How Perceived Supervisor and Organizational Support Shape Job Satisfaction: The Intervening Role of Work-Life Balance and Organizational Identification ()
1. Introduction
In today’s dynamic and high-pressure work environments, ensuring employee job satisfaction has become a strategic imperative for organizations worldwide (Lee et al., 2025a). This priority is particularly critical in the banking sector, where employees frequently confront intense workloads, extended working hours (Karatepe et al., 2019), ambitious performance targets (Lee & Han, 2020), and continuous customer-facing interactions (Mehmood et al., 2020). These occupational demands often contribute to elevated stress levels, which in turn can erode job satisfaction (Karatepe et al., 2019; Lee & Han, 2020). In Bangladesh, where over 145,000 employees are employed across more than forty private commercial banks (Bangladesh Bank, 2024), understanding the antecedents of job satisfaction is not merely an academic exercise but a practical necessity for managing workforce sustainability and well-being.
Job satisfaction, broadly defined as an employee’s emotional evaluation of their job roles, recognition, and growth opportunities, has long been recognized as a foundational driver of key organizational outcomes, including employee retention, engagement, and performance (Judge et al., 2001; Locke, 1969). In high-intensity sectors, such as banking, where emotional exhaustion is prevalent, supportive organizational conditions are crucial in mitigating stress and promoting employee satisfaction (Schaufeli & Bakker, 2004). Two critical constructs in this context are Perceived Organizational Support (POS) and Perceived Supervisory Support (PSS), which represent employees’ beliefs regarding the extent to which their organization and direct supervisors value their contributions and care about their well-being (Eisenberger et al., 1986; Eisenberger et al., 2002). These perceptions are central to employee morale and motivation and are instrumental in fostering psychological safety and emotional attachment to the workplace (Loi et al., 2006; Tang & Tsaur, 2016).
Although the individual effects of POS and PSS on employee outcomes have been widely studied within the framework of Organizational Support Theory (OST), recent scholarship highlights a significant gap in understanding how these two forms of support jointly influence job attitudes, such as satisfaction (Siddiqi et al., 2024). This gap is particularly pronounced in emerging economies, where cultural values and organizational dynamics can influence the perceived effectiveness and interplay of support systems (Agarwal et al., 2012; Lamprinou et al., 2021). Addressing this void, the current study examines how both POS and PSS impact job satisfaction in Bangladesh’s private banking sector and elucidates the mechanisms and boundary conditions that govern these relationships. Specifically, we examine work-life balance (WLB) as a key mediating variable. WLB refers to an individual’s perceived ability to effectively manage work and personal life demands with minimal conflict (Allen et al., 2000; Clark, 2000). In labor-intensive environments, such as banking, the presence of work-life balance (WLB) supportive policies and practices has been positively linked to psychological well-being and job satisfaction (Bloom et al., 2006). However, empirical studies that explore work-life balance (WLB) as a mediator in the relationship between organizational support and job satisfaction remain limited, especially in non-Western contexts where work-life dynamics are shaped by different socio-cultural expectations (Lamprinou et al., 2021).
In addition, this study introduces Organizational Identification (OI) as a moderating variable. OI reflects the degree to which employees psychologically identify with and internalize their organization’s values and successes (Mael & Ashforth, 1992). Drawing on Social Identity Theory (SIT), we argue that high organizational identification can amplify the positive effects of work-life balance on job satisfaction, as employees perceive work-life balance (WLB) initiatives as aligned with their group identity and values (Abrams & Hogg, 1988; van Dick & Haslam, 2012). This moderated mediation framework allows us to capture the complex interplay between structural supports, work-life balance perceptions, and organizational identity in shaping job satisfaction outcomes.
Taken together, this study makes a meaningful contribution to both organizational behavior and human resource management research. In four significant ways, this study makes several key contributions to the literature. First, by simultaneously examining POS and PSS, the study offers an integrated perspective on their relative and combined influence on job satisfaction, addressing ongoing calls for more comprehensive models of employee support (Siddiqi et al., 2024). Second, it introduces WLB as a mediating mechanism that explains how support perceptions translate into attitudinal outcomes, enriching theoretical insights into employee well-being and satisfaction (Islam et al., 2021). Third, by incorporating OI as a moderator, the study highlights the critical role of identity processes in enhancing or attenuating the effects of organizational practices. Finally, the research extends the applicability of OST and SIT to a developing country context, thereby contributing to the global discourse on employee support and satisfaction in underexplored economies such as Bangladesh (Ali et al., 2021; Islam et al., 2021; Siddiqi et al., 2024).
2. Literature Review and Hypothesis Development
2.1. Perceived Organizational and Supervisor Support
Perceived organizational support (POS) and perceived supervisory support (PSS) represent two interrelated but distinct facets of perceived support within the workplace, reflecting institutional and relational sources of care and concern (Lee & Shin, 2023). POS, initially conceptualized by Eisenberger et al. (1986), refers to “employees’ belief that organizations value their continued contributions and genuinely care for their well-being” (p. 501). A growing body of research suggests that individuals who perceive higher organizational support tend to report stronger emotional attachment and trust in their organization (Jones‐Carmack, 2019; Loi et al., 2006). For instance, Lajom et al. (2025) emphasize that employees who perceive high levels of organizational support tend to believe that resources such as performance feedback, career development opportunities, and emotional or social support are readily available to them—thus enhancing their job satisfaction (Abu-Tineh et al., 2023; Cao et al., 2024; Guenther et al., 2025).
Conversely, perceived supervisory support (PSS) constitutes a key dimension of social support in the workplace and refers to the extent to which employees believe that their immediate supervisors value their work, care about their well-being, and provide consistent support (Cole et al., 2006; Eisenberger et al., 2002; Tang & Tsaur, 2016). Supervisors play a pivotal role as agents of the organization (Levinson, 1965), and their behaviors significantly shape employees’ perceptions of the organization itself. Positive supervisory interactions often foster more favorable employee attitudes toward the organization, while negative experiences can produce the opposite effect. For example, Tillman et al. (2018) found that abusive supervision was associated with diminished hope and lower affective commitment among employees. Their study also highlighted the role of job autonomy in enhancing job satisfaction, suggesting that workplace dynamics mediated by supervisors have significant implications for employee attitudes.
Despite extensive research highlighting the individual importance of POS and PSS in shaping workplace outcomes (Lipponen et al., 2004; Paterson et al., 2014), there remains a notable gap in studies that examine their joint or comparative influence on job satisfaction—particularly in emerging economies. Recent research by Siddiqi et al. (2024) highlights this deficiency, noting the lack of integrated studies that examine how both organizational and supervisory support impact critical job outcomes, such as employee satisfaction. Addressing this gap, the current study explores the simultaneous effects of POS and PSS on job satisfaction, contributing to a more comprehensive understanding of workplace support dynamics.
2.2. POS and PSS on Job Satisfaction
Job satisfaction refers to employees’ overall emotional evaluation of their job and work-related experiences, encompassing elements such as job roles, interpersonal relationships, recognition, and opportunities for advancement (Fernández-Macias & Muñoz de Bustillo Llorente, 2014). As a core construct in organizational behavior, job satisfaction has a significant influence on key outcomes, including employee turnover (Jogi et al., 2025), work engagement (Gutierrez et al., 2025), and productivity (Hoboubi et al., 2017). In labor-intensive and high-pressure sectors like banking ensuring employee satisfaction becomes both a strategic and operational priority. Prior research suggests that job satisfaction in such environments is shaped not only by extrinsic rewards or role clarity, but also by relational and environmental factors, such as perceived support and recognition (Ashraf, 2019; Bulińska-Stangrecka & Bagieńska, 2021).
Among the key antecedents of job satisfaction, perceived organizational support (POS) stands out for its robust and consistent positive influence. POS reflects the degree to which employees believe their organization values their contributions and genuinely cares about their well-being (Eisenberger et al., 1986). By enhancing psychological safety and meeting employees’ socio-emotional needs, POS fosters motivation and loyalty. Organizations that provide developmental resources, equitable reward systems, transparent communication, and supportive work environments cultivate trust, goal alignment, and affective commitment, ultimately boosting job satisfaction (Karatepe & Aga, 2016; Kurtessis et al., 2017). Numerous empirical studies have affirmed that POS is associated with higher satisfaction levels, lower burnout, and greater retention—particularly in service-oriented and high-demand sectors (Huang et al., 2021).
Similarly, perceived supervisor support (PSS) plays a critical role in shaping employees’ daily work experiences. PSS refers to employees’ perceptions that their immediate supervisors are supportive, accessible, and genuinely concerned about their professional and personal well-being (Kim & Lee, 2009). Supervisors who offer constructive feedback, emotional encouragement, and developmental guidance not only help mitigate workplace stress but also foster stronger employee-supervisor relationships—key determinants of satisfaction (O’Donoghue & Tsui, 2015). In emotionally taxing fields such as human services and banking, PSS has been found to reduce emotional exhaustion and strengthen commitment and satisfaction (Eisenberger et al., 2002; Hyrkäs et al., 2006). The relational and proximal nature of PSS makes it particularly influential in the day-to-day work context, serving as a practical complement to more systemic forms of organizational support.
These relationships are grounded in Organizational Support Theory (OST), which posits that employees develop generalized beliefs about the degree to which their organization values their input and cares for their well-being (Eisenberger et al., 1990; Eisenberger et al., 1986). Underpinned by Social Exchange Theory (Blau, 1964), OST suggests that employees reciprocate perceived support through positive attitudes and behaviors, including enhanced organizational commitment, job involvement, and satisfaction (Rhoades & Eisenberger, 2002). Organizational support fulfills fundamental socio-emotional needs—such as esteem, affiliation, and approval—thereby promoting psychological safety and a stronger sense of belonging (Kurtessis et al., 2017). Furthermore, because supervisors often function as agents of the organization, their behavior significantly shapes employees’ broader perceptions of organizational support (Shanock & Eisenberger, 2006). These perspectives suggest that both POS and PSS are critical antecedents of job satisfaction, especially in demanding organizational contexts. Based on the preceding discussion, the following hypotheses are proposed:
H1: Perceived Organizational Support (POS) positively affects Job Satisfaction (JS).
H2: Perceived Supervisor Support (PSS) positively affects Job Satisfaction (JS).
2.3. The Mediating Role of Work-Life Balance
Work-life balance (WLB) is a crucial determinant of job satisfaction, particularly in environments characterized by high demands and performance pressure. It refers to a state of equilibrium wherein individuals can successfully manage both work and personal responsibilities with minimal role conflict (Allen et al., 2000; Clark, 2000). A well-maintained work-life balance reduces psychological strain and enhances overall well-being, thereby contributing positively to employees’ attitudes toward their jobs (Kamboj, 2024). In service-intensive sectors, such as banking—where long working hours, strict targets, and high client interaction are common—access to work-life balance (WLB) practices significantly improves employees’ perceptions of job quality and satisfaction (Bloom, 2009).
Extant research has consistently demonstrated a strong link between work-life balance and job satisfaction across a wide range of occupational and national contexts (Inegbedion, 2024; Susanto et al., 2022). Employees who feel they can effectively manage both professional and personal demands tend to experience reduced emotional exhaustion, improved mood, and higher job satisfaction (Ko et al., 2013). Studies conducted in Sweden, China, and Nigeria further support the relevance of Work-Life Balance (WLB) in the banking sector, where it has been shown to enhance employee satisfaction and reduce burnout (Amah, 2009; Deng & Gao, 2017). These findings reinforce the view that WLB not only functions as a stress buffer but also serves as a mechanism through which support resources are translated into positive job-related outcomes.
Work-life balance is shaped not only by formal policies such as flexible scheduling, telework, and paid leave (Greenhaus et al., 2012; Trefalt, 2013) but also by the perceived support from both organizations and supervisors. Studies suggest that Perceived Organizational Support (POS) encourages the use of work-life benefits and fosters trust, leading to improved job satisfaction (Eisenberger et al., 1986; Rhoades & Eisenberger, 2002; Swody & Powell, 2007). Similarly, Perceived Supervisor Support (PSS) enhances employees’ willingness to utilize work-life policies by mitigating the fear of judgment or career penalties (Kim & Mullins, 2016; Thompson et al., 1999). Blair-Loy and Wharton (2002) found that supervisor support is even more crucial than family obligations in predicting the actual usage of WLB policies. Thus, employee support serves as a precursor to the utilization of work-life policies, which in turn leads to improved employee attitudes, such as increased job satisfaction. Employees who experience high POS and PSS are more likely to feel empowered to maintain a work-life balance, resulting in more positive work experiences and increased satisfaction (Grover & Crooker, 1995; Swanberg et al., 2011; Valcour et al., 2011).
Based on Organizational Support Theory (Eisenberger et al., 1990; Eisenberger et al., 1986), employees who perceive high levels of support from both their organizations and supervisors internalize the belief that their well-being is valued. These beliefs foster trust, promote psychological safety, and increase the likelihood that employees will adopt WLB practices. In turn, an effective work-life balance contributes to enhanced job satisfaction by reducing strain, improving mood, and increasing perceptions of job quality (Halpern, 2005; Kurtessis et al., 2017). Drawing on this logic, we present the following hypothesis:
H3: POS positively affects WLB
H4: PSS positively affects WLB
H5: WLB positively affects JS
H6: POS positively affects JS through WLB
H7: PSS positively affects JS through WLB
2.4. Moderating Role of Organizational Identity
Organizational Identification (OI) has emerged as a pivotal psychological construct in understanding how employees connect with their organizations and interpret organizational practices (Ma et al., 2023). It is defined as a perceived sense of “oneness” with the organization and the internalization of its successes and failures as one’s own (Mael & Ashforth, 1992). OI reflects the degree to which employees align their self-concept with organizational membership (Mael & Ashforth, 1992). Such identification fosters a shared sense of identity and belonging in the workplace, promoting resilience, commitment, and cooperative behavior in response to organizational demands or changes (Bandura, 1969; Teng et al., 2020).
This identification becomes particularly important when employees evaluate organizational supports such as work-life balance (WLB) practices. Employees with strong organizational identification tend to internalize organizational values and feel a greater sense of alignment with the company’s goals (Efraty & Wolfe, 1988; Kehoe & Wright, 2013). As a result, they are more likely to interpret WLB initiatives not only as functional benefits but also as signals of shared organizational care and commitment. This enhances the motivational impact of WLB by making it personally meaningful, which leads to deeper emotional engagement and self-determined behavior (Ryan & Deci, 2000). Individuals who experience such alignment often report higher psychological fulfillment and are more likely to be committed to organizational life beyond contractual obligations (Mageau et al., 2009; Vallerand, 2003).
Organizational identification plays a significant role in enhancing job satisfaction by transforming employees’ interpretation of organizational treatment and resources (Christ et al., 2003; Riketta, 2005; van Dick & Haslam, 2012). When WLB practices are offered in a context of strong OI, employees are likely to perceive these efforts as genuine expressions of support, leading to greater satisfaction with their roles and the organization as a whole (Christ et al., 2003; van Dick & Haslam, 2012). Such employees are more resilient in facing work-related stressors and enjoy access to psychological and social resources, including collegial support and shared coping mechanisms (Haslam et al., 2009). In turn, this facilitates not only the experience of well-being but also the development of trust and satisfaction in the workplace (Riketta, 2005). This discussion is also relatable through the lens of Social Identity Theory (SIT) by Turner and Tajfel (1986). According to SIT, individuals derive their self-concept from their membership in social groups, such as organizations, and this group identification influences cognition, motivation, and behavior. Through this lens, OI acts as a filter that shapes how employees perceive and emotionally respond to organizational practices. Employees with high OI are more likely to interpret WLB as supportive of their group identity and as aligned with their personal values, thus intensifying the positive effect of WLB on job satisfaction (Abrams & Hogg, 1988; Tyler & Blader, 2003). In contrast, those with low identification may regard such practices with suspicion or detachment, thereby weakening the intended positive outcomes. So based on this, it can be hypothesized that:
H8: OI positively moderates the indirect effect of WLB on JS (Figure 1).
Figure 1. Conceptual model.
3. Methods
3.1. Participants and Procedure
According to the Bangladesh Bank (2024), Bangladesh’s banking sector employs approximately 214,245 individuals, with 145,583 working in 43 private commercial banks. This study employed a cross-sectional survey design and utilized convenience sampling to collect data from full-time employees of a major private commercial bank operating across five major cities which includes, Dhaka, Rajshahi, Chittagong, Khulna, and Sylhet. Data collection was conducted over a three-month period from July to September 2024.
To ensure broad reach and enhance response rates, both online and offline data collection methods were used. Prior to data collection, formal permission was obtained from the bank’s Human Resource Manager, who provided a list of eligible full-time employees. Participants were randomly selected from this list. For branches in remote or hard-to-access areas, the survey was administered online using Google Forms, which were distributed via email and WhatsApp groups. In urban and semi-urban branches, printed questionnaires were distributed and collected in person during working hours.
To establish face and content validity, the survey instrument was reviewed by two university faculty members in management and four senior bank professionals, ensuring relevance to the industry and local context. A pilot study involving 17 employees from a Dhaka-based branch was conducted to assess the clarity and contextual appropriateness of the items. The instrument demonstrated high internal consistency, with Cronbach’s alpha values ranging from 0.846 to 0.949.
To reduce common method bias (Podsakoff et al., 2003), the data collection was conducted in four phases spaced two weeks apart. A total of 1000 questionnaires were distributed, comprising 600 printed and 400 online versions. Printed surveys were administered by five trained research assistants who facilitated distribution, explained the study’s purpose, addressed respondents’ queries, and ensured prompt collection. Online participants received frequent reminders to encourage them to complete the task.
In total, 432 responses were received from the offline survey and 244 from the online survey, resulting in a combined response rate of 67.6%. After screening for incomplete or inconsistent responses, 634 valid questionnaires were retained for final analysis. Regarding the sample profile, 62.8% of respondents were male (n = 398) and 37.2% female (n = 236). A large majority were married (n = 531; 83.8%) and primarily aged between 30 and 35 years. Most respondents had between 3 and 7 years of tenure in their current organization. In terms of education, 37.4% (n = 237) held a master’s degree or higher, 51.3% (n = 325) had a bachelor’s degree, and 11.4% (n = 72) reported other qualifications, such as a Higher Secondary Certificate.
3.2. Measures
A five-point Likert scale was used to measure the questionnaire, with response options ranging from 1 (strongly disagree) to 5 (strongly agree). Perceived Organizational Support was measured using four items from the survey of perceived organizational support (SPOS) developed by Eisenberger et al. (1986) (α = 0.846). A sample item is “My organization really cares about my well-being”. Perceived Supervisor Support was measured in the same manner as has been done in many other studies (e.g., DeConinck & Johnson, 2009; Rhoades et al., 2001). By following the Prior research, we also substituted the word “supervisor” for “organization” in the SPOS (α = 0.867). A sample item is “My supervisor takes great pride in accomplishments”. To measure Work-life balance, this study used a total eight-item scale adapted from Judge et al. (1994) and Syrek et al. (2011) (α = 0.949). A sample item, “Flexible working options are available to me if needed”. Job satisfaction was evaluated using five items measured developed by Churchill Jr et al. (1974), and the sixth item (If I had to do it all over again, I would choose another job) was accommodated by Hunt et al. (1985) (α = 0.873). A sample item is “I feel that my job is valuable”. For Assessing Organizational Identification, Saks and Ashforth (1997) used six-item scales (α = 0.893). A sample item is, “This enterprise’s successes are my successes.” Following the empirical investigation (Roy et al., 2023; Roy et al., 2024), employees’ education, age, gender, marital status, and job tenure were considered as control variables.
3.3. Data Analytical Strategy
The data analysis was conducted in four sequential stages: preliminary analysis, descriptive statistics, confirmatory factor analysis (CFA), and hypothesis testing. In the preliminary stage, data were screened to ensure suitability for structural equation modeling (SEM), following established guidelines (Ahmad et al., 2021; Islam et al., 2021). Frequency tests were conducted to detect missing values, and Mahalanobis distance tests were employed to identify and remove multivariate outliers. Normality tests were also performed to assess the distribution of variables and ensure that key assumptions of SEM were met. The second stage involved descriptive analysis, including the computation of means and standard deviations for all latent constructs, offering a preliminary understanding of central tendencies and dispersion within the dataset. In the third stage, confirmatory factor analysis (CFA) was performed using AMOS software with the maximum likelihood estimation method. This step evaluated the adequacy of the measurement model by examining factor loadings, model fit indices, and construct validity, ensuring that observed variables effectively represented their underlying latent constructs. Finally, in the hypothesis testing stage, the bootstrapping method with 5,000 resamples was employed to assess the significance of direct, indirect, and moderating effects at a 95% confidence interval. Bootstrapping enabled the robust estimation of standard errors and confidence intervals, eliminating the need for normality assumptions and thereby enhancing the accuracy of parameter estimation (Byrne, 2016).
4. Results
4.1. Preliminary Analysis
The initial phase of analysis involved data screening and assumption testing to ensure the robustness of subsequent statistical procedures. First, the dataset was examined for missing values and their distribution patterns, as non-random missing data can threaten the validity of the findings (Sekaran, 2016). Of the 676 responses initially collected, 34 exhibited randomly missing values and were excluded from further analysis. Next, the remaining 639 responses were subjected to outlier detection using Mahalanobis distance, applying a significance threshold of p < 0.000. This procedure identified 5 multivariate outliers, which were subsequently removed (Kline, 2011), resulting in a final sample of 634 valid responses. Normality assumptions were then assessed by evaluating skewness and kurtosis values for all measured variables. The results indicated that all values were within acceptable thresholds (±1 for skewness and ±3 for kurtosis), suggesting that the data were approximately normally distributed (Byrne, 2016). Lastly, to address concerns regarding common method variance (CMV), multiple statistical techniques were employed. First, Harman’s single-factor test was conducted as recommended by Podsakoff et al. (2003), revealing that the first unrotated factor accounted for only 26.3% of the total variance—well below the 50% threshold—indicating that CMV was not a significant threat (Fuller et al., 2016). Second, confirmatory factor analysis (CFA) was used to compare the fit of a one-factor model, in which all items were loaded onto a single factor, with the hypothesized five-factor model. The one-factor model showed poor fit (CFI = 0.45, TLI = 0.406, RMSEA = 0.16, SRMR = 0.186), while the five-factor model demonstrated excellent fit (CFI = 0.988, TLI = 0.987, RMSEA = 0.024, SRMR = 0.032). The large and significant chi-square difference (Δχ2 = 5566.671, Δdf = 10) further supports the discriminant validity of the constructs and suggests that common method bias is unlikely to compromise the findings (Podsakoff et al., 2003; Williams et al., 1989). Finally, a latent common method factor was added to the CFA model to test for the presence of method variance. The comparison between the baseline model (χ2 = 464.451, df = 340) and the model including the latent method factor (χ2 = 464.451, df = 339) revealed no difference in model fit (Δχ2 = 0.000, Δdf = 1). This non-significant change indicates that the inclusion of the latent factor did not account for substantial additional variance, further confirming that common method variance is unlikely to have significantly influenced the results.
4.2. Descriptive and Confirmatory Factor Analysis
To evaluate the measurement model, both descriptive and confirmatory factor analyses were conducted. The results of the confirmatory factor analysis are presented first in Table 1. The hypothesized five-factor model was tested and compared with several alternative models, including four-factor, three-factor, two-factor, and one-factor solutions. Following the guidelines of Hair Jr et al. (2010), Kline (2011), and Hu and Bentler (1999), model fit was assessed using multiple indices. The five-factor model demonstrated a good fit to the data, with χ2/df = 1.366, CFI = 0.988, TLI = 0.987, RMSEA = 0.024, and SRMR = 0.032. These values fall well within the accepted thresholds, indicating that the five-factor structure provided a superior representation of the data compared to the alternative, more parsimonious models. Thus, the factorial distinctiveness of the study constructs was supported.
Following the assessment of model fit, we examined construct reliability and convergent validity, as shown in Table 2. All standardized factor loadings were above the recommended threshold of 0.50, indicating that each item was a good indicator of its respective latent variable. Composite reliability (CR) values ranged from 0.847 to 0.950, exceeding the minimum acceptable value of 0.70. Similarly, the average variance extracted (AVE) values ranged from 0.535 to 0.702, surpassing the threshold of 0.50. These results confirm the internal consistency and convergent validity of the measurement model, ensuring that the latent constructs were measured reliably and with sufficient explanatory power.
Descriptive statistics and discriminant validity results are reported in Table 3. The mean and standard deviation for each construct were as follows: Perceived Organizational Support (M = 3.70, SD = 0.863), Perceived Supervisor Support (M = 3.58, SD = 0.953), Work-Life Balance (M = 3.48, SD = 1.05), Job Satisfaction (M = 3.83, SD = 0.828), and Organizational Identification (M = 4.42, SD = 0.645). Discriminant validity was assessed using the Fornell-Larcker criterion and the Heterotrait-Monotrait ratio (HTMT). The square roots of AVE for each construct were greater than their inter-construct correlations, supporting discriminant validity. Additionally, all HTMT values were below the conservative threshold of 0.85, confirming that each construct was empirically distinct from the others.
Table 1. Confirmatory factor analysis.
Model |
Fit Indices |
χ2 |
df |
χ2/df |
CFI |
TLI |
RMSEA |
SRMR |
Null model |
10700.763 |
378 |
|
|
|
|
|
One-factor model |
6031.122 |
350 |
17.232 |
0.45 |
0.406 |
0.16 |
0.186 |
Two-factor model |
4580.295 |
349 |
13.124 |
0.59 |
0.556 |
0.138 |
0.165 |
Three-factor model |
3382.806 |
347 |
9.749 |
0.706 |
0.68 |
0.118 |
0.137 |
Four-factor model |
1493.144 |
344 |
4.341 |
0.889 |
0.878 |
0.073 |
0.070 |
Five-factor model |
464.451 |
340 |
1.366 |
0.988 |
0.987 |
0.024 |
0.032 |
Note: CFI = Comparative Fit Index; TLI = Tucker-Lewis index; RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Root Mean Squared Residual; POS = Perceived organizational support; PSS = Perceived supervisor support; WLB = Work life balance; JS = Job satisfaction; OI = Organizational Identification; Five-factor model: Baseline model; Four-factor model: POS and PSS were combined into one factor; Three-factor model: POS and PSS were combined into one factor and WLB and OI were combined into another factor; Two-factor model: POS, PSS, WLB and OI were combined into one factor; One-factor model: All variables combined.
Table 2. Factor loading, Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE).
Factors & Items |
Loading |
Cronbach’s alpha |
CR |
AVE |
Perceived Organizational Support |
|
0.846 |
0.847 |
0.58 |
POS1 |
0.810 |
|
|
|
POS2 |
0.789 |
|
|
|
POS3 |
0.726 |
|
|
|
POS4 |
0.719 |
|
|
|
Perceived Supervisor Support |
|
0.867 |
0.867 |
0.62 |
PSS1 |
0.768 |
|
|
|
PSS2 |
0.791 |
|
|
|
PSS3 |
0.786 |
|
|
|
PSS4 |
0.805 |
|
|
|
Work Life Balance |
|
0.949 |
0.95 |
0.702 |
WLB1 |
0.872 |
|
|
|
WLB2 |
0.851 |
|
|
|
WLB3 |
0.845 |
|
|
|
WLB4 |
0.839 |
|
|
|
WLB5 |
0.843 |
|
|
|
WLB6 |
0.834 |
|
|
|
WLB7 |
0.833 |
|
|
|
WLB8 |
0.786 |
|
|
|
Job Satisfaction |
|
0.873 |
0.873 |
0.535 |
JS1 |
0.802 |
|
|
|
JS2 |
0.752 |
|
|
|
JS3 |
0.707 |
|
|
|
JS4 |
0.665 |
|
|
|
JS5 |
0.758 |
|
|
|
JS6 |
0.698 |
|
|
|
Organizational Identification |
|
0.893 |
0.893 |
0.582 |
OI1 |
0.794 |
|
|
|
OI2 |
0.769 |
|
|
|
OI3 |
0.720 |
|
|
|
OI4 |
0.727 |
|
|
|
OI5 |
0.798 |
|
|
|
OI6 |
0.768 |
|
|
|
Note: POS = Perceived organizational support; PSS = Perceived supervisor support; WLB = Work life balance; JS = Job satisfaction; OI = Organizational Identification; CR = Composite reliability and AVE = Average variance extracted.
Table 3. Mean, standard deviation, correlations.
Variables |
M |
SD |
POS |
PSS |
WLB |
JS |
OI |
POS |
3.7027 |
0.86393 |
0.761 |
0.312 |
0.123 |
0.246 |
0.136 |
PSS |
3.5808 |
0.95364 |
0.312 |
0.787 |
0.14 |
0.206 |
0.018 |
WLB |
3.4819 |
1.05151 |
0.124 |
0.14 |
0.837 |
0.29 |
0.198 |
JS |
3.8341 |
0.82805 |
0.246 |
0.206 |
0.29 |
0.731 |
0.39 |
OI |
4.4185 |
0.64527 |
0.137 |
0.019 |
0.199 |
0.391 |
0.762 |
Note: N = 634, Underlined and bold elements in diagonal are the square root of AVE. Values below the diagonal elements are the correlations between constructs. Italicized values above diagonal elements are the HTMT ratios. SD = Standard Deviation; POS = Perceived organizational support; PSS = Perceived supervisor support; WLB = Work life balance; JS = Job satisfaction; OI = Organizational Identification.
4.3. Hypothesis Testing
The study examined the structural model using 5000 bootstraps to test the hypotheses (see Table 4). The results indicated that Perceived Organizational Support (POS) and Perceived Supervisor Support (PSS) have a positive influence on Job Satisfaction (JS) (β = 0.117 SE = 0.043, p < 0.01); (β = 0.127, SE = 0.041, p < 0.01) and Work-Life Balance (WLB) (β = 0.132, SE = 0.062, p < 0.05); (β = 0.139, SE = 0.062, p < 0.05). Additionally, WLB was found to have a positive influence on JS (β = 0.113, SE = 0.03, p < 0.01), supporting H1-H5 of the study.
Table 4. Results of hypothesis testing.
Variables |
|
Bootstraps at 95% |
β |
C. R |
LL CI |
UL CI |
POS -> JS |
0.117** |
0.043 |
0.036 |
0.215 |
PSS -> JS |
0.127** |
0.041 |
0.052 |
0.209 |
POS -> WLB |
0.132* |
0.062 |
0.012 |
0.265 |
PSS -> WLB |
0.139* |
0.06 |
0.021 |
0.259 |
WLB -> JS |
0.113** |
0.03 |
0.053 |
0.175 |
Indirect effect |
|
|
|
|
POS -> WLB -> JS |
0.015* |
0.009 |
0.002 |
0.037 |
PSS -> WLB -> JS |
0.016* |
0.008 |
0.003 |
0.04 |
Moderation analysis |
|
|
|
|
WLB |
0.113** |
0.03 |
0.053 |
0.175 |
OI |
0.469** |
0.053 |
0.374 |
0.567 |
WLB*OI -> JS |
0.211** |
0.049 |
0.129 |
0.297 |
Note: *p < 0.05, **p < 0.01. POS = Perceived organizational support; PSS = Perceived supervisor support; WLB = Work life balance; JS = Job satisfaction; OI = Organizational Identification; SE = Standard error; CR = Critical ratio; BC = Bias-corrected; CI = Confidence interval.
To test the mediating role of Work-Life Balance, the indirect effect between Perceived Organizational Support (POS) and Perceived Supervisor Support (PSS) on job satisfaction (JS) was examined. The beta coefficient between POS and JS (β = 0.117**) and PSS and JS (β = 0.127**) was multiplied by the beta coefficient between WLB and JS (β = 0.113*), resulting in an indirect path of POS-WLB-JS (β = 0.015, p < 0.05) and PSS-WLB-JS (β = 0.016, p < 0.05). The confidence interval for the indirect effect of POS-WLB-JS (LL = 0.002, UL = 0.037) and PSS-WLB-JS (LL = 0.003, UL = 0.04) did not contain zero, indicating the presence of mediation, thus supporting H6 and H7 (Figure 2).
The study also explored the moderating role of Organizational Identification (OI) on the relationship between Work-Life Balance (WLB) and Job Satisfaction (JS) by computing an interaction term (WLB × OI). This interaction term was regressed with JS and showed a significant positive effect (β = 0.211, SE = 0.049, p < 0.01, UL = 0.297, LL = 0.129), confirming the presence of moderation. Simple slopes analysis (Figure 3) showed that the positive relationship between WLB and JS was stronger for individuals with high OI. In contrast, for individuals with low OI, the relationship was weak and slightly negative. Specifically, employees with high OI experienced a significant increase in JS when WLB was high, while those with low OI showed little to no improvement in JS under the same conditions. This suggests that OI amplifies the positive effects of WLB on JS, thus supporting H8.
Figure 2. Structural model.
Figure 3. Slope of moderation.
5. Discussion
5.1. Summary of Results
Drawing upon organizational support theory (Eisenberger et al., 1990) and social identity theory (Turner & Tajfel, 1986), this study explored how perceived organizational support (POS) and perceived supervisory support (PSS) influence job satisfaction (JS), with work-life balance (WLB) serving as a mediating mechanism and organizational identification (OI) as a moderator. The findings aligned closely with our theoretical predictions. Both POS and PSS demonstrated significant positive associations with JS, reaffirming prior empirical evidence that supportive organizational and supervisory environments enhance employee satisfaction. Furthermore, WLB was found to significantly mediate the effects of both POS and PSS on JS, indicating that employees’ perceptions of balance between professional and personal life are a critical psychological pathway through which support translates into satisfaction. These results align with prior studies that emphasize the mediating role of WLB (e.g., Ghasemy et al., 2021; Ko et al., 2013; Pinnington et al., 2024; Valcour et al., 2011). Importantly, the results also provided support for the hypothesized moderated mediation model: the indirect effects of POS and PSS on JS via WLB were significantly stronger when employees reported high levels of OI. This suggests that organizational identification amplifies the psychological benefits of support and work-life balance, leading to enhanced job satisfaction. Employees who closely align their identity with their organization appear more likely to interpret organizational and supervisory support as meaningful and congruent with their values, thereby experiencing greater fulfillment in their roles.
5.2. Theoretical Contribution
This study offers several important theoretical contributions to the existing literature on organizational support, work-life balance, and job satisfaction. By drawing upon Organizational Support Theory (Eisenberger et al., 1990) and Social Identity Theory (Turner & Tajfel, 1986) and integrating these with recent developments in the understanding of motivational and identity-based mechanisms, our study advances a more comprehensive framework to explain how employees experience and respond to organizational support mechanisms.
First, our study extends Organizational Support Theory by emphasizing the mediating role of work-life balance (WLB) in the relationship between perceived organizational support (POS) and job satisfaction (JS), as well as between perceived supervisory support (PSS) and JS. While prior research has shown the direct effects of POS and PSS on JS (Ghasemy et al., 2021; Pinnington et al., 2024), limited attention has been paid to the mediating processes that explain the support perceptions translate into attitudinal outcomes (Siddiqi et al., 2024). By identifying work-life balance (WLB) as a key psychological mechanism in this linkage, our findings suggest that organizational and supervisory support enhances employees’ ability to balance work and personal life, which in turn leads to higher job satisfaction.
Second, this study reframes work-life balance (WLB) not merely as a passive outcome of organizational support, but as an interpretive lens through which employees assess and describe the meaning of organizational actions. This perspective is also consistent with the prior literature, e.g., Susanto et al. (2022); Inegbedion (2024). When perceived organizational and supervisory support is high, employees are more likely to view work-life balance (WLB) practices as authentic signals of care and respect (Lee & Shin, 2023). This perception enables WLB to function as a psychological mechanism that transforms structural support into enhanced job satisfaction by fostering feelings of trust, belonging, and organizational value (Filiz et al., 2024; Gorenak et al., 2020; Top et al., 2013).
Third, and most significantly, our study introduces organizational identification (OI) as a boundary condition that moderates the strength of the indirect relationship between perceived organizational support (POS) or perceived supervisory support (PSS) and job satisfaction (JS) via work-life balance (WLB). While Social Identity Theory emphasizes that employees derive part of their self-concept from their organizational membership (Turner & Tajfel, 1986), recent systematic reviews, such as Rovetta et al. (2025), indicate that the interaction between identity processes and organizational practices has been primarily explored within manufacturing, healthcare, and technology sectors, with limited attention in other domains such as banking and financial services (Rovetta et al., 2025). Our study addresses this gap by empirically demonstrating that high levels of OI strengthen the positive influence of WLB on JS, suggesting that employees’ identification with the organization intensifies the perceived authenticity and relational value of WLB initiatives. These findings are consistent with prior research, which shows that OI enhances the interpretation of organizational practices across a range of employee outcomes. For instance, higher levels of OI have been associated with reduced turnover intentions (Yao et al., 2025), increased organizational citizenship behaviors (Hameli & Yaslioglu, 2025), and greater innovation productivity (Lee et al., 2025b), further validating the role of identity-based mechanisms in shaping attitudinal and behavioral outcomes at work.
Furthermore, this study contributes to the understanding of moderated mediation models in organizational behavior. By empirically validating that OI moderates the indirect effects of POS and PSS on JS via WLB, we provide a more refined theoretical model that reflects the conditional nature of psychological processes at work. This aligns with recent calls in the literature from Siddiqi et al. (2024), who emphasized the versatility of POS and PSS in predicting a range of organizational outcomes.
Finally, this study contributes to bridging the gap between macro-level organizational practices and micro-level employee outcomes by elucidating the psychological and identity-based mechanisms that underpin this linkage. By doing so, it advances theoretical discourse on how organizational support systems translate into meaningful attitudinal responses among employees.
5.3. Practical Implications
The findings of this study offer several practical implications for the banking sector in Bangladesh and similar emerging economies. While public discourse in the South Asian continent has often focused on issues such as digital technology adoption, digital transformation, and financial inclusion (Muduli & Choudhury, 2024), there has been limited attention paid to the psychosocial and organizational factors affecting bank employees’ well-being and satisfaction (Rovetta et al., 2025; Siddiqi et al., 2024). In this regard, our study provides a framework for human resource practitioners and bank administrators to understand how employees’ job satisfaction is influenced by perceived organizational support (POS) and perceived supervisory support (PSS), with work-life balance (WLB) functioning as a key explanatory mechanism.
Given the competitive and high-pressure environment in commercial banks, where employees often face long hours and performance-driven targets, ensuring a healthy work-life interface is increasingly essential to reduce stress (Suhartini & Nurnadjamuddin, 2023). This study suggests that when employees perceive strong organizational and supervisory support, they are more likely to experience a better balance between work and personal life, which in turn enhances their job satisfaction. Human resource departments should, therefore, consider developing targeted initiatives such as flexible scheduling, wellness programs, and family-supportive policies that can help employees manage competing work and non-work demands more effectively (Suhartini & Nurnadjamuddin, 2023).
Training programs should also be implemented to equip supervisors with skills in empathetic leadership, communication, and conflict management. Supervisors who are able to understand and respond to the individual needs of their subordinates are more likely to foster a positive psychological climate, encouraging trust, motivation, and satisfaction at work (Calluso & Devetag, 2025; Jaiswal & Dhar, 2017; Kauppila, 2025).
Moreover, the moderating role of organizational identification (OI) found in this study suggests that employees who feel a strong sense of belonging and alignment with their organization are more receptive to work-life balance (WLB) initiatives and are more likely to interpret them as sincere expressions of care. To strengthen OI, banks can engage in practices such as involving employees in strategic conversations, recognizing individual contributions, and reinforcing shared values through internal communications and leadership behavior (Jun et al., 2025). Furthermore, a well-balanced psychological contract supported by clear organizational identity signals can promote deeper emotional engagement, thereby benefiting both employees and the institution through sustained satisfaction, commitment, and resilience in the workplace.
5.4. Limitation and Future Direction
The present study has several limitations that provide opportunities for future research. First, past studies have often relied on cross-sectional designs to predict causality (Spector, 2019). Therefore, future research should consider employing longitudinal studies to establish causal relationships with greater confidence.
Second, there is the potential for sampling bias. The participants in this study were selected using a convenience sampling method from a limited number of commercial banks in Bangladesh. This may not fully represent the diverse population of banking employees across various institutions or regions. Future research should aim to use more probabilistic sampling techniques to enhance the generalizability of the findings across the wider banking workforce. Additionally, as the study relied exclusively on self-reported data for all constructs, there is a risk of response biases, including social desirability and common method variance. Incorporating multiple-source data, such as supervisor assessments, peer evaluations, or objective performance metrics, could enhance measurement validity and reduce the likelihood of bias.
Third, the current research focused exclusively on job satisfaction as the primary outcome variable. While job satisfaction is a crucial attitudinal outcome, future researchers may consider extending the proposed model to include other important variables, such as work motivation, self-efficacy, subjective well-being, and organizational loyalty. This would enable a more comprehensive understanding of how supportive organizational climates impact a broader range of employee-related outcomes and psychological states (Siddiqi et al., 2024).
Fourth, this study was conducted within the context of the banking sector in Bangladesh, which is a highly structured and target-driven environment. While the findings provide valuable insights into support mechanisms within this context, the dynamics of organizational support, work-life balance, and identification may operate differently in other industries. Future research should apply and test this model in sectors such as education, healthcare, and information technology, where work conditions, job demands, and organizational cultures vary significantly.
Finally, while this study utilized WLB as a mediating variable and OI as a moderator, future research could explore alternative or additional psychological constructs, e.g., psychological empowerment, perceived organizational justice, emotional exhaustion, or employee engagement as a mediator or moderator that may play similar roles. Investigating these pathways may yield deeper insights into the motivational and identity-based processes that underpin employee behavior in organizational settings.
Biographies
Dr. Ishita Roy is an Associate Professor at the Department of Management Studies in Gopalganj Science and Technology University, Gopalganj, Bangladesh. She received her PhD from Gopalganj Science and Technology University, Gopalganj, Bangladesh. She published several papers in peer-reviewed international journals. Her areas of research interest include Human Resource Management, Leadership, Organizational Behavior, Work-life Balance Practices and Subjective well-being.
Rawshan Islam is currently pursuing an MBA in Human Resource Management at Gopalganj Science and Technology University, Gopalganj, Bangladesh. He completed his BBA in Management Studies from the same institution. His research interests include leadership practices, organizational behavior, sustainability, employee behavior, and knowledge management.
Dr. Md. Shamsul Arefin is an Associate professor in the Department of Management Studies at Gopalganj Science and Technology University in Bangladesh. He received his PhD from Huazhong University of Science and Technology in China. His research interest includes strategic HRM, leadership, work-life balance and positive human behavior
Acknowledgements
The authors are grateful to the anonymous referees of the journal for their insightful and constructive comments, which significantly enhanced the quality of this manuscript. Special thanks are extended to Dr. Md. Sahidur Rahman for their invaluable guidance and support throughout the research process, particularly in study design and coordination of data collection. The author also acknowledges the contributions of Omar Faruk Manik, MD. Shamimul Islam Miraz, Tanmoy Karmakar, Mehedi Hasan and Choyan Halder whose dedicated efforts in data collection and screening were instrumental. Sincere appreciation is also extended to all others who assisted in the fieldwork and data collection process, their support played a vital role in the successful completion of this study.