10.1080/02188791.2023.2183489 https://doi.org/10.1007/s10643-021-01232-y https://doi.org/10.1080/13548506.2020.1778750 https://doi.org/10.1038/s41598-023-42591-3 https://doi.org/10.1038/s41598-023-42591-3 https://doi.org/10.1080/1528008X.2024.2393336 https://doi.org/10.1007/s40299-023-00755-9 http://creativecommons.org/licenses/by/4.0). http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/